chickpea introduction research paper

REVIEW article

Developing climate-resilient chickpea involving physiological and molecular approaches with a focus on temperature and drought stresses.

• 1 Department of Botany, Panjab University, Chandigarh, India
• 2 Department of Crop Improvement Division, Indian Institute of Pulses Research, Kanpur, India
• 3 Department of Agricultural Biotechnology, Himachal Pradesh Agricultural University, Palampur, India
• 4 The UWA Institute of Agriculture, The University of Western Australia, Perth, WA, Australia

Chickpea is one of the most economically important food legumes, and a significant source of proteins. It is cultivated in more than 50 countries across Asia, Africa, Europe, Australia, North America, and South America. Chickpea production is limited by various abiotic stresses (cold, heat, drought, salt, etc .). Being a winter-season crop in northern south Asia and some parts of the Australia, chickpea faces low-temperature stress (0–15°C) during the reproductive stage that causes substantial loss of flowers, and thus pods, to inhibit its yield potential by 30–40%. The winter-sown chickpea in the Mediterranean, however, faces cold stress at vegetative stage. In late-sown environments, chickpea faces high-temperature stress during reproductive and pod filling stages, causing considerable yield losses. Both the low and the high temperatures reduce pollen viability, pollen germination on the stigma, and pollen tube growth resulting in poor pod set. Chickpea also experiences drought stress at various growth stages; terminal drought, along with heat stress at flowering and seed filling can reduce yields by 40–45%. In southern Australia and northern regions of south Asia, lack of chilling tolerance in cultivars delays flowering and pod set, and the crop is usually exposed to terminal drought. The incidences of temperature extremes (cold and heat) as well as inconsistent rainfall patterns are expected to increase in near future owing to climate change thereby necessitating the development of stress-tolerant and climate-resilient chickpea cultivars having region specific traits, which perform well under drought, heat, and/or low-temperature stress. Different approaches, such as genetic variability, genomic selection, molecular markers involving quantitative trait loci (QTLs), whole genome sequencing, and transcriptomics analysis have been exploited to improve chickpea production in extreme environments. Biotechnological tools have broadened our understanding of genetic basis as well as plants' responses to abiotic stresses in chickpea, and have opened opportunities to develop stress tolerant chickpea.

Introduction

Chickpea ( Cicer arietinum L.) is the 2 nd most important legume crop after common bean ( Phaseolus vulgaris L.) ( Gaur et al., 2008 ; Varshney et al., 2013b ) and an economically beneficial protein-rich food legume. India is the largest chickpea-producing country, with a 75% share of global production ( FAO, 2016 ; Maurya and Kumar, 2018 ; Gaur et al., 2019 ). Chickpea is produced in 50 countries, of which Australia, Canada, Ethiopia, India, Iran, Mexico, Myanmar, Pakistan, Turkey, and the USA are the major producers ( Gaur et al., 2012 ; Archak et al., 2016 ; Dixit et al., 2019 ). However, the productivity of chickpea is not sufficient to fulfill the protein requirement for the increasing human population ( Henchion et al., 2017 ; Chaturvedi et al., 2018 ). Chickpea production faces many challenges due to various abiotic stresses such as drought, and low and high temperatures ( Ryan, 1997 ; Millan et al., 2006 ; Gaur et al., 2008 ; Mantri et al., 2010 ; Jha et al., 2014 ; Garg et al., 2015 ). Most importantly, unpredictable climate change is the major constraint for chickpea production as it increases the frequency of drought and temperature extremes, i. e., high (> 30°C) and low (< 15°C) temperatures ( Gaur et al., 2013 ; Kadiyala et al., 2016 ), which reduces grain yields considerably ( Kadiyala et al., 2016 ). Thus, high- and stable-yielding varieties of chickpea during such stress conditions need to be developed ( Chaturvedi and Nadarajan, 2010 ; Krishnamurthy et al., 2010 ; Devasirvatham et al., 2015 ; Devasirvatham and Tan, 2018 ).

Drought stress is a serious situation for agriculture in the context of climate change and the ever-increasing world population ( Farooq et al., 2009 ; Tardieu et al., 2018 ). Extreme drought conditions reduce crop yields through negative impacts on plant growth, physiology, and reproduction ( Yordanov et al., 2000 ; Barnabas et al., 2008 ). Across the globe, drought stress reduces chickpea yield by about 45–50% ( Ahmad et al., 2005 ; Thudi et al., 2014 ). Numerous studies have been conducted on the drought effects on different chickpea traits, including early maturity, root traits, carbon isotope discrimination, shoot biomass ( Kashiwagi et al., 2005 ; Krishnamurthy et al., 2010 ; Upadhyaya et al., 2012 ; Krishnamurthy et al., 2013b ; Purushothaman et al., 2016 ), and morphological ( Sabaghpour et al., 2006 ), physiological ( Turner et al., 2007 ; Rahbarian et al., 2011 ), biochemical ( Gunes et al., 2006 ; Mafakheri et al., 2010 ) and molecular traits ( Mantri et al., 2007 ; Thudi et al., 2014 ; Garg et al., 2016 ). There have been various attempts to explain the advancements in “omics” technology for drought challenges. These advances should progress the development of stress-resilient, high yielding, and nutritionally superior varieties of chickpea.

Winter/autumn-sown chickpea crops in northern south Asia and south Australia face low temperature (LT) stress at reproductive (flowering/podding) stages whereas those in Mediterranean region, especially the central Anatolia, are exposed to LT at the seedling and early vegetative stages ( Berger et al., 2005 ; Berger et al., 2011 ; Berger et al., 2012 ). Winter-sown crops in the West Asia and North Africa (WANA) or northern regions of south Asia flower when cold is over and temperatures rise. Podding temperatures are slightly higher than those for flowering ( Berger et al., 2005 ), and flowers drop if temperatures remain lower than that required for podding. At flowering/podding time, the crop is also at the risk of damage by Ascochyta blight disease. A temperature of 14–6°C, usually 15°C, is considered a threshold for reproduction in chickpea ( Srinivasan et al., 1998 ; Berger et al., 2004 ; Clarke et al., 2004 ; Berger et al., 2005 ; Bakht et al., 2006b ; Berger, 2007 ), a recent study by Berger et al. (2012) , however, measured mean flowering temperature to be 21°C which is well above the earlier estimates implying that most of the world chickpea is susceptible to cold stress. Winter sown chickpea is also prone to terminal drought, as delayed flowering extends the chickpea growing season to warm but low or no rainy periods. In contrast to this, spring sown crops in the Mediterranean, USA, and Canada are of short duration and do not face terminal drought but productivity is low due to short duration ( Singh et al., 1997a ). In USA, the rains may extend the crop growth season so long that crop fails to mature especially in the Montana region ( McVay et al., 2013 ). Being a crop of indeterminate growth habit, drought conditions will hasten maturity in chickpea by stopping growth, while late season rains will cause plants to green back up ( McVay et al., 2013 ).

Despite being a cool-season crop, chickpea also faces high-temperature (HT) stress during reproductive development in warmer regions and in late-sown environments. HT aborts floral buds, flowers, and pods, ultimately leading to reduced seed size and yield ( Wang et al., 2006 ) especially those above 32°C ( Kaushal et al., 2013 ; Devasirvatham et al., 2015 ). HT like LT leads to loss of pollen viability and pollen fertility that affect pod set ( Wang et al., 2006 ; Kumar et al., 2013 ; Kaushal et al., 2016 ). HT induced disruption in sucrose synthesis and its availability to the anthers, and oxidative stress appears to contribute to loss of pollen fertility and stigmatic function ( Kaushal et al., 2013 ; Kumar et al., 2013 ; Devasirvatham et al., 2015 ), resulting in poor pod set. Heat stress can have a highly destructive effect on grain growth and development in chickpea ( Wang et al., 2006 ). The grain yield of chickpea is related to its phenology, which is influenced by temperature range ( Jumrani and Bhatia, 2014 ). High temperatures (> 35°C) during the reproductive stage is a major constraint for chickpea productivity ( Siddique et al., 1999 ; Wang et al., 2006 ; Basu et al., 2009 ), with temperatures >30°C reducing grain weight and number ( Kobraee et al., 2010 ). Substantial reductions in chickpea yield have been observed for even a 1°C rise in temperature beyond the threshold ( Kalra et al., 2008 ). Yield losses have increased to 100% in many chickpea genotypes, with increasing temperature ( Canci and Toker, 2009 ). High temperature severely affects podding in chickpea; the magnitude of which may be due to impaired source and sink relations from green leaves to anther tissue that leads to the mortality of pollen grains ( Awasthi et al., 2014 ). Heat stress after flowering and grain filling reduced chickpea yield, due to increased senescence and reduced grain set and grain weight per plant ( Wang et al., 2006 ). Post-anthesis, both grain numbers and weight decreased at high temperatures, leading to lower grain yields ( Summerfield et al., 1984 ; Wang et al., 2006 ; Devasirvatham et al., 2013 ). Heat stress, in future, would considerably reduce the grain yields in several crops, including chickpea, in many parts of the world, and thus deserves serious attention to develop heat-tolerant cultivars. Developing new cultivars with improved adaptation to high temperature is vital for increasing worldwide chickpea production.

Winter sown crops in all parts of world are prone to terminal drought, however, drought is not confined to terminal stages but it may occur at any plant growth stage. Spring-sown chickpea in WANA region and semi-arid tropics (SAT) faces drought at the vegetative as well as reproductive stages ( Silim and Saxena, 1993 ) leading to 30 to 100% yield losses, depending on the genotype, and severity as well as timing of drought ( Singh, 1993 ; Leport et al., 1999 ; Canci and Toker, 2009 ). Chickpea can tolerate drought stress based on “escape,” “tolerance,” and “avoidance” three important mechanisms ( Levitt, 1972 ). The principle of drought escape constitutes completion of plant's life-cycle before the onset of drought stress by hastening the phenological events ( Levitt, 1972 ; Berger et al., 2016 ). Drought avoidance mechanism features minimum water loss and maximizing water use ( Levitt, 1972 ). Usually, under central and south Indian conditions where chickpea is grown under stored soil moisture and having high water holding capacity soil, chickpea withstands drought stress through employing drought escape and drought avoidance mechanisms ( Berger et al., 2006 ; Berger et al., 2016 ). However, this drought avoidance strategy remains ineffective under Mediterranean climates in Western Australia featuring low water holding capacity soil ( Berger et al., 2016 ). The sources of resistance to these stresses are available either in the cultigens (heat and drought stress) or wild relatives (cold stress), and can be exploited to develop stress-resilient chickpea cultivars. The methodologies may be as simple as hybridization to use of marker assisted breeding [for genes as well as quantitative trait loci (QTLs)] or development of transgenics. QTLs for drought and temperature tolerance and in several cases genes within QTL regions have already been identified ( Varshney et al., 2013a ; Varshney et al., 2016 ; Devasirvatham and Tan, 2018 ; Kaloki et al., 2019 ). Genic, genetic, physiological, and biochemical basis of stress tolerance, once explored sufficiently, are expected to form the guiding principles for development of stress management strategies in chickpea. The objectives of sustainability of chickpea productivity or enhancing it further under changing climates can not be achieved until chickpea cultivars tolerant to combined stress, such as drought and heat, and drought and cold are developed. Various defense mechanisms regulating chickpea's adaptation during temperature and drought stress, especially the combined stresses, also need to be investigated ( Upadhyaya et al., 2012 ; Awasthi et al., 2015 ; Khan et al., 2019a ; Khan et al., 2019b ). Here, we update the research status on drought and temperature stress in chickpea, and suggest appropriate management strategies to develop stress-tolerant genotypes.

Effects of Cold Stress

Chickpea ( C. arietinum L.) has evolved in the Mediterranean region and developed sensitivity to low temperature, with adverse effects on growth and yield ( Croser et al., 2003 ; Kaur et al., 2008a ; Thakur et al., 2010 ; Kumar et al., 2013 ). About half of the productivity losses in chickpea are due to exposure to low temperature ( Saxena, 1990 ). Chilling stress in chickpea mostly affects the northern parts of India and southern Australia, as temperatures drop below 15°C at flowering ( Srinivasan et al., 1998 ; Clarke et al., 2004 ; Berger et al., 2006 ). The reproductive phase is critical for crop productivity ( Thakur et al., 2010 ); chilling stress in chickpea causes flower abortion, pollen, and ovule infertility, disrupts fertilization, reduces pod set, retards seed filling, and reduces seed size and ultimately crop yield ( Clarke and Siddique, 2004 ; Nayyar et al., 2005b ; Nayyar et al., 2007 ; Thakur et al., 2010 ; Kumar et al., 2011 ). Low temperatures can limit chickpea growth and vigor at all phenological stages but are most damaging during the reproductive stage.

Germination and Vegetative Growth

Chickpea is a cool-season crop that is exposed to chilling (3–8°C) or even freezing temperatures during germination, which can affect seedling establishment and reduce seedling vigor ( Chen et al., 1983 ; Srinivasan et al., 1998 ; Bakht et al., 2006b ). Several interacting factors (genotype, temperature, duration and time of exposure, and seed moisture content prior to imbibition) mediate seed responses to low germination temperatures. Roberts et al. (1980) and Singh et al. (2009) demonstrated that low temperature (10°C) decreased the germination rate of chickpea seeds. The recommended threshold temperatures range for chickpea germination varies from 5 to 35°C and optimum germination temperature is 20°C ( Singh and Dhaliwal, 1972 ; Ellis et al., 1986 ; Auld et al., 1988 ; Calcagno and Gallo, 1993 ). Chickpea, along with many other chilling-sensitive species, is prone to “imbibitional chilling injury” ( Tully et al., 1981 ). In the field, chilled seeds are often vulnerable to infestation by soil organisms, which reduces seedling survival. Chen et al. (1983) observed that the greatest sensitivity to cold occurs in the first 30 min of imbibition in chickpea and low temperature (3 to 8°C) during imbibition reduced chickpea germination by 15%. The combination of imbibition at low temperature and fast water uptake reduced germination by 65% ( Tully et al., 1981 ; Chen et al., 1983 ). In Australia, chilling damage during imbibition has been implicated in the poor establishment of some chickpea genotypes in cold and wet soils combined ( Knights and Mailer, 1989 ). The rapidity of imbibition is a factor, controlled principally by the thickness of the testa ( Tully et al., 1981 ; St. John et al., 1984 ). Kabuli types generally have thinner testa than desi types, resulting in more rapid imbibition of water and consequently greater levels of imbibitional damage.

Another factor affecting germination success at cold temperatures is the seed phenolic content ( Auld et al., 1983 ; Wery, 1990 ), which presumably confers fungal properties ( Wery et al., 1994 ). Thus, the poor germination of kabuli types is partly due to their thin white testa being more susceptible to soil pathogens. Cold stress adversely affects the mobilization of food reserves from cotyledons that decreases embryonic growth, germination, and growth of chickpea seedlings ( Croser et al., 2003 ). Ellis et al. (1986) found genotypic differences in the rate of germination with temperature. Given the existing genetic variability, it should be possible to select genotypes that are resistant to temperature stress during germination. Some seed treatments, such as hydropriming for 12 h or osmopriming (PEG/0.5 MPa) for 24 h have increased germination of chickpea in low-temperature soil conditions ( Elkoca et al., 2007 ), and may be linked to cross-tolerance. Chickpea plants growing under field conditions, especially in India and Australia, are exposed to gradually decreasing temperatures and photoperiods during the early vegetative stage ( Croser et al., 2003 ). The minimum temperature that chickpea generally seems to survive is –8°C; however, some lines can tolerate as low as –12°C post-emergence ( Wery, 1990 ; Croser et al., 2003 ). Thus, there is potential to select for cold tolerance at germination and during seedling growth from the existing chickpea germplasm.

Reproductive Growth and Yield

The flowering phase, the crucial phase in the plant life cycle that determines the yield of chickpea, is most sensitive to cold stress ( Sharma and Nayyar, 2014 ). Temperatures below 15°C result in the abortion of chickpea flowers leading to decline in the number of pods per plant and seeds per pod ( Srinivasan et al., 1999 ; Berger et al., 2004 ; Clarke and Siddique, 2004 ; Nayyar et al., 2005b ; Berger et al., 2006 ; Kaur et al., 2011 ; Kumar et al., 2011 ). The causes of flower abortion in sensitive genotypes of chickpea are fairly well understood. It is well documented that male gametophyte of chickpea is highly sensitive to cold stress and in genotypes sensitive to cold, both microsporogenesis and subsequent pollen development are inhibited at temperatures below 10°C ( Sharma and Nayyar, 2014 ; Kiran et al., 2019 ). Identification of flower and anther development stages in chickpea allowed studying the impact of cold at different flower development stages ( Kiran et al., 2019 ). Flowers of different development stages react differently to cold stress ( Kiran et al., 2019 ) e.g., low temperatures terminate microsporogenesis in flowers at pre-meiotic stage of anthers and microgametogenesis in those at tetrad stage. In anthers at young microspore stage, low temperatures inhibited anther dehiscence but did not inhibit development of microspores to mature pollen stage. The pollen, however, were sterile indicating that cold at this stage affected pollen viability, in addition to anther dehiscence ( Oliver et al., 2007 ). Exposure at mature pollen stage delayed anther dehiscence and induced partial pollen sterility ( Kiran et al., 2019 ). The quantum of low temperatures induced pollen sterility also depends upon the age of the flower with older flowers producing less amount of sterile pollen as compared to younger flowers, e.g., low temperature treatment at young microspore stage led to complete sterility of pollen whereas those at vacuolated microspore stage 23.59% pollen were viable, at vacuolated pollen stage 52.4% pollen were viable, at mature pollen stage 65.5% pollen were viable ( Kiran et al., 2019 ). Apparently, male gametophytes of younger flowers are more prone to damage by cold stress as compared to the older ones. In contrast, cold-tolerant chickpea genotypes maintain functional anther and pollen development, leading to pod formation and seed set during chilling stress ( Clarke and Siddique, 2004 ; Kumar et al., 2011 ). Cold stress also impairs pollen tube growth in the style and, consequently, fertilization failure ( Clarke and Siddique, 2004 ; Nayyar et al., 2007 ).

Chilling stress also has an adverse effect on gynoecium to impair ovule function; Srinivasan et al. (1998) reported missing embryo sacs in some chickpea cultivars, which reduced the number of fertilized ovules in all cultivars during cold stress. Chilling stress reduces ovule viability, stigma receptivity, and pollen load on stigma ( Kiran et al., 2019 ). While studying flower abortion due to cold stress in chickpea, it was observed that the older flowers, that have sufficient viable pollen were also aborted ( Kiran et al., 2019 ). Very low ovule viability accompanied by very low stigma receptivity in older flowers pointed toward role of female gametophyte factors in lack of fertilization and flower abortion under low temperature stress in addition to male factors. The role of female gamete was also highlighted using pollen from cold treated flowers to pollinate plants growing at normal temperatures and vice-versa ( Nayyar et al., 2005b ). The low temperature (4°C) used by Kiran et al. (2019) was, however, considerably lower than the threshold of 15°C ( Srinivasan et al., 1998 ; Clarke et al., 2004 ; Berger et al., 2004 ; Berger et al., 2005 ; Bakht et al., 2006b ; Berger, 2007 ) or 21°C ( Berger et al., 2012 ) reported for reproduction in chickpea. Further studies at temperature slightly below 15°C need to be conducted to understand behavior of flowers to threshold low temperature stress.

Ectopic persistence of tapetum in low temperature treated chickpea flowers indicates disruption of normal process of tapetum programmed cell death under low temperatures ( Kiran et al., 2019 ). Such disruption might have imbalanced nutrition to developing microspores. It has been already documented that low temperatures during flowering cause nutritional deficiencies in the tapetum ( Nayyar et al., 2005b ; Sharma and Nayyar, 2014 ) and decrease in sugar levels in anthers and pollen grains, which may be a primary cause of flower abortion. Low temperatures disrupt the mobilization of carbohydrates from source to sink and lead to nutrient deficiencies in stylar tissues too ( Nayyar et al., 2005b ). Cold stress also induces the synthesis of abscisic acid (ABA) in chickpea flowers, indicating a correlation between flower abortion and high ABA concentration ( Thakur et al., 2010 ). In chickpea exposed to low temperatures (12–15/4–6°C day/night), increased ABA concentrations caused flowers to abort ( Nayyar et al., 2005a ). ABA interferes with sucrose translocation to flowers ( Kumar et al., 2010 ) probably by inhibiting sucrose transporter gene invertase as has been observed in crops like rice ( Oliver et al., 2005 ; Sharma and Nayyar, 2016 ).

Chilling stress has a damaging effect on flower number, pod set, seed growth, and development in chickpea ( Croser et al., 2003 ; Berger et al., 2004 ; Nayyar et al., 2005b ; Thakur et al., 2010 ). Moreover, low temperature impairs seed filling processes, which reduces the size of chickpea seeds ( Nayyar et al., 2005b ; Nayyar et al., 2007 ; Kaur et al., 2008a ). Grain yield is related to phenology of chickpea and a combination of low temperature induced factors i.e., poor plant growth, delay in flowering, flower abortion, delay in podding, pod abortion, and poor seed filling contribute to lower the yield of chickpea under cold ( Berger et al., 2004 ). Poor pod set/filling as a result of cold stress is due to the disruption in photosynthesis and inhibition of translocation of initiating signals from leaves to the meristem or by changing plant architecture ( Gogoi et al., 2018 ). The studies on estimation of yield losses in chickpea due to cold are scanty. Singh et al. (1993) grew cold tolerant and cold susceptible genotypes of chickpea both in spring (temperatures normal for crop) and autumn (temperatures stressful as low as −10°C) in Syria and compared yield among the genotypes and seasons. A highly cold susceptible chickpea line with cold rating of 7.8 (1 = no visible cold damage, 9 = all plants killed) yielded 161 kg/ha during winter (low temperature) season and 474 kg/ha during warmer spring season ( Singh et al., 1993 ). In comparison to this, a line with cold rating of 5.2 yielded 632 kg/ha during winter season and 251 kg/ha during spring season ( Singh et al., 1993 ) indicating that cold in susceptible genotypes caused huge yield losses. The spring season due to short duration, reduces productivity of chickpea as compared to longer winter seasons that allows more time for crop to grow and consequently higher yields. Nayyar et al. (2005c) reported 30% increase in seed yield per plant in glycine betaine (a compatible solute that accumulate in cold-tolerant plants in higher amounts under cold stress) treated plants over control in winter sown chickpea grown in low temperature prone northern regions of India (pot-based studies). Since, winter sown chickpea yields more as compared to spring sown one if genotype has adequate cold-tolerance, the emphasis worldwide is on development of cold tolerant cultivars of chickpea to increase productivity of the crop. Wild relatives of chickpea in primary gene pool ( Cicer reticulatum , Cicer echinospermum ) that are crossable with the cultigens are tolerant to cold can be ideal sources to introgression cold tolerance to chickpea for development of varieties for winter season ( Berger et al., 2012 ).

