作物学报 ›› 2019, Vol. 45 ›› Issue (9): 1349-1364.doi: 10.3724/SP.J.1006.2019.82061
LI Xu-Kai1,LI Ren-Jian2,ZHANG Bao-Jun2,*(
)
摘要:
加权共表达网络分析(Weighted Gene Co-expression Network Analysis, WGCNA)是用来描述不同样品之间基因关联模式的系统生物学方法, 可以用来鉴定高度协同变化的基因集。本研究利用正常水稻组织共47份转录组数据, 通过冷胁迫、干旱胁迫、盐胁迫不同的处理方式, 使用WGCNA方法, 根据已克隆基因的报道与以上3种胁迫相关的关键基因, 探究不同逆境下基因之间的调控关系。通过对低表达量基因的过滤, 最终利用筛选的30,339个表达的基因来构建共表达矩阵, 得到15个模块。分析发现已知的水稻3种相关基因在各个模块均有存在, 于是对预测到的靶基因进行GO富集分析。对3种胁迫下处理的转录组数据进行差异表达基因分析, 结合已报道与胁迫相关的基因, 选取各胁迫相关的2个模块进行了基因调控网络的构建。鉴于3种胁迫相关基因在green模块中大量分布, 通过对green模块下各自特有的基因和共有的基因的GO功能富集分析, 并对共有的基因构建调控网络, 挖掘到2599个与3种胁迫都相关的基因, 并预测出25个抗逆相关的关键基因, 为水稻的抗逆及综合抗逆能力等研究提供了新思路。
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