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Haplotype-resolved and integrated genome analysis of the cancer cell line HepG2

View ORCID ProfileBo Zhou, View ORCID ProfileSteve S. Ho, Stephanie U. Greer, View ORCID ProfileNoah Spies, View ORCID ProfileJohn M. Bell, View ORCID ProfileXianglong Zhang, View ORCID ProfileXiaowei Zhu, View ORCID ProfileJoseph G. Arthur, View ORCID ProfileSeunggyu Byeon, View ORCID ProfileReenal Pattni, Ishan Saha, Yiling Huang, View ORCID ProfileGiltae Song, View ORCID ProfileDimitri Perrin, Wing H. Wong, Hanlee P. Ji, View ORCID ProfileAlexej Abyzov, View ORCID ProfileAlexander E. Urban
doi: https://doi.org/10.1101/378497
Bo Zhou
1Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA
2Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
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Steve S. Ho
1Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA
2Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
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Stephanie U. Greer
3Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, California 94305, USA
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Noah Spies
2Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
4Department of Pathology, Stanford University School of Medicine, Stanford, California 94305, USA
5Genome-scale Measurements Group, National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
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John M. Bell
6Stanford Genome Technology Center, Stanford University, Palo Alto, California 94304, USA
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Xianglong Zhang
1Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA
2Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
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Xiaowei Zhu
1Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA
2Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
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Joseph G. Arthur
7Department of Statistics, Stanford University, Stanford, California 94305, USA
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Seunggyu Byeon
8School of Computer Science and Engineering, College of Engineering, Pusan National University, Busan 46241, South Korea
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Reenal Pattni
1Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA
2Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
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Ishan Saha
2Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
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Yiling Huang
1Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA
2Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
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Giltae Song
8School of Computer Science and Engineering, College of Engineering, Pusan National University, Busan 46241, South Korea
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Dimitri Perrin
9Science and Engineering Faculty, Queensland University of Technology, Brisbane, QLD 4001, Australia
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Wing H. Wong
7Department of Statistics, Stanford University, Stanford, California 94305, USA
10Department of Biomedical Data Science, Bio-X Program, Stanford University, Stanford, California 94305, USA
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Hanlee P. Ji
3Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, California 94305, USA
6Stanford Genome Technology Center, Stanford University, Palo Alto, California 94304, USA
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Alexej Abyzov
11Department of Health Sciences Research, Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota 55905, USA
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Alexander E. Urban
1Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA
2Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
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  • For correspondence: aeurban@stanford.edu
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SUMMARY

The HepG2 cancer cell line is one of the most widely-used biomedical research and one of the main cell lines of ENCODE. Vast numbers of functional genomics and epigenomics datasets have been produced to characterize its biology. However, the correct interpretation such data requires an understanding of the cell line’s genome sequence and genome structure. Using a variety of sequencing and analysis methods, we identified a wide spectrum of HepG2 genome characteristics: copy numbers of chromosomal segments, SNVs and Indels (corrected for aneuploidy), phased haplotypes extending to entire chromosome arms, loss of heterozygosity, retrotransposon insertions, structural variants (SVs) including complex and somatic genomic rearrangements. We also identified allele-specific expression and DNA methylation genome-wide and assembled an allele-specific CRISPR/Cas9 targeting map.

SIGNIFICANCE Haplotype-resolved and comprehensive whole-genome analysis of a widely-used cell line for cancer research and ENCODE, HepG2, serves as an essential resource for unlocking complex cancer gene regulation using a genome-integrated framework and also provides genomic context for the analysis of ~1,000 functional datasets to date on ENCODE for biological discovery. We also demonstrate how deeper insights into genomic regulatory complexity are gained by adopting a genome-integrated framework.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted November 08, 2018.
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Haplotype-resolved and integrated genome analysis of the cancer cell line HepG2
Bo Zhou, Steve S. Ho, Stephanie U. Greer, Noah Spies, John M. Bell, Xianglong Zhang, Xiaowei Zhu, Joseph G. Arthur, Seunggyu Byeon, Reenal Pattni, Ishan Saha, Yiling Huang, Giltae Song, Dimitri Perrin, Wing H. Wong, Hanlee P. Ji, Alexej Abyzov, Alexander E. Urban
bioRxiv 378497; doi: https://doi.org/10.1101/378497
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Haplotype-resolved and integrated genome analysis of the cancer cell line HepG2
Bo Zhou, Steve S. Ho, Stephanie U. Greer, Noah Spies, John M. Bell, Xianglong Zhang, Xiaowei Zhu, Joseph G. Arthur, Seunggyu Byeon, Reenal Pattni, Ishan Saha, Yiling Huang, Giltae Song, Dimitri Perrin, Wing H. Wong, Hanlee P. Ji, Alexej Abyzov, Alexander E. Urban
bioRxiv 378497; doi: https://doi.org/10.1101/378497

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