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    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.
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    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.
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    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.
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    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.
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    High-density linkage map construction and mapping of seed trait QTLs in chickpea (Cicer arietinum L.) using genotyping-by-sequencing (GBS)
    (Nature Publishing Group, 2015) Verma, Subodh; Gupta, Shefali; Bandhiwal, Nitesh; Kumar, Tapan; Bharadwaj, Chellapilla; Bhatia, Sabhyata
    This study reports the use of Genotyping-by-Sequencing (GBS) for large-scale SNP discovery and simultaneous genotyping of recombinant inbred lines (RILs) of an intra-specific mapping population of chickpea contrasting for seed traits. A total of 119,672 raw SNPs were discovered, which after stringent filtering revealed 3,977 high quality SNPs of which 39.5% were present in genic regions. Comparative analysis using physically mapped marker loci revealed a higher degree of synteny with Medicago in comparison to soybean. The SNP genotyping data was utilized to construct one of the most saturated intra-specific genetic linkage maps of chickpea having 3,363 mapped positions including 3,228 SNPs on 8 linkage groups spanning 1006.98 cM at an average inter marker distance of 0.33 cM. The map was utilized to identify 20 quantitative trait loci (QTLs) associated with seed traits accounting for phenotypic variations ranging from 9.97% to 29.71%. Analysis of the genomic sequence corresponding to five robust QTLs led to the identification of 684 putative candidate genes whose expression profiling revealed that 101 genes exhibited seed specific expression. The integrated approach utilizing the identified QTLs along with the available genome and transcriptome could serve as a platform for candidate gene identification for molecular breeding of chickpea.