Title |
Large, Diverse Population Cohorts of hiPSCs and Derived Hepatocyte-like Cells Reveal Functional Genetic Variation at Blood Lipid-Associated Loci
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Published in |
Cell Stem Cell, April 2017
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DOI | 10.1016/j.stem.2017.03.017 |
Pubmed ID | |
Authors |
Evanthia E. Pashos, YoSon Park, Xiao Wang, Avanthi Raghavan, Wenli Yang, Deepti Abbey, Derek T. Peters, Juan Arbelaez, Mayda Hernandez, Nicolas Kuperwasser, Wenjun Li, Zhaorui Lian, Ying Liu, Wenjian Lv, Stacey L. Lytle-Gabbin, Dawn H. Marchadier, Peter Rogov, Jianting Shi, Katherine J. Slovik, Ioannis M. Stylianou, Li Wang, Ruilan Yan, Xiaolan Zhang, Sekar Kathiresan, Stephen A. Duncan, Tarjei S. Mikkelsen, Edward E. Morrisey, Daniel J. Rader, Christopher D. Brown, Kiran Musunuru |
Abstract |
Genome-wide association studies have struggled to identify functional genes and variants underlying complex phenotypes. We recruited a multi-ethnic cohort of healthy volunteers (n = 91) and used their tissue to generate induced pluripotent stem cells (iPSCs) and hepatocyte-like cells (HLCs) for genome-wide mapping of expression quantitative trait loci (eQTLs) and allele-specific expression (ASE). We identified many eQTL genes (eGenes) not observed in the comparably sized Genotype-Tissue Expression project's human liver cohort (n = 96). Focusing on blood lipid-associated loci, we performed massively parallel reporter assays to screen candidate functional variants and used genome-edited stem cells, CRISPR interference, and mouse modeling to establish rs2277862-CPNE1, rs10889356-DOCK7, rs10889356-ANGPTL3, and rs10872142-FRK as functional SNP-gene sets. We demonstrated HLC eGenes CPNE1, VKORC1, UBE2L3, and ANGPTL3 and HLC ASE gene ACAA2 to be lipid-functional genes in mouse models. These findings endorse an iPSC-based experimental framework to discover functional variants and genes contributing to complex human traits. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 23 | 51% |
United Kingdom | 2 | 4% |
India | 1 | 2% |
France | 1 | 2% |
Unknown | 18 | 40% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 28 | 62% |
Members of the public | 11 | 24% |
Science communicators (journalists, bloggers, editors) | 4 | 9% |
Practitioners (doctors, other healthcare professionals) | 2 | 4% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 160 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 39 | 24% |
Researcher | 30 | 19% |
Student > Master | 13 | 8% |
Other | 9 | 6% |
Student > Bachelor | 9 | 6% |
Other | 30 | 19% |
Unknown | 30 | 19% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 59 | 37% |
Agricultural and Biological Sciences | 37 | 23% |
Medicine and Dentistry | 13 | 8% |
Computer Science | 4 | 3% |
Pharmacology, Toxicology and Pharmaceutical Science | 4 | 3% |
Other | 10 | 6% |
Unknown | 33 | 21% |