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A phylogenetic method linking nucleotide substitution rates to rates of continuous trait evolution

Gemmell, Patrick, Sackton, Timothy B., Edwards, Scott V., Liu, Jun S.·2024·PLOS Computational Biology
DOI 10.1371/journal.pcbi.1011995PMC PMC11078400

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Abstract

Genomes contain conserved non-coding sequences that perform important biological functions, such as gene regulation. We present a phylogenetic method, PhyloAcc-C, that associates nucleotide substitution rates with changes in a continuous trait of interest. The method takes as input a multiple sequence alignment of conserved elements, continuous trait data observed in extant species, and a background phylogeny and substitution process. Gibbs sampling is used to assign rate categories (background, conserved, accelerated) to lineages and explore whether the assigned rate categories are associated with increases or decreases in the rate of trait evolution. We test our method using simulations and then illustrate its application using mammalian body size and lifespan data previously analyzed with respect to protein coding genes. Like other studies, we find processes such as tumor suppression, telomere maintenance, and p53 regulation to be related to changes in longevity and body size. In addition, we also find that skeletal genes, and developmental processes, such as sprouting angiogenesis, are relevant.

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Research works printed but not linked: 43

  1. SD Smith, 2020, Phylogenetics is the new genetics (for most of biodiversity), Trends in Ecology & Evolution, 35, 415, 10.1016/j.tree.2020.01.005 · DOI · Paper page
  2. M Hiller, 2012, A “forward genomics” approach links genotype to phenotype using independent phenotypic losses among related species, Cell Reports, 2, 817, 10.1016/j.celrep.2012.08.032 · DOI · Paper page
  3. A Marcovitz, 2016, “Reverse genomics” predicts function of human conserved noncoding elements, Molecular Biology and Evolution, 33, 1358, 10.1093/molbev/msw001 · DOI · Paper page
  4. X Prudent, 2016, Controlling for phylogenetic relatedness and evolutionary rates improves the discovery of associations between species’ phenotypic and genomic differences, Molecular Biology and Evolution, 33, 2135, 10.1093/molbev/msw098 · DOI · Paper page
  5. BE Langer, 2018, REforge associates transcription factor binding site divergence in regulatory elements with phenotypic differences between species, Molecular Biology and Evolution, 35, 3027
  6. R Partha, 2019, Robust method for detecting convergent shifts in evolutionary rates, Molecular Biology and Evolution, 36, 1817, 10.1093/molbev/msz107 · DOI · Paper page
  7. S Treaster, 2021, Refining convergent rate analysis with topology in mammalian longevity and marine transitions, Molecular Biology and Evolution, 38, 5190, 10.1093/molbev/msab226 · DOI · Paper page
  8. RC Hardison, 2000, Conserved noncoding sequences are reliable guides to regulatory elements, Trends in Genetics, 16, 369, 10.1016/S0168-9525(00)02081-3 · DOI
  9. Siepel A, Pollard KS, Haussler D. New methods for detecting lineage-specific selection. In: Annual International Conference on Research in Computational Molecular Biology 2006. Berlin: Springer Berlin Heidelberg; 2006 pp. 190–205. · DOI
  10. KR Rosenbloom, 2015, The UCSC genome browser database: 2015 update, Nucleic Acids Research, 43, D670, 10.1093/nar/gku1177 · DOI
  11. BM Booker, 2016, Bat accelerated regions identify a bat forelimb specific enhancer in the HoxD locus, PLoS Genetics, 12, e1005738, 10.1371/journal.pgen.1005738 · DOI · Paper page
  12. N Lartillot, 2011, A phylogenetic model for investigating correlated evolution of substitution rates and continuous phenotypic characters, Molecular Biology and Evolution, 28, 729, 10.1093/molbev/msq244 · DOI · Paper page
  13. L Yusuf, 2020, Noncoding regions underpin avian bill shape diversification at macroevolutionary scales, Genome Research, 30, 553, 10.1101/gr.255752.119 · DOI
  14. A Kowalczyk, 2020, Pan-mammalian analysis of molecular constraints underlying extended lifespan, Elife, 9, e51089, 10.7554/eLife.51089 · DOI · Paper page
  15. KS Pollard, 2010, Detection of nonneutral substitution rates on mammalian phylogenies, Genome Research, 20, 110, 10.1101/gr.097857.109 · DOI · Paper page
  16. DR Cox, 1977, The theory of stochastic processes
  17. JS Liu, 1994, The collapsed Gibbs sampler in Bayesian computations with applications to a gene regulation problem, Journal of the American Statistical Association, 89, 958, 10.1080/01621459.1994.10476829 · DOI
