Evidence map›Paper›PMID 39078610›Full record

ArticleSystematic biology2024

Bayesian Inference Under the Multispecies Coalescent with Ancient DNA Sequences.

Anna A Nagel, Tomáš Flouri, Ziheng Yang, Bruce Rannala

Abstract read
In one paragraph

Article in Systematic biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

4 authors.

Anna A NagelDepartment of Evolution and Ecology, University of California, 1 Shields Avenue, Davis, CA 95616, USA.ORCID 0000-0001-6067-2800
Tomáš FlouriDepartment of Genetics, Evolution, and Environment, University College London, Gower Street, London WC1E 6BT, UK.ORCID 0000-0002-8474-9507
Ziheng YangDepartment of Genetics, Evolution, and Environment, University College London, Gower Street, London WC1E 6BT, UK.ORCID 0000-0003-3351-7981
Bruce RannalaDepartment of Evolution and Ecology, University of California, 1 Shields Avenue, Davis, CA 95616, USA.ORCID 0000-0002-8355-9955

Funding

Statistical Methods and Algorithms for Population Genomic InferenceR01GM123306 · NIGMS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI RANNALA, BRUCE · 2020 to 2023
$1.6M
Biotechnology and Biological Sciences Research Council BB/T003502/1National Science Foundation Graduate Research 2036201NIGMS NIH HHS R01 GM123306NIH HHS GM123306
6 · The paper itself

Abstract

Ancient DNA (aDNA) is increasingly being used to investigate questions such as the phylogenetic relationships and divergence times of extant and extinct species. If aDNA samples are sufficiently old, expected branch lengths (in units of nucleotide substitutions) are reduced relative to contemporary samples. This can be accounted for by incorporating sample ages into phylogenetic analyses. Existing methods that use tip (sample) dates infer gene trees rather than species trees, which can lead to incorrect or biased inferences of the species tree. Methods using a multispecies coalescent (MSC) model overcome these issues. We developed an MSC model with tip dates and implemented it in the program BPP. The method performed well for a range of biologically realistic scenarios, estimating calibrated divergence times and mutation rates precisely. Simulations suggest that estimation precision can be best improved by prioritizing sampling of many loci and more ancient samples. Incorrectly treating ancient samples as contemporary in analyzing simulated data, mimicking a common practice of empirical analyses, led to large systematic biases in model parameters, including divergence times. Two genomic datasets of mammoths and elephants were analyzed, demonstrating the method's empirical utility.

Indexed as

Bayes TheoremClassificationDNA, AncientMammothsPhylogenyAnimalsComputer SimulationElephantsModels, GeneticDNA, AncientaDNABPPmultispecies coalescenttip dating

Identifiers

PMID39078610
PMCPMC11637557

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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.