Functional Mapping and Annotation of GWAS: FUMA Danielle Posthuma Dept. Complex Trait Genetics, VU University Amsterdam //danielle/2017/FUMA_dp.ppt Boulder, TC31, March 8 2017

S Ripke et al. Nature (2014)

Physical & chemical environment Regulation & control Protein Translation RNA Transcription DNA

Interpreting the effect of SNPs on gene-products SNPs can act to alter the protein or RNA structure alter the protein or RNA level SNPs can be located in genes outside genes

Functional categories of SNPs Protein Coding SNPs in exonic regions may alter protein structure and/or function e.g nonsense SNPs or missense SNPs Splicing Regulation SNPs in splice sites may disrupt splicing regulation, resulting in exon skipping or intron retention They can also interfere with alternative splicing regulation by changing exonic splicing enhancers or silencers. Transcriptional Regulation SNPs in transcription regulatory regions (e.g. transcription factor binding sites, CpG islands, microRNAs, etc.) can alter binding sites, and thus disrupt proper gene regulation. Post-Translational Modification SNPs in protein-coding regions may alter post-translational modification sites, interfering with proper posttranslational modification.

Example SNP effect G healthy T disease This is a ‘stop-gained’ SNP

CADD scores Combined Annotation Dependent Depletion Score CADD is a tool for scoring the deleteriousness of SNPs as well as insertion/deletions variants in the human genome. A scaled CADD score >=10 indicates that these SNPs are predicted to be the 10% most deleterious substitutions; a score >=20 indicates the 1% most deleterious

Expression QTLs Alexandra C. Nica, and Emmanouil T. Dermitzakis Phil. Trans. R. Soc. B 2013;368:20120362 © 2013 The Author(s) Published by the Royal Society. All rights reserved.

The same regulatory regions and variant could be an eQTL for gene 2 in (a) tissue 1 and for gene 1 in (b) tissue 2, suggesting that limited interrogation of tissues would be misleading for the biological signal underlying disease. Alexandra C. Nica, and Emmanouil T. Dermitzakis Phil. Trans. R. Soc. B 2013;368:20120362 © 2013 The Author(s) Published by the Royal Society. All rights reserved.

RegulomeDB score Score Supporting data 1a eQTL + TF binding + matched TF motif + matched DNase Footprint + DNase peak 1b eQTL + TF binding + any motif + DNase Footprint + DNase peak 1c eQTL + TF binding + matched TF motif + DNase peak 1d eQTL + TF binding + any motif + DNase peak 1e eQTL + TF binding + matched TF motif 1f eQTL + TF binding / DNase peak 2a TF binding + matched TF motif + matched DNase Footprint + DNase peak 2b TF binding + any motif + DNase Footprint + DNase peak 2c TF binding + matched TF motif + DNase peak 3a TF binding + any motif + DNase peak 3b TF binding + matched TF motif 4 TF binding + DNase peak 5 TF binding or DNase peak 6 other

SNP annotation implicates genes Explore gene function Explore pathway enrichment of implicated genes Explore in which tissue gene is expressed

How to pinpoint causal genes based on GWAS? Are there functional variants in the GWAS risk loci? Are there regulatory variants or eQTLs in the GWAS risk loci? Are there SNPS with high CADD scores or low RegulomeDB scores? Where are the genes expressed that lie in the risk loci? What are the implicated pathways? Answers to these questions will generate hypotheses for functional follow-up experiments to investigate causality

Combine functional annotation information from different resources Many different repositories Need knowledge of how to normalize/interpret data Output can be huge, need visualizations for interpretation

FUMA developed by Kyoko Watanabe fuma.ctglab.nl

Demo fuma.ctglab.nl Watanabe K, Taskesen E, van Bochoven A, Posthuma D. FUMA: Functional mapping and annotation. doi: https://doi.org/10.1101/110023 BiorXiv

No exonic SNPs eQTLs Third implicated gene

Exonic SNPs, high CADD scores

And also several eQTLS

In sum Upload GWAS summary statistics Adds unmeasured SNPs to genomic risk loci, with known LD to measured SNPs Annotates all SNPs in genomic risk loci Functional annotations CADD scores RegulomeDB scores Chromatin states eQTL information Prioritizes genes based on user-defined filters Conducts gene-based and pathway analyses (MAGMA & enrichment) Provides interactive plots to visualize results All generated results can be downloaded