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.

Influence of host genotype in establishing root associated microbiome of indica rice cultivars for plant growth promotion.

Rice plants display a unique root ecosystem comprising oxic-anoxic zones, harboring a plethora of metabolic interactions mediated by its root microbiome. Since agricultural land is limited, an increase in rice production will rely on novel methods of yield enhancement. The nascent concept of tailoring plant phenotype through the intervention of synthetic microbial communities (SynComs) is inspired by the genetics and ecology of core rhizobiome. In this direction, we have studied structural and functional variations in the root microbiome of 10 indica rice varieties. The studies on α and ß-diversity indices of rhizospheric root microbiome with the host genotypes revealed variations in the structuring of root microbiome as well as a strong association with the host genotypes. Biomarker discovery, using machine learning, highlighted members of class Anaerolineae, α-Proteobacteria, and bacterial genera like Desulfobacteria, Ca. Entotheonella, Algoriphagus, etc. as the most important features of indica rice microbiota having a role in improving the plant's fitness. Metabolically, rice rhizobiomes showed an abundance of genes related to sulfur oxidation and reduction, biofilm production, nitrogen fixation, denitrification, and phosphorus metabolism. This comparative study of rhizobiomes has outlined the taxonomic composition and functional diversification of rice rhizobiome, laying the foundation for the development of next-generation microbiome-based technologies for yield enhancement in rice and other crops.

SUPER STARCHY1/ONAC025 participates in rice grain filling.

NAC transcription factors (TFs) are known for their role in development and stress. This article attempts to functionally validate the role of rice SS1/ ONAC025 (LOC_Os11g31330) during seed development. The gene is seed-specific and its promoter directs reporter expression in the developing endosperm and embryo in rice transgenic plants. Furthermore, rice transgenic plants ectopically expressing SS1/ ONAC025 have a plantlet lethal phenotype with hampered vegetative growth, but increased tillers and an altered shoot apical meristem structure. The vegetative cells of these plantlets are filled with distinct starch granules. RNAseq analysis of two independent plantlets reveals the differential expression of reproductive and photosynthetic genes. A comparison with seed development transcriptome indicates differential regulation of many seed-related genes by SS1/ ONAC025. Genes involved in starch biosynthesis, especially amylopectin and those encoding seed storage proteins, and regulating seed size are also differentially expressed. In conjunction, SS1/ ONAC025 shows highest expression in japonica rice. As a TF, SS1/ ONAC025 is a transcriptional repressor localized to endoplasmic reticulum and nucleus. The article shows that SS1/ ONAC025 is a seed-specific gene promoting grain filling in rice, and negatively affecting vegetative growth.

Three Rice NAC Transcription Factors Heteromerize and Are Associated with Seed Size.

NACs are plant-specific transcription factors (TFs) involved in multiple aspects of development and stress. In rice, three NAC TF encoding genes, namely ONAC020, ONAC026, and ONAC023 express specifically during seed development, at extremely high levels. They exhibit significantly strong association with seed size/weight with the sequence variations located in the upstream regulatory region. Concomitantly, their expression pattern/levels during seed development vary amongst different accessions with variation in seed size. The alterations in the promoter sequences of the three genes, amongst the five rice accessions, correlate with the expression levels to a certain extent only. In terms of transcriptional properties, the three NAC TFs can activate and/or suppress downstream genes, though to different extents. Only ONAC026 is localized to the nucleus while ONAC020 and ONAC023 are targeted to the ER and cytoplasm, respectively. Interestingly, these two proteins interact with ONAC026 and the dimers localize in the nucleus. Trans-splicing between ONAC020 and ONAC026 results in three additional forms of ONAC020. The transcriptional properties including activation, repression, subcellular localization and heterodimerization of trans-spliced forms of ONAC020 and ONAC026 are different, indicating toward their role as competitors. The analysis presented in this paper helps to conclude that the three NAC genes, which are associated with seed size, have independent as well as overlapping roles during the process and can be exploited as potential targets for crop improvement.

Expanding frontiers in plant transcriptomics in aid of functional genomics and molecular breeding.

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.