Publications of NIPGR Scientists

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

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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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    Transcriptome landscape of early inflorescence developmental stages identifies key flowering time regulators in chickpea
    (Springer Nature Publishing AG, 2022) Basu, Udita; Hegde, Venkatraman S.; Daware, Anurag; Jha, Uday Chand; Parida, Swarup K.
    The early stages of inflorescence development in plants are as crucial as the later floral developmental stages. Several traits, such as inflorescence architecture and flower developmental timings, are determined during those early stages. In chickpea, diverse forms of inflorescence architectures regarding meristem determinacy and the number of flowers per node are observed within the germplasm. Transcriptome analysis in four desi chickpea accessions with such unique inflorescence characteristics identifies the underlying shared regulatory events leading to inflorescence development. The vegetative to reproductive stage transition brings about major changes in the transcriptome landscape. The inflorescence development progression associated genes identified through co-expression network analysis includes both protein-coding genes and long non-coding RNAs (lncRNAs). Few lncRNAs identified in our study positively regulate flowering-related mRNA stability by acting competitively with miRNAs. Bulk segregrant analysis and association mapping narrowed down an InDel marker regulating flowering time in chickpea. Deletion of 11 bp in first exon of a negative flowering time regulator, Early Flowering 3a gene, leads to early flowering phenotype in chickpea. Understanding the key players involved in vegetative to reproductive stage transition and floral meristem development will be useful in manipulating flowering time and inflorescence architecture in chickpea and other legumes.
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    Expanding frontiers in plant transcriptomics in aid of functional genomics and molecular breeding
    (John Wiley & Sons Ltd, 2014) Agarwal, Pinky; Parida, Swarup K.; Mahto, Arunima; Das, Sweta; Mathew, Iny Elizebeth; Malik, Naveen; Tyagi, Akhilesh K.
    The transcript pool of a plant part, under any given condition, is a collection of mRNAs that will pave the way for a biochemical reaction of the plant to stimuli. Over the past decades, transcriptome study has advanced from Northern blotting to RNA sequencing (RNA-seq), through other techniques, of which real-time quantitative polymerase chain reaction (PCR) and microarray are the most significant ones. The questions being addressed by such studies have also matured from a solitary process to expression atlas and marker-assisted genetic enhancement. Not only genes and their networks involved in various developmental processes of plant parts have been elucidated, but also stress tolerant genes have been highlighted. The transcriptome of a plant with altered expression of a target gene has given information about the downstream genes. Marker information has been used for breeding improved varieties. Fortunately, the data generated by transcriptome analysis has been made freely available for ample utilization and comparison. The review discusses this wide variety of transcriptome data being generated in plants, which includes developmental stages, abiotic and biotic stress, effect of altered gene expression, as well as comparative transcriptomics, with a special emphasis on microarray and RNA-seq. Such data can be used to determine the regulatory gene networks, which can subsequently be utilized for generating improved plant varieties.
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    Comparative analysis of kabuli chickpea transcriptome with desi and wild chickpea provides a rich resource for development of functional markers
    (Public Library of Science, 2012) Agarwal, Gaurav; Jhanwar, Shalu; Priya, Pushp; Singh, Vikash K.; Saxena, Maneesha S.; Parida, Swarup K.; Garg, Rohini; Tyagi, Akhilesh K.; Jain, Mukesh
    Chickpea (Cicer arietinum L.) is an important crop legume plant with high nutritional value. The transcriptomes of desi and wild chickpea have already been sequenced. In this study, we sequenced the transcriptome of kabuli chickpea, C. arietinum (genotype ICCV2), having higher commercial value, using GS-FLX Roche 454 and Illumina technologies. The assemblies of both Roche 454 and Illumina datasets were optimized using various assembly programs and parameters. The final optimized hybrid assembly generated 43,389 transcripts with an average length of 1065 bp and N50 length of 1653 bp representing 46.2 Mb of kabuli chickpea transcriptome. We identified a total of 5409 simple sequence repeats (SSRs) in these transcript sequences. Among these, at least 130 and 493 SSRs were polymorphic with desi (ICC4958) and wild (PI489777) chickpea, respectively. In addition, a total of 1986 and 37,954 single nucleotide polymorphisms (SNPs) were predicted in kabuli/desi and kabuli/wild genotypes, respectively. The SNP frequency was 0.043 SNP per kb for kabuli/desi and 0.821 SNP per kb for kabuli/wild, reflecting very low genetic diversity in chickpea. Further, SSRs and SNPs present in tissue-specific and transcription factor encoding transcripts have been identified. The experimental validation of a selected set of polymorphic SSRs and SNPs exhibited high intra-specific polymorphism potential between desi and kabuli chickpea, suggesting their utility in large-scale genotyping applications. The kabuli chickpea gene index assembled, and SSRs and SNPs identified in this study will serve as useful genomic resource for genetic improvement of chickpea.