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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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    Genome-wide cis-regulatory signatures for modulation of agronomic traits as exemplified by drought yield index (DYI) in chickpea
    (Springer Nature Publishing AG, 2019) Sharma, Akash; Basu, Udita; Malik, Naveen; Daware, Anurag; Thakro, Virevol; Narnoliya, Laxmi; Bajaj, Deepak; Tripathi, Shailesh; Hegde, V. S.; Upadhyaya, Hari D.; Tyagi, Akhilesh K.; Parida, Swarup K.
    Developing functional molecular tags from the cis-regulatory sequence components of genes is vital for their deployment in efficient genetic dissection of complex quantitative traits in crop plants including chickpea. The current study identified 431,194 conserved non-coding SNP (CNSNP) from the cis-regulatory element regions of genes which were annotated on a chickpea genome. These genome-wide CNSNP marker resources are made publicly accessible through a user-friendly web-database (http://www.cnsnpcicarbase.com). The CNSNP-based quantitative trait loci (QTL) and expression QTL (eQTL) mapping and genome-wide association study (GWAS) were further integrated with global gene expression landscapes, molecular haplotyping, and DNA-protein interaction study in the association panel and recombinant inbred lines (RIL) mapping population to decode complex genetic architecture of one of the vital seed yield trait under drought stress, drought yield index (DYI), in chickpea. This delineated two constituted natural haplotypes and alleles from a histone H3 protein-coding gene and its transcriptional regulator NAC transcription factor (TF) harboring the major QTLs and trans-acting eQTL governing DYI in chickpea. The effect of CNSNPs in TF-binding cis-element of a histone H3 gene in altering the binding affinity and transcriptional activity of NAC TF based on chromatin immunoprecipitationquantitative PCR (ChIP-qPCR) assay was evident. The CNSNP-led promising molecular tags scanned will essentially have functional significance to decode transcriptional gene regulatory function and thus can drive translational genomic analysis in chickpea.
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    eQTL regulating transcript levels associated with diverse biological processes in tomato
    (American Society of Plant Biologists, 2016) Ranjan, Aashish; Budke, Jessica; Rowland, Steven D.; Chitwood, Daniel H; Kumar, Ravi; Carriedo, Leonela G.; Ichihashi, Yasunori; Zumstein, Kristina; Maloof, Julin N.; Sinha, Neelima R.
    Variation in gene expression, in addition to sequence polymorphisms, is known to influence developmental, physiological and metabolic traits in plants. Genetic mapping populations have facilitated identification of expression Quantitative Trait Loci (eQTL), the genetic determinants of variation in gene expression patterns. We used an introgression population developed from the wild desert-adapted Solanum pennellii and domesticated tomato Solanum lycopersicum to identify the genetic basis of transcript level variation. We established the effect of each introgression on the transcriptome, and identified ~7,200 eQTL regulating the steady state transcript levels of 5,300 genes. Barnes-Hut t-distributed stochastic neighbor embedding clustering identified 42 modules revealing novel associations between transcript level patterns and biological processes. The results showed a complex genetic architecture of global transcript abundance pattern in tomato. Several genetic hotspots regulating a large number of transcript level patterns relating to diverse biological processes such as plant defense and photosynthesis were identified. Important eQTL regulating transcript level patterns were related to leaf number and complexity, and hypocotyl length. Genes associated with leaf development showed an inverse correlation with photosynthetic gene expression but eQTL regulating genes associated with leaf development and photosynthesis were dispersed across the genome. This comprehensive expression QTL analysis details the influence of these loci on plant phenotypes, and will be a valuable community resource for investigations on the genetic effects of eQTL on phenotypic traits in tomato.