CAUSEL: an epigenome- and genome-editing pipeline for establishing function of noncoding GWAS variants (original) (raw)

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References

1. Hindorff, L.A. et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl. Acad. Sci. USA 106, 9362–9367 (2009).
   Article CAS Google Scholar
2. Cookson, W., Liang, L., Abecasis, G., Moffatt, M. & Lathrop, M. Mapping complex disease traits with global gene expression. Nat. Rev. Genet. 10, 184–194 (2009).
   Article CAS Google Scholar
3. Nicolae, D.L. et al. Trait-associated SNPs are more likely to be eQTLs: annotation to enhance discovery from GWAS. PLoS Genet. 6, e1000888 (2010).
   Article Google Scholar
4. The ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).
5. Maurano, M.T. et al. Systematic localization of common disease-associated variation in regulatory DNA. Science 337, 1190–1195 (2012).
   Article CAS Google Scholar
6. Bauer, D.E. et al. An erythroid enhancer of BCL11A subject to genetic variation determines fetal hemoglobin level. Science 342, 253–257 (2013).
   Article CAS Google Scholar
7. Ochiai, H. et al. TALEN-mediated single-base-pair editing identification of an intergenic mutation upstream of BUB1B as causative of PCS (MVA) syndrome. Proc. Natl. Acad. Sci. USA 111, 1461–1466 (2014).
   Article CAS Google Scholar
8. Albert, F.W. & Kruglyak, L. The role of regulatory variation in complex traits and disease. Nat. Rev. Genet. 16, 197–212 (2015).
   Article CAS Google Scholar
9. Knight, J.C. Approaches for establishing the function of regulatory genetic variants involved in disease. Genome Med 6, 92 (2014).
   Article Google Scholar
10. Hsu, P.D., Lander, E.S. & Zhang, F. Development and applications of CRISPR-Cas9 for genome engineering. Cell 157, 1262–1278 (2014).
    Article CAS Google Scholar
11. Takata, R. et al. Genome-wide association study identifies five new susceptibility loci for prostate cancer in the Japanese population. Nat. Genet. 42, 751–754 (2010).
    Article CAS Google Scholar
12. Huang, Q. et al. A prostate cancer susceptibility allele at 6q22 increases RFX6 expression by modulating HOXB13 chromatin binding. Nat. Genet. 46, 126–135 (2014).
    Article CAS Google Scholar
13. Han, Y. et al. Integration of multiethnic fine-mapping and genomic annotation to prioritize candidate functional SNPs at prostate cancer susceptibility regions. Hum. Mol. Genet. 24, 5603–5618 (2015).
    Article CAS Google Scholar
14. Joung, J.K. & Sander, J.D. TALENs: a widely applicable technology for targeted genome editing. Nat. Rev. Mol. Cell Biol. 14, 49–55 (2013).
    Article CAS Google Scholar
15. Mendenhall, E.M. et al. Locus-specific editing of histone modifications at endogenous enhancers. Nat. Biotechnol. 31, 1133–1136 (2013).
    Article CAS Google Scholar
16. Maeder, M.L. et al. Robust, synergistic regulation of human gene expression using TALE activators. Nat. Methods 10, 243–245 (2013).
    Article CAS Google Scholar
17. Reyon, D. et al. FLASH assembly of TALENs for high-throughput genome editing. Nat. Biotechnol. 30, 460–465 (2012).
    Article CAS Google Scholar
18. Kim, Y., Kweon, J. & Kim, J.S. TALENs and ZFNs are associated with different mutation signatures. Nat. Methods 10, 185 (2013).
    Article Google Scholar
19. Joung, J.K. Unwanted mutations: Standards needed for gene-editing errors. Nature 523, 158 (2015).
    Article CAS Google Scholar
20. Guilinger, J.P. et al. Broad specificity profiling of TALENs results in engineered nucleases with improved DNA-cleavage specificity. Nat. Methods 11, 429–435 (2014).
    Article CAS Google Scholar
21. Hockemeyer, D. et al. Genetic engineering of human pluripotent cells using TALE nucleases. Nat. Biotechnol. 29, 731–734 (2011).
    Article CAS Google Scholar
22. Kim, D., et al. Digenome-seq: genome-wide profiling of CRISPR-Cas9 off-target effects in human cells. Nat. Methods 12, 237–243 (2015).
    Article CAS Google Scholar
23. Wang, X. et al. Unbiased detection of off-target cleavage by CRISPR-Cas9 and TALENs using integrase-defective lentiviral vectors. Nat. Biotechnol. 33, 175–178 (2015).
    Article CAS Google Scholar
24. Tsai, S.Q. et al. GUIDE-seq enables genome-wide profiling of off-target cleavage by CRISPR-Cas nucleases. Nat. Biotechnol. 33, 187–197 (2015).
    Article CAS Google Scholar
25. Frock, R.L. et al. Genome-wide detection of DNA double-stranded breaks induced by engineered nucleases. Nat. Biotechnol. 33, 179–186 (2015).
    Article CAS Google Scholar
26. Duggan, D. et al. Two genome-wide association studies of aggressive prostate cancer implicate putative prostate tumor suppressor gene DAB2IP. J. Natl. Cancer Inst. 99, 1836–1844 (2007).
    Article CAS Google Scholar
27. Schumacher, F.R. et al. Genome-wide association study identifies new prostate cancer susceptibility loci. Hum. Mol. Genet. 20, 3867–3875 (2011).
    Article CAS Google Scholar
28. Gohagan, J.K., Prorok, P.C., Hayes, R.B. & Kramer, B.S. The Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial of the National Cancer Institute: history, organization, and status. Control. Clin. Trials 21, 251S–272S (2000).
    Article CAS Google Scholar
29. Kolonel, L.N. et al. A multiethnic cohort in Hawaii and Los Angeles: baseline characteristics. Am. J. Epidemiol. 151, 346–357 (2000).
    Article CAS Google Scholar
30. Cook, M.B. et al. A genome-wide association study of prostate cancer in West African men. Hum. Genet. 133, 509–521 (2014).
    Article CAS Google Scholar
31. Cheng, I. et al. Evaluating genetic risk for prostate cancer among Japanese and Latinos. Cancer Epidemiol. Biomarkers Prev. 21, 2048–2058 (2012).
    Article CAS Google Scholar
32. Akamatsu, S. et al. Common variants at 11q12, 10q26 and 3p11.2 are associated with prostate cancer susceptibility in Japanese. Nat. Genet. 44, 426–429 (2012).
    Article CAS Google Scholar
33. 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, e1000529 (2009).
    Article Google Scholar
34. Pruim, R.J. et al. LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics 26, 2336–2337 (2010).
    Article CAS Google Scholar
35. Reyon, D. et al. Engineering customized TALE nucleases (TALENs) and TALE transcription factors by fast ligation-based automatable solid-phase high-throughput (FLASH) assembly. Curr. Protoc. Mol. Biol. 103, 12.16.1–12.16.18 (2013).
    Google Scholar
36. Chen, F. et al. High-frequency genome editing using ssDNA oligonucleotides with zinc-finger nucleases. Nat. Methods 8, 753–755 (2011).
    Article CAS Google Scholar
37. R Core Team. R: A language and environment for statistical computing. (R Foundation for Statistical Computing, 2015).
38. Kim, D. et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 14, R36 (2013).
    Article Google Scholar

