1
|
Zhang R, Drummond AJ, Mendes FK. Fast Bayesian Inference of Phylogenies from Multiple Continuous Characters. Syst Biol 2024; 73:102-124. [PMID: 38085256 PMCID: PMC11129596 DOI: 10.1093/sysbio/syad067] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 03/23/2023] [Accepted: 11/07/2023] [Indexed: 05/28/2024] Open
Abstract
Time-scaled phylogenetic trees are an ultimate goal of evolutionary biology and a necessary ingredient in comparative studies. The accumulation of genomic data has resolved the tree of life to a great extent, yet timing evolutionary events remain challenging if not impossible without external information such as fossil ages and morphological characters. Methods for incorporating morphology in tree estimation have lagged behind their molecular counterparts, especially in the case of continuous characters. Despite recent advances, such tools are still direly needed as we approach the limits of what molecules can teach us. Here, we implement a suite of state-of-the-art methods for leveraging continuous morphology in phylogenetics, and by conducting extensive simulation studies we thoroughly validate and explore our methods' properties. While retaining model generality and scalability, we make it possible to estimate absolute and relative divergence times from multiple continuous characters while accounting for uncertainty. We compile and analyze one of the most data-type diverse data sets to date, comprised of contemporaneous and ancient molecular sequences, and discrete and continuous morphological characters from living and extinct Carnivora taxa. We conclude by synthesizing lessons about our method's behavior, and suggest future research venues.
Collapse
Affiliation(s)
- Rong Zhang
- Programme in Emerging Infectious Diseases, Duke-NUS Medical School 169857, Singapore
| | - Alexei J Drummond
- Centre for Computational Evolution, The University of Auckland, Auckland 1010, New Zealand
- School of Biological Sciences, The University of Auckland, Auckland 1010, New Zealand
| | - Fábio K Mendes
- Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, USA
| |
Collapse
|
2
|
Rolland J, Henao-Diaz LF, Doebeli M, Germain R, Harmon LJ, Knowles LL, Liow LH, Mank JE, Machac A, Otto SP, Pennell M, Salamin N, Silvestro D, Sugawara M, Uyeda J, Wagner CE, Schluter D. Conceptual and empirical bridges between micro- and macroevolution. Nat Ecol Evol 2023; 7:1181-1193. [PMID: 37429904 DOI: 10.1038/s41559-023-02116-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 06/13/2023] [Indexed: 07/12/2023]
Abstract
Explaining broad molecular, phenotypic and species biodiversity patterns necessitates a unifying framework spanning multiple evolutionary scales. Here we argue that although substantial effort has been made to reconcile microevolution and macroevolution, much work remains to identify the links between biological processes at play. We highlight four major questions of evolutionary biology whose solutions require conceptual bridges between micro and macroevolution. We review potential avenues for future research to establish how mechanisms at one scale (drift, mutation, migration, selection) translate to processes at the other scale (speciation, extinction, biogeographic dispersal) and vice versa. We propose ways in which current comparative methods to infer molecular evolution, phenotypic evolution and species diversification could be improved to specifically address these questions. We conclude that researchers are in a better position than ever before to build a synthesis to understand how microevolutionary dynamics unfold over millions of years.
Collapse
Affiliation(s)
- Jonathan Rolland
- CNRS, UMR5174, Laboratoire Evolution et Diversité Biologique, Université Toulouse 3 Paul Sabatier, Toulouse, France.
| | - L Francisco Henao-Diaz
- Department of Zoology, and Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA
| | - Michael Doebeli
- Department of Zoology, and Department of Mathematics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Rachel Germain
- Department of Zoology, and Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - Luke J Harmon
- Dept. of Biological Sciences, University of Idaho, Moscow, ID, USA
| | - L Lacey Knowles
- Department of Ecology and Evolutionary Biology, Museum of Zoology, University of Michigan, Ann Arbor, MI, USA
| | | | - Judith E Mank
- Department of Zoology, and Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - Antonin Machac
- Department of Zoology, and Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
- Laboratory of Environmental Microbiology, Institute of Microbiology of the CAS, Prague, Czech Republic
| | - Sarah P Otto
- Department of Zoology, and Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - Matt Pennell
- Departments of Quantitative and Computational Biology and Biological Sciences, University of Southern California, Los Angeles, CA, USA
| | - Nicolas Salamin
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Daniele Silvestro
- Department of Biology, University of Fribourg, Fribourg, Switzerland
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
- Gothenburg Global Biodiversity Centre, University of Gothenburg, Gothenburg, Sweden
| | - Mauro Sugawara
- Department of Zoology, and Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
- Mário Schenberg Institute, São Paulo, Brazil
| | - Josef Uyeda
- Department of Biological Sciences, Virginia Tech, Blacksburg, VA, USA
| | - Catherine E Wagner
- Department of Botany, and Program in Ecology and Evolution, University of Wyoming, Laramie, WY, USA
| | - Dolph Schluter
- Department of Zoology, and Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| |
Collapse
|
3
|
Drummond AJ, Chen K, Mendes FK, Xie D. LinguaPhylo: A probabilistic model specification language for reproducible phylogenetic analyses. PLoS Comput Biol 2023; 19:e1011226. [PMID: 37463154 PMCID: PMC10381047 DOI: 10.1371/journal.pcbi.1011226] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 05/30/2023] [Indexed: 07/20/2023] Open
Abstract
Phylogenetic models have become increasingly complex, and phylogenetic data sets have expanded in both size and richness. However, current inference tools lack a model specification language that can concisely describe a complete phylogenetic analysis while remaining independent of implementation details. We introduce a new lightweight and concise model specification language, 'LPhy', which is designed to be both human and machine-readable. A graphical user interface accompanies 'LPhy', allowing users to build models, simulate data, and create natural language narratives describing the models. These narratives can serve as the foundation for manuscript method sections. Additionally, we present a command-line interface for converting LPhy-specified models into analysis specification files (in XML format) compatible with the BEAST2 software platform. Collectively, these tools aim to enhance the clarity of descriptions and reporting of probabilistic models in phylogenetic studies, ultimately promoting reproducibility of results.
