Peter Humburg

Postdoctoral Research Scientist

Statistical Functional genomics of the MHC

We are using functional genomic approaches to define genetic variants that are responsible for the association of genetic variation in the Major Histocompatibility Complex (MHC) with susceptibility to autoimmune, infectious and inflammatory disease. Recent work in our lab has highlighted the extent of allele-specific differences in gene expression in human lymphoblastoid cell lines and primary immune cells. We aim to resolve the functional consequences of genetic and epigenetic variation in the MHC for transcriptional regulation. 

This work involves developing and applying advanced methodologies in bioinformatics and statistical genetics to allow the analysis of large complex datasets arising from high-density genotyping, DNA sequencing and functional genomic profiling. The latter includes data arising from application of high throughput sequencing for transcript quantification (RNA-seq) and chromatin profiling (ChIP-seq), allele-specific and expression quantitative trait mapping, analysis of epigenetic modifications, noncoding RNAs, alternative splicing and DNA methylation. We collaborate with colleagues in the Bioinformatics and Statistical Genetics Core headed by Professor Gil McVean, facilitating sharing of expertise and development of analytical tools and resources.

 

Keywords: MHC, Functional Genomics, High-throughput Sequencing, Gene Expression, Epigenetics

This project is sponsored by the European Research Council