Evidence map›Paper›PMID 41289307›Full record

ArticlePLoS computational biology2025

T-shaped alignments integrating HIV-1 near full-length genome and partial pol sequences can improve phylogenetic inference of transmission clusters.

August Guang, Casey W Dunn, Vlad Novitsky, Mark Howison, Rami Kantor

Abstract read
In one paragraph

Article in PLoS computational biology, 2025. 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

5 authors.

August GuangCenter for Computation and Visualization, Brown University, Providence, Rhode Island, United States of America.ORCID 0000-0003-4974-1873
Casey W DunnEcology and Evolutionary Biology, Yale University, New Haven, Connecticut, United States of America.ORCID 0000-0003-0628-5150
Vlad NovitskyWarren Alpert Medical School, Brown University, Providence, Rhode Island, United States of America.
Mark HowisonResearch Improving Peoples' Lives, Providence, Rhode Island, United States of America.
Rami KantorWarren Alpert Medical School, Brown University, Providence, Rhode Island, United States of America.

Funding

Translational ScienceP30AI042853 · NIAID · MIRIAM HOSPITAL · PI CURT G BECKWITH, DEBBIE M. CHENG · 1998 to 2026
$51.7M
The role of Sirtuins in neurodegenerative diseaseP20GM109035 · NIGMS · BROWN UNIVERSITY · PI RAND, DAVID M · 2016 to 2025
$22.6M
Real Time Phylogeny and Contact Tracing to Disrupt HIV TransmissionR01AI136058 · NIAID · MIRIAM HOSPITAL · PI KANTOR, RAMI · 2018 to 2022
$3.4M
HIV Drug Resistance, Monitoring and TransmissionK24AI134359 · NIAID · MIRIAM HOSPITAL · PI Rami Kantor · 2018 to 2026
$1.3M
NIAID NIH HHS K24 AI134359NIAID NIH HHS P30 AI042853NIAID NIH HHS R01 AI136058NIGMS NIH HHS P20 GM109035
6 · The paper itself

Abstract

Molecular epidemiology and HIV-1 transmission networks reconstruction can provide insights into transmission dynamics and inform public health strategies. Long HIV sequences, such as near full-length (nFL) genomes, can improve the accuracy of phylogenetic inference. However, relatively short pol sequences are still broadly used for inferring molecular HIV clusters. Whether a mix of long and short HIV-1 sequences can improve phylogenetic inference of molecular HIV clusters remains unknown. We propose a flexible approach called T-shaped alignments that incorporates both nFL HIV-1 genomes and partial pol sequences, and investigate whether this approach improves phylogenetic reconstruction of molecular clusters. Under the assumption that clustering from 100% of long sequences is the most accurate, we obtained 1196 subtype B nFL HIV-1 sequences from the Los Alamos National Laboratory Database and a single-study subset, varied the proportion of long and short sequences in our T-shape alignments, systematically masked all non-pol regions with missing characters in proportional increments, and compared tree similarity and cluster inference among datasets. With the full dataset, we found that when more than 50% of available sequences are nFL, the T-shaped alignment gradually yields results closer to the 100% n, with more and larger clusters identified. However, below the 50% threshold accuracy did not increase. Stringent bootstrap thresholds decreased cluster accuracy gaps but also decreased number of clusters found and mean cluster size. For the subset dataset, we found that the introduction of nFL sequences to the T-shaped alignment improves accuracy in clustering either after a 30% threshold or immediately depending on bootstrap choice. Our new approach and results suggest that using T-shape alignments to mix HIV-1 sequences of different lengths can improve phylogenetic and clustering accuracy, with needed nFL proportion depending on analysis goals. The T-shape alignment provides a straightforward method for utilizing all available sequences to improve phylogenetic analysis.

Indexed as

Genome, ViralHIV-1HIV InfectionsPhylogenySequence AlignmentAlgorithmsCluster AnalysisComputational BiologyHumans

Identifiers

PMID41289307
PMCPMC12685204

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.