Oncology Data Analytics Program, Catalan Institute of Oncology, L'Hospitalet de Llobregat, Barcelona, Spain; Colorectal Cancer Group, Molecular Mechanisms and Experimental Therapy in Oncology (ONCOBELL) Program, Bellvitge Biomedical Research Institute, Spain; Consortium for Biomedical Research in Epidemiology and Public Health, Madrid, Spain; Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Barcelona, Spain.
Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia; Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia; Department of Surgery, University of Virginia, Charlottesville, Virginia.
Cell Mol Gastroenterol Hepatol. 2021;12(1):181-197. doi: 10.1016/j.jcmgh.2021.02.003. Epub 2021 Feb 16.
BACKGROUND & AIMS: The association of genetic variation with tissue-specific gene expression and alternative splicing guides functional characterization of complex trait-associated loci and may suggest novel genes implicated in disease. Here, our aims were as follows: (1) to generate reference profiles of colon mucosa gene expression and alternative splicing and compare them across colon subsites (ascending, transverse, and descending), (2) to identify expression and splicing quantitative trait loci (QTLs), (3) to find traits for which identified QTLs contribute to single-nucleotide polymorphism (SNP)-based heritability, (4) to propose candidate effector genes, and (5) to provide a web-based visualization resource.
We collected colonic mucosal biopsy specimens from 485 healthy adults and performed bulk RNA sequencing. We performed genome-wide SNP genotyping from blood leukocytes. Statistical approaches and bioinformatics software were used for QTL identification and downstream analyses.
We provided a complete quantification of gene expression and alternative splicing across colon subsites and described their differences. We identified thousands of expression and splicing QTLs and defined their enrichment at genome-wide regulatory regions. We found that part of the SNP-based heritability of diseases affecting colon tissue, such as colorectal cancer and inflammatory bowel disease, but also of diseases affecting other tissues, such as psychiatric conditions, can be explained by the identified QTLs. We provided candidate effector genes for multiple phenotypes. Finally, we provided the Colon Transcriptome Explorer web application.
We provide a large characterization of gene expression and splicing across colon subsites. Our findings provide greater etiologic insight into complex traits and diseases influenced by transcriptomic changes in colon tissue.
遗传变异与组织特异性基因表达和选择性剪接的关联指导了复杂性状相关基因座的功能特征,并可能提示与疾病相关的新基因。在这里,我们的目的如下:(1)生成结肠黏膜基因表达和选择性剪接的参考图谱,并比较它们在结肠亚区(升结肠、横结肠和降结肠)之间的差异;(2)识别表达和剪接数量性状基因座(QTL);(3)发现所确定的 QTL 有助于基于单核苷酸多态性(SNP)的遗传率的性状;(4)提出候选效应基因;(5)提供基于网络的可视化资源。
我们从 485 名健康成年人中收集结肠黏膜活检标本,并进行批量 RNA 测序。我们从血液白细胞中进行全基因组 SNP 基因分型。统计方法和生物信息学软件用于 QTL 鉴定和下游分析。
我们全面定量了结肠亚区的基因表达和选择性剪接,并描述了它们的差异。我们鉴定了数千个表达和剪接 QTL,并定义了它们在全基因组调控区域的富集。我们发现,部分影响结肠组织的疾病(如结直肠癌和炎症性肠病)的 SNP 遗传率,以及影响其他组织的疾病(如精神疾病)的 SNP 遗传率,可以用所鉴定的 QTL 来解释。我们为多种表型提供了候选效应基因。最后,我们提供了 Colon Transcriptome Explorer 网络应用程序。
我们对结肠亚区的基因表达和选择性剪接进行了大量的描述。我们的研究结果为受结肠组织转录组变化影响的复杂性状和疾病提供了更深入的病因学见解。