Publications of NIPGR Scientists
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Item eQTL-seq: a rapid genome-wide integrative genetical genomics strategy to dissect complex regulatory architecture of gene expression underlying quantitative trait variation in crop plants(Springer Nature Publishing AG, 2024) Mohanty, Jitendra K.; Jha, Uday Chand; Dixit, G. P.; Bharadwaj, Chellapilla; Parida, Swarup K.We developed a combinatorial next generation sequencing (NGS)-based high-throughput expression QTL-seq (eQTL-seq) strategy for rapid elucidation of complex genetic architecture and regulatory pathways of gene expression underlying quantitative trait variation in crop plants. This high-resolution genome-wide integrative genetical genomics strategy assists us to delineate functionally relevant molecular tags (QTLs/eQTLs, genes, master regulators/transcription factors, and alleles) regulating vital agronomic traits in order to expedite genomics-assisted breeding and crop improvement. As a proof-of-concept, the optimized eQTL-seq-led genetical genomics approach was employed in 192 mapping individuals of an intra-specific recombinant inbred line (RIL) population (desi accession ICC 4958 x kabuli accession ICC 12968) with contrasting seed weight trait. This led to identification and mapping of high-resolution major QTLs/eQTLs associated with seed weight based on genome resequence-derived genomic SNP-index (Delta(gSNP-index)), global transcriptome sequence-based expression SNP-index (Delta(eSNP-index)), and relative gene expression (RGE)-index (Delta(RGE-index)). The eQTL-seq scaled down the major seed weight QTLs/eQTLs into the potential candidate gene(s) governing cis- and trans-regulated expression to decipher the gene regulatory modules controlling complex quantitative seed weight trait by deriving global allele-specific gene expression polymorphism in chickpea. Henceforth, the efficacy of NGS-driven integrative eQTL-seq strategy as compared to traditional QTL mapping, fine-mapping (map-based cloning), and QTL-seq approaches that are widely adopted for delineation of candidate genes underlying major QTLs was evident in chickpea. This will further accelerate quantitative dissection of regulatory architecture by decoding the molecular genetic basis of gene expression variation controlling diverse complex phenotypic trait diversity in chickpea and other crop plants as well.Item ABC transporter-mediated transport of glutathione conjugates enhances seed yield and quality in chickpea(American Society of Plant Biologists, 2019) Basu, Udita; Upadhyaya, Hari D.; Srivastava, Rishi; Daware, Anurag; Malik, Naveen; Sharma, Akash; Bajaj, Deepak; Narnoliya, Laxmi; Thakro, Virevol; Kujur, Alice; Tripathi, Shailesh; Bharadwaj, Chellapilla; Hegde, V. S.; Pandey, Ajay K.; Singh, Ashok K.; Tyagi, Akhilesh K.; Parida, Swarup K.The identification of functionally relevant molecular tags is vital for genomics-assisted crop improvement and enhancing the seed yield, quality and productivity in chickpea. The simultaneous improvement of yield/productivity as well as quality traits often requires pyramiding of multiple genes, which remains a major hurdle given various associated epistatic and pleotropic effects. Unfortunately, no single gene that can improve yield/productivity along with quality and other desirable agromorphological traits is known, hampering the genetic enhancement of chickpea. Using a combinatorial genomics-assisted breeding and functional genomics strategy, this study identified natural alleles and haplotypes of an ABCC3-type transporter gene that regulates seed weight, an important domestication trait, by transcriptional regulation and modulating the transport of glutathione conjugates in seeds of desi and kabuli chickpea. The superior allele/haplotype of this gene introgressed in desi and kabuli near-isogenic lines enhances the seed weight, yield, productivity and multiple desirable plant architecture and seed-quality traits without compromising the agronomic performance. These salient findings can expedite crop improvement endeavors and the development of nutritionally enriched high-yielding cultivars in chickpea.Item 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.Item 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.Item 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.Item Genetic dissection of plant growth habit in chickpea(Springer, 2017) Upadhyaya, Hari D.; Bajaj, Deepak; Srivastava, Rishi; Daware, Anurag; Basu, Udita; Tripathi, Shailesh; Bharadwaj, Chellapilla; Tyagi, Akhilesh K.; Parida, Swarup K.A combinatorial