作物学报 ›› 2023, Vol. 49 ›› Issue (3): 672-686.doi: 10.3724/SP.J.1006.2023.23017
邓照(), 蒋环琪, 程丽沙, 刘睿, 黄敏, 李曼菲(), 杜何为()
DENG Zhao(), JIANG Huan-Qi, CHENG Li-Sha, LIU Rui, HUANG Min, LI Man-Fei(), DU He-Wei()
摘要:
加权基因共表达网络分析(weighted gene co-expression network analysis, WGCNA)是一种经典的系统生物学分析方法, 可用来鉴定协同表达的基因模块, 探索模块与目标性状的生物学相关性, 并挖掘模块网络中的核心基因。本文收集了低温胁迫、高温胁迫、干旱胁迫和盐胁迫处理下玉米(Zea mays L.)根、茎、叶等组织的58份转录组数据, 利用WGCNA方法鉴定玉米非生物胁迫的基因共表达网络模块。过滤转录组数据中12,552个低表达基因后, 利用余下27,204个高表达基因构建共表达网络, 分析得到25个模块。根据玉米中已报道非生物胁迫相关基因与差异表达基因在模块中的分布, 筛选出与低温胁迫、高温胁迫、干旱胁迫和盐胁迫最相关的mediumpurple4、ivory、coral2、darkseagreen4模块和响应多种胁迫的green模块。随后对这5个模块的基因进行GO富集分析, 发现在这些模块内与非生物胁迫相关基因的在非生物胁迫调控相关功能显著富集, 如胁迫响应、过氧化物酶活性等。对这5个模块作相关性分析, 预测出Zm00001eb072870、Zm00001eb320970、Zm00001eb037640、Zm00001eb423300和Zm00001eb265310等10个非生物胁迫相关的核心基因。本研究为玉米非生物胁迫相关基因的挖掘和非生物胁迫调控网络研究等提供了新思路。
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