The physiological functions of plants are adversely influenced by low temperature (<20°C) ( Thakur et al., 2010 ). Low temperatures (17.6/4.9°C; day/night for 26 days during reproductive phase) resulted in reduction in relative leaf water content, possibly due to a decline in root hydraulic conductivity, oxidative and membrane damage, and chlorophyll loss ( Kumar et al., 2011 ). Chilling stress (13/10°C; day/night for 18 h) during germination considerably inhibited α-amylase activity, disrupted sugar metabolism, reduced leaf water status, and uptake of mineral elements (N, P, and K) that delayed seedling emergence and caused poor seedling growth in chickpea ( Farooq et al., 2017 ). Temperature changes can impact root physiology, thus affecting ion absorption and may result in visible deficiency symptoms ( Gregory, 1988 ). Low-temperature stress (5°C for 3 days) inhibited root growth and the capacity for water and mineral uptake to subsequently impact the nutritional influences on plant growth ( Aroca et al., 2003 ; Heidarvand et al., 2011 ). Low temperatures (5/5°C for 4 days) also reduced the leaf water content because the stomata are unable to close ( Lee et al., 1993 ; Farooq et al., 2009 ). Flower abortion and poor pod set in chickpea due to cold stress (12–15/4–6°C day/night during flowering stage) was attributed to decreasing levels of sucrose, glucose, and fructose in anthers and pollen in sensitive genotypes ( Nayyar et al., 2005a ). Endogenous proline and carbohydrates (glucose, rhamnose, and mannose) increased with cold stress (3°C for 7 days) in chickpea genotypes, and may play a role in osmoregulation and meeting the enhanced energy requirements ( Saghfi and Eivazi, 2014 ); the cold-tolerant genotypes performed better in this regard.

Cellular and Physiological Mechanisms for Cold Survival

Low temperatures (0–10°C) result in rigidification of the plasma membrane that is sensed by plant cells ( Yadav, 2010 ) to impair the integrity of phospholipids in the plasma membrane ( Badea and Basu, 2009 ). In cold-tolerant chickpea genotypes, the content of unsaturated fatty acids increased during low-temperature exposure (10°C for 5 days followed by 4°C for 2 days) ( Shahandashti et al., 2013 ), which possibly contributed toward maintenance of membrane integrity during cold stress. Mitochondria are the most vital cell organelles and play an important role in stress tolerance mechanisms by interacting with energy-dissipating elements such as alternative oxidase (AOX) ( Borecky and Vercesi, 2005 ; Rurek et al., 2015 ). In optimum conditions, plant cells carry on the cytochrome-mediated pathway with the help of the mitochondrial electron transfer chain, which results in ATP synthesis by using the proton motive force ( Dinakar et al., 2016 ). In unfavorable conditions, a new pathway is involved in which cytochrome reductase and cytochrome oxidases are replaced by AOX to protect respiration and metabolic processes. This suggests that mitochondria have the flexibility to alter their activities and enhance AOX activity during environmental stress ( Shi et al., 2013 ; Vanlerberghe, 2013 ). There are different genes for AOXs, depending on plant species; for example, AOX in chickpea is encoded by the aox3 gene in mitochondria ( Karami-Moalem et al., 2018 ), and might be involved in cold tolerance.

Reactive oxygen species (ROS) are produced in response to cold stress in chickpea ( Kumar et al., 2011 ) and damage vital molecules in cells, including membranes. Generally, lipid peroxidation and hydrogen peroxide concentrations are measured as markers of temperature-induced oxidative stress ( Awasthi et al., 2015 ). A positive correlation was observed between lipid peroxidation and malondialdehyde (MDA) concentration in Cicer occidentalis ( Shahandashti et al., 2013 ). Plant cells have different mechanisms to combat oxidative damage by activating ant oxidative systems that include both non-enzymatic (e.g., tocopherols, ascorbate, proline) and enzymatic [e.g., superoxide dismutase (SOD), catalase (CAT), and ascorbate peroxidase (APX)] ( Turk et al., 2014 ; Zouari et al., 2016 ). A few studies in chickpea have identified an increase in the double bond index due to enhanced lipoxygenase (LOX) activity, suggesting that increased LOX activity plays an important role in providing cold tolerance in chickpea ( Padham et al., 2007 ; Wasternack, 2007 ; Pushpalatha et al., 2011 ). The up-regulation of various types of antioxidants has been correlated with cold tolerance in chickpea ( Nayyar and Chander, 2004 ).

Some plant regulating molecules look promising for imparting stress tolerance ( Bhandari et al., 2017 ), and have been investigated in chickpea for enhancing cold tolerance. Polyamines (PAs), with a polycationic nature at a physiological pH, bind strongly to the negative charges in cellular components such as nucleic acids, proteins, and phospholipids ( Bouchereau et al., 1999 ) and interact with membrane phospholipids to stabilize membranes under stress conditions ( Roberts et al., 1986 ). The depletion of PAs as a result of cold stress (5 to 25°C for 4 days) has been linked to the loss of flowers and pods ( Nayyar and Chander, 2004 ). Exogenous application of PAs reduced H 2 O 2 levels and MDA content and increased antioxidant levels in chickpea plants subjected to cold stress ( Nayyar and Chander, 2004 ). Hence, it may be possible to improve cold tolerance in chickpea by increasing the content of PAs using genetic manipulation or exogenous application. Besides PAs, abscisic acid (ABA) is also involved in providing stress tolerance ( Trivedi et al., 2016 ); cold-stressed (10–12/2–4°C day/night at bud stage) chickpea plants treated exogenously with 10 µm ABA had improved pollen viability, pollen germination, flower retention, and pod set ( Kumar et al., 2008 ). At the cellular level, ABA-treated plants increased activities of SOD, catalase (CAT), ascorbate peroxidase (APX), ascorbic acid, glutathione, and proline. Trehalose, a disaccharide of glucose plays an important role as a compatible solute, stabilizes biological structures under abiotic stress ( Jain and Roy, 2009 ), including dehydrated enzymes, proteins, and lipid membranes, and protects biological structures from damage during desiccation ( Fernandez et al., 2010 ). It also acts as a membrane and molecule chaperone during water or cold stress ( Crowe, 2007 ; Fernandez et al., 2010 ). Seed priming with trehalose reduced the oxidative damage to biological membranes and other vital organelles during cold stress (13/10°C for 18 h) in chickpea, and improved carbon assimilation, resulting in better seedling growth ( Farooq et al., 2017 ). Increased accumulation of total and reducing sugars (especially trehalose) may protect against chilling stress by stabilizing cell membranes, ceasing protein denaturation and acting as a scavenger of free radicals ( Benaroudj et al., 2001 ; Farooq et al., 2009 ).

Glycine betaine (GB), an amino acid, is a cryoprotective solute that protects the activities of enzymes and proteins and stabilizes membranes and photosynthetic apparatus under chilling (12–14/3–4°C day/night) and freezing temperatures at bud and pod filling stage ( Rhodes and Hanson, 1993 ; McNeil et al., 1999 ; Nayyar et al., 2005c ). Cold stress (12–14/3–4°C day/night at bud stage) decreased the endogenous GB concentration in chickpea leaves and flowers, resulting in the loss of pods ( Nayyar et al., 2005c ). Exogenously applied GB to chickpea plants at bud and pod filling stages during cold stress improved flower function, pollen germination, pollen tube growth, stigma receptivity, and ovule viability, leading to floral retention, pod set, and pod retention ( Nayyar et al., 2005c ). Moreover, treatment with GB at the pod filling stage improved seed yield/plant, number of seeds/100 pods. Cold tolerance induced by GB may be related to an increase in relative leaf water content (RLWC), chlorophyll and sucrose, and decrease in ABA and active oxygen species (malondialdehyde and hydrogen peroxide) ( Nayyar et al., 2005b ; Nayyar et al., 2005d ; Nayyar et al., 2005e ). Possible roles for GB in stress tolerance include stabilization of complex proteins and membranes in vivo , protection of transcriptional and translational machinery, and as a molecular chaperone for refolding enzymes ( Rhodes and Hanson, 1993 ).

Cold stress is lethal to most plants; despite this, temperate plants survive the winter months through acclimation processes, which suggest that plant exposure to low but not freezing temperatures confers cold tolerance ( Bohn et al., 2007 ). A comparative study on cold-acclimated (CA) and non-acclimated (NA) chickpea plants showed an increase in the ratio of unsaturated fatty acids and saturated fatty acids in CA plants ( Kazemi-Shahandashti et al., 2014 ). Antioxidative enzymes, such as SOD, CAT, guaiacol peroxidase (GPX), and lipoxygenase (LOX), were highly active in CA plants and resulted in enhanced cold tolerance, compared to NA plants. The transcription levels of CaCAT and CaSOD genes were higher in CA plants than NA plants. Moreover, the transcription level of the Ca-Rubisco gene was higher in CA plants than NA plants. Thus, cold acclimation (23°C for 20 days, 10°C for 5 days, followed by −10°C for 15 min.) had a positive effect on chickpea plants during long-term cold stress ( Kazemi-Shahandashti et al., 2014 ), and may be a critical means of increasing cold tolerance.

Genomics and Transcriptomics in Elucidating Molecular Responses of Chickpea Under Cold

The “omics” approaches such as genomics, transcriptomics, proteomics, and metabolomics have become integral part of scientific strategies to study regulation of plants' responses to abiotic and biotic stresses. Between the genomics and transcriptomics, genomics provide the knowledge of structure of the genome including genes, promoters, regulatory elements etc. whereas the transcriptome elucidate the functional component of genome at any stage of plant growth. Consequently, transcriptomics reveal changes, not only in the expression of genes in a plant under abiotic stresses but also the gene regulatory mechanisms that govern differential expression of genes. Transcriptomics also provide information on differences in gene regulation and expression between the tolerant and sensitive genotypes thereby depicting precisely the mechanisms that lead to tolerance or susceptibility. Such detailed information can also be used to understand coordination among different regulatory pathways and may be exploited in the agricultural crops to develop appropriate strategies to manage the abiotic stresses under field conditions. In chickpea, global transcriptome expression using complementary DNA-amplified fragment length polymorphism (cDNA-AFLP), differential display, or microarray techniques have been used to identify genes of potential importance for acclimatization/tolerance to cold and elucidate pathways regulating this process ( Mantri et al., 2007 ; Dinari et al., 2013 ; Sharma and Nayyar, 2014 ). Using microarrays, 210 differentially expressed genes under cold were identified ( Mantri et al., 2007 ). The cDNA-AFLP in association with 256 primer combinations revealed different transcript-derived fragments (TDFs) associated with cold in chickpea leaves ( Dinari et al., 2013 ). Some of the TDFs showed a differential expression pattern and belonged to putative functions associated with transport, signal transduction pathways, metabolism, and transcription factors. Various genes are activated in chickpea during low-temperature stress, which encode for transcription factors and components involved in detoxification processes and cell signaling. For example, the gene encoding phosphatidylinositol-4-kinase, a key enzyme in an influx of Ca 2+ into the cytoplasm, expressed in Jk649809 and Jk649838 chickpea genotypes, ( Scebba et al., 1998 ). The mitogen-activated protein kinase was also up-regulated in Jk649803 during cold acclimatization and might be a signal molecule for cold tolerance. It was concluded that cold tolerance in chickpea is regulated by a relatively small number of genes ( Dinari et al., 2013 ).

Transcriptome analysis of meiotic anthers of chickpea revealed that cold-tolerance-associated genes belonged to four main categories—carbohydrate/triacylglycerol metabolism, pollen development, signal transduction, and transport ( Sharma and Nayyar, 2014 ). All of the genes of these four categories were upregulated in cold-tolerant anthers, with the exception of one pollen development gene that was down-regulated. Genes involved in microspore/pollen growth (tetrad separation, pollen expansion, increased vascular transport, fatty acid transport, pollen maturation, pollen exine formation, pollen tube growth, fertility, and pollen development) were switched-on in cold-tolerant genotype under cold stress ( Sharma and Nayyar, 2014 ). Upregulation of genes associated with carbohydrate and triacylglycerol metabolism suggests that cold-tolerant chickpea plants produce viable pollen during chilling stress by maintaining pollen development and carbohydrate/triacylglycerol metabolic pathways ( Sharma and Nayyar, 2014 ). Another study reported increased expression of 109 and 210 genes when chickpea was exposed to drought and cold stress, respectively ( Mantri et al., 2007 ). Of these, 15 and 30 genes were differentially expressed between tolerant and sensitive genotypes, respectively, which coded for various regulatory and functional proteins. Significant differences were observed in stress responses within and between tolerant and susceptible genotypes indicating multi-gene control and a complex abiotic stress response mechanism in chickpea. This study demonstrated that the leaves of cold-tolerant chickpea over expressed serine/threonine protein kinase while the flowers of cold-sensitive chickpea up-regulated SOD, a copper chaperone precursor involved in oxidative stress. Auxin repressed protein (DY475078) and auxin-responsive protein IAA9 (DY396315) transcripts, which are involved in cell rescue, were induced in the flowers and leaves of both the sensitive genotypes. Two phosphate-induced proteins (DY475076 and DY475172) were induced in flowers/pods of tolerant-1 (Sonali) chickpea genotype ( Mantri et al., 2007 ). It is worth mentioning here that phosphorus is responsible for flower formation and seed production. Sucrose synthase (DY475105) was also induced in leaves of Sonali, which lead to the accumulation of sucrose that functions as an osmolyte and may provide cold tolerance.

To compare similarities and differences between cold-stressed anthers and gynoecium, a small subset of 25 genes that were up-regulated in anthers under cold, was used to study gene expression in gynoecium ( Sharma and Nayyar, 2014 ). While all the genes were expressed in both the organs, nine had contrasting expression patterns in both the organs, i.e., an increase in one organ and decrease in the other ( Sharma and Nayyar, 2014 ). The genes expressed under cold were also compared with those expressed under drought and salinity ( Mantri et al., 2007 ). Some of the genes were common between the stresses while others were unique ( Mantri et al., 2007 ; Mantri et al., 2010 ), which suggests that some segments of abiotic stress responsive machinery are shared by different abiotic stresses.

Whole genome sequencing (WGS) has also provided insights into cold-tolerance mechanisms in chickpea. The technique has been exploited to generate genomic resources for better understanding of cold-tolerance and cold-susceptibility in chickpea, such as identification of a flowering repressor gene MtVRN2 in the confidence interval of a QTL ( Mugabe et al., 2019 ), using the reference genome of CDC Frontier chickpea. GWS has also been used to identify mitogen-activated protein kinases (MAPKs) in chickpea and the impact of cold on their expression. Of the 19 MAPK genes detected in chickpea, 15 were induced by low temperature (4°C, chilling stress) compared to control plants ( Singh et al., 2018 ). Similarly, 36 genes encoding the K + transport system in the chickpea genome were identified, along with their promoters with putative cold signals ( Azeem et al., 2018 ). These studies provided new vital information about the genes, which might be associated with cold tolerance to chickpea and indicated that cold-tolerance mechanisms might have organ specific distinctions e.g., leaf, anther and gynoecium. To confirm association of these candidate genes in cold tolerance or cold susceptibility, further studies need to be conducted using appropriate models.

There is also a study indicating that changes in methylation patterns may be associated with cold tolerance in chickpea. Prolonged cold stress in a cold-tolerant genotype increased demethylation, relative to a cold-susceptible genotype, suggesting a higher potential for activation of cold-stress-responsive genes ( Rakei et al., 2016 ). Thus, WGS and its further exploitation has generated genomic resources and enhanced our understanding of mechanisms governing cold tolerance/susceptibility in chickpea. These resources are ideal starting points for subsequent studies aimed at the regulation of cold tolerance in chickpea. The recent description of flower and anther development stages in chickpea ( Kiran et al., 2019 ) is also expected to aid in the identification of molecular mechanisms for cold tolerance during different stages anther development.

Physiological studies (see previous sections for details) point to prominent role of carbohydrate metabolism, antioxidants, and free amino acids in cold-tolerance, however, gene regulatory networks for carbohydrates, antioxidants, and free amino acids under cold-tolerance have not been studied in detail. To understand intricacies and reveal complete picture of cold-susceptibility or tolerance in chickpea, merger of physiological and gene regulation knowledge under cold stress is essential. There is also a need to generate information on gene regulation/expression for antioxidants, carbohydrates, and free amino acids where physiological studies have already been conducted. Since, mechanisms of cold-tolerance by leaves may be different from flowers, which are complex organs involving microsporogenesis, microgametogenesis, megasporogenesis, pollination, fertilization, and seed development ( Kiran et al., 2019 ), studies also need to be launched to understand mechanisms of pollen viability/ovule viability under cold stress by the cold-tolerant genotypes.

Genetic Variability and Breeding for Cold Tolerance

Winter-sown chickpeas face cold stress during reproductive growth resulting in flower drop, pod drop, and poor seed set (India and Australia) and restricted vegetative growth in young plants (Mediterranean region) ( Singh et al., 1989 ; Saxena, 1990 ; Chaturvedi et al., 2009 ; Sharma and Nayyar, 2014 ; Sharma and Nayyar, 2016 ). The cold environment differs in these chickpea cultivation areas; temperatures remain subzero (freezing) for some time during early crop growth in the Mediterranean region but usually above zero in Indian and Australian regions. Consequently, the goals of cold-tolerance breeding will vary between regions, i.e., genotypes should be selected for freezing tolerance (below 0°C) during early growth in the Mediterranean region and chilling tolerance (up to 0°C) during reproductive growth in Indian subcontinent ( Chaturvedi et al., 2009 ). Screening scales based on plant death at subzero temperatures are well described for cold-tolerant chickpea germplasm ( Singh et al., 1989 [1–9 scale]; Saccardo and Calcagno, 1990 [0–5 scale]). However, no screening scales have been devised to identify chilling tolerance during reproductive growth, and appears to be due to the complexity of processes at reproductive phase (flowering, podding, seed set, seed development, etc.) and mechanisms by which cold impedes flower, anther, and pod development ( Sharma and Nayyar, 2014 ; Kiran et al., 2019 ). Moreover, temperature sensitivity varies for flower, pod, and seed growth. For example, the critical temperature for seed growth is higher than that required for pod set ( Srinivasan et al., 1998 ). Evidence is emerging that pod set is related to cumulative temperature rather than minimum temperature, as plants growing at 0°C night temperature and 20°C day temperature bore pods ( Srinivasan et al., 1998 ). These observations need to be confirmed, as an earlier study reported that pod set only occurred at minimum night temperatures above 8°C ( Saxena, 1990 ).

Several studies have been undertaken on freezing tolerance in the cultigens or Cicer species. Within C. arietinum , germplasm including M 450, ILC 8262, ICCV 88501, ICCV 88502, ICCV 88503, ICCV 88506, FLIP 84-70C, FLIP 84-71C, and FLIP84-79 C are tolerant to cold ( Singh et al., 1990 ; Singh and Saxena, 1993 ) along with FLIP 81-293C, FLIP 82-127C, FLIP82-128C ( Wery, 1990 ), ILC 8262 (a germplasm line), ILC 8617 (a mutant) and FLIP 87-82C (a breeding line) ( Singh et al., 1995 ), ICCV 88501 and ICCV 88503 ( Srinivasan et al., 1998 ), FLIP95-255C, FLIP93-260C and Sel95TH1716 ( Kanouni et al., 2009 ), and Sel96TH11404, Sel96TH11439, Sel96TH11488, Sel98TH11518, x03TH21, and FLIP93-261C ( Saeed et al., 2010 ). Freezing tolerance in chickpea is dominant over susceptibility and controlled by at least five sets of genes ( Malhotra and Singh, 1990 ). Further genetic analysis revealed the presence of genic interactions (additive × additive and dominance × dominance) with duplicate epistasis and additive gene effects ( Malhotra and Singh, 1991 ). The two types of chickpeas, desi, and kabuli, do not differ in their reaction to cold ( Berger et al., 2012 ).

There is growing evidence that wild relatives of chickpea possess a higher degree of cold tolerance than the cultigens ( Singh et al., 1995 ; Berger et al., 2012 ). Wild Cicer species of the primary gene pool are readily crossable to the cultigens and can be the potential donors of cold tolerance. Wild species were evaluated extensively for cold tolerance both at freezing (young plants) and to a limited extent in chilling environments (at the reproductive stage). Among the wild relatives, Cicer bijugum, C. echinospermum , and Cicer judaicum were more cold-tolerant than C. arietinum during early growth ( Singh et al., 1990 ; Malhotra, 1998 ) of the reproductive stage ( Berger et al., 2012 ). Among 59 lines from seven annual wild Cicer species, 26 lines of C. reticulatum , 10 of C. bijugum , 4 of C. echinospermum , 2 of Cicer pinnatifidum , and 1 of C. judaicum tolerated freezing (subzero conditions) during early vegetative growth ( Singh et al., 1995 ). Among the cold-tolerant wild species, five lines of C. bijugum and four of C. reticulatum (highly tolerant) were superior to the cultigens for cold tolerance. In another study, Toker (2005) evaluated 43 accessions of eight annual wild Cicer species ( C. bijugum, Cicer chorassanicum, Cicer cuneatum, C. echinospermum, C. judaicum, C. pinnatifidum, C. reticulatum, and Cicer yamashitae ) for cold tolerance in young plants at subzero temperatures (freezing tolerance). C. bijugum was the best source of cold tolerance, with all six accessions under study being cold-tolerant (AWC 6: free from any damage, AWC 2 and AWC 4: highly tolerant, AWC 1, AWC 3, and AWC 5: tolerant) ( Toker, 2005 ). Eleven of 15 accessions of C. reticulatum , 4 of eight C . echinospermum , and 1 of five C. pinnatifidum (score 3) were cold-tolerant.

Chilling-tolerant chickpea germplasm—CTS 60543 (ICCV88516), CTS11308 (ICCV88510)—has been identified ( Clarke and Siddique, 2004 ). Pollen selection [transfer of plants to cold stress (12/7°C) for 3 days immediately after pollination followed by F 1 seed collection] was used to develop chilling-tolerant chickpea varieties including Rupali (WACPE 2095) and Sonali (WACPE 2075) ( Clarke et al., 2004 ). Similar to freezing stress, accessions of C. arietinum had less chilling tolerance than wild accessions ( Berger et al., 2012 ). Even Rupali and WACPE 2078 developed by Clarke et al.(2004) , when grown at ∼10°C post-anthesis, had large flower–pod intervals (>65 days) indicating a low degree of cold tolerance ( Berger et al., 2006 ). Among the wild species, an accession of C. echinospermum had robust chilling tolerance, whereas JM2106 of C. reticulatum was also chilling tolerant ( Clarke and Siddique, 2004 ; Berger et al., 2012 ). The C. echinospermum accession not only expressed the early podding character at low temperature but also yielded five times more than the most productive chickpea cultivar. With duplications in gene bank accessions of wild species of Cicer ( Croser et al., 2003 ), the actual number of cold-tolerant sources may be lower than that reported in the literature. Nonetheless, wild Cicer species are important sources for improving cold tolerance in chickpea.

