Evidence map›Paper›PMID 36865215›Full record

ArticlebioRxiv : the preprint server for biology2023

Optimized SMRT-UMI protocol produces highly accurate sequence datasets from diverse populations - application to HIV-1 quasispecies.

Dylan H Westfall, Wenjie Deng, Alec Pankow, Hugh Murrell, Lennie Chen, Hong Zhao, Carolyn Williamson, Morgane Rolland, Ben Murrell, James I Mullins

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Dylan H WestfallDepartment of Microbiology, University of Washington Schools of Medicine and Public Health, Seattle, WA 98195-8070 US.
Wenjie DengDepartment of Microbiology, University of Washington Schools of Medicine and Public Health, Seattle, WA 98195-8070 US.
Alec PankowDepartment of Microbiology, University of Washington Schools of Medicine and Public Health, Seattle, WA 98195-8070 US.
Hugh MurrellDivision of Medical Virology, Department of Pathology, University of Cape Town and National Health Laboratory Services, Cape Town, South Africa.
Lennie ChenDepartment of Microbiology, University of Washington Schools of Medicine and Public Health, Seattle, WA 98195-8070 US.
Hong ZhaoDepartment of Microbiology, University of Washington Schools of Medicine and Public Health, Seattle, WA 98195-8070 US.
Carolyn WilliamsonDivision of Medical Virology, Department of Pathology, University of Cape Town and National Health Laboratory Services, Cape Town, South Africa.
Morgane RollandUS Military HIV Research Program, Walter Reed Army Institute of Research, Silver Spring, Maryland, 20910, USA.
Ben MurrellDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institutet, 17717 Stockholm, SE.
James I MullinsDepartment of Microbiology, University of Washington Schools of Medicine and Public Health, Seattle, WA 98195-8070 US.

Funding

LC: HIV Vaccine Trials NetworkUM1AI068618 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Margaret Juliana McElrath · 2011 to 2026
$483.6M
University of Washington/Fred Hutch Center for AIDS ResearchP30AI027757 · NIAID · UNIVERSITY OF WASHINGTON · PI CONNIE L CELUM · 1988 to 2026
$104.9M
NIAID NIH HHS P30 AI027757NIAID NIH HHS UM1 AI068618
6 · The paper itself

Abstract

Pathogen diversity resulting in quasispecies can enable persistence and adaptation to host defenses and therapies. However, accurate quasispecies characterization can be impeded by errors introduced during sample handling and sequencing which can require extensive optimizations to overcome. We present complete laboratory and bioinformatics workflows to overcome many of these hurdles. The Pacific Biosciences single molecule real-time platform was used to sequence PCR amplicons derived from cDNA templates tagged with universal molecular identifiers (SMRT-UMI). Optimized laboratory protocols were developed through extensive testing of different sample preparation conditions to minimize between-template recombination during PCR and the use of UMI allowed accurate template quantitation as well as removal of point mutations introduced during PCR and sequencing to produce a highly accurate consensus sequence from each template. Handling of the large datasets produced from SMRT-UMI sequencing was facilitated by a novel bioinformatic pipeline, Probabilistic Offspring Resolver for Primer IDs (PORPIDpipeline), that automatically filters and parses reads by sample, identifies and discards reads with UMIs likely created from PCR and sequencing errors, generates consensus sequences, checks for contamination within the dataset, and removes any sequence with evidence of PCR recombination or early cycle PCR errors, resulting in highly accurate sequence datasets. The optimized SMRT-UMI sequencing method presented here represents a highly adaptable and established starting point for accurate sequencing of diverse pathogens. These methods are illustrated through characterization of human immunodeficiency virus (HIV) quasispecies.

Identifiers

PMID36865215
PMCPMC9980183

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.