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<p>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 &gt;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 (<i>R</i><sup>2</sup> ≥ 95% for minor allele frequency ≥1%; ≥90% for minor allele frequency &lt;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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月8日

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

摘要

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.