One of the major consequences of low temperature has been hypothesized to be low sink utilization in northern regions of India, where low temperature causes flower abortion or failure of set pods ( Saxena et al., 1988 ). To improve harvest index due to pod set failure in this region, chilling-tolerant lines were crossed with agronomic ally desirable lines ( Saxena et al., 1988 ). Early flowering and podding in cross bred lines improved harvest index (50–54%) more than late flowering lines (39–42%). Cold-tolerant wild species of Cicer, namely C. reticulatum and C. echinospermum, have also been exploited to develop high-yielding chickpea ( Singh and Ocampo, 1997 ). Cold-tolerant and Fusarium wilt resistant accession of C. reticulatum (ILWC 124) and C. echinospermum (ILWC 179) were crossed with cultigens (ILC 482); one of the progenies out-yielded ILC 482 by 39%. In another study, lines derived from a cross of cultivated chickpea and C. reticulatum out-yielded the check cultivars ( Singh et al., 2005 ). Both studies showed that wild Cicer is not only a source of tolerance for abiotic stresses and diseases but can contribute to yield enhancement in chickpea. Both chilling tolerance during reproductive growth and yield enhancement in pedigree lines indicate that wild species of the primary gene pool have the potential to increase chickpea productivity in Australia and the Indian subcontinent (the region with the maximum area under chickpea) where cold stress coincides with the reproductive phase of the crop and productivity is low.

Genomics Advancements for Developing Cold Stress Tolerance in Chickpea

Generation of adequate genomic resources such as simple sequence repeat markers (SSRs) and single nucleotide polymorphism (SNPs) is essential for gene/QTL mapping and for identifying genes in QTL intervals. Currently available bioinformatics tools allow identification of molecular and biological functions of genes in QTL intervals based on existing scientific information, thereby allowing the selection of candidate genes governing the trait. The gene linked markers or QTLs can also be used to identify introgression of gene(s) into elite cultivars using a technique called foreground selection and recovery of recurrent parent genome using the background selection. Our understanding of cold tolerance in chickpea has increased considerably in the last decade, primarily due to advances in sequencing technologies that enabled large-scale decoding of genomic sequences at lower cost leading to gene identification, gene regulation, or large-scale development of DNA-based markers such as simple sequence repeats (SSRs) and single nucleotide polymorphism (SNPs). Development of reference genome sequences in chickpea ( Jain et al., 2013 ; Varshney et al., 2013b ; Parween et al., 2015 ) provided the much needed push in advancement of genomic resources in chickpea including development of SSR or SNP markers, identification of candidate genes within QTL intervals. Marker developments have allowed identification of QTLs governing tolerance to abiotic stresses. Association mapping of a panel of 44 genotypes was used to identify QTLs associated with freezing tolerance; however, no QTL associated with cold tolerance could be identified ( Saeed and Darvishzadeh, 2017 ). The lack of adequate marker density appears to explain the non-detection of QTLs linked to cold tolerance as only 64 AFLP markers were used. Recently, a mapping population of 129 recombinant inbred lines (RILs), derived from an interspecific cross between ICC 4958 (cold-sensitive, desi type, C. arietinum ) and PI 489777 (cold-tolerant wild relative, C. reticulatum Ladiz), followed by genotyping-by-sequencing was used to identify QTLs linked to cold tolerance ( Mugabe et al., 2019 ). A total of 747 SNP markers, spanning 393.7 cM, were used in this study. The SNPs were more abundant than traditional markers and had considerably higher marker density, with an average of 1.8 SNPs cM −1 . Freezing tolerance in PI48977 was governed by three QTLs situated on linkage groups (LGs) 1B, 3, and 8 ( Mugabe et al., 2019 ); CT Ca-3.1 (on LG3) and CT Ca-8.1 (on LG8) were more important and accounted for 34 and 48% of the phenotypic variance for cold, respectively. One of the parents used in the study, C. reticulatum , requires vernalization, i.e., acceleration of flowering following brief spells of cold exposure ( van Oss et al., 2015 ) and QTLs for vernalization response were also identified using a RIL population where one of the parents was PI 489777 ( Samineni et al., 2016 ). It is worth mentioning here that cultigen, C. arietinum , does not respond to vernalization ( Berger et al., 2005 . Using 1,291 loci [SSRs, diversity array technology (DArT), cleaved amplified polymorphic sequences (CAPs), legacy markers, etc.] for QTL identification, a major vernalization response QTL was identified ( Samineni et al., 2016 ). The QTL spanned 22 cM on LG3 and explained 47.9 to 54.9% of the phenotypic variation. Both studies, Samineni et al.(2016) and Mugabe et al.(2019) used the same cold-tolerant and vernalization responsive parent (PI 489777), and identified the same QTL (CT Ca-3.1) linked to the cold tolerance and vernalization response. This finding necessitates further research to determine the relationship between cold tolerance and vernalization response machinery in Cicer species. Using CDC Frontier chickpea as a reference genome, a homolog of the Medicago truncatula vernalization gene named VERNALISATION2‐LIKE VEFS box gene ( MtVRN2 ) was mapped in CTCa-3.1 confidence interval ( Mugabe et al., 2019 ). MtVRN2 is a repressor of the flowering locus T gene homolog from M. truncatula and is a repressor of transition to flowering ( Jaudal et al., 2016 ). This example demonstrates that genome sequences can be exploited effectively to narrow possible candidate genes in QTL regions and vernalization response in Cicer might be inversely related to flowering. None the less, QTLs governing cold tolerance in chickpea or candidate cold tolerance genes within these intervals are poorly explored so far as no information is available for QTLs in other cold-tolerant genotypes of C. reticulatum . Moreover, QTLs for cold-tolerance within cold-tolerant genotypes of C. arietinum and another annual wild relative Cicer echnospermum that possesses tolerance to cold are yet to be identified. In addition, no efforts have so far been made to transfer cold-tolerance QTLs from C. reticulatum to C. arietinum .

Impacts of Heat Stress

Excessive heat stress affects all aspects of chickpea growth, phenology, and development ( Devasirvatham et al., 2012 ; Devasirvatham et al., 2013 ; Kaushal et al., 2013 ), including biomass, flowering duration, pod number, days to maturity, seed weight, and grain yield ( Upadhyaya et al., 2011 ; Kaushal et al., 2013 ) and a wide range of plant development and physiological processes. The impact of heat stress at different stages of plant growth and development in chickpea are described below.

High temperatures affect seed germination in chickpea; genotypic variation was observed for high-temperature tolerance at seed germination, with no germination above 45°C ( Singh and Dhaliwal, 1972 ; Ibrahim, 2011 ), reduced seedling growth ( Kaushal et al., 2013 ), and even seedling death ( Kaushal et al., 2011 ). Controlled environment studies showed significant biomass increases in both tolerant and sensitive genotypes at 35/25°C whereas exposure to 40/30°C decreased biomass at maturity in all genotypes, more so in the sensitive genotypes ( Kumar et al., 2013 ).

Reproductive Growth

Heat stress limits chickpea growth and vigor at all phenological stages, but the reproductive phase is considered more sensitive to temperature extremes than the vegetative stage ( Sita et al., 2017 ). Heat stress during reproduction generally 1) reduces flower number, 2) increases flower abortion, 3) alters anther locule number decrease, 4) causes pollen sterility with poor pollen germination, 5) reduces fertilization and stigma receptivity, 6) causes ovary abnormalities, 7) reduces the remobilization of photosynthates to seeds, and 8) reduces seed number, seed weight, and seed yield ( Devasirvatham et al., 2012 ; Devasirvatham et al., 2013 ; Kaushal et al., 2013 ). Exposure of chickpea to heat stress (35/20°C) pre-anthesis reduced anther development, pollen production, and fertility by inducing physiological abnormalities ( Devasirvatham et al., 2012 ). High temperature can induce anther and pollen structural aberrations, such as alterations in anther locule number, anther epidermis wall thickening, and pollen sterility, which are key factors reducing chickpea yield under high temperature ( Devasirvatham et al., 2013 ). In chickpea, pollen is more sensitive to heat stress than the female gametophyte ( Devasirvatham et al., 2012 ). The effect of high-temperature stress post-anthesis has been associated with poor pollen germination, pollen tube growth and fertilization, and the loss of stigma receptivity ( Kaushal et al., 2013 ; Kumar et al., 2013 ), which reduces seed number, seed weight, and seed yield ( Summerfield et al., 1984 ; Wang et al., 2006 ). Temperatures above 45°C are detrimental to pollen fertility and stigma function in chickpea ( Devasirvatham et al., 2015 ).

Heat tress enhanced oxidative stress and lowered leaf photosynthesis, which reduced the soluble carbohydrate and ATP contents in the pistil ( Kumar et al., 2013 ) and prevented nutrient transport from the style to pollen tube thus inhibiting pollen tube growth and ovary development ( Kumar et al., 2013 ). Screening chickpea genotypes for heat sensitivity revealed substantial genetic variation in a high-temperature environment ( Krishnamurthy et al., 2011 ; Devasirvatham et al., 2015 ). Heat-tolerant chickpea genotypes produced pods at temperatures above 35/20°C, while sensitive genotypes aborted most of their flowers ( Kaushal et al., 2013 ). Devasirvatham et al. (2013) reported greater pod set in heat-tolerant genotypes (ICC 1205 and ICC 15614) than heat-sensitive genotypes (ICC 4567 and ICC 10685).

Influence of Heat Stress on Physiology

Some vital physiological traits, including chlorophyll concentration, photosynthetic rate, and membrane stability of leaf tissue, can be used as indicators of heat sensitivity ( Hasanuzzaman et al., 2013 ). Chickpea is relatively more sensitive in terms of membrane stability and photosystem II function at high temperatures 50°C for 48 h than other legumes ( Srinivasan et al., 1996 ). Heat stress (35/16°C for 10 days) induces leaf senescence in chickpea ( Wang et al., 2006 ) by disrupting the chloroplasts and damaging chlorophyll. Heat stress (>32/20°C during reproductive stage) reduced the chlorophyll content in chickpea leaves, which caused chlorosis ( Kaushal et al., 2013 ); this loss may have occurred due to photo-oxidative stress or inhibition of chlorophyll synthesis ( Guo et al., 2006 ). Heat stress (>32/20°C during reproductive stage) caused more leaf damage in a heat-sensitive than heat-tolerant chickpea genotype, due to a greater reduction in leaf water status (as RLWC) and possible decline in stomatal conductance, and restriction in hydraulic conductivity of root ( Kaushal et al., 2013 ). Transpiration efficiency in chickpea decreased with increasing temperature ( Singh et al., 1982 ). The quantum yield or photosystem II (PSІІ) activity in chickpea was not affected at 35°C, but a noticeable reduction occurred at 46°C (during pod filling) that caused irreversible damage to photosynthetic systems ( Basu et al., 2009 ). Similarly, Srinivasan et al. (1996) reported severe damage to PSІІ at 50°C for 48 h in chickpea. Temperatures above 35°C during reproductive stage suppressed photosynthesis and electron flow and disrupted metabolic pathways to reduce grain size ( Kaushal et al., 2013 ; Awasthi et al., 2014 ; Redden et al., 2014 ).

Heat stress alters the fluidity of plasmalemma, mitochondria, and chloroplast membranes, which can disintegrate the lipid bilayer to change the protein conformation and cause protein unfolding ( Pastor et al., 2007 ). Heat stress also results in the production of ROS that damage photosynthetic apparatus and other components, thus hampering metabolic activity ( Allakhverdiev et al., 2008 ; Das and Roychoudhury, 2014 ). Respiration is more temperature-sensitive than photosynthesis ( Hatfield et al., 2011 ). At 45/35°C (day/night), the cellular oxidizing ability of chickpea plants reduced appreciably at vegetative stage ( Kumar et al., 2013 ), suggesting impaired respiration and energy generation, possibly due to the inactivation of enzymes ( Salvucci and Crafts-Brandner, 2004 ).

At high temperature (> 32/20°C), sucrose synthesis decreased due to the inhibition (40–43%) of sucrose synthesizing enzymes (sucrose synthase and sucrose phosphate synthase) to impair sucrose metabolism in leaves of chickpea during reproductive phase ( Kaushal et al., 2013 ). As a result, the sucrose flow to flowers in heat-sensitive genotypes was considerably decreased to affect the developmental and functional aspects of pollen grains resulting in poor fertilization and pod set ( Kaushal et al., 2013 ). High temperatures (32/20°C day/night) from anthesis to maturity reduced starch deposition in chickpea grains because of reduced activity of ADP-glucose pyrophosphorylase and starch synthase ( Vu et al., 2001 ; Awasthi et al., 2014 ) resulting in reduction in grain weight.

Cellular Mechanisms for Survival Under Heat

Under heat stress (>35/23°C day/night) at the time of flowering, chickpea experiences adverse effects on growth and various metabolic processes that lead to alterations in the redox state of the cell ( Kaushal et al., 2011 ; Awasthi et al., 2015 ). At high temperature (37 and 42°C for 10 h), ROS generation causes oxidative damage to vital cellular components, such as membrane lipids, proteins, nucleic acids, pigments, and enzymes ( Rivero et al., 2001 ; Suzuki and Mittler, 2006 ; Yin et al., 2008 ). The ROS-induced oxidative damage consists of both free radicals, including hydroxyl radicals (OH˙), superoxide (O 2 − ), alkoxyl radicals, and non-radicals like hydrogen peroxide (H 2 O 2 ) and singlet oxygen ( 1 O 2 ) ( Suzuki and Mittler, 2006 ). At 40/30 and 45/35°C during growth and germination stage, increased lipid peroxidation and hydrogen peroxide levels in the leaves of heat-sensitive chickpea genotypes caused more leaf damage, than in tolerant genotypes ( Kaushal et al., 2011 ; Kumar et al., 2012b ; Kumar et al., 2013 ). Heat tolerance mechanisms in chickpea are potentially characterized by higher levels of antioxidants and osmolytes ( Kaushal et al., 2011 ), which maintain membrane integrity, protect macromolecules, and sustain metabolism, leading to heat acclimatization. Under stressful conditions, plants tend to combat ROS production by inducing an antioxidant system consisting of enzymatic and non-enzymatic components ( Gill et al., 2012 ); for example in chickpea, the activities of SOD, catalase (CAT), and ascorbate peroxidase (APX) increased at 40/35°C during growth and germination stage but decreased at 45/40°C ( Kaushal et al., 2011 ). Similar, the activity was observed in non-enzymatic antioxidants ascorbate (ASC) and glutathione (GSH). Inhibition of these enzymes and non-enzymatic antioxidants was much more in the heat-sensitive genotypes: the antioxidants increased at 40/35°C but declined at 45/40°C observed ( Kaushal et al., 2011 ) in heat-sensitive genotypes. Exogenous application of proline (Pro), an osmolyte, significantly increased SOD, CAT, ASH, and GSH activity at 45/40°C in chickpea, relative to the plants grown without proline ( Kaushal et al., 2011 ).

Salicylic acid (SA) plays a key role in providing tolerance against temperature stress in chickpea. Heat-stress-induced membrane damage in chickpea plants declined significantly with the application of SA, relative to the untreated control and heat-acclimatized plants ( Chakraborty and Tongden, 2005 ). The SA treatment also altered the contents of proteins and proline, significantly with induction of various stress enzymes such as peroxidase (POX), ascorbate peroxidase (APOX), and catalase (CAT) activities ( Chakraborty and Tongden, 2005 ). Abscisic acid also appears to be involved in thermotolerance of chickpea; exogenous ABA application (2.5 μM) at 4 day seedling significantly alleviated the effects of heat stress (45/40°C for 10 days) in chickpea ( Kumar et al., 2013 ) by improving plant growth and reducing oxidative damage. Another study showed that exogenous nitrogen application during pre-flowering and suitable irrigation helped to mitigate the effects of heat stress (>35°C) in chickpea ( Upadhyaya et al., 2011 ). Heat stress (38°C for 10 days) induced the accumulation of raffinose family oligosaccharides (RFOs), such as galactinol and raffinose; galactinol synthase (GolS) is a key regulatory enzyme of RFO biosynthesis. In a recent study, galactinol and raffinose content increased significantly in response to heat stress in chickpea ( Salvi et al., 2017 ).

During heat stress, heat shock genes encode different heat shock proteins (HSPs), which accumulate and protect cells by acting as molecular chaperones ( Huang and Xu, 2008 ). The transcription of HSP genes is controlled by heat stress transcription factors (Hsfs), which play a prominent role in thermo tolerance ( Kotak et al., 2007 ). The recent identification of 22 Hsfs genes in the chickpea genome (both desi and kabuli) has provided valuable information on thermo tolerance in chickpea ( Chidambaranathan et al., 2018 ). Quantitative PCR (Q-PCR) expression analysis of Hsfs in heat-stressed (> 35°C for 3 h) chickpea at two stages of development (15-day-old seedlings and during podding) revealed that CarHsfA2, A6 , and B2 were up-regulated at both the stages of growth and four other Hsfs ( CarHsfA2, A6a, A6c, B2a ) showed early transcriptional up-regulation ( Chidambaranathan et al., 2018 ). A previous study identified three distinct classes of Hsfs (A, B, and C) ( Lin et al., 2014 ).

Various other heat-responsive proteins induced by heat stress (42/25°C for 8 days), exclusively in the heat-tolerant chickpea genotype, may play a vital role in heat tolerance ( Parankusam et al., 2017 ). A recent study identified a set of 482 heat-responsive proteins and several metabolic proteins, including phenylalanine ammonia lyase 2-like, pectinesterase 3, cystathionine gamma-synthase, monodehydroascorbate reductase, adenosyl methionine synthase, NADH dehydrogenase subunit, cytochrome b6, inositol-3-phosphate synthase, RNA polymerase, and ATP synthase subunit alpha protein that were strongly related to the heat response in chickpea ( Parankusam et al., 2017 ). Understanding the differential role and expression of these proteins in chickpea genotypes will provide an important vision for mechanisms that confer thermotolerance in chickpea.

Transcription factors (TFs) play an important role in modulating cellular responses under different stress conditions by activating the transcription of target genes. WRKY TFs are a major family of transcriptional regulators in plants that influence the stress tolerance mechanism and form an integral part of cell signaling pathways ( Agarwal et al., 2011 ; Chen et al., 2012 ). In chickpea, TFs for heat tolerance have been reported [ CaMIPS1 and CaMIPS2 ( Kaur et al., 2008b ) and Ca_02170, Ca_16631, Ca_23016, Ca_09743, Ca_25602] ( Agarwal et al., 2016 ). Recently, a genome-wide analysis of a WRKY TF gene model revealed the presence of 78 WRKY TFs evenly distributed across eight chromosomes in chickpea ( Kumar et al., 2016 ). Car-WRKY TF is reportedly multi-stress responsive, playing a central role in stress signal transduction pathways ( Konda et al., 2018 ). In the chickpea genome, seven genes were identified based on homology, PIE1 (photoperiod independent early flowering 1), ARP6 (actin-related protein), two SEF (serrated leaf and early flowering), and three H2AZs (histone 2A variant-Z, a thermosensor in plants) and analyzed for expression under heat stress (37°C) that are homologous to chromatin remodeling complexes (SWR1) in Arabidopsis ( Chidambaranathan et al., 2016 ). Of the seven genes, PIE1 was up-regulated during podding but downregulated at the seedling stage. Higher tissue-specific expression of PIE1 and SEF genes was observed in root, flower, pod wall, and grain tissues than in shoots. During pod development, all three H2AZ genes might function as thermosensors, with greater downregulation within 15 min, 1 and 6 h of the heat stress treatment ( Chidambaranathan et al., 2016 ).

Mechanisms For Improving Heat Tolerance

The damage from high-temperature stress mainly depends on the plant's defense response and the growth stage at the time of exposure ( Farooq et al., 2017 ). Chickpea plants use adaptive strategies to avoid, escape, and tolerate heat stress ( Wery et al., 1993 ; Toker et al., 2007 ). Leaves avoid the heat by changing orientation, reducing transpiration, and reflecting light ( Wery et al., 1993 ). In heat-stressed chickpea plants, phenology was accelerated as days to flowering and podding decreased significantly at 35/20°C ( Kaushal et al., 2013 ), which also reduced total plant biomass. Therefore, accelerated phenology may be detrimental to chickpea production and considered an escape mechanism. Early maturation is closely correlated with reduced yield losses ( Jumrani et al., 2017 ). In chickpea, a simple and cost-effective field screening method for heat tolerance at the reproductive stage was developed by delayed sowing ( Krishnamurthy et al., 2011 ), which enable the plants to expose to high temperatures (>35°C) during reproductive phase; accordingly, the number of filled pods per plant in late-sown crop as identified as a selection criterion for reproductive-stage heat tolerance. Recent research has suggested that heat stress tolerance indices mean productivity, geometric mean productivity, yield index, tolerance index (TOL), superiority measure, and stress susceptibility index can be used to identify chickpea genotypes based on grain yield under normal and heat-stressed conditions. Based on these selection indices, RVG 203, RSG 888, GNG 469, IPC 06-11, and JAKI 9218 had moderate to high heat tolerance ( Jha et al., 2018a ). Using a heat tolerance index (HTI), ICC 3362, ICC 12155, and ICC 6874 were identified as heat-tolerant lines ( Krishnamurthy et al., 2011 ). Upadhyaya et al. (2011) identified ICC 14346 as a heat-tolerant genotype among 35 early maturing germplasm under ideal crop management (irrigation, nitrogen application) conditions in a field screening at Patancheru (India), based on grain yield (kg ha –1 ). The pollen selection method and pollen viability were used to confirm the heat tolerance in ICCV 92944 ( Devasirvatham et al., 2012 ), ICC 1205, and ICC 1561 ( Devasirvatham et al., 2013 ). Heat-tolerant chickpea genotypes are listed in Table 1 .

Table 1 List of chickpea genotypes tolerant to heat, cold, and drought stress.

