Evidence map›Paper›PMID 22114984›Full record

ArticleBiology direct2011

On universal common ancestry, sequence similarity, and phylogenetic structure: the sins of P-values and the virtues of Bayesian evidence.

Douglas L Theobald

Abstract read
In one paragraph

Article in Biology direct, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Testing for universal common ancestry.Systematic biology · 2014
    Article
  6. Article
  7. An empirical test of convergent evolution in rhodopsins.Molecular biology and evolution · 2014
    Article
  8. Article
  9. Proving universal common ancestry with similar sequences.Trends in evolutionary biology · 2012
    Article
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

1 author.

Douglas L TheobaldBiochemistry Department, Brandeis University, Waltham, MA 02454, USA. dtheobald@brandeis.edu

Funding

Evolution of enzyme structure and function viewed at atomic resolutionR01GM096053 · NIGMS · BRANDEIS UNIVERSITY · PI Douglas Lowell Theobald · 2011 to 2026
$3.6M
Bayesian analysis of structural shape and conformationR01GM094468 · NIGMS · BRANDEIS UNIVERSITY · PI THEOBALD, DOUGLAS LOWELL · 2010 to 2014
$1.4M
NIGMS NIH HHS GM094468NIGMS NIH HHS GM096053NIGMS NIH HHS R01 GM094468NIGMS NIH HHS R01 GM096053
6 · The paper itself

Abstract

backgroundThe universal common ancestry (UCA) of all known life is a fundamental component of modern evolutionary theory, supported by a wide range of qualitative molecular evidence. Nevertheless, recently both the status and nature of UCA has been questioned. In earlier work I presented a formal, quantitative test of UCA in which model selection criteria overwhelmingly choose common ancestry over independent ancestry, based on a dataset of universally conserved proteins. These model-based tests are founded in likelihoodist and Bayesian probability theory, in opposition to classical frequentist null hypothesis tests such as Karlin-Altschul E-values for sequence similarity. In a recent comment, Koonin and Wolf (K&W) claim that the model preference for UCA is "a trivial consequence of significant sequence similarity". They support this claim with a computational simulation, derived from universally conserved proteins, which produces similar sequences lacking phylogenetic structure. The model selection tests prefer common ancestry for this artificial data set.

resultsFor the real universal protein sequences, hierarchical phylogenetic structure (induced by genealogical history) is the overriding reason for why the tests choose UCA; sequence similarity is a relatively minor factor. First, for cases of conflicting phylogenetic structure, the tests choose independent ancestry even with highly similar sequences. Second, certain models, like star trees and K&W's profile model (corresponding to their simulation), readily explain sequence similarity yet lack phylogenetic structure. However, these are extremely poor models for the real proteins, even worse than independent ancestry models, though they explain K&W's artificial data well. Finally, K&W's simulation is an implementation of a well-known phylogenetic model, and it produces sequences that mimic homologous proteins. Therefore the model selection tests work appropriately with the artificial data.

conclusionsFor K&W's artificial protein data, sequence similarity is the predominant factor influencing the preference for common ancestry. In contrast, for the real proteins, model selection tests show that phylogenetic structure is much more important than sequence similarity. Hence, the model selection tests demonstrate that real universally conserved proteins are homologous, a conclusion based primarily on the specific nested patterns of correlations induced in genetically related protein sequences. REVIEWERS: This article was reviewed by Rob Knight, Robert Beiko (nominated by Peter Gogarten), and Michael Gilchrist.

Indexed as

Evolution, MolecularModels, GeneticPhylogenyAlgorithmsAmino Acid SequenceAnimalsBayes TheoremComputer SimulationGenetic VariationGenome, HumanHumansOrigin of Life

Identifiers

PMID22114984
PMCPMC3314578

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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.