Document Type
Article
Publication Date
1-29-2024
Original Citation
Mahmoud M,
Huang Y,
Garimella K,
Audano P,
Wan W,
Prasad N,
Handsaker R,
Hall S,
Pionzio A,
Schatz M,
Talkowski M,
Eichler E,
Levy S,
Sedlazeck F.
Utility of long-read sequencing for All of Us. Nat Commun. 2024;15(1):837.
Keywords
JGM, Humans, Sequence Analysis, DNA, High-Throughput Nucleotide Sequencing, Genome, Human, Population Health, INDEL Mutation
JAX Source
Nat Commun. 2024;15(1):837.
ISSN
2041-1723
PMID
38281971
DOI
https://doi.org/10.1038/s41467-024-44804-3
Grant
his manuscript was supported by the Baylor/JHU award (OT2 OD002751, 3OT2OD002751). The All of Us Research Program is supported by the National Institutes of Health, Office of the Director: Regional Medical Centers: 1 OT2 OD026549; 1 OT2 OD026554; 1 OT2 OD026557; 1 OT2 OD026556; 1 OT2 OD026550; 1 OT2 OD 026552; 1 OT2 OD026553; 1 OT2 OD026548; 1 OT2 OD026551; 1 OT2 OD026555; IAA #: AOD 16037; Federally Qualified Health Centers: HHSN 263201600085U; Data and Research Center: 5 U2C OD023196; Biobank: 1 U24 OD023121; The Par- ticipant Center: U24 OD023176; Participant Technology Systems Center: 1 U24 OD023163; Communications and Engagement: 3 OT2 OD023205; 3 OT2 OD023206; and Community Partners: 1 OT2 OD025277; 3 OT2 OD025315; 1 OT2 OD025337; 1 OT2 OD025276. In addition, the All of Us Research Program would not be possible without the partnership of its participants. E.E. is an investigator of the Howard Hughes Medical Institute.
Abstract
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.
Comments
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