LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

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

Photo from wikipedia

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… Click to show full abstract

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.

Keywords: genomes project; cell; 1000 genomes; novo variant; mutation; variant calling

Journal Title: Human Mutation
Year Published: 2022

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.