Publications of NIPGR Scientists

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Author: search.filters.author.Parida, Swarup K.Subject: search.filters.subject.QTL mapping

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    Rice Pangenome Genotyping Array: an efficient genotyping solution for pangenome-based accelerated genetic improvement in rice
    (John Wiley & Sons, 2022) Daware, Anurag; Malik, Ankit; Srivastava, Rishi; Das, Durdam; Ellur, Ranjith K; Singh, Ashok K; Tyagi, Akhilesh K.; Parida, Swarup K.
    The advent of the pangenome era has unraveled previously unknown genetic variation existing within diverse crop plants, including rice. This untapped genetic variation is believed to account for a major portion of phenotypic variation existing in crop plants. However, the use of conventional single reference-guided genotyping often fails to capture large portion of this genetic variation leading to a reference bias. This makes it difficult to identify and utilize novel population/cultivar-specific genes for crop improvement. Thus, we developed a rice pangenome genotyping array (RPGA) harboring probes assaying 80K single nucleotide polymorphisms (SNPs) and presence-absence variants (PAVs) spanning the entire 3K rice pangenome. This array provides a simple, user-friendly and cost-effective (60 to 80 USD per sample) solution for rapid pangenome-based genotyping in rice. The GWAS conducted using RPGA-SNP genotyping data of a rice diversity panel detected a total of 42 loci, including previously known as well as novel genomic loci regulating grain size/weight traits in rice. Eight of these identified trait-associated loci (dispensable loci) could not be detected with conventional single reference genome-based GWAS. A WD repeat-containing PROTEIN 12 gene underlying one of such dispensable locus on chromosome 7 (qLWR7) along with other non-dispensable loci were subsequently detected using high-resolution QTL mapping confirming authenticity of RPGA-led GWAS. This demonstrates the potential of RPGA-based genotyping to overcome reference bias. The application of RPGA-based genotyping for population structure analysis, hybridity testing, ultra-high-density genetic map construction and chromosome-level genome assembly, and marker-assisted selection was also demonstrated. A web application (http://www.rpgaweb.com) was further developed to provide easy to use platform for the imputation of RPGA-based genotyping data using 3K Rice Reference Panel and subsequent GWAS.
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    The Mediator subunit OsMED15a is a transcriptional co-regulator of seed size/weight-modulating genes in rice
    (Elsevier B.V., 2019) Dwivedi, Nidhi; Maji, Sourobh; Waseem, Mohd; Thakur, Pallabi; Kumar, Vinay; Parida, Swarup K.; Thakur, Jitendra K.
    Although several transcription factors (TFs) that regulate seed size/weight in plants are known, the molecular landscape regulating this important trait is unclear. Here, we report that a Mediator subunit, OsMED15a, links rice grain size/weight-regulating TFs to their target genes. Expression analysis and high-resolution quantitative trait loci (QTL) mapping suggested that OsMED15a is involved in rice seed development. OsMED15a has an N-terminal, three-helical KIX domain. Two of these helices, α1 and α3, and three amino acids, 76LRC78, within OsMED15a helix α3 were important for its interaction with several proteins, including interactions with the transactivation domains of two NAC-type TFs, OsNAC024 and OsNAC025. Moreover, OsMED15a, OsNAC024, and OsNAC025 all exhibited increased expression during seed development, and we identified several grain size/weight-associated SNPs in these genes in 509 low- and high-grain-weight rice genotypes. RNAi-mediated repression of OsMED15a expression down-regulated the expression of the grain size/weight regulating genes GW2, GW5 and DR11 and reduced grain length, weight, and yield. Of note, both OsNAC024 and OsNAC025 bound to the promoters of these three genes. We conclude that the transactivation domains of OsNAC024 and OsNAC025 target the KIX domain of OsMED15a in the regulation of grain size/weight-associated genes such as GW2, GW5, and D11. We propose that the integrated molecular-genetics approach used here could help identify networks of functional alleles of other regulator and co-regulator genes and thereby inform efforts for marker-assisted introgression of useful alleles in rice crop improvement.
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    Regional association analysis of metaQTLs delineates candidate grain size genes in rice
    (Frontiers Media S.A., 2017) Daware, Anurag V.; Srivastava, Rishi; Singh, Ashok K.; Parida, Swarup K.; Tyagi, Akhilesh K.
    Molecular mapping studies which aim to identify genetic basis of diverse agronomic traits are vital for marker-assisted crop improvement. Numerous Quantitative Trait Loci (QTLs) mapped in rice span long genomic intervals with hundreds to thousands of genes, which limits their utilization for marker-assisted genetic enhancement of rice. Although potent, fine mapping of QTLs is challenging task as it requires screening of large number of segregants to identify suitable recombination events. Association mapping offers much higher resolution as compared to QTL mapping, but detects considerable number of spurious QTLs. Therefore, combined use of QTL and association mapping strategies can provide advantages associated with both these methods. In the current study, we utilized meta-analysis approach to identify metaQTLs associated with grain size/weight in diverse Indian indica and aromatic rice accessions. Subsequently, attempt has been made to narrow-down identified grain size/weight metaQTLs through individual SNP- as well as haplotype-based regional association analysis. The study identified six different metaQTL regions, three of which were successfully revalidated, and substantially scaled-down along with GS3 QTL interval (positive control) by regional association analysis. Consequently, two potential candidate genes within two reduced metaQTLs were identified based on their differential expression profiles in different tissues/stages of rice accessions during seed development. The developed strategy has broader practical utility for rapid delineation of candidate genes and natural alleles underlying QTLs associated with complex agronomic traits in rice as well as major crop plants enriched with useful genetic and genomic information.