Various physiological traits—such as stomatal responses, membrane thermostability, chlorophyll fluorescence (CFL), canopy temperature depression (CTD)—have been associated with heat tolerance ( Priya et al., 2018 ). Stomatal responses to heat stress is one possible mechanism for heat adaptation in chickpea; in a recent study, stomatal conductance and leaf water content (RWC) were significantly lower in heat-sensitive genotypes, relative to the unstressed plants, and significantly higher in tolerant genotypes, when grown under HS environment (>32/20°C) ( Kaushal et al., 2013 ). Therefore, it can be assumed that stomatal conductance plays an important role during heat stress. Membrane thermostability is another important trait for heat tolerance, which has been considered a possible selection criterion for heat tolerance in chickpea, faba bean, and lentil based on electrolyte leakage from the leaves ( Ibrahim, 2011 ). When tissues are subjected to high temperatures, electrical conductivity increases due to damage to cell membranes, consequently resulting in solute leakage. Electrolyte leakage increased under high temperature (>32/20°C) in a heat-sensitive chickpea genotype, relative to a heat-tolerant genotype ( Kaushal et al., 2013 ; Parankusam et al., 2017 ). Thermal techniques have been used to measure canopy temperature; genetic variability in CTD (canopy temperature depression) was reported in chickpea under high temperature (32–35°C) ( Devasirvatham et al., 2012 ), which correlated with yield. The genotypes with lower CTD (1–3°C) had lower grain yields than those with higher CTD (> 4°C) ( Devasirvatham et al., 2015 ).

Effects of Drought in Chickpea

Chickpea is predominantly grown in resource-poor, arid, and semi-arid regions under rainfed conditions. Consequently, drought stress can decrease chickpea yields by up to 50% ( Sabaghpour et al., 2006 ). Drought stress impairs key physiological and biochemical processes ranging from photosynthesis, CO 2 availability, cell growth, respiration, stomatal conductance, to other essential cellular metabolisms ( Mansfield and Atkinson, 1990 ; Chaves, 1991 ; Chaves et al., 2003 ; Flexas et al., 2005 ; Chaves et al., 2009 ; Pinheiro and Chaves, 2011 ).

In subtropical (South Asia and north-eastern Australia) and Mediterranean climatic regions (such as southern Australia), chickpea faces “terminal drought” during the reproductive phase ( Leport et al., 1999 ; Siddique et al., 1999 ), which can seriously impair reproductive processes, viz. anthesis, pollination, and also causes malfunction of reproductive organs especially pollen germination, pollen viability, fertility, and pollen tube growth and even dysfunction of stigma and style ( Leport et al., 1998 ; Leport et al., 1999 ; Pang et al., 2017 ). However, drought stress at young plant stage or prior to reproduction is not uncommon. Drought at young plant stages reduces plant growth leading to stunting and reduced biomass accumulation ( Siddique et al., 1999 ). Water deficit during podding in chickpea increased ABA that may impair pod set and cause pod abscission which can ultimately cause significant yield losses ( Pang et al., 2017 ). Drought stress in chickpea can also lead to the collapse of symbiotic N2 fixation processes, resulting in serious yield losses ( Wery et al., 1993 ).

Genetic Variability for Capturing Drought Stress Tolerance in Chickpea

The exploitation of natural genetic variation across various crop gene pools remains central to improving drought stress tolerance in crops, including chickpea. Considerable genetic variability for drought stress tolerance in chickpea has been recorded for various morpho-physiological and grain yield-related parameters under contrasting water regimes in the field ( Krishnamurthy et al., 2010 ; Jha et al., 2014 ; Pang et al., 2017 ). Simple field-based screening techniques and superior crop yield performance has identified several chickpea genotypes under non-stressed and water stress conditions ( Singh et al., 1997b ; Toker and Cagirgan, 1998 ; Canci and Toker, 2009 ). Likewise, stress tolerance indices viz. drought susceptibility index and drought tolerance index, identified significant genetic variability for various phenological and yield-related traits under water stress in a large mini-core collection of 211 accessions ( Krishnamurthy et al., 2010 ) ( Table 1 ).

Considering the role of wild species as an important reservoir for imparting drought tolerance, Cicer anatolicum , Cicer microphyllum , Cicer songaricum are worth mentioning ( Toker et al., 2007 ). Likewise, Kashiwagi et al. (2005) identified chickpea landraces in the Mediterranean, west Asian, and central Asian regions with high genetic variability for root length density that could be exploited for developing high water-use-efficient chickpea genotypes under water stress. Water use efficiency (WUE) is an important strategy for drought tolerance in crop plants, including chickpea ( Condon et al., 2004 ; Zaman-Allah et al., 2011a ; Zaman-Allah et al., 2011b ), where a significant amount of genetic variability has been recorded ( Pang et al., 2017 ). The authors identified “Neelam” as drought tolerant genotype, based on high WUE, as this genotype used a “conservative water use strategy” to maintain higher seed yields under water stress during early growth.

Root architecture traits are important parameters for improving crop performance under drought stress ( Wasaya et al., 2018 ; Ye et al., 2018 ). Considerable progress has been made in elucidating the role of various root traits for drought stress tolerance in chickpea ( Kashiwagi et al., 2006a ; Kashiwagi et al., 2015 ). How root biomass, root length, and other root-related parameters, such as root length density (RLD), total root dry weight (RDW), and deep root dry weight (deep RDW), contribute to drought stress tolerance has been investigated in chickpea ( Krishnamurthy et al., 2003 ; Kashiwagi et al., 2005 ; Gaur et al., 2008 ; Kashiwagi et al., 2008 ; Kashiwagi et al., 2015 ; Purushothaman et al., 2016 ; Chen et al., 2017 ). A significant amount of genetic variability for RLD in the mini-core collection and wild species of chickpea has been reported ( Kashiwagi et al., 2005 ). Given their larger RLD, deep rooting system, and higher root biomass production, ICC 4958 and ICC 8261 genotypes are used extensively as donors for transferring important drought adaptive root traits to elite chickpea cultivars to develop drought-resilient chickpea cultivars ( Saxena et al., 1993 ; Gaur et al., 2008 ). In addition, ICC 4958 remains one of the most extensively studied chickpea genotypes both in classical and modern molecular breeding programs for dissection of various traits, including drought-stress-related root traits.

Thus, these genotypes (ICC 4958 and ICC 8261) have been steadily incorporated into drought tolerance breeding programs for transferring the above-mentioned traits into elite chickpea varieties and developing mapping populations for deciphering drought-tolerant QTLs ( Gaur et al., 2012 ). Concurrently, efforts are underway to develop multi-parent advanced generation inter-cross populations (MAGIC) by incorporating ICC 4958, JG 130, ICCV 10, JAKI 9218, JG 130, JG 16, ICCV 97105, and ICCV 00108, genotypes possessing drought and heat tolerance genomic regions/QTLs ( Devasirvatham and Tan, 2018 ). Thus, selection from the resultant crosses could increase genetic gain in chickpea. Moreover, Chen et al. (2017) provided scope for improving drought tolerance in chickpea by investigating 30 root-related traits and three shoot-related traits in a large set of 270 core collection. 13 C discrimination, an important physiological selection parameter related to water stress could also be used to enhance WUE under drought stress ( Condon et al., 2002 ). A significant amount of genetic variability for 13 C discrimination has been recorded in the chickpea reference germplasm collection (n = 280) ( Upadhyaya et al., 2008 ; Krishnamurthy et al., 2013b ).

Advancements in breeding techniques such as MAGIC have enabled the transfer of drought- and heat-tolerant traits into elite high-yielding chickpea cultivars by combining favorable allele combinations for drought and heat tolerance ( Gaur et al., 2014 ; Gaur et al., 2019 ). Furthermore, marker-assisted recurrent selection (MARS) and marker-assisted backcrossing (MABC) efforts have been successfully used to transfer a “ QTL-hotspot ” genomic region harboring important drought-tolerant-related traits from donor parent ICC 4958 to JG 11 elite cultivar ( Varshney et al., 2016 ).

Role of Physiological Traits for Adaptation Under Drought and Heat and Increasing Future Genetic Gain in Chickpea

Direct phenotypic selection for yield and yield-related traits has led to ignoring various important physiological traits that have great potential for increasing genetic gain and significantly contributing to plant acclimation under various abiotic stresses ( Reynolds and Langridge, 2016 ). The incorporation of “physiological traits” in crop breeding programs provides an opportunity to enhance the chances of “cumulative gene action for yield” ( Cossani and Reynolds, 2012 ). However, the success of incorporating various physiological traits depends on how the traits are associated with grain yield, their heritability, their ease of selection response and measurement, and their non-destructive nature ( Monneveux et al., 2012 ).

Plant withstand drought and heat stress by recruiting “escape,” “tolerance,” and “avoidance” mechanism ( Levitt, 1972 ). In the context, the major physiological traits involved in drought stress adaptation are categorized into “constitutive traits” and “acquired tolerance traits” ( Sreeman et al., 2018 ). The notable “constitutive traits” involved in drought stress adaptation in chickpea include phenology ( Kumar and Abbo, 2001 ), stomatal conductance ( Liu et al., 2003 ), specific leaf area ( Purushothaman et al., 2016 ), leaf area index ( Purushothaman et al., 2016 ), chlorophyll content ( Mafakheri et al., 2010 ), WUE ( Kashiwagi et al., 2006b ), and root traits ( Krishnamurthy et al., 2003 ; Gaur et al., 2008 ; Kashiwagi et al., 2006a ; Kashiwagi et al., 2015 ; Zaman-Allah et al., 2011b ; Purushothaman et al., 2015 ). Likewise, canopy temperature depression (CTD) ( Zaman-Allah et al., 2011a ; Purushothaman et al., 2016 ), proline accumulation ( Macar and Ekmekci, 2009 ; Mafakheri et al., 2010 ), regulation of ABA ( Pang et al., 2017 ), and production of various antioxidant scavenging enzymes ( Macar and Ekmekci, 2009 ) are the major “acquired tolerance” traits involved in drought stress tolerance in chickpea.

Prioritizing early phenology traits, viz . selection for early flowering and maturity, helps in the selection of genotypes exhibiting drought and heat stress tolerance in the form of an escape mechanism ( Canci and Toker, 2009 ; Gaur et al., 2012 ; Hamwieh and Imtiaz, 2015 ). Relying on this mechanism important drought tolerant varieties viz., ICCV 90629, ICCV 2, ICCC 37, ICCV 10 ( Kumar and Abbo, 2001 ), KAK2 ( Gaur et al., 2008 ), and heat tolerant variety ICCV92944 ( Gaur et al., 2012 ) were developed, however they suffered yield penalty due to restricted photosynthetic period, rapid growth rate, high harvest index, and short lifecycle ( Kashiwagi et al., 2015 ; Berger et al., 2016 ).

Shoot Related Traits Contributing in Drought Stress Tolerance

Stomatal conductance (g s ) is an important shoot-related parameter affecting leaf gas and water vapor exchange under stress conditions. Drought stress negatively affects stomatal conductance and leaf turgor ( Liu et al., 2003 ). Zaman-Allah et al. (2011a) and Pang et al. (2017) argued genotype having lower stomatal conductance and utilizing lower water during vegetative stage at well-watered condition displayed higher drought tolerance at reproductive stage by using the conserved soil water at “terminal drought” stress. However, this “water sparing” will be effective for the crops those grow under stored soil water condition ( Vadez et al., 2012 ). Insight into the genetic inheritance of stomatal conductivity and selection for lower stomatal conductance with higher leaf transpiration efficiency under drought could be promising for the development of drought tolerant chickpea genotypes. Likewise, correlations between crop growth rate and transpiration and transpiration efficiency are receiving attention in the development of drought-tolerant chickpea ( Purushothaman et al., 2016 ).

Among the various non-destructive physiological traits, CTD infrared thermometer based parameter acting as a surrogate trait for transpiration explains the difference between air temperature [ T a] and canopy temperature [ T c] ( Balota et al., 2007 ). It has received great attention as a potential selection tool and is regularly employed for screening high yielding drought and heat stress tolerant plants ( Mason and Singh, 2014 ). This parameter depicts plant transpiration status that plays an important role in reducing leaf temperature under both drought and heat stress. Lower canopy temperature is indicative of higher transpiration, which enables plants to maintain their water status for growth under heat stress and water stress ( Zaman-Allah et al., 2011a ). In this context, a positive association of CTD with grain yield was noted under heat stress ( Devasirvatham et al., 2015 ) and under drought stress ( Purushothaman et al., 2015 ) in chickpea. Likewise, under drought stress, cooler canopy temperatures enhance root biomass, root depth, and ultimately grain yield ( Lopes and Reynolds, 2010 ). Thus, further research of CTD at a genetic level could give better insight how to use this traits to develop drought and heat stress tolerance chickpea genotypes.

Role of Water Use Efficiency in Drought Stress Adaptation

WUE defines “biomass accumulated in plant at the cost of per unit water transpired” ( Bacon, 2004 ). An array of traits ranging from stomatal regulation, transpiration rate to root traits could be employed for increasing WUE. Regulation of stomatal opening remains a great paramount importance, as restriction in stomatal opening increases reduction in transpiration leading to enhance WUE ( Saradadevi et al., 2017 ). In this context, Zaman-Allah et al. (2011a) opined that lower stomatal conductance and lower transpiration could save water to be utilised during reproductive period under “terminal drought” stress in chickpea. However, reduction in stomatal opening causes lower intake of CO 2 that may lead to decrease in photosynthetic carbon accumulation ( Vadez et al., 2012 ). This mechanism of water stress tolerance works well when chickpea is grown in high water holding capacity soil in the south and central India featuring warmer and shorter growing period for chickpea ( Berger et al., 2006 ; Berger et al., 2016 ). Contrastingly, high transpiration rate, high above and below ground biomass, high seed yield are the characteristics features of chickpea when it is grown under high rainfall receiving areas viz., northern Indian condition with low water holding capacity and with later phenology ( Berger et al., 2006 ; Berger et al., 2016 ). Relying on the result explaining positive correlation of WUE with biomass yield under drought stress, Wright (1996) argued that increase in WUE could promisingly enhance plant yield provided harvest index is maintained.

Likewise, carbon isotope discrimination (Δ 13 C) is a noteworthy physiological attribute for measuring transpiration efficiency/WUE of plants under drought or heat stress. Kashiwagi et al. (2006b) suggested a negative correlation between Δ 13 C and WUE. However, its high cost of measurement remains a barrier to measuring WUE in larger numbers of genotypes. Thus, future genetic and molecular studies targeting traits improving WUE and optimizing transpiration rate could be beneficial in developing drought tolerant chickpea cultivars.

Role of Root Traits Contributing Drought Adaptation

Root system architecture is an important parameter that directly controls plant water content, which influences crop performance under water stress ( Ye et al., 2018 ). Besides, root senses drought stress under dry soil and signals to produce ABA that causes closure of stomata resulting restriction of water loss through transpiration ( Saradadevi et al., 2017 ). The crucial role of root traits, viz. RLD, root biomass, total RDW, root diameter, root volume, and root surface area, in controlling plant water status and how they help chickpea to adapt to water stress has been investigated ( Krishnamurthy et al., 2003 ; Gaur et al., 2008 ; Kashiwagi et al., 2006a ; Zaman-Allah et al., 2011b ; Kashiwagi et al., 2015 ; Purushothaman et al., 2015 ). Mostly root traits play critical role in drought adaptation in chickpea by facilitating mining water through deep root and minimizing transpiration under water stress ( Berger et al., 2016 ). In order to elucidate the role of root traits contributing in grain yield, Gaur et al. (2008) showed higher RLD and maximum root depth (RDp) in shallow soil could assist in increasing seed yield under drought stress. Likewise, Ramamoorthy et al. (2017) also evidenced positive association of RLD and grain yield under drought stress in chickpea. However, positive association of root traits with grain yield under drought stress remains inconsistent across various environment ( Zaman-Allah et al., 2011b ), leading plant breeders reluctant to use this trait in breeding program for drought tolerance. Thus, under central and south Indian condition where chickpea faces “terminal drought” stress, root traits based on “drought avoidance” strategy could be a promising approach for designing drought tolerant chickpea varieties ( Kashiwagi et al., 2015 ). However, when chickpea grown under “in-season rainfall” in low water holding capacity soil under Mediterranean climates in Western Australia, this “drought avoidance” strategy remains ineffective ( Berger et al., 2016 ).

Response of Biochemicals Alleviating Drought and Heat Stress

Plants including chickpea maintain turgor pressure and cell wall plasticity under water stress through recruiting osmotic adjustment mechanism that allows accumulating crucial biochemical compounds, including proline, glutathione, trehalose, molecular chaperones, and various antioxidant enzymes ( Macar and Ekmekci, 2009 ; Mafakheri et al., 2010 ; Kaushal et al., 2011 ; Berger et al., 2016 ; Kaur et al., 2017 ; Farooq et al., 2018 ). Among the various stress-responsive chemical compounds, proline remains a critical amino acid produced in plants in response to stress. The differential expression pattern of proline synthesis enzyme (Δ1-pyrroline-carboxylate synthetase) and catabolism of proline by proline dehydrogenase in response to water stress at different vegetative and reproductive stages in drought-tolerant and drought-sensitive genotypes has been investigated in chickpea ( Kaur et al., 2017 ). The desi Bakhar-2011 chickpea genotype accumulated more proline, trehalose, and non-reducing sugars to tolerate drought stress more than Bitall-2016 desi genotype by alleviating the adverse effects of oxidative stress and maintaining better carbon assimilation ( Farooq et al., 2018 ). Likewise, to detoxify and to protect cellular damage from reactive oxygen species (ROS) viz., superoxide radicals, singlet oxygen accumulating under drought and heat stress, several ROS scavenging anti-oxidant enzymes such as superoxidase dismutase, catalase, glutathione peroxidase are worth mentioning biochemicals that enable chickpea adapting under drought and heat stress ( Mafakheri et al., 2011 ; Kaur et al., 2017 ). Recently, Ullah et al. (2019) proposed that supply of zinc based nutrition could also assist in enhancing antioxidant activities and alleviate the detrimental effects of drought and heat stress in chickpea. These mechanisms are effective under moderate dehydrating conditions and impart partial drought tolerance ( Farooq et al., 2018 ).

A holistic approach encompassing plant physiological approaches, genomics tools, and innovative breeding techniques for designing drought and extreme temperature tolerant chickpea cultivars has been depicted in Figure 1 .

Figure 1 Integration of genomic approaches with physiological traits for breeding drought and temperature extreme resilient chickpea cultivar.

Advances in Genomics for Developing Drought and Heat Stress Tolerance in Chickpea

Investigating the genomic resources such as simple sequence repeat markers (SSRs) and single nucleotide polymorphism (SNPs) is vital for mapping of genes/QTL as well as for identifying genes related to drought and heat tolerance in QTL intervals. In the last decade, unprecedented advancements in molecular marker development and construction of high-density linkage maps have enabled precise mapping of various traits of breeding interest at specific locations across linkage groups in chickpea ( Thudi et al., 2011 ; Jha et al., 2018b ). Considering drought and heat stress tolerance, family-based bi-parental mating scheme derived mapping populations were limitedly devoted to elucidating QTLs controlling traits associated with various morpho-physiological and yield and yield-related traits under drought and heat stress in chickpea ( Rehman et al., 2011 ; Hamwieh et al., 2013 ; Paul et al., 2018 ). However, the resultant QTL intervals remained large. Additionally, precise mapping of drought stress tolerance QTL remains challenging as it is controlled by various “minor effect QTLs” and remains unstable across the various locations due to high G×E interaction ( Fleury et al., 2010 ). Increasing facilities of high density genotyping with large number of SSR markers and precise phenotyping of two mapping population segregating for various drought-related traits across multiple locations and multiple seasons allowed Varshney et al. (2014) to identify a “QTL-hotspot” harboring 13 main effect QTLs related to 12 drought-related traits, which explained up to 58% of the phenotypic variation on CaLG4. Subsequently, by adopting a marker-assisted backcross breeding scheme, this QTL-hotspot genomic region was introgressed from ICC4958 into JG11, an elite chickpea cultivar ( Varshney et al., 2016 ). The resultant introgressed lines had greater root depth, RLD, and RDW ( Varshney et al., 2016 ). However, this marker assisted breeding scheme remains effective for transferring “major effect QTLs” ( Hayes et al., 2009 ). Further, advancements in next-generation sequencing technology (NGS) and high resolution genotyping platforms enabled the generation of huge numbers of SSR and SNP markers that assisted in narrowing the previously identified QTL-hotspot ( Varshney et al., 2014 ) region to ~14 cM by recruiting genotyping-by-sequencing ( Jaganathan et al., 2015 ). Furthermore, the combination of high density bin mapping and precise phenotyping of 17 drought-related traits across multiple locations and seasons further narrowed the QTL-hotspot region to ~300 Kb, and subdivided this genomic region into “ QTL-hotspot_a ” and “ QTL-hotspot_b ” regions on CaLG4 ( Kale et al., 2015 ). Interestingly, QTLs contributing to plant vigor and canopy conductance under water stress were unfolded in this genomic region ( Sivasakthi et al., 2018 ). Likewise, a total of four major QTLs developed from ICC 15614 × ICC 4567 RIL population controlling pod and grain yield trait were mapped on CaLG5 and CaLG6 under heat stress ( Paul et al., 2018 ). Future cloning and functional characterization of these genomic regions could unravel the function of underlying gene(s), and thus facilitating designing of drought and heat stress tolerant chickpea genotypes.

Taking the advantage of higher resolution power of mapping complex QTLs owing to “natural evolutionary recombination events” genome-wide association study (GWAS) received great attention for unveiling “genotype-phenotype” associations elucidating the underlying novel candidate gene(s) controlling various complex traits including drought stress tolerance across large germplasm panel in various crop plants ( Zhu et al., 2008 ; Huang and Han, 2014 ; Liu and Yan, 2019 ). In chickpea, GWAS has been used to better understand the genetic architecture of various complex traits of breeding importance [see Jha (2018) ]. To elucidate marker-trait associations (MTA) for drought-related traits, Thudi et al. (2014) conducted GWAS in a large global collection of 300 chickpea genotypes. A total of 312 significant MTAs related to various drought and heat stress-related traits were identified providing a great opportunity for targeting those genomic regions for drought and heat stress tolerance breeding ( Thudi et al., 2014 ). Similarly, five significant MTAs for cell membrane stability and chlorophyll content related to heat stress tolerance were deciphered from 71 chickpea genotypes containing historically released varieties of Indian and improved breeding lines ( Jha et al., 2018b ). Likewise, recently given the 3.65 million SNPs emanating from resequencing 429 globally collected chickpea germplasm, GWAS was used to elucidate significant MTAs for drought and heat stress tolerance in chickpea ( Varshney et al., 2019 ). A total of 262 significant MTAs for various heat stress relevant traits, along with several potential candidate genes, viz. TIC , REF6 , aspartic protease, cc-NBS-LRR , RGA3 contributing in heat and drought tolerance were uncovered. Thus, the consistent and stable significant MTAs/genomic regions controlling pods/plant, yield trait, and phenological traits could be potentially incorporated in the high yielding yet drought/heat stress sensitive popular chickpea cultivars for improving drought and heat stress in chickpea.

