Yield-associated putative gene regulatory networks in Oryza sativa L. subsp. indica and their association with high-yielding genotypes.

BACKGROUND: With the increase in population and economies of developing countries in Asia and Africa, the research towards securing future food demands is an imminent need. Among japonica and indica genotypes, indica rice varieties are largely cultivated across the globe. However, our present understanding of yield-contributing gene information stems mainly from japonica and studies on the yield potential of indica genotypes are limited. METHODS AND RESULTS: In the present study, yield contributing orthologous genes previously characterized from japonica varieties were identified in the indica genome and analysed with binGO tool for GO biological processes categorization. Transcription factor binding site enrichment analysis in the promoters of yield-related genes of indica was performed with MEME-AME tool that revealed putative common TF regulators are enriched in flower development, two-component signalling and water deprivation biological processes. Gene regulatory networks revealed important TF-target interactions that might govern yield-related traits. Some of the identified candidate genes were validated by qRT-PCR analysis for their expression and association with yield-related traits among 16 widely cultivated popular indica genotypes. Further, SNP-metabolite-trait association analysis was performed using high-yielding indica variety Rasi. This resulted in the identification of putative SNP variations in TF regulators and targeted yield genes significantly linked with metabolite accumulation. CONCLUSIONS: The study suggests some of the high yielding indica genotypes such as Ravi003, Rasi and Kavya could be used as potential donors in breeding programs based on yield gene expression analysis and SNP-metabolites associations.

A novel barcode system for rapid identification of rice (Oryza sativa L.) varieties using agro-morphological descriptors and molecular markers.

Rice varietal identification is a crucial aspect in breeding, seed production and trade in order to protect the interests of the farmers and consumers. As the number of varieties released is rising every year, the need to identify them unambiguously also increases. Here, we developed a novel barcode system to identify 62 rice genotypes using agro-morphological descriptors and molecular markers. In all, 62 rice genotypes, for 22 agro-morphological traits were recorded. In addition, 19 molecular markers were used for developing genotype-specific DNA fingerprints. The descriptor notes of 10 essential agro-morphological traits and allele codes of the polymorphic markers were used to generate two-dimensional (2-D) barcodes for the rice genotypes. Using agro-morphological traits, 31 rice genotypes were unambiguously distinguished while, with the polymorphic markers we were able to distinguish all rice genotypes except BPT2295 and Jaya. However, using both agro-morphological descriptors and molecular markers in combination, it was possible to distinguish all the rice genotypes used in the present study. These agro-morphological notes and allele codes from the molecular marker data together were used to develop QR (Quick Response) codes for rapid identification of rice genotypes as they facilitate storage of more data. In the present investigation, we have demonstrated the potentiality of agro-morphological traits and molecular markers in distinguishing rice genotypes. The novel QR code system proposed in the present study can also be extended to other crops not only for varietal identification but also for germplasm management and trade.