genomics-assisted breeding strategy encompassing association analysis, genetic mapping and expression profiling is found most promising for quantitative dissection of complex traits in crop plants. The present study employed GWAS (genome-wide association study) using 24,405 SNPs (single nucleotide polymorphisms) obtained with genotyping-by-sequencing (GBS) of 92 sequenced desi and kabuli accessions of chickpea. This identified eight significant genomic loci associated with erect (E)/semi-erect (SE) vs. spreading (S)/semi-spreading (SS)/prostrate (P) plant growth habit (PGH) trait differentiation regardless of diverse desi and kabuli genetic backgrounds of chickpea. These associated SNPs in combination explained 23.8% phenotypic variation for PGH in chickpea. Five PGH-associated genes were validated successfully in E/SE and SS/S/P PGH-bearing parental accessions and homozygous individuals of three intra- and interspecific RIL (recombinant inbred line) mapping populations as well as 12 contrasting desi and kabuli chickpea germplasm accessions by selective genotyping through Sequenom MassARRAY. The shoot apical, inflorescence and floral meristems-specific expression, including upregulation (seven-fold) of five PGH-associated genes especially in germplasm accessions and homozygous RIL mapping individuals contrasting with E/SE PGH traits was apparent. Collectively, this integrated genomic strategy delineated diverse non-synonymous SNPs from five candidate genes with strong allelic effects on PGH trait variation in chickpea. Of these, two vernalization-responsive non-synonymous SNP alleles carrying SNF2 protein-coding gene and B3 transcription factor associated with PGH traits were found to be the most promising in chickpea. The SNP allelic variants associated with E/SE/SS/S PGH trait differentiation were exclusively present in all cultivated desi and kabuli chickpea accessions while wild species/accessions belonging to primary, secondary and tertiary gene pools mostly contained prostrate PGH-associated SNP alleles. This indicates strong adaptive natural/artificial selection pressure (Tajima's D 3.15 to 4.57) on PGH-associated target genomic loci during chickpea domestication. These vital leads thus have potential to decipher complex transcriptional regulatory gene function of PGH trait differentiation and for understanding the selective sweep-based PGH trait evolution and domestication pattern in cultivated and wild chickpea accessions adapted to diverse agroclimatic conditions. Collectively, the essential inputs generated will be of profound use in marker-assisted genetic enhancement to develop cultivars with desirable plant architecture of erect growth habit types in chickpea.Item Eco TILLING-based association mapping efficiently delineates functionally relevant natural allelic variants of candidate genes governing agronomic traits in chickpea(Frontiers Media S.A., 2016) Bajaj, Deepak; Srivastava, Rishi; Nath, Manoj; Tripathi, Shailesh; Bharadwaj, Chellapilla; Upadhyaya, Hari D.; Tyagi, Akhilesh K.; Parida, Swarup K.The large-scale mining and high-throughput genotyping of novel gene-based allelic variants in natural mapping population are essential for association mapping to identify functionally relevant molecular tags governing useful agronomic traits in chickpea. The present study employs an alternative time-saving, non-laborious and economical pool-based EcoTILLING approach coupled with agarose gel detection assay to discover 1133 novel SNP allelic variants from diverse coding and regulatory sequence components of 1133 transcription factor (TF) genes by genotyping in 192 diverse desi and kabuli chickpea accessions constituting a seed weight association panel. Integrating these SNP genotyping data with seed weight field phenotypic information of 192 structured association panel identified eight SNP alleles in the eight TF genes regulating seed weight of chickpea. The associated individual and combination of all SNPs explained 10-15 and 31% phenotypic variation for seed weight, respectively. The EcoTILLING-based large-scale allele mining and genotyping strategy implemented for association mapping is found much effective for a diploid genome crop species like chickpea with narrow genetic base and low genetic polymorphism. This optimized approach thus can be deployed for various genomics-assisted breeding applications with optimal expense of resources in domesticated chickpea. The seed weight-associated natural allelic variants and candidate TF genes delineated have potential to accelerate marker-assisted genetic improvement of chickpea.