Construction of regulatory networks mediated by small RNAs responsive to abiotic stresses in rice (Oryza sativa). (October 2015)

• Record Type: Journal Article
• Authors: Qin, Jingping; Ma, Xiaoxia; Tang, Zhonghai; Meng, Yijun
• Is Part Of: Computational biology and chemistry. Volume 58(2015)
• Page Start: 69
• Page End: 80
• Publication Date: 2015-10
• Subjects: Abiotic stress -- Argonaute 1 (AGO1) -- Degradome -- High-throughput sequencing (HTS) -- Network -- Rice small RNA (sRNA) -- Signal interaction; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2015.05.006
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: Thousands of sRNAs responsive to abiotic stresses were identified in the rice. The sRNAs enriched in Argonaute 1 were extracted for target identification. Twelve sRNA—target lists were obtained for network construction. Within certain subnetworks, some targets were supported by microarray data. Literature mining indicated that some targets were involved in stress response. Abstract: Plants have evolved exquisite molecular mechanisms to adapt to diverse abiotic stresses. MicroRNAs play an important role in stress response in plants. However, whether the other small RNAs (sRNAs) possess stress-related roles remains elusive. In this study, thousands of sRNAs responsive to cold, drought and salt stresses were identified in rice seedlings and panicles by using high-throughput sequencing data. These sRNAs were classified into 12 categories, including "Panicle_Cold_Down", "Panicle_Cold_Up", "Panicle_Drought_Down", "Panicle_Drought_Up", "Panicle_Salt_Down", "Panicle_Salt_Up", "Seedling_Cold_Down", "Seedling_Cold_Up", "Seedling_Drought_Down", "Seedling_Drought_Up", "Seedling_Salt_Down" and "Seedling_Salt_Up". The stress-responsive sRNAs enriched in Argonaute 1 were extracted for target prediction and degradome sequencing data-based validation, which enabled network construction. Within certain subnetworks, some target genes were further supported by microarray data. Literature mining indicated that certain targets were potentially involved in stress response. These results demonstrate that the established networks are biologically meaningful. We discovered that in some cases, one sRNA sequence could be assigned to two or more categories. Moreover, within certain target-centered subnetworks, one transcript was regulated by several stress-responsive sRNAs assigned to different categories. It implies that these subnetworks are potentially implicated in stress signal crosstalk. Together, our results could advance the current understanding of the biological role of plant sRNAs in stress signaling.