Unparalleled advances in cost-effective genotyping platforms have enabled the generation of large-scale SNP marker information using WGS and WGRS of globally released chickpea cultivars, breeding lines, and germplasm accessions ( Varshney et al., 2013b ; Thudi et al., 2016 ; Roorkiwal et al., 2018a ; Varshney et al., 2019 ). This has provided opportunities for the chickpea breeding community to use genomic selection (GS) ( Meuwissen et al., 2001 ; Jannink et al., 2010 ) for various complex traits including drought stress tolerance ( Roorkiwal et al., 2016 ; Li et al., 2018 ; Roorkiwal et al., 2018b ). To date, several conventional breeding approaches have been devoted to increasing genetic gain by selecting superior individuals in chickpea under various biotic and abiotic stresses, including drought stress. However, this process remains slow due to yield and yield-related traits being governed by “small effect QTLs,” low heritability, and the influence of G × E interactions. GS could be one of the promising approaches to minimize this problem. GS constitutes “training population” with known genotypic and trait information, and is used to predict the genomic estimated breeding value of unobserved individuals of “candidate population” for complex traits with only genotypic information byusing various “trained statistical”/prediction models ( Meuwissen et al., 2001 ; Jannink et al., 2010 ). Thus, the adoption of GS scheme could be a new avenue for capturing the “minor effect QTLs” across the whole genome and predicting increased genetic gain based on various prediction models under water stress in various crops, including chickpea ( Hayes et al.2009 ; Crossa et al., 2017 ). The profuse numbers of SNP markers generated from 132 chickpea genotypes by WGRS allowed to conduct “SUPER GWAS” for unveiling the candidate genes associate to drought stress tolerance and also the sub set of SNPs were also used for performing GS for “prediction accuracy” of important yield related traits under drought stress ( Li et al., 2018 ). Subsequently, Roorkiwal et al., 2018b investigated the implications of GS for precise prediction accuracy of genotypes incorporating G × E effects to enable selection of superior genotypes under various target environments for enhanced genetic gains in chickpea. However, the success of GS relies on high marker density, advanced genotyping platforms, heritability of trait, and optimization of the statistical model frameworks devised for GS ( Roorkiwal et al., 2018a ; Voss-Fels et al., 2019 ). Therefore, GS has great scope for selecting superior parents for crossing programs, maximizing selection accuracy, multi-trait selection in early generation, and speeding up the breeding cycle ( Hayes et al., 2009 ; Jia and Jannink, 2012 ; Crossa et al., 2014 ; Crossa et al., 2017 ; Dias et al., 2018 ).

The arrival of NGS technologies in the last decade created a new dimension in genome sequencing chemistry, enabling the release of draft genome sequences of various plants of agricultural and economic importance ( Michael and Jackson, 2013 ). The availability of draft genome sequences of kabuli ( Varshney et al., 2013b ), desi ( Jain et al., 2013 ), and wild species ( Parween et al., 2015 ) has sped up genomics research in chickpea. However, these genome sequences do not capture all the structural variations and presence–absence variation related to various traits. Falling cost of sequencing allowed us to sequence several genotypes/lines at a reasonable cost to capture the desired genomic regions. To obtain novel insight into drought-controlling genomic regions, WGRS of 100 chickpea genotypes has provided several important haplotypes that control drought stress tolerance ( Thudi et al., 2016 ). Subsequently, Li et al. (2018) have unfolded significant associations of SNP markers released from WGRS of 132 chickpea lines with important drought tolerance candidate genes encoding auxin efflux carrier protein (PIN3), p-glycoprotein (PGP), and nodulin MtN21/EamA-like transporter. Recent efforts in WGRS of global chickpea germplasm coupled with GWAS have identified several drought-stress-controlling genomic regions (root traits, phenological traits, harvest index, 100 seed weight, delta carbon ratio etc.), including an important candidate gene REF6 responsible for early phenology trait ( Varshney et al., 2019 ). Further cloning and functional validation of this REF6 gene and transfer of this gene through marker assisted breeding could help developing drought tolerant chickpea cultivar based on drought escape mechanism. Thus, translation of these genomics resources into applied breeding could expedite designing drought-tolerant chickpea varieties.

Functional Genomic Resources for Drought and Heat Stress Tolerance

Functional genomics remains a powerful approach for identifying the underlying candidate gene(s) and deciphering their functional role in response to various stresses including drought and heat stress in plant ( Langridge et al., 2006 ). This approach can be employed in chickpea genotypes contrasting for stress sensitivity to obtain critical information about specific genes and their roles related to drought and heat tolerance. A significant progress in the development of genomic resources for dissection of drought and heat stress tolerance has been made ( Varshney et al., 2014 ; Jaganathan et al., 2015 ; Kale et al., 2015 ; Varshney et al., 2016 ; Paul et al., 2018 ). However, the role of various candidate genes and their complex regulatory networks controlling drought and heat tolerance in chickpea at the functional level is limited ( Hiremath et al., 2011 ; Agarwal et al., 2016 ; Garg et al., 2016 ); the information available about functional genomics largely pertains to drought tolerance.

Current advances in high throughput transcriptome sequencing technologies, especially RNA sequencing (RNA-seq), have provided novel insights into the molecular basis of drought tolerance by revealing the comprehensive landscape of divergent gene expression and their complex regulatory networks at various developmental stages at the transcriptional level ( Garg et al., 2016 ; Kudapa et al., 2018 ). Before the advent of RNA-seq, microarray-based technologies and expressed sequenced tags (ESTs) were exclusively devoted to elucidating the preliminary function of various drought-stress-responsive genes/differentially expressed genes (DEGs) in chickpea ( Mantri et al., 2007 ; Varshney et al., 2009 ; Deokar et al., 2011 ). Subsequently, given the RNA-seq driven global transcriptome analysis, a large number of water stress responsive DEGs (4954) were unearthed from root tissues of two contrasting drought tolerant (ICC 4958) and drought sensitive (ICC 1882) parents responding under water stress condition ( Garg et al., 2016 ). Various DEGs identified under drought stress were found to be drought responsive TFs genes involved in controlling various hormone signaling ranging from abscisic acid, auxin, gibberellins, jasmonic acid, brassinosteroid to cytokinin ( Garg et al., 2016 ; Badhan et al., 2018 ). Likewise, recently transcriptome sequencing of root and shoot tissue of two contrasting parents Bivanij and Hashem for drought resulted in 4,572 DEGs ( Mahdavi Mashaki et al., 2018 ). From this investigation a total of seventeen common drought responsive genes from shoot and root were recovered. Importantly, to elucidate the role of candidate genes responding under drought stress, Bhattacharjee et al. (2015) reported higher up-regulatory role of Ca_19899 (homeobox gene) in shoot tissue and down-regulatory role of Ca_00550 gene both in root and shoot under drought stress. To mitigate the toxic effect of ROS activity produced under drought stress, Mahdavi Mashaki et al. (2018) unveiled up-regulatory activity of three genes (in Hashem) and Ca_04125 gene (in Bivanij) involved in safeguarding cells against ROS toxicity. Likewise, up-regulatory activity of Ca_05702 gene (participating in flavonoid biosynthesis), CaNAC16 (Ca_18090 ) (involved in water stress tolerance) and Ca_00449 (carotenoid biosynthesis and producing ABA contributing in drought stress tolerance) in shoots of Bivanij under water stress were also substantiated ( Mahdavi Mashaki et al., 2018 ). Additionally, participatory role of several TFs genes ranging from NAC, AP2/ERF, bHLH, WRKY, to MYB/MYC in essential metabolic pathways were also deciphered in chickpea under drought stress ( Badhan et al., 2018 ; Mahdavi Mashaki et al., 2018 ; Kumar et al., 2019 ).

Furthermore, to identify the precise role of various candidate genes identified in the “hotspot QTL” region pinpointed by Kale et al. (2015) at the gene expression level, RNA-seq based global gene expression analysis revealed differential expression of nine candidate genes under water stress ( Kudapa et al., 2018 ). Four genes namely E3 ubiquitin‐protein ligase , LRX 2, kinase interacting (KIP1‐like) family, and homocysteine S‐methyltransferase , displayed induced expression under drought stress ( Kudapa et al., 2018 ). Likewise, RNA-seq analysis of various vegetative and reproductive tissues subjected to heat stress identified several important candidate genes, viz. Ca_25811, Ca_23016, Ca_09743, Ca_17680 , contributing in heat-stress tolerance ( Agarwal et al., 2016 ).

Similarly, non-coding RNA, including microRNA and long non-coding RNA (lncRNA), have received attention for their regulatory role in the expression of various genes controlling complex traits at the post-transcriptional level, including for drought stress in chickpea ( Khandal et al., 2017 ; Singh et al., 2017 ). A microRNA (miRNA) profiling study of root apical meristem identified 284 unique miRNA sequences; of which 259 were differentially expressed under drought and salinity stress ( Khandal et al., 2017 ). Functional validation of miRNA397 through qRT-PCR revealed its up-regulatory role under drought stress and it targeted LACCASE4 gene that participate in lignin metabolism. To obtain deeper insight into the role of lncRNA for drought, a new tool “PLncPRO” was developed ( Singh et al., 2017 ). A total of 3,714 lncRNAs involved in drought stress response in rice and chickpea have been discovered using this tool. However, the precise role of these lncRNAs in the drought stress response in chickpea and their functional annotation need further investigation. Further, availability of reference genome sequences, “ C. arietinum gene expression atlas (CaGEA)” ( Kudapa et al., 2018 ) and further refinement of transcriptome analysis could further increase our understanding of the complex drought and temperature stress responsive pathways, tracing the regulatory gene networks, and the underlying candidate gene(s), and their precise role in controlling drought and extreme temperature stress tolerances in chickpea. Moreover, transcriptome analysis could provide us great opportunity for revealing the genetic basis of higher adaptation of crop wild relatives (CWRs) and landraces to the counterpart of the cultivated species under various abiotic stresses ( Srivastava et al., 2016 ). However, limited availability of abiotic stress tolerant cloned gene(s) has hampered the progress of functional genomics in chickpea ( Deokar et al., 2015 ; Sen et al., 2017 ). Thus, in future mapbased cloning of abiotic stress tolerant gene(s)/QTLs could further illuminate our understanding of various mechanisms and key molecular players involved in drought, heat and cold tolerance in chickpea.

Conclusion and Future Perspective

Current trends of unpredictable global climate change have resulted in periodic spells of drought stress and frequent episodes of extreme temperature, thus challenging plant growth and yield in several crops, including chickpea. Harnessing of crop germplasm, including various gene pools remains one of the most viable options in design of climate-resilient chickpea plants. Cicer cultigens are not adequately equipped with cold-tolerance; wild relatives C. echinospermum or C. reticulatum , the species of primary gene pool which are crossable to the cultigen, are however, good sources of cold tolerance. These species can be exploited to introgress cold tolerance to the cultigen. Incorporation of cold-tolerance in winter sown crop will lead to early flowering and maturity, a strategy that would allow the crop to avoid terminal drought, expected terminal high temperature due to global warming especially in winter/autumn sown crop and would increase reproductive period leading to enhanced productivity. Chickpea has indeterminate growth, and observations at two sites in north India (Palampur and Chandigarh, India) showed that temperature increase acts as a cue to terminate flowering and podding (Sharma and Nayyar, personal observations). If temperature remains conducive, chickpea plants would continue to flower and set pods due to indeterminate growth habit and this period can be increased by introgression of cold tolerance in chickpea. On the other hand, chickpea in warmer climates especially the spring-sown regions is expected to face higher terminal temperatures and high temperature tolerant chickpea must be developed for these regions for sustained productivity under global warming. Incorporation of drought tolerance in the cold tolerant as well as heat tolerant cultivars would be desirable as such dual tolerance chickpea would have additional protection from damage by drought apart from cold or heat stress.

Unlike cold-tolerance, heat-tolerant chickpea genotypes are relatively common to find in C. arietinum . In both types of temperature stresses, reproductive stage is the most sensitive one, and fails for similar reasons. Some cellular defense mechanisms such as osmolytes, carbohydrates, and antioxidants have been worked out by us under both heat and cold stress environments, which showed commonalities in their expression in responses to both the stresses but the picture fully clear in this context. Physiological mechanisms under combination of drought and heat as well as drought and cold are not fully understood. Further, it needs to be investigated whether heat-tolerant genotypes set pods under cold stress by subjecting them to LT under controlled environment, and testing their reproductive function and pod set. In case of cross tolerance, cellular defense mechanisms involving some stress-related metabolites and related genes may be probed to understand the underlying mechanisms. Since chickpeas have maximum acreage under rainfed and leftover soil moisture conditions and the crop invariably faces droughts at reproductive stage, this coupled with expected erratic rainfall under climate change scenarios warrants development of drought tolerant varieties. Terminal drought usually coincides with terminal heat stress in several chickpea growing regions, and hence, development of heat and drought tolerant chickpea cultivars is desired. Incorporation of various landraces and a range of crop gene pool harboring “adaptive traits” could enhance the resilience of chickpea genotypes under extreme climates.

Considerable understanding of physiological responses of genotypes of chickpea tolerant/sensitive to cold, heat, and drought is available, this understanding have, however, not been underpinned completely by the genetics/genomics. Genomics and transcriptomics have increased our understanding of gene and gene regulatory networks governing cold, drought, and heat stress, the understanding is, however, incomplete as it does not converge into well defined pathways governing tolerance or susceptibility to these three major abiotic stresses of chickpea. Unlike chickpea, we have considerably more information of plants' responses to various abiotic stresses in Arabidopsis thaliana . To identify well defined regulatory pathways for abiotic stress tolerance/sensitivity in chickpea, focus should be on establishment of role of individual genes identified through transcriptomics/genomics in tolerance or sensitivity and advancing this knowledge gradually to elucidate some specific as well as common responses of chickpea plants to these abiotic stresses. Owing to advancements in genomics in chickpea, QTLs/genes governing tolerance to the three abiotic stress traits and preliminary information on genes/gene interactions governing susceptibility/tolerance to these traits is available. The DNA-based markers, despite accelerated development during the last decade, are still inadequate and further enrichment of genomic resources for marker assisted selection is required so that adequately dense genetic maps be developed to map all the possible traits and narrow down the QTL boundaries in case of quantitative traits such as cold, drought, and heat stress tolerance. Considering drought stress, a “ QTL-hotspot ” harboring root and various drought related trait has been introgressed into elite chickpea genotype ( Varshney et al., 2016 ). However, the other minor QTLs need to be pyramided individually or in combination for developing drought and heat tolerant elite chickpea varieties. Chickpea breeders still rely primarily on phenotypic selection for progeny plants while marker assisted selection (MAS) remained an underutilized technology even for monogenic traits like Fusarium wilt. Similarly, gene/QTL pyramiding has not been exploited in chickpea. Clearly, marker technology in chickpea is still in the laboratory stage waiting to be exploited commercially. Nonetheless, genomic resources such as markers linked to phenotypic traits and genes governing several traits are already known and this knowledge is expanding rapidly e.g., sequencing and resequencing approaches have increased repertoire of SNP markers during the last decade. This information indicates toward possible exploitation of genomic selection for phenotypic traits for chickpea in future.

Future research must aim at developing designer chickpea cultivars that can tolerate combination of stress environments, such as heat and drought, and cold and drought, to expand its stress tolerance ability along with superior agronomic performance. Exploitation of genomics/transcriptomics/resequencing coupled with reference genome sequences in chickpea, are expected to enhance our understanding of cold, heat and drought stress tolerance that in near future will boost development of single- or multiple stress tolerant high-yielding chickpea cultivars suited to specific climatic niches. This knowledge may consequently result in development of better and economical stress management options based on chemical/agronomic means, apart from host resistance, to enable us to deal with unexpected climatic contingencies.

Author Contributions

AR and KDS compiled information about cold stress, and PD and UJ about heat and drought stress. KHM and HN thoroughly edited the manuscript and gave their inputs in organizing the text.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

HN thanks Department of Science and Technology (DST), Department of Biotechnology (DBT), University grants commission (UGC), CGIAR, University of Western Australia of supporting work on cold and heat stress in chickpea. Thanks are also to DST-PURSE grants for research facilities. HN is also thankful to Punjab Agricultural University (PAU), Ludhiana, India, and ICRISAT for providing chickpea germplasm. KS is thankful to Department of Biotechnology (DBT), India for supporting the work on cold stress in chickpea.

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Keywords: chickpea, water limitation, high temperature, tolerance, genomics

Citation: Rani A, Devi P, Jha UC, Sharma KD, Siddique KHM and Nayyar H (2020) Developing Climate-Resilient Chickpea Involving Physiological and Molecular Approaches With a Focus on Temperature and Drought Stresses. Front. Plant Sci. 10:1759. doi: 10.3389/fpls.2019.01759

Received: 12 June 2019; Accepted: 16 December 2019; Published: 25 February 2020.

Reviewed by:

Copyright © 2020 Rani, Devi, Jha, Sharma, Siddique and Nayyar. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Harsh Nayyar, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Exploring Chickpea Germplasm Diversity for Broadening the Genetic Base Utilizing Genomic Resourses

Rajesh kumar singh.

1 Indian Agricultural Research Institute (ICAR), New Delhi, India

Charul Singh

2 University School of Biotechnology, Guru Gobind Singh Indraprastha University, New Delhi, India

3 Department of Genetics and Plant Breeding, University of Agricultural Sciences, Bangalore, Bangalore, India

B. S. Chandana

Rohit k. mahto, ranjana patial.

4 Department of Agricultural Sciences, Chandigarh University, Mohali, India

Astha Gupta

5 School of Agricultural Sciences, Sharda University, Greater Noida, India

Vijay Gahlaut

6 Institute of Himalayan Bioresource Technology (CSIR), Pālampur, India

7 National Bureau of Plant Genetic Resources (ICAR), New Delhi, India

Aladdin Hamwieh

8 International Center for Agriculture Research in the Dry Areas (ICARDA), Giza, Egypt

H. D. Upadhyaya

9 Department of Entomology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India

10 Plant Genome Mapping Laboratory, University of Georgia, Athens, GA, United States

Rajendra Kumar

Muhammad Azhar Nadeem , Sivas University of Science and Technology, Turkey

Associated Data

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.

Legume crops provide significant nutrition to humans as a source of protein, omega-3 fatty acids as well as specific macro and micronutrients. Additionally, legumes improve the cropping environment by replenishing the soil nitrogen content. Chickpeas are the second most significant staple legume food crop worldwide behind dry bean which contains 17%–24% protein, 41%–51% carbohydrate, and other important essential minerals, vitamins, dietary fiber, folate, β-carotene, anti-oxidants, micronutrients (phosphorus, calcium, magnesium, iron, and zinc) as well as linoleic and oleic unsaturated fatty acids. Despite these advantages, legumes are far behind cereals in terms of genetic improvement mainly due to far less effort, the bottlenecks of the narrow genetic base, and several biotic and abiotic factors in the scenario of changing climatic conditions. Measures are now called for beyond conventional breeding practices to strategically broadening of narrow genetic base utilizing chickpea wild relatives and improvement of cultivars through advanced breeding approaches with a focus on high yield productivity, biotic and abiotic stresses including climate resilience, and enhanced nutritional values. Desirable donors having such multiple traits have been identified using core and mini core collections from the cultivated gene pool and wild relatives of Chickpea. Several methods have been developed to address cross-species fertilization obstacles and to aid in inter-specific hybridization and introgression of the target gene sequences from wild Cicer species. Additionally, recent advances in “Omics” sciences along with high-throughput and precise phenotyping tools have made it easier to identify genes that regulate traits of interest. Next-generation sequencing technologies, whole-genome sequencing, transcriptomics, and differential genes expression profiling along with a plethora of novel techniques like single nucleotide polymorphism exploiting high-density genotyping by sequencing assays, simple sequence repeat markers, diversity array technology platform, and whole-genome re-sequencing technique led to the identification and development of QTLs and high-density trait mapping of the global chickpea germplasm. These altogether have helped in broadening the narrow genetic base of chickpeas.

1 Introduction

Grain legumes are a key component of the agricultural ecosystem. These plants are a chief member of the most diverse and ecologically crucial botanical families. Legumes play a vital role in crop rotations or intercropping schemes as these plants are capable of nitrogen assimilation through symbiotic relationship with rhizobia. Chickpea ( Cicer arietinum ) is the second most important grain legume after dry bean ( Phaseolus vulgaris L.). Chickpeas have eight pairs of homologous chromosomes (2n = 16) with an estimated genome size of 738 Mb and 28,269 annotated genes ( Varshney et al., 2013 ). The cultivated chickpea is believed to be originated in the Anatolia of Turkey ( Van der Maesen, 1984 ). Vavilov denominated two primary centers of origin for chickpea viz., southwest Asia (Afghanistan) and the Mediterranean with the secondary center of origin as Ethiopia. Since ancient’s times, legumes have been grown for human subsistence. Globally, India is the largest producer and consumer of pulse crops. Pulses are the major source of carbohydrates, proteins, lipids, vitamins, and minerals for people across the globe ( Aykroyd and Doughty, 1982 ). Pulses complement the nutritional quality, bioavailability of nutrients, when consumed along with cereals. Pulses provide 22–24% of protein, which is about twice the amount of wheat and three times the rice. Pulses are one of the cheapest sources of protein and play a very significant role in sustaining nutritional requirements in developing and economically poor countries. They have a low glycemic index (GI) and elicit only a moderate postprandial glycemic response after consumption. As a result, incorporating legumes into one’s diet is advised for glycemic-influenced diabetes control ( Rizkalla et al., 2002 ).

