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Next generation genomics for chickpea (Cicer arietinum L.) improvement
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Next generation genomics for chickpea (Cicer arietinum L.) improvement

  1. Inclusive Market-Oriented Development (IMOD) – our approach to bringing prosperity in the drylands. ICRISAT is a member of the CGIAR Consortium. Large scale genomic resources including draft genome sequence, re-sequencing of 90 lines, comprehensive transcriptome assembly and high density genetic maps have been developed for chickpea. Linkage mapping and genome wide association studies (GWAS) are being used for trait mapping. One genomic region (“QTL-hotspot”) harboring QTLs for several drought tolerance traits has been identified and genotyping-by-sequencing (GBS) approach is being used to fine-map this region. Introgression of this region in to elite chickpea lines have shown yield improvement under irrigated as well as rainfed conditions. Similarly QTLs controlling important biotic stresses like Fusarium wilt (FW) and Ascochyta blight (AB) have been mapped and used for introgression. In parallel, association mapping approaches using genotyping data for 1882 markers and sequence data for 10 genes together with phenotyping data for 24 drought tolerance traits on the reference set comprising 300 genotypes provided 335 significant marker-trait associations (MTAs). In addition, 5X- 10X coverage whole genome re-sequencing data have been generated on the reference set that is being used for GWAS analysis. In order to deploy genomic selection, a training population of 320 elite breeding lines was phenotyped at two locations for yield related traits. Generated genome-wide marker profiling data (Total >3000 markers) along with phenotyping data was used with a range of regression and bayesian based statistical methods to predict genomic estimated breeding values. Furthermore, several transcriptomics and functional genomics approaches such as RNA-seq, Massive Analysis of cDNA Ends (MACE) with parental genotypes of mapping populations as well NILs have provided some candidate genes for biotic and abiotic stress response that are being validated through quantitative real time PCR (qRT-PCR) and TILLING approaches. Genetic mapping of these candidate genes may provide perfect markers for use in chickpea molecular breeding. Abstract Molecular markers and genotyping platforms 547 –GSSs from enriched library 25,000 BAC-end sequences 2,460 markers 435,018 FLX/454 STRs SSRs identified 3,728 26,252 6,845 643 Primer-pairs synthesized 77 728 1,344 311 20,162 ESTs Novel SSR markers SSRs 768 SNPs GoldenGate assay615 SNPs based on legume COSs 153 SNPs from allele specific sequencing 2,068 KASPar assays >10,000 SNPs based on Solexa sequencing 742 CAPS markers SNPs 96 VeraCode assays DArT arrays DArT arrays with 15,360 features/DArT seq Genome sequencing, re-sequencing and GWAS Reference genetic map Mapping population ICC 4958 × PI 489777 Marker loci mapped 1,291 Total map distance (cM) 845.56 Trait mapping C 214 × ILC 3279 - Ascochyta blight (AB) C214 × WR 315: Fusarium wilt (FW) LG 1 LG 2 LG 3 LG 4 LG 5 LG 6 LG 7 LG 8 Drought tolerance Disease resistance ICC 4958 × ICC 1882 Consensus map ICC 283 × ICC8261 Functional validation of candidate genes TILLING population development and allele mining Morphological mutants in field (M3 generation) NCBI 41,984 ESTs ICC 4958 (NIPGR) 97,257 Sanger reads 134.99 Million Illumina tags 7,127,750 FLX/454 STRs ICC 4958 (NIPGR) ICC 4958 (ICRISAT) 103,215 TUSs 34,760 TUSs 46,369 TACs Amit, Cr5-10 CDC Frontier, CDC Xana, ICC 12512-1, ICCV 96029, ILWC 118, Y9563-28 (NRC) AAFC CDC Frontier (NRC) Comprehensive transcriptome assembly Allelic variants in Ca220909 gene Genomic selection Varshney RK1*, Kudapa H1, Roorkiwal M1, Thudi M1, Chitikineni A1, Odeny DA2, Sabbavarapu MM1, Jaganathan D1, Singh M1, Katta KM1, Agarwal G1, Khan AW1, Ganga Rao NVPR2, Gaur PM1, Upadhyaya HD1, Rathore A1, Krishnamurthy L1, Shah TM1, Sharma M1, Samineni S1, Siambi M2, Waliyar F3 Next generation genomics for chickpea (Cicer arietinum L.) improvement 1International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India; 2ICRISAT, Nairobi, Kenya; 3ICRISAT, Bamako, Mali; *Address for correspondence: r.k.varshney@cgiar.org PPI predicted for MYB1R1 qRT-PCR validation Global distribution of reference set <7X, 8 7X-8X, 10 8X-9X, 40 9X-10X, 106 10X-11X, 81 11X-12X, 25 >12X, 30 Re-sequencing of reference set  Illumina sequencing used to generate 153.01 Gb  73.8% of the genome captured in scaffolds  Genome analysis predicted 28,269 genes  > 81,845 SSRs and 1.97 million variants  Assembly contains 187 disease resistance gene homologs  90 cultivated and wild genotypes re- sequenced Draft genome sequence Genome wide association scan for 100 seed weight Training Population Two locations IARI ICRISAT Two seasons 2011-12 2012-13 Two treatments Irrigated Rainfed KASPar (651) DArT arrays (15,360) DArT-Seq Training Population: 320 elite breeding lines KASPar: 67 polymorphic out of total 651 DArT: 1432 polymorphic out of 15,360 DArTseq:1684 polymorphic Control
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