CoChat
Sign Up
Cited by 51Genomics and Phylogenetic StudiesGenetic diversity and population structurePlant Diversity and Evolution

The devil in the details: interactions between the branch-length prior and likelihood model affect node support and branch lengths in the phylogeny of the Psoraceae

Ekman, Stefan, Blaalid, Rakel·2011·Systematic Biology
DOI 10.1093/sysbio/syr022
Open this paper in CoChat — free account

Abstract

In popular use of Bayesian phylogenetics, a default branch-length prior is almost universally applied without knowing how a different prior would have affected the outcome. We performed Bayesian and maximum likelihood (ML) inference of phylogeny based on empirical nucleotide sequence data from a family of lichenized ascomycetes, the Psoraceae, the morphological delimitation of which has been controversial. We specifically assessed the influence of the combination of Bayesian branch-length prior and likelihood model on the properties of the Markov chain Monte Carlo tree sample, including node support, branch lengths, and taxon stability. Data included two regions of the mitochondrial ribosomal RNA gene, the internal transcribed spacer region of the nuclear ribosomal RNA gene, and the protein-coding largest subunit of RNA polymerase II. Data partitioning was performed using Bayes' factors, whereas the best-fitting model of each partition was selected using the Bayesian information criterion (BIC). Given the data and model, short Bayesian branch-length priors generate higher numbers of strongly supported nodes as well as short and topologically similar trees sampled from parts of tree space that are largely unexplored by the ML bootstrap. Long branch-length priors generate fewer strongly supported nodes and longer and more dissimilar trees that are sampled mostly from inside the range of tree space sampled by the ML bootstrap. Priors near the ML distribution of branch lengths generate the best marginal likelihood and the highest frequency of "rogue" (unstable) taxa. The branch-length prior was shown to interact with the likelihood model. Trees inferred under complex partitioned models are more affected by the stretching effect of the branch-length prior. Fewer nodes are strongly supported under a complex model given the same branch-length prior. Irrespective of model, internal branches make up a larger proportion of total tree length under the shortest branch-length priors compared with longer priors. Relative effects on branch lengths caused by the branch-length prior can be problematic to downstream phylogenetic comparative methods making use of the branch lengths. Furthermore, given the same branch-length prior, trees are on average more dissimilar under a simple unpartitioned model compared with a more complex partitioned models. The distribution of ML branch lengths was shown to better fit a gamma or Pareto distribution than an exponential one. Model adequacy tests indicate that the best-fitting model selected by the BIC is insufficient for describing data patterns in 5 of 8 partitions. More general substitution models are required to explain the data in three of these partitions, one of which also requires nonstationarity. The two mitochondrial ribosomal RNA gene partitions need heterotachous models. We found no significant correlations between, on the one hand, the amount of ambiguous data or the smallest branch-length distance to another taxon and, on the other hand, the topological stability of individual taxa. Integrating over several exponentially distributed means under the best-fitting model, node support for the family Psoraceae, including Psora, Protoblastenia, and the Micarea sylvicola group, is approximately 0.96. Support for the genus Psora is distinctly lower, but we found no evidence to contradict the current classification.

Integrity signals

Registry

Crossref · 10.1093/sysbio/syr022

Cites

112 of 112 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • If the best-fitting model does not describe the evolutionary process that generated the data adequately, there can still be a high probability of recovering a tree with relationships representing systematic error.

    “Yet, if the best-fitting model does not describe the evolutionary process that generated the data adequately, there can still be a high probability of recovering a tree with relationships representing systematic error [16-20].”

    From Improved Modeling of Compositional Heterogeneity Supports Sponges as Sister to All Other Animals (2017) · cites this paper as [20]

  • An adequate modeling of the evolutionary process that generated the data is fundamental to the recovery of accurate phylogenies.

    “An adequate modeling of the evolutionary process that generated the data is fundamental to the recovery of accurate phylogenies [16-20].”

    From Improved Modeling of Compositional Heterogeneity Supports Sponges as Sister to All Other Animals (2017) · cites this paper as [20]

  • Porifera-sister better represents the phylogenetic signal in the data.

    “As phylogenetic methods are less likely to recover artifactual topologies when the models of evolution moreadequatelydescribethedata[16-20],weconcludethatPorifera-sister better represents the phylogenetic signal in the data.”

    From Improved Modeling of Compositional Heterogeneity Supports Sponges as Sister to All Other Animals (2017) · cites this paper as [20]

Cites

1 retracted

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
Ekman, S., & Blaalid, R.
Affiliations
  • Uppsala University (SE)
  • University of Oslo (NO)
Corresponding author
Ekman, Stefan
ORCID
Venue
Systematic Biology
Publisher
Oxford University Press (OUP)
Published
2011-03-24
Volume
60
Issue
4
Pages
541-561
ISSN
  • 1063-5157 (ISSN-L)
  • 1076-836X
DOI
10.1093/sysbio/syr022
OpenAlex
W2168697257
Cited by
51
References
112
Citations by year
2026: 1 · 2025: 5 · 2024: 2 · 2023: 1 · 2022: 3 · 2021: 5 · 2019: 4 · 2018: 5 · 2017: 4 · 2016: 2 · 2015: 4 · 2014: 6 · 2013: 5 · 2012: 1
FWCI
1.94
Type
journal article
Language
en
Open access
closed
Locations
  • Systematic Biology (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
  • Life Sciences › Agricultural and Biological Sciences › Ecology, Evolution, Behavior and Systematics › Plant Diversity and Evolution
Keywords
Psoraceae, lichenized Ascomycota, partitioned models, Bayesian phylogenetics, marginal likelihood, substitution models, non-stationarity, mitochondrial ribosomal RNA, ITS, RNA polymerase II, model adequacy testing
MeSH terms
RNA, Mitochondrial, Ascomycota, Bayes Theorem, Markov Chains, Monte Carlo Method, Phylogeny, RNA, RNA Polymerase II, RNA, Ribosomal, Likelihood Functions, DNA, Ribosomal Spacer

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review