A blended genome and exome sequencing method captures genetic variation in an unbiased, high-quality, and cost-effective manner
Document Type
Article
Department
Brain and Mind Institute
Abstract
We deployed the Blended Genome Exome (BGE), a DNA library blending approach that generates low pass whole genome (1-4x mean depth) and deep whole exome (30-40x mean depth) data in a single sequencing run. This technology is cost-effective, empowers most genomic discoveries possible with deep whole genome sequencing, and provides an unbiased method to capture the diversity of common SNP variation across the globe. To evaluate this new technology at scale, we applied BGE to sequence >53,000 samples from the Populations Underrepresented in Mental Illness Associations Studies (PUMAS) Project, which included participants across African, African American, and Latin American populations. We evaluated the accuracy of BGE imputed genotypes against raw genotype calls from the Illumina Global Screening Array. All PUMAS cohorts had R2 concordance ≥95% among SNPs with MAF≥1%, and never fell below ≥90% R2 for SNPs with MAF
Publication (Name of Journal)
bioRxiv
DOI
https://doi.org/10.1101/2024.09.06.611689
Recommended Citation
Boltz, T.,
Chu, B.,
Liao, C.,
Sealock, J.,
Ye, R.,
Majara, L.,
Fu, J.,
Service, S.,
Zhan, L.,
Atwoli, L.
(2024). A blended genome and exome sequencing method captures genetic variation in an unbiased, high-quality, and cost-effective manner. bioRxiv, 1-23.
Available at:
https://ecommons.aku.edu/bmi/436