Chickpea is the major source of food and nutrition in the semi-arid tropics. In comparison to other pulses, chickpeas are a rich source of protein and carbohydrates, accounting 80% to the whole mass of dried seeds ( Geervani, 1991 ; Chibbar et al., 2010 ). Chickpea is high in dietary fiber (DF), vitamins, and minerals and is known to lower low-density lipoprotein ( Wood and Grusak, 2007 ). Chickpea has the highest quantity of total DF amongst pulses, which ranges from 18 to 22 g/100 g of raw seed ( Aguilera et al., 2009 ). The soluble and insoluble DF contents of chickpea raw seeds are about 4–8 and 10–18 g/100 g, respectively ( Dalgetty and Baik, 2003 ). It has been demonstrated that chickpeas have more bioavailable protein than other legumes ( Sánchez-Vioque et al., 1999 ; Yust et al., 2003 ). The changes in protein content of pre- and post-dehulled chickpea dried seeds are observed which range from 17%–22% and 25.3%–28.9%, respectively ( Hulse, 1991 ; Badshah et al., 2003 ). Raw chickpea seeds have a total fat content ranging from 2.70 to 6.48% ( Kaur et al., 2005 ; Alajaji and El-Adawy, 2006 ). On an average, raw chickpea seeds give 5.0 mg/100 g Fe, 4.1 mg/100 g Zn, 138 mg/100 g Mg, and 160 mg/100 g Ca. Chickpea is an inexpensive, rich source of folate and tocopherol ( Ciftci et al., 2010 ). The major carotenoids, viz . , β-carotene, lutein, zeaxanthin, β-cryptoxanthin, lycopene, and α-carotene are also found in chickpea.

Globally two types of chickpea cultivars desi or microsperma and Kabuli or macrosperma are cultivated. Generally, Kabuli chickpea is predominantly cultivated in temperate regions like the Mediterranean region that includes Western Asia, Southern Europe, and Northern Africa. However, desi chickpea is raised mainly in the semi-arid tropics ( Malhotra et al., 1987 ; Muehlbauer and Singh, 1987 ) such as Ethiopia and the Indian sub-continent. In general, desi types are characterized by small seeds, angular shape with a rough surface having a dark seed coat and flowers of pink or purple color due to the presence of anthocyanin pigment, whereas Kabuli types are bold seeded owl shaped with smooth surface have beige seed coat and bear white color flowers because of lack of anthocyanin pigment ( Pundir et al., 1985 ). Desi-type chickpeas are generally early maturing and high yielding than the Kabuli type. The desi chickpea is the predominant form cultivated in India occupying approximately 80–85% and the Kabuli chickpea occupies the remaining 15–20% of the total area and production. The chickpea draft genome sequences are already reported for desi ( Jain et al., 2013 ) and Kabuli ( Varshney et al., 2013 ) types.

Chickpeas are majorly grown as rainfed crops since they require less irrigation than other competitive crops such as cereals. However, it can be grown in a wide range of soils and agro-climatic conditions. Chickpea contributes to farming systems’ long-term survival as it plays important roles in crop rotation, mixed and intercropping, soil fertility maintenance through nitrogen fixation, and the release of soil-bound phosphorus; overall it improves the soil ecosystem. Globally, chickpea is grown on 14.842 m ha with an annual production volume of 15.083 m tones having a productivity average of 1,016 kg/ha. Indian contribution to the globe is 73.769% (10.949 m ha) in terms of area and 73.456% (11.080 m tones) production as depicted in Figures 1A,B with average productivity of 1,012 kg/ha ( FAOSTAT 2020 ). Pakistan, Turkey, Australia, Myanmar, Ethiopia, Iran, Mexico, Canada, China, and the United States are among the other significant chickpea producers.

(A) Area and (B) Production of chickpea during 2020 in major producing countries in the world.

Rajasthan, Maharashtra, Madhya Pradesh (MP), Uttar Pradesh (UP), Karnataka, and Andhra Pradesh (AP) are the major states growing chickpea and other pulses in India. Rajasthan is also the highest producer of chickpea in India followed by Maharashtra, MP, UP, and Karnataka; and together contribute to 83% of production and 82% of the area in India ( Figures 2A,B ).

(A) Area and (B) Production of chickpea during 2020 in major producing States in India.

Although the productivity is a little higher than average global productivity, it is lesser than the estimated potential yield, i.e., 6 tones/ha under optimum conditions for the crop (Thudi et al., 2016). Ever-increasing the human population linked with climate change and limited arable land poses a challenge to meet the demands of growing malnutrition and hunger. A lot of efforts had been made by the national and international scientific community to enhance the productivity of chickpeas, but unable to enhance up to a significant level. The reasons underlying are a narrow genetic base and as a result poor genetic gains in the breeding of improved varieties which, leads to the reduction in the yield and its adaptation ( Varshney et al., 2012 ). Devastating pests, pathogens, and increased incidences and severity of abiotic stress amid climate change are the major factors adversely affecting chickpea yield and production. Therefore, diverse sources of variations including wild Cicer species need to be explored for the genetic enhancement of chickpeas.

Chickpea performs better in cooler areas since it is a C-3 plant, implying that C-3 plants are better for the winter season. However, the harvest index (HI) in pulses (15%–20%) is low when compared to cereals (45–50%), which is a concerning issue. It is caused by excessive vegetative growth and can be countered by early dry matter partitioning into seeds ( Saxena and Johansen, 1990 ). Despite continued efforts by national and international chickpea improvement programs for the last several decades, the production and productivity of chickpeas have not increased significantly. Probably, this has happened due to the lack of variability for desired plant ideotypes, resistance sources for devastating pests and pathogens, and less responsive behavior of pulses toward modern agricultural practices and inputs. In general, chickpeas and other pulses are grown as a residual or alternative crop in marginal areas, only if the farmers have met their food/income requirements from high productivity- high input responsive crops such as paddy and wheat. After the onset of the green revolution, pulses were further marginalized in their traditional farming systems and local landrace variability in the farmer’s field was lost. Furthermore, chickpea is subjected to various types of biotic and abiotic stresses, which are blamed for much of the crop’s unstable and low yields ( Reddy, 2016 ).

In the production of chickpea, there has been a considerable risk of abiotic stresses. Crop failure is frequently attributed to moisture and temperature stresses, which leave the greatest impact on grain yield. Drought and heat stresses cause forced maturity, resulting in reduced yield. For example, the terminal drought stress in the Mediterranean region when chickpea is grown in the spring season. Drought along with heat stress alone annually reduces productivity by up to 70%. Another major problem in chickpea production is soil salinity and alkalinity. High levels of salinity and alkalinity in both semi-arid tropics and irrigated sections of the Indo-Gangetic plains are a major problem, as most of the pulses are highly sensitive to salinity and alkalinity. Another abiotic factor that limits chickpea grain yield is cold, particularly in temperate regions. Yield is further affected by lack of highly resistant sources in the cultivated gene pool for many of the devastating pathogens and biotic stresses such as dry root rot, ascochyta blight, collar rot, botrytis grey mold (BGM) and Helicoverpa species further aggravate the situation ( Reddy, 2016 ). In India, more than 250 insect species have been documented to be harmful to pulses including the chickpea crop.

To achieve higher and stable productivity, it is crucial to breed superior crop varieties with high yield, improved nutrition, disease, and pest resistance to meet the rising global demands. The genetic gains of chickpea and other legume crops are very less as compared to other crops, the reason behind this is the narrow genetic base. To meet the future demand, we have to accelerate genetic gains which are a cyclic process of identifying new variants, carrying selection, and fixing desirable traits. Further, to sustain higher genetic gain for a longer duration, infusion of genetic diversity in modern varieties from landraces and wild Cicer species is required. Genomics, high throughput precision phenotyping tools, and artificial intelligence can help in making a desired selection, and in achieving accelerated genetic gain while reducing genetic diversity loss ( Varshney et al., 2018 ).

2 Narrow Genetic Base—A Major Bottleneck in Chickpea

Chickpeas have an inherently narrow genetic base as the crop had been subjected to a series of major genetic bottlenecks such as natural selection driven by biotic and abiotic stresses, farmers’ selection pressure (domestication syndrome effect), the introduction of a small set of variability (founder effect), utilization of a very small proportion of variability in the breeding of modern cultivars, etc. ( Abbo et al., 2003 ). Chickpea is a self-fertilization crop, which enhances the probability of loss of variability particularly rare alleles/traits in a population during the selection processes, leading to further narrowing of the chickpea genetic base. Some of the other major factors causing narrowed genetic base of chickpea are areas given below:

• • Restricted distribution of wild progenitors of chickpea ( C. reticulatum is restricted to a small area in SE turkey) ( Abbo et al., 2003 ), which obstructs the gene flow from the wild to the cultivated types.
• • Founder effect: similar to any other Neolithic crops, chickpea crop is of monophyletic origin from its wild progenitor and only a limited amount of variability is spread to other parts of the world, causing a genetic bottleneck and narrowed genetic base ( Ladizinsky, 1985 ).
• • Domestication syndrome: wild progenitors have ordained to cultivated forms after passing through various genetic modifications and acquiring a combination of traits which might have led to the disappearance of many genes/alleles responsible for input response and higher gain yield ( Jain et al., 2014 ).
• • The change from autumn to spring sowing in chickpea: in the Early Bronze Age, the shift of chickpea sowing from autumn to spring to avoid certain biotic stresses, i.e., ascochyta blight. This was possible through the selection for vernalization response in chickpea wild progenitor species; which must have caused a drastic loss of genetic diversity ( Abbo et al., 2003 ).
• • The replacement of the land races by elite cultivars produced by modern plant breeding methods which are often developed by genetically similar parental lines and most of the breeding programs shares a limited set of parental lines ( Tanksley and McCouch, 1997 ).

Crop improvement mainly relies on the genetic matter available for exploration through the methods of plant breeding, i.e., classical and molecular breeding. The repeated use of the same germplasm has made very less contribution to the development of the new cultivars. Hence, it could be inferred that chickpea has a narrow genetic base and prompt measures for the transfer of targeted traits from wild Cicer species to cultivated one should be taken up by properly evaluating, characterizing, identifying, and utilizing the available germplasm during hybridization programs ( Varshney et al., 2021 ).

In cereals, the amount of yield improvement achieved by breeding is substantially more than chickpea and other pulses. This is probably because the crops have not faced such a harsh bottleneck, and have a comparative broader genetic base ( Abbo et al., 2003 ). The drawback of chickpea breeding programs is their narrow genetic base and unavailability of high input responsive cultivars. In order to develop high-yielding lines, chickpea genetic resources are needed to be explored to broaden the genetic base. Genetic diversity is a major contributor to selection-induced genetic gain, therefore, poor genetic diversity in chickpeas is the major limiting factor in enhancing chickpea yield. As a result, expanding the genetic base of chickpeas is critical for enhancing breeding efficiency. Chickpea wild species are an important genetic resource, especially for biotic and abiotic stress resistance and nutritional quality. Chickpea mutants with novel features like brachytic growing behavior ( Gaur et al., 2008 ), more than three flowers per node–the cymose inflorescence ( Gaur and Gour, 2002 ), determinate ( Hegde, 2011 ), and semi-determinate growth habit ( Harshavardhan et al., 2019 ; Ambika et al., 2021 ) with the potential to generate futuristic plant types have been identified. In addition, several relevant agro-morphological features and key biotic factors in a variety of wild annual Cicer species have been discovered and proposed for their introgressions into the cultivated gene pool to expand the genetic basis ( Singh et al., 2014 ). Therefore, there is an emergent need to strengthen research efforts for identifying useful breeding techniques to enhance the genetic base of chickpea for enhancing genetic gains and finally chickpea yield. One of the greatest challenges in boosting grain legume output is the availability of high-quality seed and other inputs, which is lagging in the chickpea crop and only possible through infusing more and more variability in seed chain systems ( David et al., 2002 ).

3 Sources of Genetic Diversity and Broadening of Chickpeagenetic Base

In the past, crop improvement has led to narrowing down of the genetic base resulting in low genetic gains and increased risk of genetic vulnerability. In order to overcome the genetic bottlenecks and create superior gene pools, broadening the genetic base through pre-breeding is required to enhance the utility of germplasm. To attain sustainable growth in chickpeas, new sources of genes need to be identified and incorporated into high-yielding cultivars. The systematic evaluation, characterization, and utilization of wild species-specific targeted genes, to overcome the drawbacks of the abiotic and biotic stresses by broadening the genetic base of chickpea cultivars, are the emergent and immediate requirements. Broadening of the genetic base is now necessary and useful and it is well recognized in all crops mainly in chickpeas and other pulse crops.

The genetic base of cultivated chickpeas is limited ( Kumar and Gugita, 2004 ). Breeders are unwilling to employ exotic germplasm because of linkage drag and/or loss of adaptive gene complex, which necessitates a prolonged time for developing cultivars. As a result, breeders prefer to focus on adapted and improved materials; while ignoring wild relatives, landraces, and exotic germplasm accessible in gene banks ( Nass and Paterniani, 2000 ); thus, further narrowing the genetic base and expanding the gap between available genetic resources and their use in breeding programs ( Marshall, 1989 ). However, substantial diversity among specified parental lines is critical for the success of any breeding program, particularly when the traits to be improved are quantitative, highly variable, and exhibit high G × E interactions.

3.1 Sources for Broadening of Genetic Base

There are several sources that could be used for broadening of the genetic base in chickpea to overcome the bottleneck of biotic and abiotic stress in the scenario of changing climatic conditions. Tolerance may be contained in the wild relatives, landraces, advanced breeding materials, initial breeding material, and high-yielding cultivars ( Meena et al., 2017 ). Landraces and wild progenitors have been used for the introgression of various abiotic and biotic stress tolerant gene(s). Mini core germplasm ( Upadhyaya et al., 2013 ) along with several varieties and cultivars have been screened intensively for various biotic and abiotic stresses and used for numerous tolerances in chickpeas.

3.1.1 Sources of Chickpea Genetic Diversity: Cicer Wild Relatives

The genus Cicer currently comprises 44 species ( Table 1 ) containing 10 annuals and 34 perennials ( van der Maesenet al., 2007 ). C. turcicum is the recent most identified wild Cicer species endemic to Southeast Anatolia (Turkey) ( Toker et al., 2021 ). This is an annual species, and with sequence similarity based on the internal transcribed spacer (ITS) region, it appears that C. turcicum is a sister species of C. reticulatum and C. echinospermum , both of which gives fertile progenies when crossed with the cultivated species. Utilization of the new species in the chickpea improvement program will have a great impact on the genetic base broadening. C. arietinum is the only species that is extensively recognized as cultivated species. Cicer reticulatum is identified as a probable ancestor of chickpea ( Ladizinsky and Adler, 1976a ). The cultivated chickpea is believed to be originated in the Anatolia of Turkey ( Van der Maesen, 1984 ). Vavilov specified two primary centres of origin for chickpea, southwest Asia and the Mediterranean with the secondary center of origin as Ethiopia. The chickpea closely associated species viz.; C. bijugum , C. echinospermum , and C. reticulatum are widely distributed across southeastern Turkey and neighboring Syria ( Ladizinsky and Adler, 1975 ; Ladizinsky, 1998 ). However, several Cicer species are restricted to particular geographic areas such as C. bijugum in Syria and Turkey, C. anatolicum in Armenia and Turkey, C. macracanthum in Pakistan, C. microphyllum in India and Pakistan, and so on. C. arietinum is a cultivated species that can’t colonize without human assistance. C. reticulatum and C. bijugum grow naturally in weedy habitats (fallow lands, road sides, cultivated fields of wheat, and other territories not grabbed by human beings or livestock), C. pungens and C. yamashitae are found in mountain slopes among rubbles, C. montbretia and C. floribundum are distributed on forest soils, in broad leaf or pine forests and C. microphyllum grows naturally in stony and desert areas of the Himalayas in India ( Chandel, 1984 ). Different Cicer species and their distributions are presented in Table 1.

List of Cicer species and their distribution.

The primary gene pool constitutes domesticated chickpea, C. arietinum, and the immediate progenitor, C. reticulatum , the species which are easily crossable with regular gene exchange. They differ either by a reciprocal inversion, a paracentric inversion or by the location of chromosomal satellites ( Ladizinsky, 1998 ). The C. echinospermum represents a secondary gene pool and is crossable with cultivated chickpea, but gives reduced pollen fertility in the hybrids and their advanced generations. The tertiary gene pool contained remnant 6 annual and 34 perennial species having poor crossing compatibility with cultivated chickpea and requiring advanced approaches for gene transfer. Wild lines of chickpeas are very good sources of the genes/QTLs for the development of varieties which could be climate-resilient and tolerant to most of the biotic and abiotic stresses ( Table 2 ). These lines consist of different species of chickpea of the primary, secondary, and tertiary gene pool ( Figure 3 ). The resistance transfer from wild species poses several problems such as cross incompatibility, hybrid sterility, hybrid inevitability, and linkage of undesirable traits.

Sources of desirable traits in Cicer species for introgression into elite genetic background of chickpea to broaden genetic base.

Chickpea gene pool concept and their crossing compatibility.

3.1.2 Sources of Chickpea Genetic Diversity: Gene Bank Collections and Introductions

The primary goal of a germplasm collection is to capture a significant amount of genetic variation, conserve, and enhance utilization ( Singh and Singh, 1997 ). The first exploration expedition, led by the United States Department of Agriculture’s Regional Pulse Improvement, was conducted in India in the 1970s, collecting almost 7,000 chickpea accessions. In India, systematic explorations to expand chickpea germplasm began only after the establishment of the National Bureau of Plant Genetic Resources (NBPGR) in 1976. In India, the area surveyed for chickpea germplasm collection included regions of Rajasthan, Odisha, Maharashtra, Gujarat, eastern parts of Arunachal Pradesh, Bihar, and southern parts of Tamil Nadu and Karnataka ( Singh and Singh, 1997 ). The awareness about the wild Cicer species as rich sources of genes/alleles not just for biotic and abiotic stresses, but also for superior agro-morphological features, has sparked a lot of interest in the researchers ( Van der Maesen and Pundir, 1984 ). Chickpea collection displays variations in plant height, foliage color, pod size, pod bearing habit, seed coat texture, seed coat surface, seed color, and seed size ( Singh et al., 2001 ; Archak et al., 2016 ). Madhya Pradesh collections were double podded, large-seeded (kabuli type), and tuberculated seeded (desi type) with short and medium duration ( Pundir and Reddy, 1989 ; Pundir et al., 1990 ). NBPGR has introduced valuable germplasm material from many agroecological zones throughout the world. Some of the potential exotic Cicer arietinum germplasm exhibit significant levels of resilience to biotic and abiotic stresses. The imports of Cicer wild species ( C. canariense, C. anatolicum, C. oxyodon, C. bijugum, C. reticulatum, C. pinnatifidum and C. judaicuni ) have received special attention for use in breeding programs. The majority of the introductions came from International Center for Agricultural Research in the Dry Areas (ICARDA). Other important introduction sources included Spain, Afghanistan, The Former Soviet Union, Iran, United States, Morocco, and Greece. Some of the introduced chickpea lines made significant contributions to the genetic enhancement and pre-breeding, mainly for resistance to Fusarium wilt, Ascochyta blight, leaf miner, cyst nematode, cold, drought, earliness, tall stature, and bold seeds. The important chickpea germplasm collections, including wild species that have been preserved in ex-situ collections in various gene banks around the world ( Table 3 ).

Ex-situ conservation of Cicer accessions in the world.

Source: http://www.fao.org/wiews-archive/germplasm_query.htm?i_l¼EN .

3.1.3 Sources of Chickpea Genetic Diversity: Landraces and Cultivated Varieties

Landraces are locally adapted cultivars that evolved in a diverse range of environmental conditions and are maintained generation after generation by farmers and local seed systems. The landraces are the goldmines for trait identification for various biotic and abiotic stresses viz.; drought, salinity and cold. These land races could be exploited in breeding programs for introgression of useful genes/QTLs and enhancing the genetic variability in the modern chickpea cultivars.

The tolerance variation depends on various factors viz.; climatic factors, genotypes, seed attributes, and seed compositions. The most important prerequisite is seedling salinity tolerance since this attribute facilitates the establishment and growth of tolerant genotypes in saline soils. The roles of seed yield, yield components, pods per plant, number of seeds, in vitro pollen germination, pollen viability, and in vivo pollen tube development to assess the reproductive successful outcome of chickpea under saline stress were investigated ( Turner et al., 2013 ). The increased salt tolerance, as measured under salty ambient by relative yield, was correlated positively with increased shoot biomass, number of pods, and seeds. Pollen viability, in vitro pollen germination, and in vivo pollen tube growth were uninfluenced by salty ambient in either of the tolerant or sensitive genotypes but pod abortion was relatively higher in salt-sensitive genotypes. Genotypes ICCV-00104, ICCV-06101, CSG-8962, and JG-62 showed a minimum reduction in seedling characters in salt stress conditions. Similar findings were reported by Samineni et al., 2011 , while studying chickpea seedlings under saline stress. Flowering terminates at temperatures below 15°C as reported in Australia ( Siddique and Sedgley, 1986 ), India ( Savithri et al., 1980 ; Srinivasan et al., 1999 ) and the Mediterranean ( Singh and Ocampo 1993 ). It was observed that, when average daily temperature remained below 15°C, plants produced flowers but did not set pods. However, scientists at International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) could develop numerous breeding materials (e.g., ICCV series 88502, 88503, 88506, 88510, and 88516) that are capable to set pods at 12°C–15°C lower average daily temperatures. A pollen selection was applied in Australia to transfer chilling tolerance from ICCV 88516 to chilling sensitive cultivars, leading to the development and release of two chilling tolerant cultivars namely Sonali and Rupali ( Clarke and Siddique, 2004 ). Minicore germplasm was screened for drought tolerance and a few germplasm accessions viz.; ICC series 1356, 3512, 4872, 13523, and 15697 with deeper root systems were identified. The Germplasm accession ICC8261 had the highest root length density, an extremely high root/shoot ratio and rooting depth in both Rabi and Kharif seasons. ICC4958, which is a source used as a deep and large root system parent or check in most drought avoidance studies, was reported to be an extremely prolific rooting genotype. The new genotypes identified could be used as valuable alternative sources for diversification of mapping populations with varying characters and growth durations to obtain the required polymorphism for successfully mapping root traits in chickpeas.

3.2 Approaches for Broadening the Genetic Base

Broadening of the genetic base, up to now, has utilized the techniques of classical breeding viz.; hybridization, segregation, back crossing, cyclic population improvement, pedigree selection among selfed progenies. However, wild relatives couldn’t be utilized because of inter-specific hybridization barriers, limited data for specific traits, and linkage drag. With the advent of molecular breeding techniques, new biotechnological methods, which are being applied for the identification of the QTLs for the traits of interest and needs to be incorporated through various techniques of pre-breeding which are used in transferring useful genes from the exotic or wild species into the high-yielding cultivars. The halted speed of chickpea breeding due to narrow genetic diversity could be fastened by employing wild relatives as a valuable source of new genes and alleles to be further exploited by breeders for allelic richness and broadening of chickpea germplasm. Thus, comprehensive approaches could be utilized for broadening the genetic base in chickpea and other grain legume crops as depicted ( Figure 4 ).

Comprehensive approach for broadening the genetic base of chickpea.

