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Accurate Detection of Convergent Amino-Acid Evolution with PCOC

Rey, Carine, Guéguen, Laurent, Sémon, Marie, Boussau, Bastien·2018·Molecular Biology and Evolution
DOI 10.1093/molbev/msy114PMC PMC6106957

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  • The need for genome-wide statistical analysis methods with low error rates prompted the development of several new and updated phylogenetic methods that could be applied to genomic data.

    “This need prompted the development of several new and updated phylogenetic methods that could be applied to this genomic data (Zou and Zhang 2015; Prudent et al. 2016; Rey et al. 2018; Hu et al. 2019; Kowalczyk et al. 2019; Treaster et al. 2021; Duchemin et al. 2022; Fukushima and Pollock 2023; Morel et al. 2024)”

    From From Trees to Traits: A Review of Advances in PhyloG2P Methods and Future Directions (2025) · cites this paper as Rey et al. 2018

  • PCOC is available as a container and RERconverge is available as an R package.

    “such as PCOC being available as a container (Rey et al. 2018) or RERconverge being available as an R package Kowalczyk et al. 2019”

    From From Trees to Traits: A Review of Advances in PhyloG2P Methods and Future Directions (2025) · cites this paper as Rey et al. 2018

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Research works printed but not linked: 26

  1. Bazykin, 2007, Extensive parallelism in protein evolution, Biol Dir, 2, 20., 10.1186/1745-6150-2-20 · DOI
  2. Besnard, 2009, Phylogenomics of C4 photosynthesis in sedges (Cyperaceae): multiple appearances and genetic convergence, Mol Biol Evol, 26, 1909, 10.1093/molbev/msp103 · DOI
  3. Castoe, 2009, Evidence for an ancient adaptive episode of convergent molecular evolution, Proc Natl Acad Sci U S A, 106, 8986, 10.1073/pnas.0900233106 · DOI
  4. Chabrol, 2017, Detecting molecular basis of phenotypic convergence, bioRxiv
  5. Dutheil, 2008, Non-homogeneous models of sequence evolution in the Bio++ suite of libraries and programs, BMC Evol Biol, 8, 255., 10.1186/1471-2148-8-255 · DOI
  6. Foote, 2015, Convergent evolution of the genomes of marine mammals, Nat Genet, 47, 272, 10.1038/ng.3198 · DOI
  7. Guindon, 2010, New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0, Syst Biol, 59, 307, 10.1093/sysbio/syq010 · DOI · Paper page
  8. Herrero, 2016, Ensembl comparative genomics resources, Database J Biol Databases Curation, 2016, bav096.
  9. Jarvis, 2014, Whole-genome analyses resolve early branches in the tree of life of modern birds, Science, 346, 1126, 10.1126/science.1253451 · DOI · Paper page
  10. Marcovitz, 2017, A novel unbiased test for molecular convergent evolution and discoveries in echolocating, aquatic and high-altitude mammals, bioRxiv
  11. Parker, 2013, Genome-wide signatures of convergent evolution in echolocating mammals, Nature, 502, 228, 10.1038/nature12511 · DOI
  12. Partha, 2017, Subterranean mammals show convergent regression in ocular genes and enhancers, along with adaptation to tunneling, eLife, 6, 10.7554/eLife.25884 · DOI · Paper page
  13. Parto, 2017, Detecting consistent patterns of directional adaptation using differential selection codon models, BMC Evol Biol, 17, 147., 10.1186/s12862-017-0979-y · DOI
  14. Parto, 2018, Molecular adaptation in rubisco: discriminating between convergent evolution and positive selection using mechanistic and classical codon models, PLoS One, 13, e0192697., 10.1371/journal.pone.0192697 · DOI
  15. Quang, 2008, Empirical profile mixture models for phylogenetic reconstruction, Bioinformatics, 24, 2317, 10.1093/bioinformatics/btn445 · DOI
  16. Rokas, 2008, Frequent and widespread parallel evolution of protein sequences, Mol Biol Evol, 25, 1943, 10.1093/molbev/msn143 · DOI
  17. Schenk, 2013, Ecological opportunity and incumbency in the diversification of repeated continental colonizations by muroid rodents, Syst Biol, 62, 837, 10.1093/sysbio/syt050 · DOI
  18. Studer, 2014, Stability-activity tradeoffs constrain the adaptive evolution of rubisco, Proc Natl Acad Sci U S A, 111, 2223, 10.1073/pnas.1310811111 · DOI
  19. Tamuri, 2009, Identifying changes in selective constraints: host shifts in influenza, PLoS Comput Biol, 5, e1000564, 10.1371/journal.pcbi.1000564 · DOI
  20. Thomas, 2015, Determining the null model for detecting adaptive convergence from genomic data: a case study using echolocating mammals, Mol Biol Evol, 32, 1232, 10.1093/molbev/msv013 · DOI
  21. Thomas, 2017, The effects of increasing the number of taxa on inferences of molecular convergence, Genome Biol Evol, 9, 213
  22. Yates, 2016, Ensembl 2016, Nucleic Acids Res, 44, D710, 10.1093/nar/gkv1157 · DOI
  23. Zhang, 1997, Detection of convergent and parallel evolution at the amino acid sequence level, Mol Biol Evol, 14, 527, 10.1093/oxfordjournals.molbev.a025789 · DOI
  24. Zhen, 2012, Parallel molecular evolution in an herbivore community, Science, 337, 1634, 10.1126/science.1226630 · DOI · Paper page
  25. Zou, 2015, Are convergent and parallel amino acid substitutions in protein evolution more prevalent than neutral expectations?, Mol Biol Evol, 32, 2085, 10.1093/molbev/msv091 · DOI · Paper page
  26. Zou, 2015, No genome-wide protein sequence convergence for echolocation, Mol Biol Evol, 32, 1237, 10.1093/molbev/msv014 · DOI

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Metadata

Authors
Rey, C., Guéguen, L., Sémon, M., & Boussau, B.
Affiliations
  • UnivLyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, Laboratoire de Biologie et Modélisation de la Cellule, Lyon, France
  • Laboratoire de Biométrie et Biologie Évolutive (LBBE), Université de Lyon, Université Lyon 1, CNRS, Villeurbanne, France
ORCID
Boussau, Bastien
Venue
Molecular Biology and Evolution
Publisher
Oxford University Press (OUP)
Published
2018-07-07
Volume
35
Issue
9
Pages
2296-2306
ISSN
  • 0737-4038
  • 1537-1719
DOI
10.1093/molbev/msy114
PMC
PMC6106957
Cited by
82
References
2
Language
en
Licence
creativecommons.org/licenses/by-nc/4.0/ (vor)

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