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Evaluating the Contribution of Cell Type–Specific Alternative Splicing to Variation in Lipid Levels
Genome-wide association studies have identified hundreds of loci associated with lipid levels. However, the genetic mechanisms underlying most of these loci are not well-understood. Recent work indicates that changes in the abundance of alternatively spliced transcripts contribute to complex trait v...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10284136/ https://www.ncbi.nlm.nih.gov/pubmed/37165871 http://dx.doi.org/10.1161/CIRCGEN.120.003249 |
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author | Gawronski, Katerina A.B. Bone, William P. Park, YoSon Pashos, Evanthia E. Wenz, Brandon M. Dudek, Max F. Wang, Xiao Yang, Wenli Rader, Daniel J. Musunuru, Kiran Voight, Benjamin F. Brown, Christopher D. |
author_facet | Gawronski, Katerina A.B. Bone, William P. Park, YoSon Pashos, Evanthia E. Wenz, Brandon M. Dudek, Max F. Wang, Xiao Yang, Wenli Rader, Daniel J. Musunuru, Kiran Voight, Benjamin F. Brown, Christopher D. |
author_sort | Gawronski, Katerina A.B. |
collection | PubMed |
description | Genome-wide association studies have identified hundreds of loci associated with lipid levels. However, the genetic mechanisms underlying most of these loci are not well-understood. Recent work indicates that changes in the abundance of alternatively spliced transcripts contribute to complex trait variation. Consequently, identifying genetic loci that associate with alternative splicing in disease-relevant cell types and determining the degree to which these loci are informative for lipid biology is of broad interest. METHODS: We analyze gene splicing in 83 sample-matched induced pluripotent stem cell (iPSC) and hepatocyte-like cell lines (n=166), as well as in an independent collection of primary liver tissues (n=96) to perform discovery of splicing quantitative trait loci (sQTLs). RESULTS: We observe that transcript splicing is highly cell type specific, and the genes that are differentially spliced between iPSCs and hepatocyte-like cells are enriched for metabolism pathway annotations. We identify 1384 hepatocyte-like cell sQTLs and 1455 iPSC sQTLs at a false discovery rate of <5% and find that sQTLs are often shared across cell types. To evaluate the contribution of sQTLs to variation in lipid levels, we conduct colocalization analysis using lipid genome-wide association data. We identify 19 lipid-associated loci that colocalize either with an hepatocyte-like cell expression quantitative trait locus or sQTL. Only 2 loci colocalize with both a sQTL and expression quantitative trait locus, indicating that sQTLs contribute information about genome-wide association studies loci that cannot be obtained by analysis of steady-state gene expression alone. CONCLUSIONS: These results provide an important foundation for future efforts that use iPSC and iPSC-derived cells to evaluate genetic mechanisms influencing both cardiovascular disease risk and complex traits in general. |
format | Online Article Text |
id | pubmed-10284136 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-102841362023-06-22 Evaluating the Contribution of Cell Type–Specific Alternative Splicing to Variation in Lipid Levels Gawronski, Katerina A.B. Bone, William P. Park, YoSon Pashos, Evanthia E. Wenz, Brandon M. Dudek, Max F. Wang, Xiao Yang, Wenli Rader, Daniel J. Musunuru, Kiran Voight, Benjamin F. Brown, Christopher D. Circ Genom Precis Med Original Articles Genome-wide association studies have identified hundreds of loci associated with lipid levels. However, the genetic mechanisms underlying most of these loci are not well-understood. Recent work indicates that changes in the abundance of alternatively spliced transcripts contribute to complex trait variation. Consequently, identifying genetic loci that associate with alternative splicing in disease-relevant cell types and determining the degree to which these loci are informative for lipid biology is of broad interest. METHODS: We analyze gene splicing in 83 sample-matched induced pluripotent stem cell (iPSC) and hepatocyte-like cell lines (n=166), as well as in an independent collection of primary liver tissues (n=96) to perform discovery of splicing quantitative trait loci (sQTLs). RESULTS: We observe that transcript splicing is highly cell type specific, and the genes that are differentially spliced between iPSCs and hepatocyte-like cells are enriched for metabolism pathway annotations. We identify 1384 hepatocyte-like cell sQTLs and 1455 iPSC sQTLs at a false discovery rate of <5% and find that sQTLs are often shared across cell types. To evaluate the contribution of sQTLs to variation in lipid levels, we conduct colocalization analysis using lipid genome-wide association data. We identify 19 lipid-associated loci that colocalize either with an hepatocyte-like cell expression quantitative trait locus or sQTL. Only 2 loci colocalize with both a sQTL and expression quantitative trait locus, indicating that sQTLs contribute information about genome-wide association studies loci that cannot be obtained by analysis of steady-state gene expression alone. CONCLUSIONS: These results provide an important foundation for future efforts that use iPSC and iPSC-derived cells to evaluate genetic mechanisms influencing both cardiovascular disease risk and complex traits in general. Lippincott Williams & Wilkins 2023-05-11 2023-06 /pmc/articles/PMC10284136/ /pubmed/37165871 http://dx.doi.org/10.1161/CIRCGEN.120.003249 Text en © 2023 The Authors. https://creativecommons.org/licenses/by/4.0/Circulation: Genomic and Precision Medicine is published on behalf of the American Heart Association, Inc., by Wolters Kluwer Health, Inc. This is an open access article under the terms of the Creative Commons Attribution (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution, and reproduction in any medium, provided that the original work is properly cited. |
spellingShingle | Original Articles Gawronski, Katerina A.B. Bone, William P. Park, YoSon Pashos, Evanthia E. Wenz, Brandon M. Dudek, Max F. Wang, Xiao Yang, Wenli Rader, Daniel J. Musunuru, Kiran Voight, Benjamin F. Brown, Christopher D. Evaluating the Contribution of Cell Type–Specific Alternative Splicing to Variation in Lipid Levels |
title | Evaluating the Contribution of Cell Type–Specific Alternative Splicing to Variation in Lipid Levels |
title_full | Evaluating the Contribution of Cell Type–Specific Alternative Splicing to Variation in Lipid Levels |
title_fullStr | Evaluating the Contribution of Cell Type–Specific Alternative Splicing to Variation in Lipid Levels |
title_full_unstemmed | Evaluating the Contribution of Cell Type–Specific Alternative Splicing to Variation in Lipid Levels |
title_short | Evaluating the Contribution of Cell Type–Specific Alternative Splicing to Variation in Lipid Levels |
title_sort | evaluating the contribution of cell type–specific alternative splicing to variation in lipid levels |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10284136/ https://www.ncbi.nlm.nih.gov/pubmed/37165871 http://dx.doi.org/10.1161/CIRCGEN.120.003249 |
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