Large, Diverse Population Cohorts of hiPSCs and Derived Hepatocyte-like Cells Reveal Functional Genetic Variation at Blood Lipid-Associated Loci

Cell Stem Cell

Volumn 20, Issue 4, 2017, Pages 558-570.e10

  Pashos, Evanthia E ^a,b   Park, YoSon ^a   Wang, Xiao ^a   Raghavan, Avanthi ^c   Yang, Wenli ^a   Abbey, Deepti ^a,b   Peters, Derek T ^c   Arbelaez, Juan ^a   Hernandez, Mayda ^a,b   Kuperwasser, Nicolas ^c   Li, Wenjun ^a   Lian, Zhaorui ^a   Liu, Ying ^a   Lv, Wenjian ^a   Lytle Gabbin, Stacey L ^a,b   Marchadier, Dawn H ^a,b   Rogov, Peter ^d   Shi, Jianting ^a   Slovik, Katherine J ^a   Stylianou, Ioannis M ^a,b   Wang, Li ^d   Yan, Ruilan ^a   Zhang, Xiaolan ^d   Kathiresan, Sekar ^c,d,e   Duncan, Stephen A ^f   Mikkelsen, Tarjei S ^d   Morrisey, Edward E ^a   Rader, Daniel J ^a,b   Brown, Christopher D ^a   Musunuru, Kiran ^a,b   more..

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

^c HARVARD MEDICAL SCHOOL   (United States)

^d BROAD INSTITUTE OF MIT AND HARVARD   (United States)

^e MASSACHUSETTS GENERAL HOSPITAL   (United States)

^f MEDICAL UNIVERSITY OF SOUTH CAROLINA   (United States)

Author keywords

Cas9; CRISPR; expression quantitative trait loci; genetics; genome wide association studies; genomics; induced pluripotent stem cells

Indexed keywords

ALBUMIN; APOLIPOPROTEIN B; HIGH DENSITY LIPOPROTEIN CHOLESTEROL; LIPID; LOW DENSITY LIPOPROTEIN CHOLESTEROL; TRIACYLGLYCEROL;

ACAA2 GENE; ANGPTL3 GENE; ANIMAL CELL; ANIMAL EXPERIMENT; ARTICLE; CHOLESTEROL BLOOD LEVEL; CLUSTERED REGULARLY INTERSPACED SHORT PALINDROMIC REPEAT; CPNE1 GENE; DOCK7 GENE; GENE EXPRESSION; GENE OVEREXPRESSION; GENETIC VARIATION; GENOME-WIDE ASSOCIATION STUDY; GENOTYPE; HUMAN; HUMAN CELL; INDUCED PLURIPOTENT STEM CELL; LIPID BLOOD LEVEL; LIPID METABOLISM; LIVER CELL; MAJOR CLINICAL STUDY; MOUSE; NONHUMAN; PRIORITY JOURNAL; QUANTITATIVE TRAIT LOCUS; RNA SEQUENCE; SINGLE NUCLEOTIDE POLYMORPHISM; TRIACYLGLYCEROL BLOOD LEVEL; UBE2L3 GENE; VKORC1 GENE; ANIMAL; ANTIBODY SPECIFICITY; BLOOD; COHORT ANALYSIS; CYTOLOGY; GENE EXPRESSION PROFILING; GENE LOCUS; GENETIC PREDISPOSITION; GENETICS; LIVER; METABOLISM; NUCLEOTIDE SEQUENCE;

ANIMALS; BASE SEQUENCE; COHORT STUDIES; GENE EXPRESSION PROFILING; GENETIC LOCI; GENETIC PREDISPOSITION TO DISEASE; GENETIC VARIATION; GENOME-WIDE ASSOCIATION STUDY; HEPATOCYTES; HUMANS; INDUCED PLURIPOTENT STEM CELLS; LIPID METABOLISM; LIPIDS; LIVER; MICE; ORGAN SPECIFICITY; POLYMORPHISM, SINGLE NUCLEOTIDE; QUANTITATIVE TRAIT LOCI;

EID: 85017182988     PISSN: 19345909     EISSN: 18759777     Source Type: Journal    
DOI: 10.1016/j.stem.2017.03.017     Document Type: Article

References (45)

