Evidence map›Paper›PMID 42229890›Full record

ArticleMolecular biology and evolution2026

The Phylodynamic Threshold of Measurably Evolving Populations.

Ariane Weber, Julia Kende, Camila Duitama González, Sanni Översti, Sebastian Duchene

Abstract read
In one paragraph

Article in Molecular biology and evolution, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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.

Ariane WeberHuman Palaeosystems Research Group, Max Planck Institute of Geoanthropology, Jena, Germany.ORCID 0009-0008-7854-2121
Julia KendeBioinformatics and Biostatistics Hub, Institut Pasteur, Paris, France.ORCID 0000-0002-7287-9582
Camila Duitama GonzálezUniversité Paris Cité, Paris, France.ORCID 0000-0001-6805-2331
Sanni ÖverstiHuman Palaeosystems Research Group, Max Planck Institute of Geoanthropology, Jena, Germany.ORCID 0000-0001-7118-1281
Sebastian DucheneUniversité Paris Cité, Paris, France.ORCID 0000-0002-2863-0907

Funding

National Health and Medical Research Council 2017284
6 · The paper itself

Abstract

The molecular clock is a fundamental tool for understanding the time and pace of evolution, requiring calibration information alongside molecular data. Sampling times are often used for calibration since some organisms accumulate enough mutations over the course of their sampling period. This practice ties together two key concepts: measurably evolving populations and the phylodynamic threshold. Our current understanding suggests that populations meeting these criteria are suitable for molecular clock calibration via sampling times. However, the definitions and implications of these concepts remain unclear. Using Hepatitis B virus-like simulations and analyses of empirical data, this study shows that determining whether a population is measurably evolving or has reached the phylodynamic threshold does not only depend on the data, but also on model assumptions and sampling strategies. In Bayesian applications, a lack of temporal signal due to a narrow sampling window results in a prior that is overly informative relative to the data, such that a prior that is potentially misleading typically requires a wider sampling window than one that is reasonable. In our analyses we demonstrate that assessing prior sensitivity is more important than the outcome of tests of temporal signal. Our results offer guidelines to improve molecular clock inferences and highlight limitations in molecular sequence sampling procedures.

Indexed as

Evolution, MolecularHepatitis B virusPhylogenyBayes TheoremComputer SimulationModels, GeneticBayesian phylogeneticsmeasurably evolving populationmicrobial evolutionmolecular clockphylodynamic threshold

Identifiers

PMID42229890
PMCPMC13278492

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Registered trials

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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.