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

2. S Ripke et al. Nature (2014)

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

6. 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

7. 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.

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

10. 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

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

12. 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:
© 2013 The Author(s) Published by the Royal Society. All rights reserved.

13. 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

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

15. 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

16. 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

17. FUMA developed by Kyoko Watanabe
fuma.ctglab.nl

18. Demo
fuma.ctglab.nl
Watanabe K, Taskesen E, van Bochoven A, Posthuma D.
FUMA: Functional mapping and annotation.
doi:  BiorXiv

37. No exonic SNPs
eQTLs
Third implicated gene

40. Exonic SNPs, high CADD scores

41. And also several eQTLS

48. 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