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

Autor: Aparna Eragam, Vishnu Shukla, Vijaya Sudhakararao Kola, P. Latha, Srividhya Akkareddy, Madhavi L. Kommana, Eswarayya Ramireddy, Lakshminarayana R. Vemireddy
Rok vydání: 2022
Předmět:
Zdroj: Molecular biology reports. 49(8)
ISSN: 1573-4978
Popis: 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.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.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.
Databáze: OpenAIRE