Unravelling miRNA regulation in yield of rice (Oryza sativa) based on differential network model.

ABSTRACT: Rice (Oryza sativa L.) is one of the essential staple food crops and tillering, panicle branching and grain filling are three important traits determining the grain yield. Although miRNAs have been reported being regulating yield, no study has systematically investigated how miRNAs differentially function in high and low yield rice, in particular at a network level. This abundance of data from high-throughput sequencing provides an effective solution for systematic identification of regulatory miRNAs using developed algorithms in plants. We here present a novel algorithm, Gene Co-expression Network differential edge-like transformation (GRN-DET), which can identify key regulatory miRNAs in plant development. Based on the small RNA and RNA-seq data, miRNA-gene-TF co-regulation networks were

SUBMITTER: Hu J 

PROVIDER: S-EPMC5981461 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature