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冠心病差异表达基因的鉴定及生物信息学分析

2021-04-12李召水王光静乔友进生伟黄强池一凡

青岛大学学报(医学版) 2021年6期

[摘要] 目的 识别冠心病(CHD)的差异表达基因(DEGs),通过分析DEGs参与的生物学途径阐明CHD疾病发生涉及的细胞内通路。

方法 从GEO数据库下载两个已发表的CHD微阵列数据集中mRNA表达芯片的原始数据。筛选DEGs并对其进行生物信息学分析,包括Venn分析、基因本体(GO)注释分析、KEGG(Kyoto Encyclopedia of Genes and Genomes)细胞通路富集分析、蛋白质相互作用(PPI)网络分析。采用实时荧光定量聚合酶链反应(RT-qPCR)验证CHD病例外周血中核心DEGs的表达水平。

结果 共筛选出122个CHD的DEGs。GO及KEGG分析显示,这些DEGs参与了DNA转录和mRNA剪接调控。PPI网络分析显示,表达下调基因LUC7L3、HNRNPA1、SF3B1、ARGLU1、SRSF5、SRSF11、SREK1、PNISR、DIDO1、ZRSR2和NKTR位于网络中心,且这些基因均为DNA转录和RNA剪接相关基因。RT-qPCR检测证实以上基因在CHD中均表达下降,与前期芯片结果一致。

结论 RNA剪接在CHD的发生过程中可能发挥了重要作用。

[关键词] 冠心病;基因表达;计算生物学;RNA剪接

[中图分类号] R541.4

[文献标志码] A

[文章编号] 2096-5532(2021)06-0852-08

doi:10.11712/jms.2096-5532.2021.57.204

[开放科学(资源服务)标识码(OSID)]

[网络出版] https://kns.cnki.net/kcms/detail/37.1517.r.20211230.1017.011.html;2021-12-30 14:59:52

IDENTIFICATION AND BIOINFORMATICS ANALYSIS OF DIFFERENTIALLY EXPRESSED GENE IN CORONARY HEART DI-SEASE

LI Zhaoshui, WANG Guangjing, QIAO Youjin, SHENG Wei, HUANG Qiang, CHI Yifan

(Department of Car-diovascular Surgery, Qingdao Hiser Hospital Affiliated to Qingdao University, Qingdao 266033, China)

[ABSTRACT]Objective To identify the differentially expressed genes (DEGs) in coronary heart disease (CHD), and to clarify the cellular pathways involved in the onset of CHD by analyzing the biological pathways involving such DEGs.

Methods The raw data of two published mRNA expression microarray datasets of CHD were downloaded from the GEO database. DEGs were screened out and a bioinformatics analysis was performed, including Venn analysis, gene ontology (GO) annotation analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) network analysis. RT-qPCR was used to validate the expression levels of core DEGs in peripheral blood of patients with CHD.

Results A total of 122 DEGs were screened out in CHD. GO and KEGG analyses showed that these DEGs were involved in DNA transcription and mRNA splicing regulation. The PPI network analysis showed the downregulated genes LUC7L3, HNRNPA1, SF3B1, ARGLU1, SRSF5, SRSF11, SREK1, PNISR, DIDO1, ZRSR2, and NKTR were located in the center of the network, and all these genes were associated with DNA transcription and RNA splicing regulation. RT-qPCR confirmed that all the above genes were downregulated in CHD, which was consistent with the previous microarray results.

Conclusion RNA splicing may play an important role in the development of CHD.

[KEY WORDS]coronary disease; gene expression; computational biology; RNA splicing

心血管疾病是目前世界上人类死亡的主要原因之一。冠心病(CHD)是最常见的一种心血管疾病,在全球范围内每年导致超过700万人死亡[1]。2014年的一项研究显示,近1/5的男性和1/10的女性死于CHD[2-4]。据估计,未来20年CHD患病率将增加约10%[5]。CHD已成为威胁人类健康的重要疾病之一,对CHD发病机制及有效疗法的研究和探索从未停止。CHD的主要危险因素包括血脂异常、糖尿病、动脉硬化、肥胖、吸烟、久坐的生活方式、压力、年龄、男性和家族病史等[6],但其具体发病机制尚不完全清楚。既往研究显示,遗传因素在心血管疾病的发生过程中发挥了极大的作用[7]。CHD发生的生物学机制有多种,其中研究较为清楚的为炎症反应,炎症反应失调是CHD发生的一种潜在的生物学机制[8]。相关研究表明,基因表达差异,尤其是炎症调控相关基因表达异常与CHD的发生紧密关联[9]。除了炎症异常调控外,还有其他因素的变化参与CHD的发生。本研究旨在通过对GEO数据库中CHD发生的基因表达谱进行生物信息学分析,揭示与CHD疾病发生相关的生物学过程及信号通路,为进一步阐明CHD的发病机制提供有价值的信息,并为CHD的诊断、治疗提供新的思路。

1 资料和方法

1.1 基因微阵列数据收集

CHD样本的基因表达芯片来自GEO数据库(http://www.ncbi.nlm.nih.gov/geo/)[10-12]。以“Coronary Heart Disease”为关键词在GEO数据库中进行检索,最终在210个相关数据集中选取2个来自Affymetrix Human Genome U133 Plus 2.0 Array分析平台的基因集GSE71226及GSE19339,共包含7个CHD样本和7个正常样本的表达矩阵。

1.2 原始数据预处理及差异表达基因(DEGs)鉴别

下载原始数据,采用R语言(affy,limma包)对其进行噪声去除、分位数归一化等处理,然后筛选CHD组和正常对照组的DEGs。筛选DEGs的阈值设定为P值<0.05,且|log2(Fold change)|≥1。最后,采用R语言(pheatmap包)对基于mRNA表达水平的组样本进行可视化层次聚类分析。

1.3 GSE71226和GSE19339中共有差异表达基因(co-DEGs)的Venn分析

通过Draw Venn Diagram线上数据库(http://bioinformatics.psb.ugent.be/webtools/Venn/)对GSE71226和GSE19339数据集中的co-DEGs进行分析[13-15]。将待分析基因列表上传到数据库,即可显示维恩图及相关共有基因列表。

1.4 基因本体(GO)和基因通路富集分析

GO注释分析通常用于大规模转录组数据的功能研究。KEGG(Kyoto Encyclopedia of Genes and Genomes)包含了多种生物化学通路。将待分析基因列表上传至DAVID生物信息学资源6.8数据库(https://david.ncifcrf.gov/)[16-17],即可显示GO及 KEGG分析结果,将其下载为文本文件。最后,通过R语言(ggplot2包)可视化GO结果。

1.5 基因集富集分析(GSEA)

将特定规格的矩阵表格加载到GSEA_4.0.2软件,通过GSEA online进行可视化即可完成GSEA分析[18-19]。DEGs途径富集的阈值为P值<0.01。

1.6 蛋白质调控网络分析

DEGs的蛋白质相互作用(PPI)网络分析通过STRING (https://string-db.org/)在线分析软件完成[19-20]。将基因列表上传到多个蛋白质分析菜单栏,稍后即可显示PPI结果。最后用Cytoscape软件将具体的网络图可视化。

1.7 实时荧光定量聚合酶链反应(RT-qPCR)验证CHD病人核心DEGs的表达水平

取青岛市市立医院心脏外科10例50~80岁CHD病人和10例同龄健康人的外周血样本,使用高效血液总RNA提取试剂盒(天根生化科技(北京)有限公司,Lot#DP443)提取总RNA。用Oligo(dT)引物(Takara, cat#3806,Lot#T2301AA)在65 ℃条件下退火5 min得到mRNA,用RevertAid逆转录酶(Thermo Scientific,#EP0441)和dNTP混合物(Takara,Cat#4019, Lot#AI11312A)进行逆转录得到cDNA模板。最后使用PowerTrack SYBR Green Master Mix(Thermo Scientific,#4367659)及基因特异性引物进行RT-qPCR,检测目的基因的相对mRNA水平。引物序列见表1。

2 结果

2.1 CHD DEGs的筛选

从GEO数据库中收集了7例CHD病人和7例正常对照者的mRNA表达谱。根据|log2(Foldchange)|≥1、P值<0.05的筛选条件,GSE71226数据集中共鉴定出2 262个DEGs,其中包含上调基因694个及下调基因1 568个(图1A);GSE19339数据集中共鉴定出537个DEGs,其中包含上调基因263个及下调基因274个(图1B)。对这些DEGs进行热图聚类分析结果显示,CHD组和正常对照组的基因表达模式差异显著(图1C、D)。

由于样本来源不同(GSE71226数据集中样本来自CHD病人和正常人的外周血;GSE19339数据集中样本分别来自经皮冠状动脉介入治疗的CHD病人冠状动脉闭塞部位的血管和正常人外周血),两个数据集中分析得到的DEGs具有一定差别。而且,两个数据集中病人信息极少,故无法分析年龄、性别和病史对CHD DEGs的影响。

2.2 co-DEGs的Venn分析

为了较为精确地研究CHD的DEGs,本研究分析了GSE71226和GSE19339两个数据集中的co-DEGs。结果筛选得到两个数据集中共同上调基因8个及共同下调基因114个,共计122个co-DEGs。见图2。两个数据集中大部分co-DEGs均为表达下调基因,提示这些共同下调基因可能是CHD发病的关键基因。

2.3 CHD co-DEGs的GO和KEGG分析

为了阐明DEGs的生物学功能,对以上122个co-DEGs进行了GO富集分析。结果显示,CHD中大多数的co-DEGs参与的生物学过程(biological process)为mRNA加工和剪接调控、细胞内转录调控(图3A);co-DEGs所属的细胞成分(cell components)为核质、细胞核和细胞质(图3B);其分子功能(molecular functions)主要为poly(A)RNA结合、蛋白结合、DNA结合(图3C)。KEGG富集分析显示,大多数co-DEGs显著富集的信号通路为剪接体(图3D)。以上分析结果表明,CHD的发生与细胞整体蛋白质表达调控紊乱或RNA剪接紊乱具有重要关联。

2.4 CHD DEGs的GSEA分析

为了进一步分析CHD DEGs可能参与的信号通路,本研究对其进行了GSEA分析。结果显示,两个GEO数据集中DEGs共同低表达的基因富集的信号通路为mRNA过程的调节及DNA损伤修复(DNA damage repair)(图4)。表明CHD发生过程中,涉及mRNA调节过程及DNA损伤修复途径的相关基因表达水平下降。GSEA分析结果与GO分析结果相一致。

2.5 CHD DEGs的蛋白质调控网络分析

为了筛选CHD的关键DEGs,本研究对122个co-DEGs进行了PPI分析。结果显示,两个数据集共同下调的基因大部分处于PPI网络中间,而共同上调的基因则处于网络边缘。其中,位于PPI网络中心的基因分别为LUC7L3、HNRNPA1、SF3B1、ARGLU1、SRSF5、SRSF11、SREK1、PNISR、DIDO1、ZRSR2及NKTR(图5)。提示这些基因的异常低表达可能在CHD的发生过程中发挥了重要作用。

2.6 CHD关键DEGs分析

筛选出的11个关键DEGs在CHD中均显著低表达(图6)。GO分析结果显示,这些关键DEGs涉及的生物学过程为DNA转录和RNA剪接体调控(表2)。表明CHD的发生与RNA剪接异常调控具有重要关系。

2.7 RT-qPCR验证CHD关键DEGs的表达

分别收集10例CHD病人及10例正常人的外周血,对筛选出的关键DEGs的表达水平进行了RT-qPCR验证。结果显示,CHD病人外周血中这些DEGs的表达水平均较正常人显著下调。见表3。

3 讨论

尽管对CHD进行了40多年的基础和临床研究,但其具体发病机制仍不完全清楚。通过分析CHD发生过程中涉及的生物学途径,增加对CHD发病机制的了解,可为CHD的临床治疗及预后判断提供新思路。

剪接体被证明是一种蛋白质定向金属酶[21]。作为真核细胞中最复杂的调控机制之一,剪接体从初级转录本中去除内含子序列,生成功能性mRNA和长链非编码RNA(lncRNA)[22],这一过程称为选择性剪接。选择性剪接是一个动态且受调控的生物学过程,受到一系列变量的影响,如顺式调控序列和反式作用因子、转录过程和DNA/RNA的甲基化等[23-24]。多项研究表明,异常可变剪接与人类疾病有关,它既可能是疾病的发生原因,也可能是疾病造成的结果[25]。有研究结果表明,参与剪接体正常功能的基因突变被认为是脊髓性肌萎缩、色素性视网膜炎和普瑞德-威利综合征等的关键因素[26-28]。然而,剪接因子中导致人类心脏病变的突变并不多见。到目前为止,只有剪接因子RNA结合基序蛋白20(RBM20)的突变被证实与心脏病有因果关系[29-31]。此外,相关研究结果表明,与RNA剪接相关基因在心脏病中异常表达。例如,剪切因子SF3B1在患病的人和小鼠心脏中均表达上调[32],Rbfox1基因在人类和小鼠心脏中表达下调[33]。然而,CHD病人中DEGs一直未被明确阐述。