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Acknowledgements

M.L.F. and J.K.J. were supported by US National Institutes of Health (NIH) grant no. R01 GM107427; J.K.J. was supported by a NIH Director's Pioneer Award (DP1 GM105378) and The Jim and Ann Orr Massachusetts General Hospital Research Scholar Award; M.L.F. is supported by the Prostate Cancer Foundation (Challenge Award), the US NIH grant no. R01CA193910, and the H.L. Snyder Medical Foundation. The scientific development and funding for this project were in part supported by the US National Cancer Institute GAME-ON Post-GWAS Initiative (U19CA148112 and U19CA148537). K.L. is supported by a K99/R00 grant from the National Cancer Institute (grant no. 1K99CA184415-01). I.C. is supported by grants from the Hungarian National Research, Development and Innovation Office (KMR-12-1-2012-0216) and the Hungarian National Research Fund (OTKA103244). Z.S. is supported by the Breast Cancer Research Foundation and the Széchenyi Progam, Hungary (KTIA_NAP_13-2014-0021). This project was also supported by a Program Project Development Grant from the Ovarian Cancer Research Fund (K.L. and S.A.G). We thank the Dana-Farber Cancer Institute Molecular Biology Core Facility for Sanger sequencing and Illumina high-throughput sequencing. We thank C. Nicolet at the University of Southern California Epigenome Center Core for RNA-seq services and M. Li at the University of Southern California Norris Medical Library Bioinformatics Center, who provided assistance with the analysis of RNA-seq data.

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Author notes

1. Kate Lawrenson
   Present address: Present address: Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA,
2. Yanfang Fu
   Present address: Present address: Cell and Gene Therapy, Biogen, Cambridge, Massachusetts, USA.,
3. Sándor Spisák, Kate Lawrenson and Yanfang Fu: These authors contributed equally to this work.
4. Center for Cancer Prevention and Translational Genomics at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.

