Colon-specific eQTL analysis to inform on functional SNPs. Issue 8 (16th October 2018)

• Record Type: Journal Article
• Authors: Moreno, Victor; Alonso, M.; Closa, Adrià; Vallés, Xavier; Diez-Villanueva, Anna; Valle, Laura; Castellví-Bel, Sergi; Sanz-Pamplona, Rebeca; Lopez-Doriga, Adriana; Cordero, David; Solé, Xavier
• Is Part Of: British journal of cancer. Volume 119:Issue 8(2018)
• Page Start: 971
• Page End: 977
• Publication Date: 2018-10-16
• Subjects: Cancer -- Periodicals; Cancer -- Research -- Periodicals; Tumors -- Periodicals; 616.994
• DOI: 10.1038/s41416-018-0018-9
• Languages: English
• ISSNs: 0007-0920

Abstract

Abstract Background Genome-wide association studies on colorectal cancer have identified more than 60 susceptibility loci, but for most of them there is no clear knowledge of functionality or the underlying gene responsible for the risk modification. Expression quantitative trail loci (eQTL) may provide functional information for such single nucleotide polymorphisms (SNPs). Methods We have performed detailed eQTL analysis specific for colon tissue on a series of 97 colon tumours, their paired adjacent normal mucosa and 47 colon mucosa samples donated by healthy individuals. R packageMatrixEQTL was used to search for genome-widecis -eQTL andtrans -eQTL fitting linear models adjusted for age, gender and tissue type to rank transformed expression data. Results Thecis -eQTL analyses has revealed 29, 073 SNP-gene associations with permutation-adjustedP -values < 0.01. These correspond to 363 unique genes. Thetrans -eQTL analysis identified 10, 665 significant SNP-gene associations, most of them in the same chromosome, further than 1 Mb of the gene. We provide a web tool to search for specific SNPs or genes. The tool calculates Pearson or Spearman correlation, and allows to select tissue type for analysis. Data and plots can be exported. Conclusions This resource should be useful to prioritise SNPs for further functional studies and to identify relevant genes behind identified loci.