de novo variant calling identifies cancer mutation signatures in the 1000 Genomes Project

Detection of de novo variants (DNVs) is critical for studies of disease‐related variation and mutation rates. To accelerate DNV calling, we developed a graphics processing units‐based workflow. We applied our workflow to whole‐genome sequencing data from three parent‐child sequenced cohorts includin...

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Bibliographic Details
Published in:	Human mutation Vol. 43; no. 12; pp. 1979 - 1993
Main Authors:	Ng, Jeffrey K., Vats, Pankaj, Fritz‐Waters, Elyn, Sarkar, Stephanie, Sams, Eleanor I., Padhi, Evin M., Payne, Zachary L., Leonard, Shawn, West, Marc A., Prince, Chandler, Trani, Lee, Jansen, Marshall, Vacek, George, Samadi, Mehrzad, Harkins, Timothy T., Pohl, Craig, Turner, Tychele N.
Format:	Journal Article
Language:	English
Published:	United States Hindawi Limited 01-12-2022 John Wiley and Sons Inc
Subjects:	1000 Genomes Project Alleles Autism cell line artifacts Chromosomes CpG islands de novo variants DNA repair Genomes GPU accelerated workflow Humans Lymphoblastoid cell lines Lymphoma Mutation Mutation rates Neoplasms - genetics Nucleotide sequence Saliva Simons Simplex Collection Whole Genome Sequencing de novo variants Simons Simplex Collection 1000 Genomes Project GPU accelerated workflow cell line artifacts
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Summary:	Detection of de novo variants (DNVs) is critical for studies of disease‐related variation and mutation rates. To accelerate DNV calling, we developed a graphics processing units‐based workflow. We applied our workflow to whole‐genome sequencing data from three parent‐child sequenced cohorts including the Simons Simplex Collection (SSC), Simons Foundation Powering Autism Research (SPARK), and the 1000 Genomes Project (1000G) that were sequenced using DNA from blood, saliva, and lymphoblastoid cell lines (LCLs), respectively. The SSC and SPARK DNV callsets were within expectations for number of DNVs, percent at CpG sites, phasing to the paternal chromosome of origin, and average allele balance. However, the 1000G DNV callset was not within expectations and contained excessive DNVs that are likely cell line artifacts. Mutation signature analysis revealed 30% of 1000G DNV signatures matched B‐cell lymphoma. Furthermore, we found variants in DNA repair genes and at Clinvar pathogenic or likely‐pathogenic sites and significant excess of protein‐coding DNVs in IGLL5; a gene known to be involved in B‐cell lymphomas. Our study provides a new rapid DNV caller for the field and elucidates important implications of using sequencing data from LCLs for reference building and disease‐related projects.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1059-7794 1098-1004
DOI:	10.1002/humu.24455