本研究分析了GEO数据库的GSE71226和GSE19339数据集中CHD病人的基因表达数据,拟筛选与CHD发生密切相关的DEGs,探讨CHD基因水平的发病机制。结果显示,1.118%~2.954%(GSE71226:2.954%;GSE19339:1.118%)的基因表达水平上调,同时有1.165%~6.667%(GSE71226:6.667%;GSE19339:1.165%)的基因表达水平下调,表明CHD的发生与细胞中基因表达的变化密切相关。由于样本来源和各微阵列平台研究都存在差别,综合分析各种微阵列数据集可以获得更为准确的结果,故选择了两个数据集中8个共同表达上调基因及114个共同表达下调基因进行进一步分析。GO注释分析结果表明,这些DEGs参与了DNA转录和mRNA剪接调控,提示CHD的发生与细胞中RNA剪接紊乱有关。选择性剪接是一种可实质上改变基因表达模式的转录后机制。高达95%的人类基因具有多外显子可变剪接形式,表明可变剪接是人类基因组功能复杂性的最重要组成部分之一。本研究结果表明,大部分的CHD DEGs是可变剪接相关的基因,提示可变剪接调控在心脏病的研究中应受到更多的重视。

在DEGs调控网络中,表达下调的LUC7L3、HNRNPA1、SF3B1、ARGLU1、SRSF5、SRSF11、SREK1、PNISR、DIDO1、ZRSR2和NKTR位于网络控制中心,且均为DNA转录和RNA剪接调控相关基因。既往研究表明,LUC7L3通过RE和RS域参与了剪接体的形成,在心脏钠通道剪接调节人类心力衰竭中发挥作用[34-35]。HNRNPA1为异质性核糖核蛋白(hnRNP)复合体中含量最丰富的核心蛋白之一,在选择性剪接的调控中发挥关键作用。SF3B1为一种重要的pre-mRNA剪接因子,与癌症突变相关,并可以作为靶向药物治疗靶点[36-40]。在剪接体装配的早期阶段,SF3B1在pre-mRNA剪接位点的小核核糖核酸蛋白(snRNP)之间促发了一系列依赖ATP的结构和成分重排,最终完成pre-mRNA剪接的行为[36,41-42],但其在CHD中的作用尚未得到证实。据报道,ARGLU1为一种转录共激活因子和剪接调节因子,对应激性激素信号转导和发育以及多种癌症调控非常重要[43-44]。SRSF5是pre-mRNA剪接因子中SR的家族成员,是剪接体的一部分[45]。已有研究结果表明,SRSF5作为一种新型的致癌剪接因子,在多种癌症和免疫调节中发挥关键作用[46-51],但其在CHD中的作用未见报道。SRSF11为一种在可变剪接过程中发挥作用的剪接因子[52]。SREK1为富含SR剪接蛋白家族的一个成员[53]。PNISR,又被称为SFRS18,使用公开交互数据库的数据挖掘也支持了LUC7L3和SFRS18在RNA剪接中的相互作用[54]。GARCIA-DOMINGO等[55-56]研究表明,DIDO1通过上调procaspase 3和9参与细胞凋亡的激活。此外,F TTERER等[57]观察到,小鼠中DIDO的缺失与骨髓增生异常综合征相关。FLEISCHMAN等[58]的研究则表明,ZRSR2突变病人的常见临床特征为白细胞减少、血小板减少或骨髓母细胞百分比增加的大细胞性贫血。本研究中筛选到的CHD DEGs大部分都是mRNA剪接相关基因,这些基因通过RNA剪接功能调控不同的人类疾病。但是,这些基因与CHD之间的关系目前尚未被报道。

综上所述,本文结果显示,CHD病人RNA剪接相关基因的表达水平发生显著改变,表明RNA剪接调控在CHD的发生过程中可能发挥了重要作用,但其在CHD中的具体作用机制仍有待进一步研究。本研究结果为CHD的进一步研究及高危人群的筛查提供了新的思路。

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(本文编辑 马伟平)