Identification of genetic and epigenetic determinants of allele-specific gene expression in the human major histocompatibility complex (MHC) in patients with inflammatory bowel diseases (IBD)

Alumni

Principal Investigator

Prof. Dr. rer. nat.

Associated Principal Investigator

Background and current state of research

The MHC is a paradigm for genomics, showing remarkable polymorphism and a striking association with several chronic immune-mediated diseases (CID) such as IBD (two main subtypes are Crohn’s disease and ulcerative colitis). The association between genetic variants in the MHC and IBD has been known for decades and in 20151 we completed a fine mapping effort in European-ancestry patients, revealing a dense risk map of the locus for IBD. Yet, the actual causal candidate variants are manifold and the underlying functional mechanisms are not well understood. Specifically, the relative contributions of regulatory and functional variation in IBD are still elusive. This shortcoming needs to be addressed as the MHC is perhaps the most important disease locus in autoimmune diseases and CID.

Our goals

The overall goal of this project is to understand how individual genetic and epigenetic variation in MHC determines susceptibility to IBD. We here aim to (i) identify regulatory variants in the MHC and allele-specific gene expression and (ii) specifically search for genetic variants that are associated with T cell receptor (TCR) expression biases2 in the disease context.

How to get there

We will build on prior knowledge and experimental data that has been generated in the last years within the institute and the RTG 1743. Next generation sequencing data exists for >1000 patients and healthy controls. In brief, SNP array, exome sequencing, HLA typing and RNA-Seq expression data will be combined in a well-powered eQTL (expression quantitative trait locus) study. Before, bioinformatics algorithms have to be developed that (a) accurately align reads from exome-Seq data and call SNVs within the xHLA region (extended human leukocyte antigen complex; corresponds to human MHC and the herein-studied region of interest on chromosome 6p21) and (b) accurately determine the expression levels of transcripts within the xHLA. Next, we will correlate the genetic and HLA typing data with in-house available TCR profiling results3. In a final step, we will integrate existing methylation array data into the analyses to identify functionally relevant epigenetic modifications within the xHLA.

1 High-density mapping of the MHC identifies a shared role for HLA-DRB1*01:03 in inflammatory bowel diseases and heterozygous advantage in ulcerative colitis. Goyette P, Boucher G, Mallon D, Ellinghaus E, Jostins L, Huang H, Ripke S, Gusareva ES, Annese V, Hauser SL, Oksenberg JR, Thomsen I, Leslie S; International Inflammatory Bowel Disease Genetics Consortium; Australia and New Zealand IBDGC; Belgium IBD Genetics Consortium; Italian Group for IBD Genetic Consortium; NIDDK Inflammatory Bowel Disease Genetics Consortium; United Kingdom IBDGC; Wellcome Trust Case Control Consortium; Quebec IBD Genetics Consortium, Daly MJ, Van Steen K, Duerr RH, Barrett JC, McGovern DP, Schumm LP, Traherne JA, Carrington MN, Kosmoliaptsis V, Karlsen TH, Franke A*, Rioux JD. Nat Genet. 2015 Feb;47(2):172-9. doi: 10.1038/ng.3176. Epub 2015 Jan 5. PMID: 25559196
2 Genetic variation in MHC proteins is associated with T cell receptor expression biases. Sharon E, Sibener LV, Battle A, Fraser HB, Garcia KC, Pritchard JK. Nat Genet. 2016 Sep;48(9):995-1002. doi: 10.1038/ng.3625. Epub 2016 Aug 1. PMID: 27479906
3 Overview of methodologies for T-cell receptor repertoire analysis. Rosati E, Dowds CM, Liaskou E, Henriksen EKK, Karlsen TH, Franke A. BMC Biotechnol. 2017 Jul 10;17(1):61. D

More information

Requirements for the position:
We are searching for a motivated bioinformatician (or related education) that is interested in performing state-of-the-art analyses in the field of immunogenetics and next generation sequencing data analysis. You will work in an interdisciplinary team of experts and will have access to a large supercomputing environment. Prior basic knowledge in statistics, python and NGS data analysis is expected