Evaluating the Contribution of Cell Type-Specific Alternative Splicing to Variation in Lipid Levels.

Autor:	Gawronski KAB; Cell and Molecular Biology Graduate Group (K.A.B.G., B.M.W.), University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA., Bone WP; Genomics and Computational Biology Graduate Group (W.P.B., M.F.D.), University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA., Park Y; Department of Genetics (Y.P., E.E.P., D.J.R., K.M., B.F.V., C.D.B.), University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA., Pashos EE; Department of Genetics (Y.P., E.E.P., D.J.R., K.M., B.F.V., C.D.B.), University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA., Wenz BM; Cell and Molecular Biology Graduate Group (K.A.B.G., B.M.W.), University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA., Dudek MF; Genomics and Computational Biology Graduate Group (W.P.B., M.F.D.), University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA., Wang X; Cardiovascular Institute (X.W.), University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA., Yang W; Institute for Regenerative Medicine (W.Y.), University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA., Rader DJ; Department of Genetics (Y.P., E.E.P., D.J.R., K.M., B.F.V., C.D.B.), University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA.; Department of Medicine (D.J.R., K.M.), University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA.; Division of Translational Medicine & Human Genetics (D.J.R.), University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA., Musunuru K; Department of Genetics (Y.P., E.E.P., D.J.R., K.M., B.F.V., C.D.B.), University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA.; Department of Medicine (D.J.R., K.M.), University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA., Voight BF; Department of Genetics (Y.P., E.E.P., D.J.R., K.M., B.F.V., C.D.B.), University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA.; Department of Systems Pharmacology and Translational Therapeutics (B.F.V.), University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA.; Institute for Translational Medicine and Therapeutics (B.F.V.), University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA., Brown CD; Department of Genetics (Y.P., E.E.P., D.J.R., K.M., B.F.V., C.D.B.), University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA.
Jazyk:	angličtina
Zdroj:	Circulation. Genomic and precision medicine [Circ Genom Precis Med] 2023 Jun; Vol. 16 (3), pp. 248-257. Date of Electronic Publication: 2023 May 11.
DOI:	10.1161/CIRCGEN.120.003249
Abstrakt:	Background: 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. Competing Interests: Disclosures Dr Voight is an associate editor for Circulation: Genomics and Precision Medicine. Dr Pashos was solely affiliated with the University of Pennsylvania at the time of their contribution to this article; their current affiliation is now with Pfizer, Inc. The contents and viewpoints expressed herein and the materials therein reflect the personal opinion of the authors, and cannot be construed as representation of any position or opinion of Pfizer Inc. or any of its subsidiaries. All materials were created at the University of Pennsylvania. The other authors report no conflicts.
Databáze:	MEDLINE
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