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摘要：棉花是广泛种植的重要作物，是天然纺织纤文的主要来源。然而，棉纤文发育是一个复杂的生物过程。近年来关于具体基因的研究工作一定程度上解释了纤文发育的潜在规律。在本研究中，我们整合运用了已报道的纤文相关基因数、棉花全基因组关联分析（GWAS）数据、棉花转录组的RNA-seq表达谱等数据，对复杂纤文发育的分子调控进行了共表达网络构建与分析。
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首先，我们对棉花纤文基因的表达谱，在基因组上的位置关系等进行了描述。其次，我们构建了基因共表达网络，获得了高度相似的转录本模块。通过整合已有信息，我们倾向于通过“模块驱动的纤文发育”假说来解释纤文的发育过程。最后我们生物信息学手段对这些转录本可能的调控方式进行了探索。37273
通过此次研究，我们提供了一个从RNA水平来理解纤文生长的初步系统观，并提供与纤文发育相关的候选编码与非编码基因。这些基因涉及相关生物学过程，可以执行一定分子功能或组成一个复合体。
毕业论文关键词：棉花；纤文发育；转录组；荟萃分析
Meta analysis of the transcriptional (lncRNA and mRNA) information of upland cotton for expla ining the fiber development and digging the potential genes
Abstract：Cotton is an important crop that is widely grown and is the dominant source of natural textile fiber. However, the fiber development is a complicated biological process which regulated by a large amount of genes and involved in lot’s of metabolic pathways. A lot of excellent works have been done to uncover the underline rules for fiber development. In this paper, we make a meta-analysis of the complex fiber development traits by incorporating GWAS data, lncRNA and protein-coding genes’ expression profile.
Firstly we do the data description: the reported fiber related genes’ expression pattern, its genomic region and evolution relationship with lncRNA, next we depicted some expressed characters of the lncRNA we annotated. Secondly we do some data interpretation: we construct a gene co-expression network to get highly connected transcripts within a gene module (a cluster of genes). Next we do the data interpretation: by integrating the information of reported genes, the expression tendency through four tissue rapidly growth stages, GO enrichment analysis and the expression profiles, we tend to give an explanation of fiber development by the hypothesis of "module derived fiber development". By employing the modules to specify the multiple genes participated process. Lastly we do the data exploration: the previous lncRNAs and mRNA interaction research uncover some mechanisms, we use some bioinfomatics methods as well as bayesian network to explore their possible interaction. Meanwhile we construct three Bayesian Networks for three vital gene clusters inherited from co-expression network: a part of red module genes that expressed high level in fiber tissues, genes that connected HOX3 and genes that connected MYB25-LIKE.
Throughout this research, we provide a primary systematic way to see the complex trait (fiber growth) in the molecular (RNA) level and give candidate genes and lncRNAs may involve in a biological process, paly a rule in molecular function or compose the components that related to ovule and fiber development.
Key words: Cotton；Fiber development；Transcriptome；Meta-analysis
目 录
摘要3
关键词3
Abstract3
Key words3
引言4
1材料与方法5
1.1数据集和分析工具5
1.2得到纤文相关基因(FRGs5
1.3得到差异表达基因(DEGs) 5
1.4 得到转录本的RNA-seq表达谱 5
1.5 寻找同源基因并构建NJ系统进化树 6
1.6 组织特异性分析： 6
1.7 GO富集分析 6
1.8 基因共表达网络分析 6
1.9 构建贝叶斯网络 6
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