Evidence map›Paper›PMID 30851112›Full record

ArticleMolecular biology and evolution2019

Bayesian Detection of Convergent Rate Changes of Conserved Noncoding Elements on Phylogenetic Trees.

Zhirui Hu, Timothy B Sackton, Scott V Edwards, Jun S Liu

Abstract readValidation Study
In one paragraph

Article in Molecular biology and evolution, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

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42citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

42 citing papers in PubMed.

  1. Article
  2. Article
  3. The genetic foundations of convergent traits.Nature reviews. Genetics · 2026
    Review
  4. MoleRate: comparing molecular relative evolutionary rates to detect convergent evolution.Evolution; international journal of organic evolution · 2026
    Article
  5. Remodeling ofScience advances · 2026
    Article
  6. Review
  7. Article
  8. Language models reveal a complex sequence basis for adaptive convergent evolution of protein functions.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  9. Review
  10. Article
  11. Article
  12. A phylogenetic approach to comparative genomics.Nature reviews. Genetics · 2025
    Review
  13. Article
  14. Article
  15. Article
  16. Diversity ofFrontiers in cell and developmental biology · 2025
    Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Zhirui HuDepartment of Statistics, Harvard University, Cambridge, MA.
Timothy B SacktonInformatics Group, Harvard University, Cambridge, MA.
Scott V EdwardsDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA.
Jun S LiuDepartment of Statistics, Harvard University, Cambridge, MA.

Funding

Deciphering the Regulatory Role of Small RNAs on Alternative Splicing R01GM122080 · NIGMS · UNIVERSITY OF GEORGIA · PI MA, PING · 2016 to 2019
$1.3M
National Science Foundation DEB-1355343National Science Foundation EAR-1355292NIGMS NIH HHS R01 GM122080
6 · The paper itself

Abstract

Conservation of DNA sequence over evolutionary time is a strong indicator of function, and gain or loss of sequence conservation can be used to infer changes in function across a phylogeny. Changes in evolutionary rates on particular lineages in a phylogeny can indicate shared functional shifts, and thus can be used to detect genomic correlates of phenotypic convergence. However, existing methods do not allow easy detection of patterns of rate variation, which causes challenges for detecting convergent rate shifts or other complex evolutionary scenarios. Here we introduce PhyloAcc, a new Bayesian method to model substitution rate changes in conserved elements across a phylogeny. The method assumes several categories of substitution rate for each branch on the phylogenetic tree, estimates substitution rates per category, and detects changes of substitution rate as the posterior probability of a category switch. Simulations show that PhyloAcc can detect genomic regions with rate shifts in multiple target species better than previous methods and has a higher accuracy of reconstructing complex patterns of substitution rate changes than prevalent Bayesian relaxed clock models. We demonstrate the utility of PhyloAcc in two classic examples of convergent phenotypes: loss of flight in birds and the transition to marine life in mammals. In each case, our approach reveals numerous examples of conserved nonexonic elements with accelerations specific to the phenotypically convergent lineages. Our method is widely applicable to any set of conserved elements where multiple rate changes are expected on a phylogeny.

Indexed as

Evolution, MolecularGenetic TechniquesModels, GeneticPhylogenyAnimalsBayes TheoremBirdsComputer SimulationMammalsSoftwareBayesian modelcomparative genomicsconvergencemammalphylogenetics

Identifiers

PMID30851112
PMCPMC6501877

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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.