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The missing link between genetic association and regulatory function
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 lin...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9842386/ https://www.ncbi.nlm.nih.gov/pubmed/36515579 http://dx.doi.org/10.7554/eLife.74970 |
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author | Connally, Noah J Nazeen, Sumaiya Lee, Daniel Shi, Huwenbo Stamatoyannopoulos, John Chun, Sung Cotsapas, Chris Cassa, Christopher A Sunyaev, Shamil R |
author_facet | Connally, Noah J Nazeen, Sumaiya Lee, Daniel Shi, Huwenbo Stamatoyannopoulos, John Chun, Sung Cotsapas, Chris Cassa, Christopher A Sunyaev, Shamil R |
author_sort | Connally, Noah J |
collection | PubMed |
description | 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.’ |
format | Online Article Text |
id | pubmed-9842386 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-98423862023-01-17 The missing link between genetic association and regulatory function Connally, Noah J Nazeen, Sumaiya Lee, Daniel Shi, Huwenbo Stamatoyannopoulos, John Chun, Sung Cotsapas, Chris Cassa, Christopher A Sunyaev, Shamil R eLife Genetics and Genomics 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.’ eLife Sciences Publications, Ltd 2022-12-14 /pmc/articles/PMC9842386/ /pubmed/36515579 http://dx.doi.org/10.7554/eLife.74970 Text en © 2022, Connally et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Genetics and Genomics Connally, Noah J Nazeen, Sumaiya Lee, Daniel Shi, Huwenbo Stamatoyannopoulos, John Chun, Sung Cotsapas, Chris Cassa, Christopher A Sunyaev, Shamil R The missing link between genetic association and regulatory function |
title | The missing link between genetic association and regulatory function |
title_full | The missing link between genetic association and regulatory function |
title_fullStr | The missing link between genetic association and regulatory function |
title_full_unstemmed | The missing link between genetic association and regulatory function |
title_short | The missing link between genetic association and regulatory function |
title_sort | missing link between genetic association and regulatory function |
topic | Genetics and Genomics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9842386/ https://www.ncbi.nlm.nih.gov/pubmed/36515579 http://dx.doi.org/10.7554/eLife.74970 |
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