Nature genetics · 2026

A blended genome and exome sequencing method captures genetic variation in an unbiased and cost-effective manner.

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Boltz Toni A, Chu Benjamin B, DeFelice Matthew, Liao Calwing, Sealock Julia M, Ye Robert, Goldstein Jacqueline I, Majara Lerato, Fu Jack M, Service Susan K, Zhan Lingyu, Medland Sarah E, Chapman Sinéad B, Rubinacci Simone, Grimsby Jonna L, Abebe Tamrat, Alemayehu Melkam, Ashaba Fred K, Atkinson Elizabeth G, Bigdeli Tim B, Bradway Amanda B, Brand Harrison, Chibnik Lori B, DeLuca Samuel, Diaz-Zuluaga Ana M, Fekadu Abebaw, Gatzen Michael, Gelaye Bizu, Gichuru Stella, Gildea Marissa L, Hill Toni C, Huang Hailiang, Hubbard Kalyn M, Injera Wilfred E, James Roxanne, Joloba Moses, Kachulis Christopher, Kalmbach Phillip R, Kamulegeya Rogers, Kigen Gabriel, Kim Soyeon, Koen Nastassja, Kwobah Edith K, Kyebuzibwa Joseph, Lee Seungmo, Lennon Niall J, Lind Penelope A, Lopera-Maya Esteban A, Makale Johnstone, Mangul Serghei, McMahon Justin, Mowlem Pierre, Musinguzi Henry, Mwema Rehema M, Nakasujja Noeline, Newman Carter P, Nkambule Lethukuthula L, O'Neil Conor R, Olivares Ana Maria, Olsen Catherine M, Ongeri Linnet, Parsa Sophie J, Pretorius Adele, Qin Shengying, Ramesar Raj, Reagan Faye L, Sabatti Chiara, Schneider Jacquelyn A, Shiferaw Welelta, Stevens Christine, Stevenson Anne, Stricker Erik, Stroud Rocky E, Tang Jessie, Townsend Megan, Whiteman David, Yohannes Mary T, Yu Mingrui, Yuan Kai, NeuroGAP-Psychosis Study, Akena Dickens, Atwoli Lukoye, Kariuki Symon M, Koenen Karestan C, Newton Charles R J C, Stein Dan J, Teferra Solomon, Zingela Zukiswa, Pato Carlos N, Pato Michele T, Lopez-Jaramillo Carlos, Freimer Nelson B, Ophoff Roel A, Olde Loohuis Loes M, Talkowski Michael E, Neale Benjamin M, Howrigan Daniel P, Martin Alicia R

Аннотация

Here we developed and deployed the blended genome exome (BGE) method, a DNA library approach that generates low-pass whole-genome (1-4× mean depth) and deep whole-exome (30-40× mean depth) data in a single sequencing run. BGE is cost-effective, empowers most genomic discoveries possible with deep whole-genome sequencing and captures global common single-nucleotide polymorphism diversity. We applied BGE to sequence >53,000 samples from the PUMAS Project (Populations Underrepresented in Mental Illness Associations Studies), including African, African American and Latin American populations. Imputed genotypes showed high concordance with Illumina Global Screening Array calls (R2 ≥ 95% for minor allele frequency ≥1%; ≥90% for minor allele frequency <1%), with consistent performance across local ancestries in admixed cohorts. For protein-coding copy number variants, deletions and duplications spanning at least three exons had a positive predicted value of ~90% relative to deep whole-genome data. At ~28% of the cost of deep whole-genome sequencing, BGE provides a scalable, reliable platform to expand genomic discovery and equitable access to sequencing in underrepresented populations.

Предметные рубрики MeSH

Humans Polymorphism, Single Nucleotide Exome Sequencing DNA Copy Number Variations Genetic Variation Cost-Benefit Analysis Exome Genome, Human Whole Genome Sequencing High-Throughput Nucleotide Sequencing Gene Frequency Sequence Analysis, DNA Genotype Genomics Gene Library

A blended genome and exome sequencing method captures genetic variation in an unbiased and cost-effective manner.

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Аннотация

Предметные рубрики MeSH