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Br J Cancer. 2018 Oct;119(8):971-977. doi: 10.1038/s41416-018-0018-9. Epub 2018 Oct 4.

Colon-specific eQTL analysis to inform on functional SNPs.

Author information

1
Unit of Biomarkers and Susceptibility, Cancer Prevention and Control Program, Catalan Institute of Oncology (ICO), Barcelona, 08908, Spain. v.moreno@iconcologia.net.
2
Institut d'Investigacions Biomèdiques de Bellvitge (IDIBELL), Barcelona, 08908, Spain. v.moreno@iconcologia.net.
3
Centro de Investigación Biomédica en Red de Epidemiologia y Salud Pública (CIBERESP), Madrid, 28029, Spain. v.moreno@iconcologia.net.
4
Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Barcelona, 08907, Spain. v.moreno@iconcologia.net.
5
Unit of Biomarkers and Susceptibility, Cancer Prevention and Control Program, Catalan Institute of Oncology (ICO), Barcelona, 08908, Spain.
6
Institut d'Investigacions Biomèdiques de Bellvitge (IDIBELL), Barcelona, 08908, Spain.
7
Centro de Investigación Biomédica en Red de Epidemiologia y Salud Pública (CIBERESP), Madrid, 28029, Spain.
8
Hereditary Cancer Program, Catalan Institute of Oncology (ICO), Barcelona, 08908, Spain.
9
Centro de Investigación Biomédica en Red de Oncologia (CIBERONC), Madrid, 28029, Spain.
10
Department of Gastroenterology, Hospital Clínic de Barcelona, Barcelona, 08036, Spain.
11
Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Madrid, 28029, Spain.
12
Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, 08036, Spain.

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 package MatrixEQTL was used to search for genome-wide cis-eQTL and trans-eQTL fitting linear models adjusted for age, gender and tissue type to rank transformed expression data.

RESULTS:

The cis-eQTL analyses has revealed 29,073 SNP-gene associations with permutation-adjusted P-values < 0.01. These correspond to 363 unique genes. The trans-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.

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