Comprehensive, integrated, and phased whole-genome analysis of the primary ENCODE cell line K562
Steve S. Ho,
Stephanie U. Greer,
John M. Bell,
Joseph G. Arthur,
Michael S. Haney,
Rajini R. Haraksingh,
Hanlee P. Ji,
Wing H. Wong,
Alexander E. Urban
Posted 02 Dec 2017
bioRxiv DOI: 10.1101/192344 (published DOI: 10.1101/gr.234948.118)
Posted 02 Dec 2017
K562 is widely used in biomedical research. It is one of three tier-one cell lines of ENCODE and also most commonly used for large-scale CRISPR/Cas9 screens. Although its functional genomic and epigenomic characteristics have been extensively studied, its genome sequence and genomic structural features have never been comprehensively analyzed. Such information is essential for the correct interpretation and understanding of the vast troves of existing functional genomics and epigenomics data for K562. We performed and integrated deep-coverage whole-genome (short-insert), mate-pair, and linked-read sequencing as well as karyotyping and array CGH analysis to identify a wide spectrum of genome characteristics in K562: copy numbers (CN) of aneuploid chromosome segments at high-resolution, SNVs and Indels (both corrected for CN in aneuploid regions), loss of heterozygosity, mega-base-scale phased haplotypes often spanning entire chromosome arms, structural variants (SVs) including small and large-scale complex SVs and non-reference retrotransposon insertions. Many SVs were phased, assembled, and experimentally validated. We identified multiple allele-specific deletions and duplications within the tumor suppressor gene FHIT. Taking aneuploidy into account, we re-analyzed K562 RNA-seq and whole-genome bisulfite sequencing data for allele-specific expression and allele-specific DNA methylation. We also show examples of how deeper insights into regulatory complexity are gained by integrating genomic variant information and structural context with functional genomics and epigenomics data. Furthermore, using K562 haplotype information, we produced an allele-specific CRISPR targeting map. This comprehensive whole-genome analysis serves as a resource for future studies that utilize K562 as well as a framework for the analysis of other cancer genomes.
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