Unravelling MiRNA Regulation in Yield of Rice (Oryza Sativa) Based on Differential Network Model

Overview

Journal Sci Rep

Specialty Science

Date 2018 Jun 2

PMID 29855560

Citations 15

Authors

Jihong Hu

Tao Zeng

Qiongmei Xia

Qian Qian

Congdang Yang

Yi Ding

Luonan Chen

Wen Wang

Affiliations

Soon will be listed here.

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 constructed for yield of rice. Using GRN-DET, the key regulatory miRNAs for rice yield were characterized by the differential expression variances of miRNAs and co-variances of miRNA-mRNA, including osa-miR171 and osa-miR1432. Phytohormone cross-talks (auxin and brassinosteroid) were also revealed by these co-expression networks for the yield of rice.

Citing Articles

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