A framework for accurate prediction of effector genes in genetic loci for complex traits

Genome-wide association studies (GWAS) yield large numbers of genetic loci associated with traits and diseases. Predicting the effector genes that mediate these locus associations remains challenging. Here we present the FLAMES framework, which predicts the most likely effector gene in a locus. FLAMES integrates machine learning with biological data linking single nucleotide polymorphisms (SNPs) to genes, and GWAS-wide convergence of gene interactions. We benchmark FLAMES on gene-locus pairs derived by expert curation, rare variant implication, and domain knowledge of molecular traits. We demonstrate that combining SNP-based and convergence-based evidence outperforms prioritization strategies using a single line of evidence. Applying FLAMES, we resolve the FSHB locus in the GWAS for dizygotic twinning and further leverage this framework to find novel schizophrenia risk genes that converge with rare coding evidence and are relevant in different stages of life. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This project was funded by NWO Gravitation: BRAINSCAPES: A Roadmap from Neurogenetics to Neurobiology (Grant No. 024.004.012). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Human HiC interaction data from: https://www.cell.com/cms/10.1016/j.cell.2016.09.037/attachment/5bc79f6f-1b69-4192-8cb8-4247cc2e0f39/mmc4.zip and from https://www.ncbi.nlm.nih.gov/geo/download/?acc=GSE86189&format=file&file=GSE86189%5Fall%5Finteraction%2Epo%2Etxt%2Egz Human enhancer data from: https://bioinfo.vanderbilt.edu/AE/HACER/download.html, https://ernstlab.biolchem.ucla.edu/roadmaplinking/RoadmapLinks.zip, https://zenodo.org/record/7754032/files/S2G\_original.zip?download=1, https://zenodo.org/record/7754032/files/S2G\_original.zip?download=1, https://osf.io/uhnb4/ and ftp://ftp.broadinstitute.org/outgoing/lincRNA/ABC/AllPredictions.AvgHiC.ABC0.015.minus150.ForABCPaperV3.txt.gz. Human fine-mapped eQTL data from: https://storage.googleapis.com/gtex\_analysis\_v8/single\_tissue\_qtl\_data/GTEx\_v8\_finemapping\_CAVIAR.tar, https://zenodo.org/record/7754032/files/S2G\_original.zip?download=1 and https://ftp.ebi.ac.uk/pub/databases/spot/eQTL/susie Epigenetic data: https://personal.broadinstitute.org/cboix/epimap/links/links\_corr\_only/, https://ernstlab.biolchem.ucla.edu/roadmaplinking/RoadmapLinks.zip and https://zenodo.org/record/7754032/files/S2G\_original.zip?download=1. GWAS data was acquired from : https://pan.ukbb.broadinstitute.org/downloads and from https://genetics.opentargets.org/ I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data used and produced in this manuscript are available in the supplementary data, Zenodo and GitHub [https://github.com/Marijn-Schipper/FLAMES\_paper\_analyses][1] [1]: https://github.com/Marijn-Schipper/FLAMES_paper_analyses