Utility of long-read sequencing for All of Us

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作者
M. Mahmoud
Y. Huang
K. Garimella
P. A. Audano
W. Wan
N. Prasad
R. E. Handsaker
S. Hall
A. Pionzio
M. C. Schatz
M. E. Talkowski
E. E. Eichler
S. E. Levy
F. J. Sedlazeck
机构
[1] Human Genome Sequencing Center,Department of Molecular and Human Genetics
[2] Baylor College of Medicine,Data Sciences Platform
[3] Baylor College of Medicine,Department of Genetics
[4] Broad Institute of MIT and Harvard,Program in Medical and Population Genetics
[5] The Jackson Laboratory for Genomic Medicine,Department of Computer Science
[6] Discovery Life Sciences,Center for Genomic Medicine
[7] Harvard Medical School,Department of Genome Sciences
[8] Broad Institute of MIT and Harvard,Howard Hughes Medical Institute
[9] Johns Hopkins University,Department of Computer Science
[10] Massachusetts General Hospital,undefined
[11] University of Washington School of Medicine,undefined
[12] University of Washington,undefined
[13] HudsonAlpha Institute for Biotechnology,undefined
[14] Rice University,undefined
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摘要
The All of Us (AoU) initiative aims to sequence the genomes of over one million Americans from diverse ethnic backgrounds to improve personalized medical care. In a recent technical pilot, we compare the performance of traditional short-read sequencing with long-read sequencing in a small cohort of samples from the HapMap project and two AoU control samples representing eight datasets. Our analysis reveals substantial differences in the ability of these technologies to accurately sequence complex medically relevant genes, particularly in terms of gene coverage and pathogenic variant identification. We also consider the advantages and challenges of using low coverage sequencing to increase sample numbers in large cohort analysis. Our results show that HiFi reads produce the most accurate results for both small and large variants. Further, we present a cloud-based pipeline to optimize SNV, indel and SV calling at scale for long-reads analysis. These results lead to widespread improvements across AoU.
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