  18. J Liu, 2001, Monte Carlo strategies in scientific computing
  19. J Felsenstein, 1981, Evolutionary trees from DNA sequences: a maximum likelihood approach, Journal of Molecular Evolution, 17, 368, 10.1007/BF01734359 · DOI · Paper page
  20. RE Kass, 1995, Bayes factors, Journal of the American Statistical Association, 90, 773, 10.1080/01621459.1995.10476572 · DOI · Paper page
  21. EJ Wagenmakers, 2010, Bayesian hypothesis testing for psychologists: A tutorial on the Savage–Dickey method, Cognitive Psychology, 60, 158, 10.1016/j.cogpsych.2009.12.001 · DOI · Paper page
  22. M Blanchette, 2004, Aligning multiple genomic sequences with the threaded blockset aligner, Genome Research, 14, 708, 10.1101/gr.1933104 · DOI · Paper page
  23. WJ Murphy, 2004, Mammalian phylogenomics comes of age, Trends in Genetics, 20, 631, 10.1016/j.tig.2004.09.005 · DOI
  24. D Eddelbuettel, 2011, Rcpp: Seamless R and C++ integration, Journal of Statistical Software, 40, 1, 10.18637/jss.v040.i08 · DOI
  25. D Eddelbuettel, 2014, RcppArmadillo: Accelerating R with high-performance C++ linear algebra, Computational Statistics & Data Analysis, 71, 1054, 10.1016/j.csda.2013.02.005 · DOI
  26. E Paradis, 2004, APE: analyses of phylogenetics and evolution in R language, Bioinformatics, 20, 289, 10.1093/bioinformatics/btg412 · DOI · Paper page
  27. A Gelman, 1992, Inference from iterative simulation using multiple sequences, Statistical Science, 7, 457, 10.1214/ss/1177011136 · DOI · Paper page
  28. CY McLean, 2010, GREAT improves functional interpretation of cis-regulatory regions, Nature Biotechnology, 28, 495, 10.1038/nbt.1630 · DOI · Paper page
  29. P Flicek, 2012, Ensembl 2012, Nucleic Acids Research, 40, D84, 10.1093/nar/gkr991 · DOI
  30. G Stelzer, 2016, The GeneCards suite: from gene data mining to disease genome sequence analyses, Current Protocols in Bioinformatics, 54, 1, 10.1002/cpbi.5 · DOI · Paper page
  31. E Sollis, 2023, The NHGRI-EBI GWAS Catalog: knowledgebase and deposition resource, Nucleic Acids Research, 51, D977, 10.1093/nar/gkac1010 · DOI · Paper page
  32. JB Dorman, 1995, The age-1 and daf-2 genes function in a common pathway to control the lifespan of Caenorhabditis elegans, Genetics, 141, 1399, 10.1093/genetics/141.4.1399 · DOI
  33. AA Maklakov, 2016, The expensive germline and the evolution of ageing, Current Biology, 26, R577, 10.1016/j.cub.2016.04.012 · DOI
  34. G Muntané, 2018, Biological processes modulating longevity across primates: a phylogenetic genome-phenome analysis, Molecular Biology and Evolution, 35, 1990, 10.1093/molbev/msy105 · DOI · Paper page
  35. M Tollis, 2017, Peto’s Paradox: how has evolution solved the problem of cancer prevention?, BMC Biology, 15, 1
  36. D Tejada-Martinez, 2022, Positive selection and enhancer evolution shaped lifespan and body mass in great apes, Molecular Biology and Evolution, 39, msab369, 10.1093/molbev/msab369 · DOI
  37. S Treaster, 2023, Convergent genomics of longevity in rockfishes highlights the genetics of human life span variation, Science Advances, 9, eadd2743, 10.1126/sciadv.add2743 · DOI
  38. SRR Kolora, 2021, Origins and evolution of extreme life span in Pacific Ocean rockfishes, Science, 374, 842, 10.1126/science.abg5332 · DOI
  39. M Kirschner, 1998, Evolvability, Proceedings of the National Academy of Sciences, 95, 8420, 10.1073/pnas.95.15.8420 · DOI · Paper page
  40. MW Kirschner, 2005, The plausibility of life: Resolving Darwin’s dilemma
  41. P Zhu, 2023, Correlated evolution of social organization and lifespan in mammals, Nature Communications, 14, 372, 10.1038/s41467-023-35869-7 · DOI
  42. AA Fisher, 2023, Shrinkage-based random local clocks with scalable inference, Molecular Biology and Evolution, 40, 10.1093/molbev/msad242 · DOI
  43. JC Uyeda, 2014, A novel Bayesian method for inferring and interpreting the dynamics of adaptive landscapes from phylogenetic comparative data, Systematic Biology, 63, 902, 10.1093/sysbio/syu057 · DOI

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Metadata

Authors
Gemmell, P., Sackton, T. B., Edwards, S. V., & Liu, J. S.
ORCID
Venue
PLOS Computational Biology
Publisher
Public Library of Science (PLoS)
Published
2024-04-24
Volume
20
Issue
4
Pages
e1011995
ISSN
1553-7358
DOI
10.1371/journal.pcbi.1011995
PMC
PMC11078400
Cited by
11
References
5
Language
en
Update notices
new_version (2024-05-08)
Licence
creativecommons.org/licenses/by/4.0/ (vor)
Funders
  • National Human Genome Research Institute (R01HG011485)
  • National Institute of General Medical Sciences (R01GM152814)

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