Browsing by Author "Kumar, Rajendra"

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Genetic dissection of photosynthetic efficiency traits for enhancing seed yield in chickpea
(John Wiley & Sons, 2019) Basu, Udita; Bajaj, Deepak; Sharma, Akash; Malik, Naveen; Daware, Anurag; Narnoliya, Laxmi; Thakro, Virevol; Upadhyaya, Hari D.; Kumar, Rajendra; Tripathi, Shailesh; Bharadwaj, Chellapilla; Tyagi, Akhilesh K.; Parida, Swarup K.
Understanding the genetic basis of photosynthetic efficiency (PE) contributing to enhanced seed yield per plant (SYP) is vital for genomics-assisted crop improvement of chickpea. The current study employed an integrated genomic strategy involving photosynthesis pathway gene-based association mapping, genome-wide association study, QTL mapping and expression profiling. This identified 16 potential SNP loci linked to major QTLs underlying 16 candidate genes significantly associated with PE and SYP traits in chickpea. The allelic variants were tightly linked to positively interacting QTLs regulating both enhanced PE and SYP traits as exemplified by a chlorophyll A-B binding protein-coding gene. The leaf tissue-specific pronounced up-regulated expression of 16 associated genes in germplasm accessions and homozygous individuals of mapping population was evident. Such combinatorial genomic strategy coupled with gene haplotype-specific association as well as in silico protein-protein interaction study delineated natural alleles and superior haplotypes from a chlorophyll A-B binding protein-coding gene and its interacting gene, Timing of CAB Expression 1, which appear to be most-promising candidates in modulating chickpea PE and SYP traits. These functionally pertinent molecular signatures identified have efficacy to drive marker-assisted selection for developing PE-enriched cultivars with high seed yield in chickpea.
Genome-wide development and deployment of informative intron-spanning and intron-length polymorphism markers for genomics-assisted breeding applications in chickpea
(Elsevier B.V., 2016) Srivastava, Rishi; Bajaj, Deepak; Sayal, Yogesh K.; Meher, Prabina K.; Upadhyaya, Hari D.; Kumar, Rajendra; Tripathi, Shailesh; Bharadwaj, Chellapilla; Rao, Atmakuri R.; Parida, Swarup K.
The discovery and large-scale genotyping of informative gene-based markers is essential for rapid delineation of genes/QTLs governing stress tolerance and yield component traits in order to drive genetic enhancement in chickpea. A genome-wide 119169 and 110491 ISM (intron-spanning markers) from 23129 desi and 20386 kabuli protein-coding genes and 7454 in silico InDel (insertion-deletion) (1–45-bp)-based ILP (intron-length polymorphism) markers from 3283 genes were developed that were structurally and functionally annotated on eight chromosomes and unanchored scaffolds of chickpea. A much higher amplification efficiency (83%) and intra-specific polymorphic potential (86%) detected by these markers than that of other sequence-based genetic markers among desi and kabuli chickpea accessions was apparent even by a cost-effective agarose gel-based assay. The genome-wide physically mapped 1718 ILP markers assayed a wider level of functional genetic diversity (19–81%) and well-defined phylogenetics among domesticated chickpea accessions. The gene-derived 1424 ILP markers were anchored on a high-density (inter-marker distance: 0.65 cM) desi intra-specific genetic linkage map/functional transcript map (ICC 4958 × ICC 2263) of chickpea. This reference genetic map identified six major genomic regions harbouring six robust QTLs mapped on five chromosomes, which explained 11–23% seed weight trait variation (7.6–10.5 LOD) in chickpea. The integration of high-resolution QTL mapping with differential expression profiling detected six including one potential serine carboxypeptidase gene with ILP markers (linked tightly to the major seed weight QTLs) exhibiting seed-specific expression as well as pronounced up-regulation especially in seeds of high (ICC 4958) as compared to low (ICC 2263) seed weight mapping parental accessions. The marker information generated in the present study was made publicly accessible through a user-friendly web-resource, “Chickpea ISM-ILP Marker Database”. The designing of multiple ISM and ILP markers (2–5 markers/gene) from an individual gene (transcription factor) with numerous aforementioned desirable genetic attributes can widen the user-preference to select suitable primer combination for simultaneous large-scale assaying of functional allelic variation, natural allelic diversity, molecular mapping and expression profiling of genes among chickpea accessions. This will essentially accelerate the identification of functionally relevant molecular tags regulating vital agronomic traits for genomics-assisted crop improvement by optimal resource expenses in chickpea.
Identifying transcription factor genes associated with yield traits in chickpea
(Springer, 2017) Shimray, Philanim Wungmarong; Bajaj, Deepak; Srivastava, Rishi; Daware, Anurag; Upadhyaya, Hari D.; Kumar, Rajendra; Bharadwaj, Chellapilla; Tyagi, Akhilesh K.; Parida, Swarup K.
