Nat Genet | 融合测序策略高效解析遗传变异

TL;DR - A Broad Institute team (Martin, Howrigan, Neale) published in Nature Genetics a "blended genome exome" (BGE) method that produces low-coverage whole-genome and high-coverage exome data from a single sequencing run at ~28% the cost of deep WGS, making large-scale, ancestrally diverse genomic studies far cheaper and less Eurocentric-biased.

• Protocol: after six optimization rounds, the final mix is 33% WES / 67% WGS, yielding 30–40× exome coverage and 1–4× genome coverage, with >99% genotype concordance for common variants.
• Scale validation: applied to 53,446 (reported elsewhere as 53,448) multi-ancestry samples in the PUMAS project; >30× mean exome depth, >99% variant call rate, <1% sample failure rate.
• Variant detection: with GATK-gCNV, CNVs spanning ≥5 exons were recalled at 87% (up to 100% at higher BGE coverage) with ~90% PPV, validated against high-coverage WGS from the Simons Simplex Collection; SV calling via VISTA/INSurVeyor had limited sensitivity for very large events but high PPV.
• Imputation equity: low-coverage WGS-based imputation exceeded 90% accuracy for common variants versus Illumina GSA arrays, holding up in admixed Latino and African American cohorts.