Genome wide in-silico miRNA and target network prediction from stress responsive Horsegram (Macrotyloma uniflorum) accessions

从应激反应马豆 (Macrotyloma uniflorum) 种质中进行全基因组在线 miRNA 和靶标网络预测

阅读:5
作者:Jeshima Khan Yasin, Bharat Kumar Mishra, M Arumugam Pillai, Nidhi Verma, Shabir H Wani, Hosam O Elansary, Diaa O El-Ansary, P S Pandey, Viswanathan Chinnusamy

Abstract

Horsegram (Macrotyloma uniflorum (Lam.) Verdc.) is a drought hardy food and fodder legume of Indo-African continents with diverse germplasm sources demonstrating alternating mechanisms depicting contrasting adaptations to different climatic zones. Tissue specific expression of genes contributes substantially to location specific adaptations. Regulatory networks of such adaptive genes are elucidated for downstream translational research. MicroRNAs are small endogenous regulatory RNAs which alters the gene expression profiles at a particular time and type of tissue. Identification of such small regulatory RNAs in low moisture stress hardy crops can help in cross species transfer and validation confirming stress tolerance ability. This study outlined prediction of conserved miRNAs from transcriptome shotgun assembled sequences and EST sequences of horsegram. We could validate eight out of 15 of the identified miRNAs to demonstrate their role in deficit moisture stress tolerance mechanism of horsegram variety Paiyur1 with their target networks. The putative mumiRs were related to other food legumes indicating the presence of gene regulatory networks. Differential miRNA expression among drought specific tissues indicted the probable energy conservation mechanism. Targets were identified for functional characterization and regulatory network was constructed to find out the probable pathways of post-transcriptional regulation. The functional network revealed mechanism of biotic and abiotic stress tolerance, energy conservation and photoperiod responsiveness.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。