Authors and Affiliations

1. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
   Sándor Spisák, Ji-Heui Seo, Romina Lenci, Qiyuan Li, Viktória Tisza, Matthew Chabot, Mark Pomerantz & Matthew L Freedman
2. Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
   Sándor Spisák, Ji-Heui Seo, Romina Lenci, Qiyuan Li & Matthew L Freedman
3. Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
   Kate Lawrenson, Christopher Haiman, Ying Han & Simon A Gayther
4. Molecular Pathology Unit, Massachusetts General Hospital, Charlestown, Massachusetts, USA
   Yanfang Fu, Rebecca T Cottman & J Keith Joung
5. Center for Cancer Research, Massachusetts General Hospital, Charlestown, Massachusetts, USA
   Yanfang Fu, Rebecca T Cottman & J Keith Joung
6. Center for Computational and Integrative Biology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
   Yanfang Fu, Rebecca T Cottman & J Keith Joung
7. Department of Pathology, Harvard Medical School, Boston, Massachusetts, USA
   Yanfang Fu & J Keith Joung
8. Department of Physics of Complex Systems, Eötvös Loránd University, Budapest, Hungary
   István Csabai
9. Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, Massachusetts, USA
   Rebecca T Cottman & J Keith Joung
10. Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA
    Christopher Haiman
11. Medical College, Xiamen University, Xiamen, China
    Qiyuan Li
12. Computational Health Informatics Program (CHIP), Boston Children's Hospital, Boston, Massachusetts, USA
    Viktória Tisza & Zoltán Szállási
13. Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark
    Zoltán Szállási
14. Second Department of Pathology, Semmelweis University, Budapest, Hungary
    Zoltán Szállási
15. Molecular Biology Core Facilities at Dana-Farber Cancer Institute, Boston, Massachusetts, USA
    Zachery T Herbert
16. Department of Animal Hygiene, Szent István University, Budapest, Hungary
    Norbert Solymosi
17. The Eli and Edythe L. Broad Institute, Cambridge, Massachusetts, USA
    Simon A Gayther & Matthew L Freedman

Authors

1. Sándor Spisák
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2. Kate Lawrenson
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3. Yanfang Fu
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4. István Csabai
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5. Rebecca T Cottman
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6. Ji-Heui Seo
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7. Christopher Haiman
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8. Ying Han
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9. Romina Lenci
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10. Qiyuan Li
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11. Viktória Tisza
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12. Zoltán Szállási
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13. Zachery T Herbert
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14. Matthew Chabot
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15. Mark Pomerantz
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16. Norbert Solymosi
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17. Simon A Gayther
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18. J Keith Joung
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19. Matthew L Freedman
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Consortia

The GAME-ON/ELLIPSE Consortium

Contributions

S.S., K.L. and Y.F. designed and performed experiments, J.K.J. and M.L.F. designed experiments, R.T.C., J.-H.S., R.L., V.T., M.C. and M.P. performed experiments, S.S., I.C. and M.L.F. developed the sequencing pipeline, S.S., K.L., Y.F., Y.H., Q.L., I.C., Z.T.H. and N.S. analyzed the data, S.S., K.L., I.C., J.K.J. and M.L.F. wrote the manuscript, S.S., Y.F., R.T.C., S.A.G., J.K.J. and M.L.F. revised the manuscript, C.H., Z.S., Z.T.H. and S.A.G. provided technical support and conceptual advice. The GAME-ON/ELLIPSE Consortium provided early access to fine-mapping data.

Corresponding authors

Correspondence toSimon A Gayther, J Keith Joung or Matthew L Freedman.

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Competing interests

J.K.J. is a consultant for Horizon Discovery. J.K.J. has financial interests in Editas Medicine, Hera Testing Laboratories, Poseida Therapeutics, and Transposagen Biopharmaceuticals. J.K.J.'s interests were reviewed and are managed by Massachusetts General Hospital and Partners HealthCare in accordance with their conflict of interest policies.

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A complete list of all consortium members is provided in the Supplementary Note.

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Spisák, S., Lawrenson, K., Fu, Y. et al. CAUSEL: an epigenome- and genome-editing pipeline for establishing function of noncoding GWAS variants.Nat Med 21, 1357–1363 (2015). https://doi.org/10.1038/nm.3975

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• Received: 11 August 2015
• Accepted: 17 September 2015
• Published: 23 September 2015
• Issue Date: November 2015
• DOI: https://doi.org/10.1038/nm.3975