Institutional Publications

Permanent URI for this collectionhttps://ndkr-library.nipgr.ac.in/handle/123456789/11

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Author: search.filters.author.Parida, Swarup K.Subject: search.filters.subject.Oryza sativa

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    Cytological, transcriptome and miRNome temporal landscapes decode enhancement of rice grain size
    (BioMed Central Ltd, 2023) Mahto, Arunima; Yadav, Antima; Aswathi, P. V.; Parida, Swarup K.; Tyagi, Akhilesh K.; Agarwal, Pinky
    Background Rice grain size (GS) is an essential agronomic trait. Though several genes and miRNA modules influencing GS are known and seed development transcriptomes analyzed, a comprehensive compendium connecting all possible players is lacking. This study utilizes two contrasting GS indica rice genotypes (small-grained SN and large-grained LGR). Rice seed development involves five stages (S1–S5). Comparative transcriptome and miRNome atlases, substantiated with morphological and cytological studies, from S1–S5 stages and flag leaf have been analyzed to identify GS proponents. Results Histology shows prolonged endosperm development and cell enlargement in LGR. Stand-alone and comparative RNAseq analyses manifest S3 (5–10 days after pollination) stage as crucial for GS enhancement, coherently with cell cycle, endoreduplication, and programmed cell death participating genes. Seed storage protein and carbohydrate accumulation, cytologically and by RNAseq, is shown to be delayed in LGR. Fourteen transcription factor families influence GS. Pathway genes for four phytohormones display opposite patterns of higher expression. A total of 186 genes generated from the transcriptome analyses are located within GS trait-related QTLs deciphered by a cross between SN and LGR. Fourteen miRNA families express specifically in SN or LGR seeds. Eight miRNA-target modules display contrasting expressions amongst SN and LGR, while 26 (SN) and 43 (LGR) modules are differentially expressed in all stages. Conclusions Integration of all analyses concludes in a “Domino effect” model for GS regulation highlighting chronology and fruition of each event. This study delineates the essence of GS regulation, providing scope for future exploits. The rice grain development database (RGDD) ( www.nipgr.ac.in/RGDD/index.php; https://doi.org/10.5281/zenodo.7762870) has been developed for easy access of data generated in this paper.
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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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    Rice improvement through genome-based functional analysis and molecular breeding in India
    (Springer, 2016) Agarwal, Pinky; Parida, Swarup K.; Raghuvanshi, Saurabh; Kapoor, Sanjay; Khurana, Paramjit; Khurana, Jitendra P.; Tyagi, Akhilesh K.
    Rice is one of the main pillars of food security in India. Its improvement for higher yield in sustainable agriculture system is also vital to provide energy and nutritional needs of growing world population, expected to reach more than 9 billion by 2050. The high quality genome sequence of rice has provided a rich resource to mine information about diversity of genes and alleles which can contribute to improvement of useful agronomic traits. Defining the function of each gene and regulatory element of rice remains a challenge for the rice community in the coming years. Subsequent to participation in IRGSP, India has continued to contribute in the areas of diversity analysis, transcriptomics, functional genomics, marker development, QTL mapping and molecular breeding, through national and multi-national research programs. These efforts have helped generate resources for rice improvement, some of which have already been deployed to mitigate loss due to environmental stress and pathogens. With renewed efforts, Indian researchers are making new strides, along with the international scientific community, in both basic research and realization of its translational impact.
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    Genetic diversity and population structure of rice landraces from Eastern and North Eastern States of India
    (BioMed Central Ltd, 2013) Das, Basabdatta; Sengupta, Samik; Parida, Swarup K.; Roy, Bipasha; Ghosh, Mrityunjay; Prasad, Manoj; Ghose, Tapas Kumar
    Adaptations to different habitats across the globe and consequent genetic variation within rice have resulted in more than 120,000 diverse accessions including landraces, which are vital genetic resources for agronomic and quality traits. In India the rice landraces of the states West Bengal, Assam, Mizoram, Manipur and Nagaland are worthy candidates for genetic assessment. Keeping the above in view, the present study was conducted with the aim to (i) calculate the genetic distances among the accessions of 83 landraces collected from these states along with 8 check accessions (total 91 accessions) using 23 previously mapped SSR markers and (ii) examine the population structure among the accessions using model-based clustering approach