Evidence map›Paper›PMID 39282457›Full record

ArticlebioRxiv : the preprint server for biology2024

Examining intra-host genetic variation of RSV by short read high-throughput sequencing.

David Henke, Felipe-Andrés Piedra, Vasanthi Avadhanula, Harsha Doddapaneni, Donna M Muzny, Vipin K Menon, Kristi L Hoffman, Matthew C Ross, Sara J Javornik Cregeen, Ginger Metcalf and 3 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

David HenkeDepartment of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA.
Felipe-Andrés PiedraDepartment of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA.ORCID 0000-0002-0100-2919
Vasanthi AvadhanulaDepartment of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA.
Harsha DoddapaneniDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
Donna M MuznyDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
Vipin K MenonDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
Kristi L HoffmanDepartment of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA.
Matthew C RossDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
Sara J Javornik CregeenDepartment of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA.
Ginger MetcalfDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
Richard A GibbsDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
Joseph F PetrosinoDepartment of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA.
Pedro A PiedraDepartment of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA.

Funding

Viral Diversity and Pathogenicity in Mucosal Respiratory and Gastrointestinal DiseaseU19AI144297 · NIAID · BAYLOR COLLEGE OF MEDICINE · PI ESTES, MARY KOLB, GIBBS, RICHARD A · 2019 to 2024
$30.1M
NIAID NIH HHS U19 AI144297
6 · The paper itself

Abstract

Every viral infection entails an evolving population of viral genomes. High-throughput sequencing technologies can be used to characterize such populations, but to date there are few published examples of such work. In addition, mixed sequencing data are sometimes used to infer properties of infecting genomes without discriminating between genome-derived reads and reads from the much more abundant, in the case of a typical active viral infection, transcripts. Here we apply capture probe-based short read high-throughput sequencing to nasal wash samples taken from a previously described group of adult hematopoietic cell transplant (HCT) recipients naturally infected with respiratory syncytial virus (RSV). We separately analyzed reads from genomes and transcripts for the levels and distribution of genetic variation by calculating per position Shannon entropies. Our analysis reveals a low level of genetic variation within the RSV infections analyzed here, but with interesting differences between genomes and transcripts in 1) average per sample Shannon entropies; 2) the genomic distribution of variation 'hotspots'; and 3) the genomic distribution of hotspots encoding alternative amino acids. In all, our results suggest the importance of separately analyzing reads from genomes and transcripts when interpreting high-throughput sequencing data for insight into intra-host viral genome replication, expression, and evolution.

Identifiers

PMID39282457
PMCPMC11398394

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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.