Identification of potential transcription factor (TF) gene-derived natural SNP allelic variants regulating pod and seed yield component traits by large-scale mining and genotyping of SNPs in natural germplasm accessions coupled with high-resolution association mapping is vital for understanding the complex genetic architecture of quantitative yield traits in chickpea. In these perspectives, the current study employed a genome-wide GBS (genotyping-by-sequencing) and targeted gene amplicon resequencing-based simultaneous SNP discovery and genotyping assays, which discovered 1611 novel SNPs from 736 TF genes physically mapped on eight chromosomes and unanchored scaffolds of kabuli chickpea genome. These SNPs were structurally and functionally annotated in diverse synonymous and non-synonymous coding as well as non-coding regulatory and intronic sequence components of chickpea TF genes. A high-resolution genetic association analysis was performed by correlating the genotyping information of 1611 TF gene-based SNPs with multi-location/years field phenotyping data of six major pod and seed yield traits evaluated in a constituted association panel (326 desi and kabuli germplasm accessions) of chickpea. This essentially identified 27 TF gene-derived SNPs exhibiting significant association with six major yield traits, namely days to 50% flowering (DF), plant height (PH), branch number (BN), pod number (PN), seed number (SN) and seed weight (SW) in chickpea. These trait-associated SNPs individually and in combination explained 10–23% and 32% phenotypic variation respectively for the studied yield component traits. Interestingly, novel non-synonymous coding SNP allelic variants in five potential candidate TF genes encoding SBP (squamosal promoter binding protein), SNF2 (sucrose non-fermenting 2), GRAS [Gibberellic acid insensitive (GAI)-Repressor of GAI (RGA)-SCARECROW (SCR)], bZIP (basic leucine zipper) and LOB (lateral organ boundaries)-domain proteins associated strongly with DF, PH, BN, PN, SN and SW traits respectively were found most promising in chickpea. The functionally relevant molecular signatures (TFs and natural SNP alleles) delineated by us have potential to accelerate marker-assisted genetic enhancement by developing high pod and seed yielding cultivars of chickpea.
A multiple QTL-Seq strategy delineates potential genomic loci governing flowering time in chickpea
(Frontiers Media S.A., 2017) Srivastava, Rishi; Upadhyaya, Hari D.; Kumar, Rajendra; Daware, Anurag; Basu, Udita; Shimray, Philanim W.; Tripathi, Shailesh; Bharadwaj, Chellapilla; Tyagi, Akhilesh K.; Parida, Swarup K.
Identification of functionally relevant potential genomic loci using an economical, simpler and user-friendly genomics-assisted breeding strategy is vital for rapid genetic dissection of complex flowering time quantitative trait in chickpea. A high-throughput multiple QTL-seq strategy was employed in two inter (Cicer arietinum desi accession ICC 4958 × C reticulatum wild accession ICC 17160)- and intra (ICC 4958 × C. arietinum kabuli accession ICC 8261)-specific RIL mapping populations to identify the major QTL genomic regions governing flowering time in chickpea. The whole genome resequencing discovered 1635117 and 592486 SNPs exhibiting differentiation between early- and late-flowering mapping parents and bulks, constituted by pooling the homozygous individuals of extreme flowering time phenotypic trait from each of two aforesaid RIL populations. The multiple QTL-seq analysis using these mined SNPs in two RIL mapping populations narrowed-down two longer (907.1 kb and 1.99 Mb) major flowering time QTL genomic regions into the high-resolution shorter (757.7 kb and 1.39 Mb) QTL intervals on chickpea chromosome 4. This essentially identified regulatory as well as coding (non-synonymous/synonymous) novel SNP allelic variants from two efl1 (early flowering 1) and GI (GIGANTEA) genes regulating flowering time in chickpea. Interestingly, strong natural allelic diversity reduction (88-91%) of two known flowering genes especially mapped at major QTL intervals as compared to that of background genomic regions (where no flowering time QTLs were mapped; 61.8%) in cultivated vis-à-vis wild Cicer gene pools was evident inferring the significant impact of evolutionary bottlenecks on these loci during chickpea domestication. Higher association potential of coding non-synonymous and regulatory SNP alleles mined from efl1 (36-49%) and GI (33-42%) flowering genes for early and late flowering time differentiation among chickpea accessions was evident. The robustness and validity of two functional allelic variants-containing genes localized at major flowering time QTLs was apparent by their identification from multiple intra-/inter-specific mapping populations of chickpea. The functionally relevant molecular tags delineated can be of immense use for deciphering the natural allelic diversity-based domestication pattern of flowering time and expediting genomics-aided crop improvement to develop early flowering cultivars of chickpea.