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Identification of transcription factors and cofactors binding to type 2 diabetes risk variants which modulate allele- and tissue-specific gene expression and phenotypes.

Applicant Professor Dr. Heiko Witt, since 1/2021
Subject Area Endocrinology, Diabetology, Metabolism
Term from 2016 to 2022
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 321768878
 
For types 2 diabetes (T2D) more than 65 genetic risk loci have been identified. Most variants are located in noncoding regions, suggesting that regulatory variants modulating gene expression are major contributors to disease risk. Both, regulatory variants and regulated genes at risk loci with numerous variants in linkage disequilibrium remain elusive in most cases. Moreover, numerous data support tissue- and allele-specific regulation of gene expression, which depends on a highly regulated interaction of transcription factors and cofactors, but the precise mechanisms remain elusive in particular for allele-specific gene regulation. Here, we will find regulatory variants by combining a bioinformatics strategy introduced by our group with public domain epigenomic marks of regulatory regions. Moreover, we will identify both, allele- and tissue-specific transcription factors and cofactors, using a highly efficient proteomics methodology. By diverse approaches, such as reporter- and DNA-binding assays, genome-wide expression profiling and CRISPR genome editing, we will confirm genotype dependent modulation of transcriptional activity, nearby and distant gene regulation by the identified factors. Finally, modulation of disease specific phenotypes will be assessed, such as insulin-sensitivity and insulin-secretion for T2D. We will uncover mechanisms at the TCF7L2 locus, reported to modulate T2D phenotypes in beta-cells, liver and adipose-tissue; and consider analysis at further loci suggested to modulate tissue-specific gene expression such as FTO or TLE1. Our tissue-specific in-depth analysis at risk loci, ranging from identification of regulatory variants, binding protein-complexes, regulated genes and modulated phenotypes may guide identification of previously unknown entry points for personalized intervention.
DFG Programme Research Grants
Ehemaliger Antragsteller Dr. Helmut Laumen, until 12/2020
 
 

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