基于RNA-Seq数据的心肌病相关基因标志物识别及功能分析

发布时间：2018-05-08 23:04

本文选题：DCM + RCM　；参考：《电子科技大学》2017年硕士论文

【摘要】：心血管疾病一直都是威胁全人类健康的复杂疾病,而心肌病在心血管疾病的发病中占据了重要的位置,并且有着逐年上升的趋势。心肌病又分为继发性心肌病与原发性心肌病,继发性心肌病的病因多数已经清楚,而原发性心肌病的病因迄今为止尚未明确。本文所研究的扩张型心肌病(Dilated cardiomyopathy,DCM)和限制型心肌病(Restrictive cardiomyopathy,RCM)都属于原发性心肌病。其中,DCM的发病率占心肌病的发病率80%以上,并且心肌病患者中有58.3%死于该病。RCM发病率虽然仅占心肌病发病率的4.5%,然而它是原发性心肌病中最严重的一种类型,并且其预后性很差。因此,对于这两类心肌疾病发生发展机制的研究工作刻不容缓。转录组作为连接基因组遗传信息与蛋白质组生物功能的纽带,相比于基因组,它更具备时间性和空间性,因此被广泛地应用于医学、病理学和药学等相关领域。随着二代测序技术成本的降低,使得转录组测序被大规模地应用于生物学与医学研究中。本文通过对DCM和RCM的RNA-Seq数据进行挖掘,旨在对这两类原发性心肌疾病的发生发展机制进行研究和探索,为两类心肌病的精确诊断、及时控制以及治疗预后等提供一些新思路。本文的主要研究内容如下:(1)采用标准化的RNA-Seq数据处理方法,包括质量控制(Fast QC)、参考序列比对(Tophat)、计数数据的转换(HTSeq)、归一化(EDASeq)和差异表达(DESeq),筛选和识别出分别与DCM、RCM相关的差异表达基因。对于DCM,筛选出451个相关的差异表达基因;对于RCM,筛选出1326个相关的差异表达基因。(2)分别用DCM和RCM相关的差异表达基因构建共表达网络。通过对共表达网络作网络特征分析,找出与疾病相关的关键节点基因,即疾病可能的基因标志物。对每种疾病的基因标志物进行生物功能分析,并对其在疾病发生发展中的作用进行阐释。(3)从生物功能和信号通路的角度,对DCM和RCM的基因标志物进行比较,为从分子层面上区分两类心肌病提供一些新思路。
[Abstract]:Cardiovascular disease has always been a complex disease threatening the health of mankind. Cardiomyopathy occupies an important position in the incidence of cardiovascular disease and has a rising trend year by year. Cardiomyopathy is divided into secondary cardiomyopathy and primary cardiomyopathy. Both dilated cardiomyopathy (DCM) and restricted cardiomyopathy (RCM) are primary cardiomyopathy. The incidence of DCM accounts for more than 80% of the incidence of cardiomyopathy, and 58.3% of the patients with cardiomyopathy died of the disease. Although the incidence of RCM is only 4.5% of the incidence of cardiomyopathy, it is the most serious type of primary cardiomyopathy. And its prognosis is very poor. Therefore, it is urgent to study the development mechanism of these two kinds of myocardial diseases. As a link between genomic genetic information and proteome biological function, transcriptome is more temporal and spatial than genome, so it has been widely used in medicine, pathology, pharmacy and other related fields. With the reduction of the cost of second generation sequencing, transcriptome sequencing has been widely used in biological and medical research. By mining the RNA-Seq data of DCM and RCM, this paper aims to study and explore the mechanism of the occurrence and development of these two kinds of primary myocardial diseases, and to provide some new ideas for the accurate diagnosis, timely control and treatment and prognosis of the two kinds of cardiomyopathy. The main contents of this paper are as follows: (1) A standardized RNA-Seq data processing method is used. It includes quality control fast QCN, reference sequence alignment, Tophata, conversion of counting data, normalized EDASeqand differential expression, and screening and identification of differentially expressed genes associated with DCMN RCM respectively. For DCM, 451 differentially expressed genes were screened. For RCM, 136 differentially expressed genes were screened. By analyzing the network characteristics of coexpression networks, we find out the key node genes related to disease, that is, the possible gene markers of disease. The biomarkers of each disease were analyzed, and their role in the development of the disease was explained. (3) from the perspective of biological function and signal pathway, the genetic markers of DCM and RCM were compared. It provides some new ideas for differentiating two kinds of cardiomyopathy from the molecular level.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R542.2

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