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      Using deep whole genome sequence, transcriptome and epigenome data to characterize the mutational burden of induced pluripotent stem cells

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          Abstract

          To understand the mutational burden of human induced pluripotent stem cells (iPSCs), we whole genome sequenced 18 fibroblast-derived iPSC lines and identified different classes of somatic mutations based on structure, origin and frequency. Copy number alterations affected 295 kb in each sample and strongly impacted gene expression. UV-damage mutations were present in ~45% of the iPSCs and accounted for most of the observed heterogeneity in mutation rates across lines. Subclonal mutations (not present in all iPSCs within a line) composed 10% of point mutations, and compared with clonal variants, showed an enrichment in active promoters and increased association with altered gene expression. Our study shows that, by combining WGS, transcriptome and epigenome data, we can understand the mutational burden of each iPSC line on an individual basis and suggests that this information could be used to prioritize iPSC lines for models of specific human diseases and/or transplantation therapy.

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          Author and article information

          Journal
          bioRxiv
          May 30 2018
          Article
          10.1101/334870
          © 2018
          Product

          Human biology, Genetics

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