Genetic dissection of drought tolerance in chickpea (Cicer arietinum L.)

Varshney, Rajeev K.; Thudi, Mahendar; Nayak, Spurthi N.; Gaur, Pooran M.; Kashiwagi, Junichi; Krishnamurthy, L.; Jaganathan, Deepa; Koppolu, Jahnavi; Bohra, Abhishek; Tripathi, Shailesh; Rathore, Abhishek; Jukanti, Aravind Kumar; Jayalakshmi, V.; Vemula, Anilkumar; Singh, Sarvjeet; Yasin, Mohammad; Sheshshayee, M. S.; Viswanatha, K. P.

doi:10.1007/s00122-013-2230-6

Cited by 342 publications

(433 citation statements)

References 38 publications

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“…In another deepSuperSAGE application, 80 238 tags representing 17 493 unique transcripts from drought-stressed Table 1. Summary of main-effect, stable and consistent quantitative trait loci (QTLs) for drought tolerance related traits in chickpea QTL explaining >10% of phenotypic variation are referred to as main-effect QTLs; QTL for a given trait appearing in more than one location are referred to as 'stable' QTL; QTL appearing in more than 1 year or season are considered to be 'consistent' QTL (Varshney et al 2014b A These markers are already being deployed in several marker-assisted backcrossing programs, as listed in Table 2. and nonstressed control roots in chickpea have been identified (Molina et al 2008(Molina et al , 2011. Gene cloning is an approach for isolating candidate genes that are functionally related to the trait of interest.…”

Section: Transcriptome Sequencing In Chickpeamentioning

confidence: 99%

“…Although efforts were made to understand drought tolerance (Rehman et al 2011;Hamwieh et al 2013), the studies aimed to understand the performance of agronomic or physiological traits. Recent research endeavours at ICRISAT by Varshney et al (2014b) may eventually lead to a comprehensive understanding of drought tolerance in chickpea. For understanding the complex nature of drought tolerance, precise phenotypic data (from 20 drought component traits evaluated in one to seven seasons at one to five locations in India on two intraspecific mapping populations (ICC 4958 Â ICC 1882 and ICC 283 Â ICC 8261) where analysed, alongside extensive genotyping data.…”

Section: Trait Mappingmentioning

confidence: 99%

“…For understanding the complex nature of drought tolerance, precise phenotypic data (from 20 drought component traits evaluated in one to seven seasons at one to five locations in India on two intraspecific mapping populations (ICC 4958 Â ICC 1882 and ICC 283 Â ICC 8261) where analysed, alongside extensive genotyping data. Comprehensive QTL analysis has provided several stable, consistent and robust main-effect QTLs for 13 out of 20 drought tolerance traits explaining 10-58.20% of phenotypic variation (Table 1; Varshney et al 2014b). Markers flanking these QTLs can be deployed for enhancing drought tolerance as well as individual trait improvement through MABC breeding.…”

Section: Trait Mappingmentioning

confidence: 99%

“…Markers flanking these QTLs can be deployed for enhancing drought tolerance as well as individual trait improvement through MABC breeding. A genomic region referred to as 'QTL-hotspot', spanning~29cM on Cicer arietinum Linkage Group 04 (CaLG04) of an intraspecific genetic map (ICC 4958 Â ICC 1882), was found to harbour 12 out of 25 main-effect QTLs for 12 traits explaining~58.20% of phenotypic variation (Varshney et al 2014b; Table 1). Seven SSR markers (ICCM0249, NCPGR127, TAA170, NCPGR21, TR11, GA24 and STMS11) present in QTL-hotspot are the most important markers for marker-assisted introgression of this genomic region into elite genetic backgrounds for enhancing drought tolerance through MABC.…”

Section: Trait Mappingmentioning

confidence: 99%

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Genomics-assisted breeding for drought tolerance in chickpea

Thudi

Gaur

Krishnamurthy

et al. 2014

Functional Plant Biol.