1. Aguet, F., Brown, A.A., Castel, S., Davis, J.R., Mohammadi, P., Segre, A.V., Zappala, Z., Abell, N.S., Fresard, L., Gamazon, E.R., et al. Local genetic effects on gene expression across 44 human tissues. bioRxiv, 2016, 10.1101/074450.
2. Andrews, S. (2010). FastQC: a quality control tool for high throughput sequence data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc.
3. Bass, A.J., Storey, J.D., Dabney, A., and Robinson, D. (2015). qvalue: Q-value estimation for false discovery rate control. https://github.com/jdstorey/qvalue.
4. Benjamini, Y., Hochberg, Y., Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Series B Stat. Methodol. 57 (1995), 289–300.
5. Burkhardt, R., Toh, S.A., Lagor, W.R., Birkeland, A., Levin, M., Li, X., Robblee, M., Fedorov, V.D., Yamamoto, M., Satoh, T., et al. Trib1 is a lipid- and myocardial infarction-associated gene that regulates hepatic lipogenesis and VLDL production in mice. J. Clin. Invest. 120 (2010), 4410–4414.
6. Cai, J., DeLaForest, A., Fisher, J., Urick, A., Wagner, T., Twaroski, K., Cayo, M., Nagaoka, M., Duncan, S.A., Protocol for directed differentiation of human pluripotent stem cells toward a hepatocyte fate. StemBook, 2012, Harvard Stem Cell Institute.
7. Carcamo-Orive, I., Hoffman, G.E., Cundiff, P., Beckmann, N.D., D'Souza, S.L., Knowles, J.W., Patel, A., Papatsenko, D., Abbasi, F., Reaven, G.M., et al. Analysis of transcriptional variability in a large human iPSC library reveals genetic and non-genetic determinants of heterogeneity. Cell Stem Cell 20 (2017), 518–532 this issue.
8. Chen, J., Bardes, E.E., Aronow, B.J., Jegga, A.G., ToppGene Suite for gene list enrichment analysis and candidate gene prioritization. Nucleic Acids Res., 37, 2009 W305–11.
9. Chen, B., Gilbert, L.A., Cimini, B.A., Schnitzbauer, J., Zhang, W., Li, G.W., Park, J., Blackburn, E.H., Weissman, J.S., Qi, L.S., Huang, B., Dynamic imaging of genomic loci in living human cells by an optimized CRISPR/Cas system. Cell 155 (2013), 1479–1491.
10. Choi, J., Lee, S., Mallard, W., Clement, K., Tagliazucchi, G.M., Lim, H., Choi, I.Y., Ferrari, F., Tsankov, A.M., Pop, R., et al. A comparison of genetically matched cell lines reveals the equivalence of human iPSCs and ESCs. Nat. Biotechnol. 33 (2015), 1173–1181.
11. Delaneau, O., Zagury, J.F., Marchini, J., Improved whole-chromosome phasing for disease and population genetic studies. Nat. Methods 10 (2013), 5–6.
12. Dobin, A., Davis, C.A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., Gingeras, T.R., STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29 (2013), 15–21.
13. Giambartolomei, C., Vukcevic, D., Schadt, E.E., Franke, L., Hingorani, A.D., Wallace, C., Plagnol, V., Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. PLoS Genet., 10, 2014, e1004383.
14. Gilbert, L.A., Larson, M.H., Morsut, L., Liu, Z., Brar, G.A., Torres, S.E., Stern-Ginossar, N., Brandman, O., Whitehead, E.H., Doudna, J.A., et al. CRISPR-mediated modular RNA-guided regulation of transcription in eukaryotes. Cell 154 (2013), 442–451.
15. GTEx Consortium. Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 348 (2015), 648–660.
16. Han, B., Eskin, E., Interpreting meta-analyses of genome-wide association studies. PLoS Genet., 8, 2012, e1002555.
17. Harvey, C.T., Moyerbrailean, G.A., Davis, G.O., Wen, X., Luca, F., Pique-Regi, R., QuASAR: quantitative allele-specific analysis of reads. Bioinformatics 31 (2015), 1235–1242.
18. Howie, B.N., Donnelly, P., Marchini, J., A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet., 5, 2009, e1000529.
19. Innocenti, F., Cooper, G.M., Stanaway, I.B., Gamazon, E.R., Smith, J.D., Mirkov, S., Ramirez, J., Liu, W., Lin, Y.S., Moloney, C., et al. Identification, replication, and functional fine-mapping of expression quantitative trait loci in primary human liver tissue. PLoS Genet., 7, 2011, e1002078.
20. Koishi, R., Ando, Y., Ono, M., Shimamura, M., Yasumo, H., Fujiwara, T., Horikoshi, H., Furukawa, H., Angptl3 regulates lipid metabolism in mice. Nat. Genet. 30 (2002), 151–157.
21. Krueger, F. (2012). Trim Galore! http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/.
22. Li, B., Dewey, C.N., RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics, 12, 2011, 323.
23. Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., 1000 Genome Project Data Processing Subgroup. The sequence alignment/map format and SAMtools. Bioinformatics 25 (2009), 2078–2079.
24. Love, M.I., Huber, W., Anders, S., Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol., 15, 2014, 550.
