Transcriptome sequencing and expression profiling of genes involved in the response to abiotic stress in Medicago ruthenica

被引:3
|
作者
Shu, Yongjun [1 ]
Li, Wei [1 ]
Zhao, Jinyue [1 ]
Liu, Ying [1 ]
Guo, Changhong [1 ]
机构
[1] Harbin Normal Univ, Coll Life Sci & Technol, 1 Shida Rd, Harbin 150025, Heilongjiang, Peoples R China
基金
中国博士后科学基金;
关键词
Medicago ruthenica; RNA-Seq; transcription factor (TF); abiotic stress; reactive oxygen species (ROS); RNA-SEQ; PLANT-RESPONSES; TOLERANCE; DROUGHT; GENERATION; SALINITY; TOPHAT; TOOL; ROS;
D O I
10.1590/1678-4685-GMB-2017-0284
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Medicago ruthenica is a perennial forage legume with the remarkable ability to survive under unfavorable environmental conditions. It has been identified as an excellent species of Medicago that can adapt to various environmental stresses including low temperature, drought, and salinity. To investigate its potential as a genetic resource, we performed transcriptome sequencing and analysis in M. ruthenica under abiotic stresses. We generated >120 million reads from six cDNA libraries, resulting in 79,249 unique transcripts, most of which were highly similar to transcripts from M. truncatula (44,608, 56.3%) and alfalfa (M. sativa, 48,023, 60.6%). Based on gene expression profiles, 2,721 transcripts were identified as abiotic stress responsive genes which were predicted to be mainly involved in phytohormone signaling pathways, transcriptional regulation, and ROS-scavenging. These results suggest that they play critical roles in the response to abiotic stress. In summary, we identified genes in our transcriptome dataset involved in the regulation of the abiotic stress response in M. ruthenica which will provide a valuable resource for the future identification and functional analysis of candidate genes for adaption to unfavorable conditions. The genes identified here could be also useful for improving stress tolerance traits in alfalfa through molecular breeding in the future.
引用
收藏
页码:638 / 648
页数:11
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