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Abstract.Terminal drought is one of the major constraints in chickpea (Cicer arietinum L.), causing more than 50% production losses. With the objective of accelerating genetic understanding and crop improvement through genomicsassisted breeding, a draft genome sequence has been assembled for the CDC Frontier variety. In this context, 544.73 Mb of sequence data were assembled, capturing of 73.8% of the genome in scaffolds. In addition, large-scale genomic resources including several thousand simple sequence repeats and several million single nucleotide polymorphisms, high-density diversity array technology (15 360 clones) and Illumina GoldenGate assay genotyping platforms, high-density genetic maps and transcriptome assemblies have been developed. In parallel, by using linkage mapping approach, one genomic region harbouring quantitative trait loci for several drought tolerance traits has been identified and successfully introgressed in three leading chickpea varieties (e.g. JG 11, Chefe, KAK 2) by using a marker-assisted backcrossing approach. A multilocation evaluation of these marker-assisted backcrossing lines provided several lines with 10-24% higher yield than the respective recurrent parents.Modern breeding approaches like marker-assisted recurrent selection and genomic selection are being deployed for enhancing drought tolerance in chickpea. Some novel mapping populations such as multiparent advanced generation intercross and nested association mapping populations are also being developed for trait mapping at higher resolution, as well as for enhancing the genetic base of chickpea. Such advances in genomics and genomics-assisted breeding will accelerate precision and efficiency in breeding for stress tolerance in chickpea.

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Section: Transcriptome Sequencing In Chickpeamentioning

confidence: 99%

Section: Trait Mappingmentioning

confidence: 99%

Section: Trait Mappingmentioning

confidence: 99%

Section: Trait Mappingmentioning

confidence: 99%

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Genomics-assisted breeding for drought tolerance in chickpea

Thudi

Gaur

Krishnamurthy

et al. 2014

Functional Plant Biol.

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“…The effect of branching on seed and pod yield as well as water-use efficiency is extensively studied and well documented in chickpea [17]. Only limited number of QTLs/genes regulating branch number have been identified utilizing QTL mapping and trait association analysis [18][19][20][21][22][23]. However, these identified QTLs/genes are yet to be deployed in marker-assisted selection for developing cultivars with high branch number in chickpea.…”

Section: Introductionmentioning

confidence: 99%

Identification of candidate genes for dissecting complex branch number trait in chickpea

et al. 2016

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a b s t r a c tThe present study exploited integrated genomics-assisted breeding strategy for genetic dissection of complex branch number quantitative trait in chickpea. Candidate gene-based association analysis in a branch number association panel was performed by utilizing the genotyping data of 401 SNP allelic variants mined from 27 known cloned branch number gene orthologs of chickpea. The genome-wide association study (GWAS) integrating both genome-wide GBS-(4556 SNPs) and candidate gene-based genotyping information of 4957 SNPs in a structured population of 60 sequenced desi and kabuli accessions (with 350-400 kb LD decay), detected 11 significant genomic loci (genes) associated (41% combined PVE) with branch number in chickpea. Of these, seven branch number-associated genes were further validated successfully in two inter (ICC 4958 × ICC 17160)-and intra (ICC 12299 × ICC 8261)-specific mapping populations. The axillary meristem and shoot apical meristem-specific expression, including differential up-and down-regulation (4-5 fold) of the validated seven branch number-associated genes especially in high branch number as compared to the low branch number-containing parental accessions and homozygous individuals of two aforesaid mapping populations was apparent. Collectively, this combinatorial genomic approach delineated diverse naturally occurring novel functional SNP allelic variants in seven potential known/candidate genes [PIN1 (PIN-FORMED protein 1), TB1 (teosinte branched 1), BA1/LAX1 (BARREN STALK1/LIKE AUXIN1), GRAS8 (gibberellic acid insensitive/GAI, Repressor of ga13/RGA and Scarecrow8/SCR8), ERF (ethylene-responsive element-binding factor), MAX2 (more axillary growth 2) and lipase] governing chickpea branch number. The useful information generated from this study have potential to expedite marker-assisted genetic enhancement by developing high-yielding cultivars with more number of productive (pods and seeds) branches in chickpea.

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