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

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.

HAT:de novovariant calling for highly accurate short-read and long-read sequencing data

“…We previously tested HAT on 4,216 trios, with DNA derived from blood, from the Simons Simplex Collection (SSC) (Ng, et al, 2022). Overall, we identified a total of 329,589 DNVs with 78 ± 15 DNVs per individual.…”

“…Short-read WES data for 100 trios from the SPARK collection (SPARK, 2018) were assessed using HAT. Short-read WGS data were assessed from our previous publication in 4,216 trios from the Simons Simplex Collection (Ng, et al, 2022). Highly accurate long-read WGS data for four trios were assessed from our previous publications (Mehinovic, et al, 2022; Sams, et al, 2022).…”

“…The main HAT GitHub repo can be found here: https://github.com/TNTurnerLab/HAT. The SSC WGS data are available as described previously (Ng, et al, 2022). The PB.100 and 9p.100 family datasets are available as described previously (Mehinovic, et al, 2022; Sams, et al, 2022).…”

“…On average, humans have ~40-100 DNVs within their genome. Characteristics of DNVs genome-wide include approximately 20% occur at CpG sites and approximately 75% arise on the paternal chromosome of origin (Ng, et al, 2022). To date, DNV calling and methods for DNV calling have primarily focused on whole-exome sequencing (WES) and whole-genome sequencing (WGS) from short-read technologies (i.e., Illumina) (Allen, et al, 2013; DDD, 2017; Iossifov, et al, 2014; Turner, et al, 2017; Werling, et al, 2018).…”

acorn: an R package forde novovariant analysis

“…We provide test data with acorn, on our acorn GitHub site, consisting of a subset of our DNV dataset from our recent paper [10] (dnms_from_Ng_et_al_2022_Human_Mutation_paper.txt.gz, Supplemental File 1), simulated count data (dnm_count_example.txt, Supplemental Table 1), and simulated parental age data (parental_age_example.txt, Supplemental Table 2). We detail the use of these in the Vignette included with the acorn package.…”