Chickpea’s limited genetic base is a major source of anxiety for chickpea breeding programs, as genetic variability is a major contributor to selection-induced genetic gain. As a result, expanding the genetic base of chickpeas is critical for enhancing breeding efficiency. Chickpea wild species are an important genetic resource, especially for biotic and abiotic stress resistance and nutritional quality. Chickpea mutants with novel features like brachytic growing behavior ( Gaur et al., 2008 ), more than three flowers per node—the cymose inflorescence ( Gaur and Gour, 2002 ), determinate ( Hegde, 2011 ), upright peduncle podding ( Singh et al., 2013 ) and semi-determinate growth habit ( Harshavardhan et al., 2019 ; Ambika et al., 2021 ) with the potential to generate futuristic plant types have been identified. In addition, several relevant agro-morphological features and key biotic factors in a variety of wild annual Cicer species have been discovered and proposed for their introgressions into the cultivated gene pool to expand the genetic basis ( Singh et al., 2014 ). Some of the useful agro-morphological traits including major biotic and abiotic stresses are presented in Tables 2 , ​ ,4. 4 . There is an emergent need to strengthen research efforts for identifying useful breeding techniques to enhance the genetic base of chickpeas.

Sources of resistance to abiotic and biotic stresses as reported by various workers after evaluating the chickpea mini core collection.

3.2.1 Utilization of Adapted and Un-Adapted Germplasm for Traits Discovery and Broadening the Genetic Base

Pre-breeding offers an unparallel opportunity for the introgression of desired genes and gene combinations from exotic germplasm into genetic backgrounds easily employed by breeders with minimal linkage drag ( Sharma et al., 2013 ). Comprehensive broadening of the genetic base through incorporation is the most suitable method when new genetic variabilities for quantitative traits are required, latest and most reliable methods could be optical contribution selection (OCS) based pre-breeding, haplotype-based genomic approaches, and genomic predictions ( Varshney et al., 2021 ). To achieve the highest level of yield, the existing variability among indigenous germplasm has been used. Wild Cicer species and exotic germplasm lines include valuable alleles that, if discovered, can aid in breaking yield barriers and improving resistance to various stresses for crop yield stability ( Labdi et al., 1996 ; Tayyar and Waines, 1996 ; Ahmad and Slinkard, 2003 ; Ahmad et al., 2005 ).

Several inter-specific crosses between Cicer arietinum and its annual wild relatives have been attempted in the context of wild Cicer species usage. There is no evidence of successful hybridization between a perennial Cicer species and Cicer arietinum . Ladizinsky and Adler (1976b) reported inter-specific crosses amongst C. arietinum, C. reticulatum and C. cuneatum for the first time. Several researchers have successfully attempted inter-specific hybrids between Cicer arietinum and Cicer echinospermum ( Verma et al., 1990 ; Singh and Ocampo, 1993 ; Pundir and Mengesha, 1995 ). Numerous crossings between Cicer arietinum as the female parent and Cicer reticulatum, C. echinospermum, C. judaicum, C. bijugum , and C. pinnatifidum as the male parent have been conducted ( Verma et al., 1990 ). Van Dorrestein et al., 1998 aimed to cross C. arietinum with C. judaicum and C. bijugum . Badami et al., 1997 used an embryo rescue strategy to successfully hybridize C. arietinum with C. pinnatifidum . Inter-specific crosses have resulted in the development of certain pre-breeding lines at IIPR, Kanpur, and PAU, Ludhiana ( Singh et al., 2012 ). Singh et al. (2015) attempted inter-specific crosses and the results revealed a high level of heterosis for the number of pods and seed yield per plant in the F 1 generation. Three cross-combinations viz.; Pusa 1103 x ILWC 46, Pusa 256 x ILWC 46, and Pusa 256 x ILWC 239 demonstrated significantly increased variability for crucial yield related characteristics.

Adoption and harmonizing conventional and modern approaches like molecular breeding, physiological breeding, biotechnological methods, high throughput genomics, and phenomics will aid in the broadening of the genetic base and release of high-yielding varieties which will be tolerant to various biotic and abiotic stresses. Several mapping populations could be developed for the identification of trait-specific QTLs and can be introgressed into high-yielding cultivars for enhancing the gene pool of chickpea.

3.2.2 Bi-Parental Populations for Broadening Genetic Bases

Two inbred lineages are generally crossed in bi-parental populations to generate one or more segregating progenies ( Xu et al., 2017 ). This is the basic approach of combining desired traits in a genotype through ongoing breeding programs. Parents are chosen for a trait of interest based on their genetic and phenotypic diversity allowing the reconstruction of progeny genomes from founder haplotypes to find genomic areas related to the target trait ( Dell’Acqua et al., 2015 ). Bi-parental crosses derived populations capture only a modest impression of the genetic determinants that influence targeted traits in the species and suffer from a lack of diversity owing to the limited genetic base of both parents. Therefore, while the approach is indispensable for any breeding program, genetic diversity must not be reduced in the selection process, to sustain genetic gains for a longer duration. Molecular tools such as re-sequencing technologies and other cost-effective genotyping technologies, which can scan the whole genome, may be useful in the identification of diverse parental lines having the target traits of interest. The utilization of such parental lines will enhance the genetic diversity in the released varieties without compromising the desired yield gain. High-throughput precision phenotyping, genomic selection, and identification of superior haplotypes may further accelerate the breeding cycle and boost the genetic diversity in farmers’ fields to enhance the crop resilience toward the biotic and abiotic stresses. In addition, the QTLs detected in the two-parent population may not be expressed in other genetic origins ( Rakshit et al., 2012) . Mallikarjuna et al., 2017 , utilized F2 populations derived from four crosses (ICCV96029 x CDC frontier, ICC5810 x CDC frontier, BGD 132 x CDC frontier, ICC 16641 x CDC frontier) and found major QTLs corresponding to flowering time genes.

3.2.3 Multi-Parent Populations for Broadening Genetic Bases

Multi-parental and germplasm populations, on the other hand, may offer solutions to bi-parental and germplasm populations’ major flaws. Throughout the history of scientific crop improvement multi-parental populations or multi-parental cross designs (MpCD) have been generated in a range of crop species. Adaptation to crops that are difficult to artificially hybridize, multi-parental populations are created by making crossings amongst more than two inbred founder lines, which serve as a link between association mapping (GWAS) and traditional bi-parental crosses. While such populations are able to combine and reveal better allelic combinations, transgressive segregants, and simultaneously genetic diversity in the progenies are also enhanced. Multi-parent populations also are more efficient in increasing mapping resolution, if they are used for high-density genotyping using advanced high-throughput genomic technologies ( Rakshit et al., 2012 ). This unique technique dramatically improves mapping resolution by merging numerous founder parents with higher phenotypic and genetic diversity. Thanks to the evolution of more powerful techniques, multi-parental populations can now be utilized in numerous genetic mapping studies ( Mackay and Powell, 2007 ; Huang et al., 2015 ). Here, the emphasis is on MAGIC populations, which are RILs of fine-scale mosaic panels, although numerous MpCD other forms are also available. Thus, MAGIC populations are considered as a growing and next-generation powerful resource for plant genetics mapping, combining variation and high genetic recombination to analyze complex traits’ structure and enhance crop improvement techniques. In various model crop species, MAGIC populations have been generated illustrating their potential to find polymorphisms for underlying QTLs or genes of importance for useful complex traits. There are already MAGIC like or MAGIC populations obtainable in numerous crop species, viz., cereals, legumes, vegetables, fruit trees, and industrial crops with many more in the other works and because of their large genetic foundation, MAGIC populations could be used for discovery of QTL(s) and gene (s), enhancement of breeding populations, introduction and development and of novel genotypes ( Pascual et al., 2015 ). Multi-parent populations such as multiparent advanced generation intercross (MAGIC) populations have gained a tremendous popularity among researchers and breeders. Such populations, along with enhancing genetic diversity, also make it easier to examine the genomic framework and their relationships with phenotypic traits.

3.2.4 Molecular Markers Based Approaches for Broadening Genetic Bases

Since the advent of molecular markers, these tools have played an indispensable role in understanding genetic diversity, phylogenetic relationship, background, and foreground selection in molecular and conventional breeding programs. Recent advances in genomics, coupled with high throughput and precise phenotyping, have made it easier to identify genes that regulate important agronomic attributes. Genetic variability such as multiple podding per peduncle, multiple seeds per pod, upright podding, tall and erect genotypes, and several other traits for biotic stress tolerance are rare, and incorporating these traits to the major cultivars helps in enhancing the variability in the gene pool. These traits could be used in combination with tools for genomics to expedite the generation of crops with higher genetic variability with better agronomic traits, improved resilience to climate change, and nutritional values ( Pourkheirandish et al., 2020 ). Exploring the marker-assisted selection (MAS) technique along with other biotechnological tools can boost genetic diversity and simultaneously enhancing the yield in chickpeas ( Varshney et al., 2005 ; Varshney et al., 2009 ).

Genomic advancements have aided in understanding the complex trait’s mechanisms affecting chickpeas economically important characters’ genetic architecture as well as productivity in order to speed up breeding programs ( Roorkiwal et al., 2020 ). In chickpea, a number of markers and trait relationships and dense genetic maps have allowed MAS to become a routine practice in crop breeding programs ( Kulwal et al., 2011 ; Madrid et al., 2013 ; Ali et al., 2016 ; Caballo et al., 2019 ). Single nucleotide polymorphism (SNP) allelic variants on 27 ortholog candidate genes were utilized for the GWAS study, and potential candidate genes such as PIN1 , TB1 , BA1/LAX1 , GRAS8 , and MAX2 were identified for branch number in chickpea utilizing highly diverse chickpea germplasm ( Bajaj et al., 2016 ). The gene for double podding per peduncle was linked to Tr44 and Tr35 on linkage group 6 ( Cho et al., 2002 ). Saxena et al. (2014) has mapped four traits viz. 100-seed weight, pod, number of branches per plant and plant hairiness, using simple sequence repeats (SSRs) and SNP markers. There are several other examples of utilization of molecular makers for the identification of traits and underlying genes/QTLs in chickpea such as 100-seed weight ( Das et al., 2015 ; Kujur et al., 2015b ), resistance to Helicoverpa armigera ( Sharma et al., 2005 ), pod number ( Das et al., 2016 ), flowering time ( Srivastava et al., 2017 ), plant height ( Parida et al., 2017 ), photosynthetic efficiency traits ( Basu et al., 2019 ), etc. Furthermore, comprehending the chickpea developmental processes’ regulations has been facilitated by the framework offered due to discoveries of new microRNAs (miRNAs) and their expression patterns ( Jain et al., 2014 ).

For genomic investigations and crop improvement, numerous polymorphic molecular markers that could be exposed to high-throughput analysis are sought. On the basis of isozyme analysis, Cicer arietinum is most closely related to C. reticulatum , followed by C. echinospermum, C. bijugum, C. pinnatifidum, C. judaicum, C. chorassanicum, C. yamashitae and C. cuneatum ( Ahmad et al., 1992 ). Cicer reticulatum and Cicer echinospermum were grouped together in the same cluster; Cicer chorassanicum and Cicer yamashitae were grouped together in another cluster; Cicer bijugum , Cicer judaicum , and Cicer pinnatifidum were grouped together in the third different cluster; and Cicer cuneatum alone formed the fourth different cluster based on the analysis of RAPD markers ( Ahmad, 1999 ; Sudupak et al., 2002 ). An AFLP analysis for the same Cicer species also confirmed the same pattern ( Sudupak et al., 2004 ). RAPD and ISSR fingerprinting demonstrate that C. arietinum cultivars had the narrowest genetic variation while its wild C. reticulatum accessions had much greater genetic variation, which could be used in chickpea improvement ( Rao et al., 2007 ). The widespread use of molecular markers in chickpea genetics and breeding began with the introduction of SSR markers. The draft genome sequence of chickpea identified approximately 48,000 SSRs appropriate for PCR primer design for use as genetic markers ( Varshney et al., 2013 ), whereas a draft sequence of C. reticulatum (PI 4889777) spanning 327.07 Mb was assembled to the eight linkage groups with 25,680 protein-coding genes ( Gupta et al., 2017 ).

A variety of comparatively new marker systems have recently been introduced including sequence-based SNP and hybridization-based diversity array technology (DArT) markers which offer medium to high-throughput genotyping and are simple to automate. Two sets of Axiom®CicerSNP array have been developed in chickpea, one was including 50,590 probes distributed on all eight linkage groups as described by Roorkiwal et al. (2014) and the second multispecies SNP chip includes chickpea along with other pulses using markers that can be imputed up to whole-genome (800,000 markers) was developed by AgriBio, Centre for AgriBioscience Melbourne, Australia (personal communication).

To date, several studies have been published using DArT and SNP chips. We highlight the 5397 polymorphic DArT markers identified from a pool of 15,360 developed markers utilizing 94 different chickpea genotypes ( Thudi et al., 2011 ). The low genetic diversity was unraveled between wild Cicer and cultivated species through DArT markers ( Roorkiwal et al., 2014 ). Although transcriptome investigation of chickpea and its wild progenitors detected thousands of SNPs ( Coram and Pang, 2005 ; Varshney et al., 2009 ; Gujaria et al., 2011 ; Agarwal et al., 2012 ; Bajaj et al., 2015b ; Kujur et al., 2015a ). These SNPs and markers can be utilized by chickpea breeders in MAS-assisted breeding programs.

3.2.5 Trait Identificationin Legumes for Broadening Genetic Bases

3.2.5.1 trait identification through sequencing.

With the advancement in the next-generation sequencing (NGS)-based approaches, trait mapping has become an easy job to do. Not only are these technologies time-saving but also cutting the cost at basal levels. The genetic mapping is based on recombination (the exchange of DNA sequence between sister chromatids during meiosis) and the distance between the markers measured by cM representing approximately 1% of the recombination frequency, while the physical map is based on the alignment of the DNA sequences, with the distance between markers measured in base pairs. However, the high-resolution physical maps serve as the scaffold for genome sequence assembly to identify the most accurate distance between the markers and the genes linked in addition to exploring the potential candidate gene(s) linked to desired traits. The trait mapping through sequencing approaches may be categorized into two classes 1) Sequencing of complete populations for trait mapping and 2) Sequencing of pooled samples for trait mapping. Using composite interval mapping a high-density genetic map consisting of 788 SNP markers spanning through 1125cMalong with the identification of 77 QTLs for 12 traits was reported ( Jha et al., 2021 ). Similarly, several QTLs were mapped for several other traits like flowering time ( Mallikarjuna et al., 2017 ; Jha et al., 2021 ), plant height ( Kujur et al., 2016 ; Barmukh et al., 2021 ), and primary branches ( Barmukh et al., 2021 ).

3.2.5.2 Trait Identification Through Sequencing of Complete Populations

It primarily consists of the genotyping by sequencing (GBS) and whole-genome re-sequencing (WGRS) mapping populations, both of which yield genome-wide SNPs. GBS is popular because it is inexpensive and provides a lot of genetic data. The discovery of a large number of genome-wide SNPs has facilitated rapid diversity assessment, trait mapping, GS and GWAS in a variety of crop by employing GBS—a potential strategy. A chickpea genetic variation map was developed using whole-genome sequencing technique and genomes were characterized at the sequence level, observing variations in 3,171 cultivated and 195 wild accessions and construction of a pan-genome to explain the genomic diversity across wild progenitors and cultivated chickpea ( Varsheny et al., 2021 ). The 16 mapping populations segregating for different abiotic (drought, heat, salinity), biotic stress (Fusarium wilt, Aschochyta blight, BGM & Helicoverpa armigera ) and protein contents along with their 35 chickpea parental genotypes were re-sequenced in order to exploit the genetic potential for chickpea improvement ( Thudi et al., 2016 ). Genetic analysis, fine-tuning of genomic areas, and production of genetic maps are facilitated by re-sequencing ( Kujur et al., 2015b ; Li et al., 2015 ). Chickpea is one of the best examples of crops in which GBS was used to identify 828 SNPs in addition to the previously mapped SSRs. The creation of these detailed genetic maps aids in the discovery of QTLs in chickpea that controls yield, drought tolerance, and seed weight. It is quite useful for locating QTL hotspots. Moving on to the second promising strategy, WGRS has been found to be more useful in finding candidate genes than GWAS ( Jaganathan et al., 2015 ; Varshney et al., 2014 ).

3.2.5.3 Trait Identification Through Pooled Sequencing

The analysis is done on the basis of the pooled population through the inclusion of BSR-Seq, Indel-Seq, Mut-Map, QTL-Seq, and Seq-BSA the five major approaches. The “QTL-Seq” is the first and foremost promising technique to have been successfully employed with larger crop plant genomes. This strategy has been used to pinpoint the blast resistance and seedling vigor governing genomic areas in rice, flowering QTLs in cucumber, fruit weight and locule number loci in tomatoes and successfully applied for localization of QTLs/candidate genes for 100 seed weight in chickpea ( Takagi et al., 2013 ; Li et al., 2015 ). The “MutMap” is a robust and simple NGS-based approach, first of all which was applied for the identification of EMS-induced interesting candidate genes in rice. Crossing of selected mutant plants with wild types, which reduces background noise—the fundamental benefit, is the necessity of mapping the population created for the MutMap experimental strategies. Consequently, using extreme pool samples derived from segregating populations coupled to a wild parent the genome-wide SNP index is calculated. The third method, known as “Seq-BSA,” is a straightforward and reliable NGS-based strategy for identifying potential SNPs in specific genomic regions ( Takagi et al., 2013 ). Employing QTL-seq pipelines utilizing parent with high-value trait as reference parent assemblage, genome-wide SNP indexes of both extreme bulks are calculated in the third method. The fourth strategy, “Indel-Seq” which is mostly focused on insertions and deletions, has also emerged as a potential trait mapping approach. To date, the proposed methodologies for identifying genomic regions have relied on the discovery of SNPs followed by the use of various statistical approaches to recognize candidate genomic gene/regions. However, in all approaches, the relevant genomic region-specific existing Indels have not been targeted for trait mapping but ignored. The fact that the Indels reported in the candidate genes are found in most of the cloned genes in rice and other crops and makes this strategy more practicable. The strength of the RNA-seq and BSA were combined for enhancing the strength to find candidate genes for the targeted characteristic—a novel genetic mapping approach as the fifth strategy, dubbed as “Bulked segregant RNA-Seq (BSR-Seq)”. This method has been used to successfully identify the glossy3 genes in maize. RNA-seq-based investigations will be cheaper than WGRS at higher coverage; hence, this strategy has more cost savings. We believe that, given the benefits of RNA-Seq, this approach will be effective for legumes with larger genomes ( Liu et al., 2012 ; Trick et al., 2012 ). Thus, chickpea breeders utilize these generated informations in chickpea MAS-assisted breeding programs.

3.2.6 Transcriptomics Utilization for Broadening the Genetic Bases

Work on legumes focused on building libraries of cDNAs, gene expression profiling, the manufacture of expressed sequence tags (EST), and in silico extraction of EST data sets’ functional information even before sequences of the genome achievability. Transcriptome sequencing has been employed in other functional genomics methodologies, viz., genome annotation, gene expression profiling, and non-coding RNA identification employed transcriptome sequencing ( Morozova and Marra, 2008 ). In recent years, for generating a large number of transcript reads from a variety of developing and distress-responsive tissues in several leguminous crops through several low-cost sequencing systems has already been established, viz., an improved transcriptome assembly, utilizing FLX/454 sequencing together with Sanger ESTs comprised 103,215 Transcript Assembly Contigs (TACs) with an average contig length of 459 base pairs in chickpea ( Hiremath et al., 2011 ). Employing various sequencing technologies or a combination of two or more sequencing technologies created by transcriptome assemblies provides useful transcriptomic resources such as functional markers, EST-SSRs, Spanning Regions (ISRs), SNPs, Introns, and so on in soybean and common bean 1,682 and 4,099 SNPs, respectively ( Deschamps and Campbell, 2012 ), ESTs comprising of 103,215 Transcript Assembly Contigs (TACs) in chickpea (Hiremath et al., 2011) can be utilized by the breeders to achieve a better grasping of the molecular underpinnings of distress tolerance and as a result more stress-tolerant beans as well chickpea cultivars may be produced and narrow genetic base may be broadened.

3.2.7 Proteomics and Metabolomics for Broadening the Genetic Bases

New datasets for crop plants can be created by exploiting the opportunities of advancement in “omics” technologies. The advancements will result in a greater integrated association of “omics” data and crop improvement resulting in the evolution from genomic assisted breeding (GAB) to omics assisted breeding (OAB) in the future ( Langridge and Fleury, 2011 ) that can also be utilized for broadening the genetic bases in chickpea.

3.2.7.1 Proteomics Approaches

Increased proteome coverage and advancements in quantitative evaluations have benefitted plant proteome composition, modulation, and alterations of developmental phases including stress–response mechanisms. Proteomic pipelines are rapidly being used in crop research notably to investigate crop-specific features and stress response mechanisms. Proteome mapping, comparative proteomics, discovery of post-translational modifications (PTMs), and protein–protein interaction networks are key topics of plant proteomics ( Vanderschuren et al., 2013 ). In chickpea the comparative root proteomic analysis for the effect of drought and its tolerance in hydroponics using 2D gel electrophoresis coupled with MALDI-TOF revealed eight categories of protein-based on their functional annotation viz.; proteins involved in carbon and energy metabolism, proteins involved in stress response, ROS metabolism, signal transduction, secondary metabolism, nitrogen and amino acid metabolism ( Gupta and Laxman, 2020 ). High-throughput protein quantification has benefited from advancements in accuracy, speed, mass spectrometry (MS) utilizations in terms of sensitivity, and software tools. Gel-based or gel-free, shot-gun, and label-based (isotopic/isobaric) or label-free quantitative proteomics platforms have emerged as a result of developments in MS technology for high-throughput protein quantifications ( Abdallah et al., 2012 ; Hu et al., 2015 ). In legume crops, comparative proteomics approaches and differential expression analyses have given understanding of distress responses including dehydration, and early phases of cold stress in chickpeas ( Pandey et al., 2008 ) and can be effectively integrated into genomic-assisted breeding programs for broadening the narrow genetic bases.