25. Maller, J.B., McVean, G., Byrnes, J., Vukcevic, D., Palin, K., Su, Z., Howson, J.M., Auton, A., Myers, S., Morris, A., et al., Wellcome Trust Case Control Consortium. Bayesian refinement of association signals for 14 loci in 3 common diseases. Nat. Genet. 44 (2012), 1294–1301.
26. Manolio, T.A., Genomewide association studies and assessment of the risk of disease. N. Engl. J. Med. 363 (2010), 166–176.
27. Melnikov, A., Murugan, A., Zhang, X., Tesileanu, T., Wang, L., Rogov, P., Feizi, S., Gnirke, A., Callan, C.G. Jr., Kinney, J.B., et al. Systematic dissection and optimization of inducible enhancers in human cells using a massively parallel reporter assay. Nat. Biotechnol. 30 (2012), 271–277.
28. Musunuru, K., Genome editing of human pluripotent stem cells to generate human cellular disease models. Dis. Model. Mech. 6 (2013), 896–904.
29. Musunuru, K., Pirruccello, J.P., Do, R., Peloso, G.M., Guiducci, C., Sougnez, C., Garimella, K.V., Fisher, S., Abreu, J., Barry, A.J., et al. Exome sequencing, ANGPTL3 mutations, and familial combined hypolipidemia. N. Engl. J. Med. 363 (2010), 2220–2227.
30. Patwardhan, R.P., Hiatt, J.B., Witten, D.M., Kim, M.J., Smith, R.P., May, D., Lee, C., Andrie, J.M., Lee, S.I., Cooper, G.M., et al. Massively parallel functional dissection of mammalian enhancers in vivo. Nat. Biotechnol. 30 (2012), 265–270.
31. Price, A.L., Patterson, N.J., Plenge, R.M., Weinblatt, M.E., Shadick, N.A., Reich, D., Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38 (2006), 904–909.
32. Qi, L.S., Larson, M.H., Gilbert, L.A., Doudna, J.A., Weissman, J.S., Arkin, A.P., Lim, W.A., Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression. Cell 152 (2013), 1173–1183.
33. Schwartz, R.E., Fleming, H.E., Khetani, S.R., Bhatia, S.N., Pluripotent stem cell-derived hepatocyte-like cells. Biotechnol. Adv. 32 (2014), 504–513.
34. Shabalin, A.A., Matrix eQTL: ultra fast eQTL analysis via large matrix operations. Bioinformatics 28 (2012), 1353–1358.
35. Soldner, F., Stelzer, Y., Shivalila, C.S., Abraham, B.J., Latourelle, J.C., Barrasa, M.I., Goldmann, J., Myers, R.H., Young, R.A., Jaenisch, R., Parkinson-associated risk variant in distal enhancer of α-synuclein modulates target gene expression. Nature 533 (2016), 95–99.
36. Stacklies, W., Redestig, H., Scholz, M., Walther, D., Selbig, J., pcaMethods–a bioconductor package providing PCA methods for incomplete data. Bioinformatics 23 (2007), 1164–1167.
37. Stegle, O., Parts, L., Durbin, R., Winn, J., A Bayesian framework to account for complex non-genetic factors in gene expression levels greatly increases power in eQTL studies. PLoS Comput. Biol., 6, 2010, e1000770.
38. Sul, J.H., Han, B., Ye, C., Choi, T., Eskin, E., Effectively identifying eQTLs from multiple tissues by combining mixed model and meta-analytic approaches. PLoS Genet., 9, 2013, e1003491.
39. Teslovich, T.M., Musunuru, K., Smith, A.V., Edmondson, A.C., Stylianou, I.M., Koseki, M., Pirruccello, J.P., Ripatti, S., Chasman, D.I., Willer, C.J., et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature 466 (2010), 707–713.
40. Tewhey, R., Kotliar, D., Park, D.S., Liu, B., Winnicki, S., Reilly, S.K., Andersen, K.G., Mikkelsen, T.S., Lander, E.S., Schaffner, S.F., Sabeti, P.C., Direct identification of hundreds of expression-modulating variants using a multiplexed reporter assay. Cell 165 (2016), 1519–1529.
41. Ulirsch, J.C., Nandakumar, S.K., Wang, L., Giani, F.C., Zhang, X., Rogov, P., Melnikov, A., McDonel, P., Do, R., Mikkelsen, T.S., Sankaran, V.G., Systematic functional dissection of common genetic variation affecting red blood cell traits. Cell 165 (2016), 1530–1545.
42. van de Geijn, B., McVicker, G., Gilad, Y., Pritchard, J.K., WASP: allele-specific software for robust molecular quantitative trait locus discovery. Nat. Methods 12 (2015), 1061–1063.
43. Willer, C.J., Schmidt, E.M., Sengupta, S., Peloso, G.M., Gustafsson, S., Kanoni, S., Ganna, A., Chen, J., Buchkovich, M.L., Mora, S., et al., Global Lipids Genetics Consortium. Discovery and refinement of loci associated with lipid levels. Nat. Genet. 45 (2013), 1274–1283.
44. Yang, W., Mills, J.A., Sullivan, S., Liu, Y., French, D.L., Gadue, P., iPSC reprogramming from human peripheral blood using Sendai virus mediated gene transfer. StemBook, 2012, Harvard Stem Cell Institute.
45. Zhu, H., Lensch, M.W., Cahan, P., Daley, G.Q., Investigating monogenic and complex diseases with pluripotent stem cells. Nat. Rev. Genet. 12 (2011), 266–275.