Cytological, transcriptome and miRNome temporal landscapes decode enhancement of rice grain size

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.

Automated summary

By analyzing the transcriptomes and miRNomes of small-grained and large-grained indica rice, this study identified the crucial role of the S3 stage in enhancing grain size and discovered several transcription factor and miRNA families that influence grain size. A Domino effect model was proposed to explain the regulation of grain size. Additionally, a rice grain development database was established for easy access to the data generated in this study.