基于转录组和WGCNA筛选小麦籽粒蛋白质累积相关调控基因  

Screening Regulatory Genes Related to Wheat Grain Protein Accumulation Based on Transcriptome and WGCNA Analysis

作　　者：潘丽媛 王永军[1] 李海军[1] 侯富 李菁 李丽丽[1] 孙苏阳[1,2,3] PAN LiYuan;WANG YongJun;LI HaiJun;HOU Fu;LI Jing;LI LiLi;SUN SuYang(Huaiyin Institute of Agricultural Sciences of Xuhuai Region in Jiangsu,Huai’an 223001,Jiangsu;Zhongshan Laboratory of Biological Breeding,Jiangsu Academy of Agricultural Sciences,Nanjing 210014;Jiangsu Provincial Collaborative Innovation Center of Modern Industrial Technology for Grain Crops,Yangzhou University,Yangzhou 225009,Jiangsu)

机构地区：[1]江苏徐淮地区淮阴农业科学研究所,江苏淮安223001 [2]江苏省农业科学院生物育种钟山实验室,南京210014 [3]扬州大学江苏省粮食作物现代产业技术协同创新中心,江苏扬州225009

出　　处：《中国农业科学》2025年第6期1065-1082,共18页Scientia Agricultura Sinica

基　　金：江苏省种业振兴“揭榜挂帅”项目(JBGS[2021]051);淮安市农业科学研究院发展基金(HNY202007);淮安市农业科学研究院高层次引进人才科研启动发展基金(0052023016B);生物育种钟山实验室项目(ZSBBL-KY2023-02-4)。

摘　　要：【目的】小麦作为重要的粮食作物,鉴定参与籽粒蛋白质合成的基因调控网络,并确定关键候选基因,为小麦品质育种和改良提供理论依据。【方法】以淮麦48的6个发育时期(花后5、10、15、20、25和30 d)的籽粒为研究材料,总结小麦籽粒蛋白质累积规律,利用WGCNA方法分析转录组数据和籽粒蛋白质含量表型数据,构建加权基因共表达网络,筛选关键枢纽转录因子(transcript factors,TFs)。【结果】小麦籽粒蛋白质含量积累过程表现为先减少后升高的趋势,并且在花后25 d达到最低值(12.16%),相邻发育时期的蛋白质含量差异显著。在相邻发育时期之间共鉴定到25427个差异表达基因(differentially expressed genes,DEGs)。通过聚类分析可分为5组(A—E),其中,B组的差异表达基因数量最多(10906个),包含49个家族的1022个转录因子,其中,NAC家族的TFs数量最多(107个)。通过WGCNA分析,发现5个与蛋白质含量显著相关的共表达模块。turquoise模块与蛋白质含量的正相关性最高(r=0.80,P=1×10^(-4))。通过整合差异表达基因和加权基因共表达网络,在2个模块(turquoise和blue)中发现了6个正向调控的枢纽TFs,分别来自MIKC-MADS、TCP、TALE和CPP家族。进一步对淮麦48的蛋白质含量与不同时期的基因表达量进行相关性分析,发现其中5个枢纽TFs的表达量与蛋白质含量存在显著正相关性,并且Traes CS5B03G0740100和Traes CS7D03G0590500在穗和籽粒中特异性高表达。【结论】鉴定到与小麦蛋白质含量累积相关的重要模块turquoise和blue模块,筛选到6个枢纽TFs,并发现2个重要的枢纽基因表达量与蛋白质含量呈显著正相关,且在穗和籽粒组织中特异性高表达,可作为小麦籽粒蛋白质积累调控的候选基因。【Objective】Common wheat,as an important food crop,plays a crucial role in global food security.Identifying the gene regulatory networks involved in wheat grain protein synthesis and determining key candidate genes will provide theoretical support for quality breeding and improvement of wheat.【Method】The study used wheat grains at six developmental stages(5,10,15,20,25,and 30 days post-anthesis)as research materials to summarize the pattern of protein accumulation in wheat grains.Transcriptome data and grain protein content phenotypic data were analyzed using the WGCNA(Weighted Gene Co-expression Network Analysis)method to construct weighted gene co-expression networks and identify key hub transcription factor(TFs)genes.【Result】The accumulation of protein content in wheat grains showed a trend of initial decline followed by an increase,reaching its lowest value(12.16%)at 25 days post-anthesis,with significant differences in protein content between adjacent developmental stages.A total of 25427 differentially expressed genes(DEGs)were identified between adjacent developmental stages.Cluster analysis divided these DEGs into five groups(A-E),with group B containing the highest number of DEGs(10906).A total of 1022 transcription factors(TFs)from 49 families were identified,with the NAC family containing the most TFs(107).WGCNA analysis identified five co-expression modules significantly associated with protein content.The turquoise module showed the highest positive correlation with protein content(r=0.80,P=1×10^(-4)).By integrating differentially expressed genes and weighted gene co-expression networks,six positively regulated hub TFs from the MIKC-MADS,TCP,TALE,and CPP families were identified in two modules(turquoise and blue).Further correlation analysis between the protein content phenotype of Huaimai 48 and gene expression levels at different time points revealed that the expression levels of five hub TFs were significantly positively correlated with the protein content phenotype.Specifically,TraesC

关 键 词：普通小麦 籽粒发育 蛋白质含量 加权基因共表达网络分析 转录因子 

分 类 号：S51[农业科学—作物学]