prof. dr. L.H. (Lude) Franke

Lude Franke is an associate professor in the Department of Genetics at the UMCG. He has over 12 years of research experience on the development and application of computational methods for performing functional genomics. In particular he has performed several large-scale expression quantitative trait locus (eQTL) mapping analysis, showing that disease-associated SNPs typically have regulatory effects.

He obtained his PhD in 2008 (cum laude) while developing new, cutting-edge computational and statistical methods for conducting genome-wide association studies (GWAS) and gene network reconstruction using gene expression data. After graduation, he took up a concurrent postdoc positions in London (Institute of Cell and Molecular Science), and Groningen (University Medical Centre Groningen). In London he conducted research on the genetics of immune-mediated diseases (i.e. celiac disease) and in Groningen he worked on the development of methods to identify the effects of GWAS risk-SNPs on gene expression levels (Franke and Jansen, Methods Mol Bio 2009). His post-doc work resulted in a landmark paper (Dubois et al, Nature Genetics 2010, cited >200 times) that combined his work in London and Groningen. In this paper he demonstrated that there were many independent genetic risk-variants in celiac disease and that they mostly increase disease-risk by altering gene expression levels.

As senior author, he subsequently developed various computational methods and software to increase statistical power to identify such effects on gene expression (Westra et al, Bioinformatics 2010, Fehrmann et al, PLoS Genetics 2011, cited >90 times). By using these methods, he was able to demonstrate that the genetic risk-variants for many other diseases also have an effect on gene-expression levels, and that these genetic variants often affect gene expression levels in only specific cell types (Fu et al, PLoS Genetics 2012). He showed that SNPs affect the expression levels of many long non-coding genes (lncRNAs, Kumar et al, PLoS Genetics, January 2013) and that they can affect poly-adenylation of genes (Zhernakova et al, PLoS Genetics, June 2013). Through a large-scale blood eQTL meta-analysis consortium that he initiated in 2010 and is currently leading (eQTLGen), he identified downstream (trans-eQTL) effects for over 100 different risk-SNPs (Westra et al, Nature Genetics, October 2013). 

By reanalysing considerable amounts of publicly available expression data, his group could accurately predict the biological functions of many genes, and developed a method to accurately identify deletions and duplications based on gene expression measurements (Fehrmann et al, Nature Genetics in press). Based on these predicted gene functions we developed DEPICT (Pers et al, Nature Communications in press), a method that uses these predicted gene functions to better interpret genome-wide association studies.

The current focus of the lab is on applying RNA-seq in both research and diagnostic setting for identification of disease mutations.