Evidence map›Paper›PMID 30425841›Full record

ArticleVirus evolution2018

Modeling site-specific amino-acid preferences deepens phylogenetic estimates of viral sequence divergence.

Sarah K Hilton, Jesse D Bloom

Abstract read
In one paragraph

Article in Virus evolution, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

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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

16 citing papers in PubMed.

  1. Review
  2. Recovery of an 18bioRxiv : the preprint server for biology · 2026
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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

2 authors.

Sarah K HiltonBasic Sciences and Computational Biology Program, Fred Hutchinson Cancer Research Center.
Jesse D BloomBasic Sciences and Computational Biology Program, Fred Hutchinson Cancer Research Center.ORCID 0000-0003-1267-3408

Funding

Viral Pathogenesis Training ProgramT32AI083203 · NIAID · UNIVERSITY OF WASHINGTON · PI BLOOM, JESSE D, LAGUNOFF, MICHAEL · 2009 to 2023
$2.7M
High-throughput experiments to guide influenza vaccine strain selectionR01AI127893 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI BLOOM, JESSE D · 2016 to 2020
$2.1M
FHCRC High-Performance Computing ClusterS10OD020069 · OD · FRED HUTCHINSON CANCER RESEARCH CENTER · PI KOOPERBERG, CHARLES L · 2015 to 2015
$600k
Realistic quantitative models of protein and viral evolutionR35GM126911 · NIGMS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI BLOOM, JESSE D · 2018 to 2018
$40k
NIAID NIH HHS R01 AI127893NIAID NIH HHS T32 AI083203NIGMS NIH HHS R35 GM126911NIH HHS S10 OD020069
6 · The paper itself

Abstract

Molecular phylogenetics is often used to estimate the time since the divergence of modern gene sequences. For highly diverged sequences, such phylogenetic techniques sometimes estimate surprisingly recent divergence times. In the case of viruses, independent evidence indicates that the estimates of deep divergence times from molecular phylogenetics are sometimes too recent. This discrepancy is caused in part by inadequate models of purifying selection leading to branch-length underestimation. Here we examine the effect on branch-length estimation of using models that incorporate experimental measurements of purifying selection. We find that models informed by experimentally measured site-specific amino-acid preferences estimate longer deep branches on phylogenies of influenza virus hemagglutinin. This lengthening of branches is due to more realistic stationary states of the models, and is mostly independent of the branch-length extension from modeling site-to-site variation in amino-acid substitution rate. The branch-length extension from experimentally informed site-specific models is similar to that achieved by other approaches that allow the stationary state to vary across sites. However, the improvements from all of these site-specific but time homogeneous and site independent models are limited by the fact that a protein's amino-acid preferences gradually shift as it evolves. Overall, our work underscores the importance of modeling site-specific amino-acid preferences when estimating deep divergence times-but also shows the inherent limitations of approaches that fail to account for how these preferences shift over time.

Indexed as

deep mutational scanningExpCMhemagglutinininfluenza virusphylogeneticssite-specific substitution model

Identifiers

PMID30425841
PMCPMC6220371

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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.