The missing link between genetic association and regulatory function

Author:

Connally Noah J123ORCID,Nazeen Sumaiya124,Lee Daniel123,Shi Huwenbo35,Stamatoyannopoulos John6,Chun Sung7,Cotsapas Chris389,Cassa Christopher A23,Sunyaev Shamil R123ORCID

Affiliation:

1. Department of Biomedical Informatics, Harvard Medical School

2. Brigham and Women’s Hospital, Division of Genetics, Harvard Medical School

3. Program in Medical and Population Genetics, Broad Institute of MIT and Harvard

4. Brigham and Women’s Hospital, Department of Neurology, Harvard Medical School

5. Department of Epidemiology, Harvard T.H. Chan School of Public Health

6. Altius Institute

7. Division of Pulmonary Medicine, Boston Children’s Hospital

8. Department of Neurology, Yale Medical School

9. Department of Genetics, Yale Medical School

Abstract

The genetic basis of most traits is highly polygenic and dominated by non-coding alleles. It is widely assumed that such alleles exert small regulatory effects on the expression of cis-linked genes. However, despite the availability of gene expression and epigenomic datasets, few variant-to-gene links have emerged. It is unclear whether these sparse results are due to limitations in available data and methods, or to deficiencies in the underlying assumed model. To better distinguish between these possibilities, we identified 220 gene–trait pairs in which protein-coding variants influence a complex trait or its Mendelian cognate. Despite the presence of expression quantitative trait loci near most GWAS associations, by applying a gene-based approach we found limited evidence that the baseline expression of trait-related genes explains GWAS associations, whether using colocalization methods (8% of genes implicated), transcription-wide association (2% of genes implicated), or a combination of regulatory annotations and distance (4% of genes implicated). These results contradict the hypothesis that most complex trait-associated variants coincide with homeostatic expression QTLs, suggesting that better models are needed. The field must confront this deficit and pursue this ‘missing regulation.’

Funder

National Institutes of Health

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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