3.2.7.2 Metabolomics Approaches

In plant metabolic engineering, targeted reverse genetic methods and high-throughput metabolite screening have the advantage of providing a better understanding of metabolic networks on a larger scale in relation to developmental stages of phenotypes and the ability to screen out undesirable traits ( Fernie and Schauer, 2009 ). The literature describes two major metabolomics profiling methodologies that use nuclear magnetic resonance (NMR) and MS. A combination of many analytical techniques generated from one of the MS was frequently used to obtain a larger range of numerous metabolites in plants ( Arbona et al., 2013 ). Flow injection-based analysis with Fourier Transform Infrared spectroscopy and MS (FIA/MS) are two further approaches. The identification of new metabolic QTLs and candidates for the desired traits are made possible by combining metabolomics data, transcriptomics data, high-throughput phenotypes, and bioinformatics platforms to profile large genetically varied populations and increase the accuracy of targeted gene identification. To boost yields and broaden the narrow genetic bases, metabolomics is utilized in conjunction with a genomic-assisted selection and introgression techniques, minimizing the time spent in uncovering new characteristics and allelic mutations ( Fernie and Schauer, 2009 ).

3.2.8 Pan Genomics

Recent developments in genome sequencing technologies have revolutionized the crop improvement programs. Now the whole-genome sequencing (WGS) is not limited to one or two individuals, but a large set of accessions of a species (pangenome) including their crop wild relatives (super-pangenome) are the whole genome sequenced to unravel the full potential of the species for the crop improvement programs. Once the pangenome information is available, the genomic segments/genes lacking in cultivated germplasm can be identified and introgressed in cultivated germplasm to enhance the genetic variability. The total number of genes of a species are collectively known as its pan-genome. It was observed from several evidences that a sole organism can’t contain all the genes of a species due to variability present in the genomic sequences. The desirable features of an ideal pan-genome are completeness (i.e., contains all functional genes), stability (i.e., unique catechistic features), comprehensibility (i.e., contains all the genomic information of all the species or individuals), and efficacy (i.e., organized data structure). Pangenome information of a species helps in the identification of desired alleles, rare alleles, presence or absence of a traits in a species. Recently a chickpea pangenome of 592.58 Mb was constructed which containsa total of 29,870 genes ( Varshney et al., 2021 ). The pan-genome was constructed using whole-genome sequencing using 3,366 comprising 3,171 cultivated and 195 wild accessions. Assembly was done by combining the CDC frontier reference genome including 53.60 Mb from cultivated chickpea inclusive of 2.93 Mb from ICC 4958 and 5.28 Mb from 28 accessions of C. reticulatum . This pan-genome analysis revealed useful information on genomic regions more often selected during the domestication process, superior haplotypes, and targets for purging deleterious alleles. The new genes identified encoding responses to oxidative stress, response to stimuli, heat shock proteins, cellular response to acidic pH, and response to cold, which could have a possible contribution to the adaptation of chickpea.

3.2.9 QTL Mappings, Their Introgression and Utilization for Broadening the Genetic Bases

The utility of the fundamental assumption of locus finding by co-segregation of characteristics with markers is enhanced by new permutations of QTL mapping ( Table 5 ). However, the definition of a trait can now be expanded beyond whole-organism phenotypes to include phenotypes like the amount of RNA transcript or protein produced by a specific gene because these phenotypes have more typical organismal characteristics viz.; yield in corn are polygenic and QTL mapping works in these situations. Transcript abundance is regulated not only by cis-acting regions like the promoter but also by Transacting transcription factors that may or may not be related. Similarly, local variation at the coding gene and distant variation mapping to other areas of the genome control protein abundance. Local variation is most likely made up of cis variations that regulate transcript levels. Polymorphisms for the protein’s stability or control could be another local mechanism. Distant variation, on the other hand, could comprise upstream regulatory control areas ( Upadhyaya et al., 2016 ).

List of QTLs for various traits in chickpea.

Quantitative trait loci (QTLs) conferring resistance to biotic and abiotic stresses have been applied in chickpeas in the last 2 decades and the molecular markers closely associated with these loci are also located ( Santra et al., 2000 ). For example, several QTLs conferring Ascochyta blight resistance are identified, and several MAS (SCY17 and SCAE19) were reported as the best markers linked to AB-resistant genes. These two markers were validated on different populations ( Iruela et al., 2006 ; Imtiaz et al., 2008 ; Madrid et al., 2014 ). More recently, three major conserved quantitative trait loci (QTLs) that confer AB resistance have been reported, two on chromosome Ca2 and one on chromosome Ca4. These QTLs explained a maximum of 18.5%, and 25% of the total variation. In total, 27 predicted genes were located in chromosome IV close to these QTL (Hamwieh et al., Unpublished data).

The 20 QTLs and candidate genes associated with seed traits were also identified in chickpeas using the GBS approach ( Pavan et al., 2017 ). In pigeon pea, the GBS-based mapping of two RIL populations led to the identification of QTLs and candidate genes for resistance to fusarium wilt (FW) and sterility mosaic disease (SMD) ( Saxena et al., 2017 ) in addition to restoration of fertility (Rf) ( Saxena et al., 2018 ), using GWAS drought tolerance-related traits in chickpea (Kale et al., 2015), flowering time control, seed development and pod dehiscence in pigeon pea ( Varshney et al., 2017 ) have been mapped. The GBS has been utilized in the fine mapping of the “ QTL-hotspot ” region for drought tolerance-related traits in chickpeas ( Kale et al., 2015 ). In the case of chickpea, QTL seq approach has successfully identified a major genomic region (836,859–872,247 bp) on Ca1 chromosome which was further narrowed down to a 35-kb region harboring six candidate genes for 100 seed weight ( Das et al., 2015 ).

Plant breeding can help in solving the global problem of micronutrient deficiencies in a cost-effective and long-term manner. The development of biofortified chickpea varieties is aided by evaluating cultivars for micronutrient contents and identifying quantitative trait loci (QTLs)/genes and markers. The F 2:3 derived population resulting from a cross between MNK-1 and Annigeri-1 was dissected employing the GBS technique and concentrations of Fe and Zn were examined with the goal of determining the responsible genetic areas ( Vandemark et al., 2018 ). The researchers mapped 839 SNPs on an intra-specific genetic linkage map covering a total distance of 1,088.04 cM with a marker density of 1.30 cM. By combining linkage map data with phenotypic data from the F2:3 populations a total of 11 QTLs for seed Fe concentration on CaLG03, CaLG04, and CaLG05 with phenotypic variance varying from 7.2% (CaqFe3.4) to 13.4% (CaqFe3.4; CaqFe4.2). On CaLG04, CaLG05, and CaLG08 along with eight QTLs for seed Zn concentration with explained phenotypic variances ranging from 5.7% (CaqZn8.1) to 13.7% (CaqZn4.3) were discovered ( Pandey et al., 2016 ).

The identification of marker-trait association between a genetic marker and a trait of interest is the initial stride in crop breeding utilizing molecular breeding/genomics assisted breeding. For initial experiments, linkage maps were created employing F 2 populations. The inter-specific cross C. arietinum (ICC 4958) x C. reticulatum (PI 489777) was employed to create the first recombinant inbred lines (RILS) mapping population which is now being used as a chickpea reference mapping population for genome mapping ( Nayak et al., 2010 ). Maps created from intra-specific mapping populations have a smaller number of markers (<250 markers) and poorer genome coverage (<800 cM) due to minimal variation in the cultivated chickpea. Consensus genetic maps were also created utilizing both inter and intra-specific mapping populations.

The genetic mapping of QTLs affecting resistance to various diseases, and also vital agronomical traits, in chickpea are extensively documented. Santra et al. (2000) identified two quantitative trait loci (QTL1 and QTL2) that give resistance to Ascochyta blight. These QTLs were predicted to be responsible for overall phenotypic variance (34.4%, 14.6%), respectively ( Santra et al., 2000 ; Tekeoglu et al., 2002 ). Comparative protein profiling of wild chickpeas and induced mutants was carried out in order to measure genetic diversity between mutants and parental genotypes ( Patil and Kamble, 2014 ). Kujur et al. (2016) reported candidate genes and natural allelic variations for QTLs determining plant height, which was followed by the discovery of QTLs for heat distress response ( Paul et al., 2018 ) as well as photosynthetic efficiency attributes for boosting seed yield in chickpea using GWAS and expression profiling ( Basu et al., 2019 ). These discoveries have opened up new paths for analysis and comprehensive characterization of wild Cicer species, which will help in harnessing unidentified allelic variations to extend the genetic foundation of cultivars.

Molecular markers have been discovered for gene(s)/QTL(s) linked to abiotic stress resistances, viz., drought tolerance ( Molina et al., 2008 ; Rehman et al., 2012 ), salinity resilience ( Vadez et al.,2012 ), biotic stresses, viz., Ascochyta blight ( Milla´n et al., 2003 ; Iruela et al., 2006 ; Aryamanesh et al., 2010 ; Garg et al., 2019 ), Fusarium wilt ( Cobos et al., 2005 ; Gowda et al., 2009 ; Sabbavarapu et al., 2013 ) and botrytis gray mold ( Anuradha et al., 2011 ) along with seed characteristics ( Gowda et al., 2009 ) in chickpea. These technologies can be employed to improve chickpea genetics and breeding as well as to explain the variety of the chickpea genome and domestication events. Furthermore, genomic selection has been presented as a promising strategy for enhancing traits that are influenced by a large number of gene (s)/QTL (s) ( Bajaj et al., 2015a ; Bajaj et al., 2015b ). Both phenotypic and genotypic data sets are employed in this approach to determine genomic estimated breeding values (GEBV) of improved progenies.

3.2.10 Genome-Wide Association Studies for Broadening the Genetic Bases

GWAS have become one of the most important genetic methods for analyzing complicated trait QTLs and underlying genes. Many studies have shown that GWAS can be used to map more authentically new genes implicated in complex agronomic variables in plants. Given this, linkage disequilibrium (LD), population substructure, and imbalanced allele frequencies are the key drawbacks of GWAS. Many markers associated with tolerance to abiotic stresses have been also reported in chickpea. In brief, the germplasm of 186 chickpea genotypes has been genotyped with 1856 DArTseq markers. The association with the salinity tolerance in the field (Arish, Sinai, Egypt) and the greenhouse by using hydroponic system at 100 mM NaCl concentration indicated one locus on chromosome Ca4 at 10,618,070 bp associated with salinity tolerance, in addition to another locus-specific to the hydroponic system on chromosome Ca2 at 30,537,619 bp. The gene annotation analysis revealed the location of rs5825813 within the Embryogenesis-associated protein (EMB8-like), while the location of rs5825939 is within the Ribosomal Protein Large P0 (RPLP0) ( Ahmed et al., 2021 ). Utilizing such markers in practical breeding programs can effectively improve the adaptability of current chickpea cultivars in saline soil.

Besides the above-mentioned reports, GWAS has also been conducted for yield and related traits in chickpea ( Li et al., 2021 ), root morphological traits ( Thudi et al., 2021 ), nutrient content ( Diapari et al., 2014 ; Sab et al., 2020 ) and abiotic tolerance traits ( Thudi et al., 2014 ; Samineni et al., 2022 ). Thus, the associated genomic regions identified through GWAS could be used for breeding programs to improve yield-related traits, nutrient content, and biotic and abiotic stress tolerance in chickpea. Recently, in other studies, we have accomplished GWAS for nodule numbers in chickpea by conducting multi-locational phenotypic evaluations and have identified seven significant SNP IDs (Kumar et al. unpublished data).

3.2.11 Genetic Engineering for Broadening Genetic Bases

Genetic engineering has been widely utilized to select resistant gene(s) ( Table 6 ) from various resources and transmit them to selected plants to introgress resistance to various abiotic as well as biotic challenges. Various genes are now being deployed in pulses using Agrobacterium -mediated ( Eapen et al., 1987 ; Krishnamurthy et al., 2000 ; Sharma K. K. et al., 2006 ), particle gun bombardment ( Kamble et al., 2003 ; Indurker et al., 2007 ), electroporation of intact axillary buds ( Chowrira et al., 1996 ) electroporation and PEG mediated transformation using protoplasts ( Köhler et al., 1987a ; Köhler et al., 1987b ). The most widely used method for developing transgenics in pulse crops is Agrobacterium mediated explant transformation. To generate transgenic plants, numerous transgenes from various sources have been introduced into pulse crops.

List of engineered genes/traits in chickpea.

Transgenic chickpea is developed either by gene gun ( Kar et al., 1997 ; Husnain et al., 2000 ; Tewari-Singh et al., 2004 ; Indurker et al., 2007 ) or Agrobacterium -mediated method ( Kar et al., 1997 ; Sanyal et al., 2005 ; Biradar et al., 2009 ; Acharjee et al., 2010 ; Asharani et al., 2011 ; Mehrotra et al., 2011 ; Ganguly et al., 2014 ). Important target traits for transgenic plant development in chickpea are insect pest resistance including α amylase inhibitor genes and lectin genes ( Dita et al., 2006 ), Cry genes from Bacillus thuringiensis , protease inhibitor genes, disease resistance including transfer of genes such as chitinase gene, antifungal protein genes or stilbene synthase gene for fungal resistance, coat protein genes of viruses for viral resistance and bacterial resistance from T 4 lysozyme gene ( Eapen, 2008 ), various abiotic stresses like salinity, drought, mineral toxicities, cold, temperature, etc., seed proteins, plant architecture, and RNA interference technology could be used to increase carotenoids and flavanoids by engineering metabolic pathways to decrease the effect of endogenous genes ( Eapen, 2008 ).

As presented in Table 7 transformation through Agrobacterium with the cry1Ab/Ac gene in chickpea has resulted in resistance to Helicoverpa armigera ( Lawo et al., 2008 ; Ganguly et al., 2014 ). Bombardment of calli with DNA-coated tungsten particles resulted in somatic embryogenesis and the subsequent generation of transgenic chickpea ( Husnain et al., 2000 ). Other researchers have also reported on the use of transgenic chickpea as a drought-tolerant and pest-resistant cultivar ( Bhatnagar-Mathur et al., 2009 ; Khatodia et al., 2014 ; Kumar et al., 2014 ).

Genetic transformation of chickpea.

3.2.12 Bioinformatic Molecular Data Bases/Resources for Broadening Genetic Bases

The recent data reports on leguminous genomics and transcriptomics have forced the creation of an exhaustive model of legume genomics and transcriptomics databases. Readily available data through online database portals are playing a significant role in research and development. LegumeIP ( http://plantgrn.noble.org/LegumeIP/ ), an integrative database for comparative genomics and transcriptomics of model legumes, for use in studying gene function and genome evolution in this center-stage plant family including the genome sequences of M. truncatula , G. max and L. japonicas and two reference plant species, i.e., A. thaliana and Populus trichocarpa were employed ( Li et al., 2012 ). The Legume Information System (LIS; https://legumeinfo.org ) ( Dash et al., 2016 ) gives users access to genetic and genomic data for model legumes. KnowPulse ( https://knowpulse.usask.ca ) for chickpea, common bean, field pea, fababean, and lentil, focuses on diversity data and gives information on germplasm, genetic markers, sequence variants, and phenotypic traits ( Sanderson et al., 2019 ).

The construction of bioinformatics databases ( Table 8 ) for the chickpea gene pool, according to recent breakthroughs in computational genomics, will permit users to visualize and extract chickpea genomics data in order to learn comparative genomics, annotate gene function, and investigate novel transcription factors ( Doddamani et al., 2015 ; Verma et al., 2015 ; Gayali et al., 2016 ). Many databases have been built for chickpea, including CicArMiSatDB ( https://cegresources.icrisat.org/CicArMiSatDB/ ) for SSR markers ( Doddamani et al., 2014 ), CicArVarDB ( https://cegresources.icrisat.org/cicarvardb/ ) for SNPs and QTLs, and Chickpea Transcriptome Database ( Verma et al., 2015 ). Furthermore, a few years ago, the PLncPRO tool was developed to acquire unique insights into the rising importance of long noncoding RNAs in response to various abiotic challenges in chickpea ( Singh et al., 2017 ).

Bioinformatics resources for chickpea.

There are also other molecular databases developed in other pulse crops which are useful in comparative genomics studies. Some of the important databases are highlighted as further. The PIgeonPEa Microsatellite DataBase (PIPEMicroDB) program ( http://cabindb.iasri.res.in/pigeonpea/ ) stores a catalogue of microsatellites retrieved from the pigeon pea genome ( Sarika et al., 2013 ). The adaptation of this program for chromosome-based search may be utilized for QTL markers for crop improvement and mapping of genes. With the fast development of publicly available Affymetrix GeneChip Medicago Genome Array Gene Chip data from cell types, a wide range of tissues, growth conditions, and stress treatments, the legume research group is in need of an efficient bioinformatics system to assist efforts to analyze the Medicago genome through functional genomics. The MtGEA ( Medicago truncatula Gene Expression Atlas) website ( http://bioinfo.noble.org/gene-atlas/ ) now includes additional gene expression data and genome annotation ( He et al., 2009 ). The Medicago truncatula Genome Database ( http://www.medicagogenome.org ) houses a diverse collection of genomic data sets ( Krishnakumar et al., 2015 ). RNA-Seq Atlas (Seq-Atlas) for Glycine max ( http://www.soybase.org/soyseq ) gathers RNASeq data from a variety of tissues and offers new techniques for analyzing huge transcriptome data sets produced from next-generation sequencing ( Severin et al., 2010 ). SoyBase ( https://www.soybase.org/ ), the USDA-ARS soybean genetic database, is a comprehensive library of professionally maintained soybean genetics, genomics, and related data resources ( Grant et al., 2010 ). The Lotus japonicus Gene Expression Atlas (LjGEA: http://ljgea.noble.org/ ) provides a global picture of gene expression in organ systems of the species including roots, nodules, stems, petioles, leaves, flowers, pods, and seeds. It enables versatile, multifaceted transcriptome analysis ( Verdier et al., 2013 ).

3.2.13 Genome Editing for Broadening Genetic Bases

Genome editing promises giant leaps forward in broadening the genetic bases research. Targeted DNA integration into known locations in the genome has potential advantages over the random insertional events typically achieved using conventional means of genetic modification. The gene of interest is positioned near the T-DNA left border which is responsible for the insertion of plant cell. Molecular biologists can now more accurately target any gene of interest because advances in genome editing tools such as zinc-finger nucleases (ZFNs), homing endonuclease and transcription activator-like effector nucleases (TALENs) could possibly be exploited for genomics-assisted selection toward accelerated genetic gains ( Shan et al., 2013 ; Bortesi and Fischer, 2015 ), while more advancements in chickpea enhancement using these cutting-edge approaches are still awaited. In chickpea, the 4-coumarate ligase (4CL) and Reveille 7 (RVE7) genes were selected as genes associated with drought tolerance for CRISPR/Cas9 editing in chickpea protoplast. The knockout of these selected genes in the chickpea protoplast showed high-efficiency editing was achieved for RVE7 gene in vivo compared to the 4CL gene ( Badhan et al., 2021 ). These methods, however, are costly and time-consuming since they need complex procedures that require protein engineering. Unlike first-generation genome editing techniques, CRISPR/Cas9 genome editing is straightforward to design and clone and the same Cas9 can theoretically be used with various guide RNAs targeting many places in the genome. Several proof-of-concept demonstrations in crop plants using the primary CRISPR-Cas9 module, and numerous customized Cas9 cassettes have been used to improve target selectivity and reduce off-target cleavage. Thus, the applications of genome editing techniques in chickpea research have great potential ( Mahto et al., 2022 ).

4 Integrating Various Omics Approaches for Broadening the Chckpea Genetic Base

The technological advances that transformed chickpea from an orphan crop to a genomic resource enriched crop in the post-genomics era, Re-sequencing efforts using WGRS have led to the dissection of genetic diversity, population structure, domestication patterns, linkage disequilibrium and the unexploited genetic potential for chickpea improvement ( Varshney et al., 2019 ). Modern genomics technologies have the potential to speed up the process for trait mapping, gene discovery, marker development and molecular breeding, in addition to enhancing the rate of productivity gains in chickpea. Integration of genome-wide sequence information with precise phenotypic variation allows capturing accessions with low-frequency variants that may be responsible for essential phenotypes such as yield components, abiotic stress tolerance, or disease resistance ( Roorkiwal et al., 2020 ). NGS technology has resulted in the development and application of a wide variety of molecular markers for chickpea improvement ( Kale et al., 2015 ; Varshney et al., 2018 ). Over the past decade, more than 2000 simple sequence repeat (SSR) markers, 15,000 features-based diversity array technology (DArT) platform, and millions of SNP markers have been developed for chickpea ( Varshney 2016 ). The revolution in NGS technologies has enabled sequencing to be performed at a higher depth (whole-genome re-sequencing), mid-depth (skim sequencing), or lower depth (genotyping by sequencing, RAD-Seq). Integrating omics data from multiple platforms such as transcriptomics, proteomics and metabolomics are paramount to bridging the genome-to-phenome gap in crop plants and ultimately identifying the phenotype based on their genetics. applications of genomic technologies for bridging the genotype–phenotype gap in chickpea ( Figure 5 ). With the availability of the reference genome, these genetic resources can be subjected to whole-genome re-sequencing (WGRS) or high- to low-density genotyping, based on the objective of the study, using the available genotyping platforms (e.g., genotyping by sequencing, GBS; array-based genotyping). Analysis at the transcriptome, proteome, and metabolome levels can be performed to gain novel insights into the candidate genes and biological processes involved. Using a genomics approach Fusarium wilt resistance WR 315 Annigeri 1 foc4 has been Released as “Super Annigeri 1′ for commercial cultivation in India Mannur et al. (2019) .

Integrating various approaches for broadening the genetic base.

5 Conclusion and Future Perspective

With the employment of modern “Omics” technologies in combination with traditional methods, it is now possible to overcome yield limits, and achieve higher genetic gains ensuring high output for chickpea production and quality features. Chickpea land races and wild Cicer species are the goldmines of beneficial genes influencing desired traits of interest for biotic, abiotic, and yield component features. Identification of novel sources of desired traits, QTLs or alleles through extensive evaluation and utilization of landraces and wild Cicer species will have a greater impact on developing chickpeas for better climate resilience and higher yield. Many desirable features from primary and secondary gene pools in wild Cicer species have been successfully transmitted into cultivated cultivars using both traditional and modern procedures. The wealth of new omics approaches and growing resources offer great potential to transform chickpea breeding in the near future. An integrated application of chickpea “Omics”, classical and modern breeding methods, marker-assisted selection, and biotechnological application promises for the broadening of the chickpea genetic base and introgression of new genes for crop traits for higher productivity will lead to next-generation chickpea varieties.

Acknowledgments

ICARDA authors received support from CWANA integrated initiative.

Data Availability Statement

Author contributions.

RK conceptualized and supervised the manuscript writing. RS, CS, Ambika, BC, RM, RP, and AG collected the related literature and contributed to the original writing. VG, Gayacharan, AH, HU, and RK extended their help in the inference, review, and editing of the manuscript. All authors went through the final manuscript draft and approved it.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The reviewer RS declared a shared affiliation with the author Gayacharan to the handling editor at the time of review.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors, and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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