1. Genetic Effects on Transcriptome Profiles in Colon Epithelium Provide Functional Insights for Genetic Risk Loci
- Author
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Ferran Moratalla-Navarro, Jeroen R. Huyghe, Anshul Kundaje, Elisabeth Guino, Stephanie A. Bien, Anna Díez-Villanueva, Ulrike Peters, Gemma Ibáñez-Sanz, Mireia Obón-Santacana, Victor Moreno, Graham Casey, Virginia Díez-Obrero, Christopher H. Dampier, Robert Carreras-Torres, Matthew Devall, and Sarah J. Plummer
- Subjects
Male ,0301 basic medicine ,Colon ,Biopsy ,Quantitative Trait Loci ,Gene Expression ,Computational biology ,RC799-869 ,Biology ,Quantitative trait locus ,Polymorphism, Single Nucleotide ,Epithelium ,Transcriptome ,03 medical and health sciences ,0302 clinical medicine ,Humans ,SNP ,Gene ,Hepatology ,Colon (Anatomy) ,Alternative splicing ,Gastroenterology ,Middle Aged ,QTLs ,Diseases of the digestive system. Gastroenterology ,Expressió gènica ,SNP genotyping ,Alternative Splicing ,030104 developmental biology ,Regulatory sequence ,RNA splicing ,Female ,030211 gastroenterology & hepatology ,Gene expression ,Biòpsia ,Còlon - Abstract
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. Methods 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. Results 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. Conclusions 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.
- Published
- 2021