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Author: search.filters.author.Mahto, ArunimaSubject: 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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    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.