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 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.

Drought Response in Rice: The miRNA Story

“…Further, different miRNAs connected to auxin signaling have been shown to affect developmental activities such as tillering and branching. miR156 regulates yield (OsSPL14) while miR393a, miR396b, miR397, and miR167 promotes panicle branching and better grain yield [16,74,75]. The up regulation of miR397 in rice negatively regulates OsLAC (laccase) which is associated to brassinosteroids and grain yield increase [75].…”

“…Majority of the miRNAs above target GRF-interacting factor 1 (GIF1), which are responsible for cell proliferation and growth [35,77,78]. The suppression of miR396 up regulates auxin responsive genes, where OsGRF6 positively regulates auxin signaling in rice [16,79]. Contrary to the above, miR396 is up regulated in drought-stressed Arabidopsis [71] and tobacco [59].…”

“…Studies have shown that miRNAs are important modulators of drought tolerance in plants where it influences the cleavage of several drought responsive genes and thence inhibits their translation. The regulatory information derived from these components control the networking between miRNA and their target genes [16]. However, to date, the information on miRNAs, target genes and the cross talk between pathways is not well understood in plants, especially in rice.…”

High-Order Correlation Integration for Single-Cell or Bulk RNA-seq Data Analysis

“…We found the key genes in the DEGs, which can be linked and correlated by the combined functional couplings of protein-protein interactions of STRING. MicroRNAs which can regulate key DEGs were defined as key miRNAs (degree s > 80) (Hu et al, 2018). Cytoscape was used to reconstruct and visualize gene-gene and miRNA-gene network.…”

Identification of Key Genes for the Ultrahigh Yield of Rice Using Dynamic Cross-Tissue Network Analysis

“…However, rice breeding is now confronted with the challenge of overcoming the yield plateau [3] . Interestingly, Taoyuan of Yunnan in China is a well-known place where the highest rice yield in the world was recorded with an average rice yield of 13.91 t·ha −1 [3] , [4] . Taoyuan is a dry and hot valley of the upstream part of Yangtze River in Yunnan Province, where the temperature difference is large after heading, and the humidity is slightly lower throughout the growing period.…”