Collapse
Affiliation(s)
- Alexei J Drummond
- Centre for Computational Evolution, University of Auckland, Auckland, New Zealand
- School of Biological Sciences, University of Auckland, Auckland, New Zealand
- School of Computer Science, University of Auckland, Auckland, New Zealand
| | - Kylie Chen
- Centre for Computational Evolution, University of Auckland, Auckland, New Zealand
- School of Biological Sciences, University of Auckland, Auckland, New Zealand
- School of Computer Science, University of Auckland, Auckland, New Zealand
| | - Fábio K Mendes
- Centre for Computational Evolution, University of Auckland, Auckland, New Zealand
- Department of Biology, Washington University in St. Louis, St. Louis, United States of America
| | - Dong Xie
- Centre for Computational Evolution, University of Auckland, Auckland, New Zealand
- School of Biological Sciences, University of Auckland, Auckland, New Zealand
- School of Computer Science, University of Auckland, Auckland, New Zealand
| |
Collapse
|
4
|
Ogilvie HA, Mendes FK, Vaughan TG, Matzke NJ, Stadler T, Welch D, Drummond AJ. Novel Integrative Modeling of Molecules and Morphology across Evolutionary Timescales. Syst Biol 2021; 71:208-220. [PMID: 34228807 PMCID: PMC8677526 DOI: 10.1093/sysbio/syab054] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 06/23/2021] [Accepted: 06/29/2021] [Indexed: 11/13/2022] Open
Abstract
Evolutionary models account for either population- or species-level processes but usually not both. We introduce a new model, the FBD-MSC, which makes it possible for the first time to integrate both the genealogical and fossilization phenomena, by means of the multispecies coalescent (MSC) and the fossilized birth–death (FBD) processes. Using this model, we reconstruct the phylogeny representing all extant and many fossil Caninae, recovering both the relative and absolute time of speciation events. We quantify known inaccuracy issues with divergence time estimates using the popular strategy of concatenating molecular alignments and show that the FBD-MSC solves them. Our new integrative method and empirical results advance the paradigm and practice of probabilistic total evidence analyses in evolutionary biology.[Caninae; fossilized birth–death; molecular clock; multispecies coalescent; phylogenetics; species trees.]
Collapse
Affiliation(s)
- Huw A Ogilvie
- Department of Computer Science, Rice University, Houston TX, 77005, USA
| | - Fábio K Mendes
- Centre for Computational Evolution, The University of Auckland, Auckland, 1010, New Zealand.,School of Biological Sciences, The University of Auckland, Auckland, 1010, New Zealand
| | - Timothy G Vaughan
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, 4058, Switzerland.,SIB Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland
| | - Nicholas J Matzke
- Centre for Computational Evolution, The University of Auckland, Auckland, 1010, New Zealand.,School of Biological Sciences, The University of Auckland, Auckland, 1010, New Zealand
| | - Tanja Stadler
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, 4058, Switzerland.,SIB Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland
| | - David Welch
- Centre for Computational Evolution, The University of Auckland, Auckland, 1010, New Zealand.,School of Computer Science, The University of Auckland, Auckland, 1010, New Zealand
| | - Alexei J Drummond
- Centre for Computational Evolution, The University of Auckland, Auckland, 1010, New Zealand.,School of Computer Science, The University of Auckland, Auckland, 1010, New Zealand.,School of Biological Sciences, The University of Auckland, Auckland, 1010, New Zealand
| |
Collapse
|
5
|
Duchen P, Alfaro ML, Rolland J, Salamin N, Silvestro D. On the Effect of Asymmetrical Trait Inheritance on Models of Trait Evolution. Syst Biol 2021; 70:376-388. [PMID: 32681798 PMCID: PMC7875446 DOI: 10.1093/sysbio/syaa055] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Revised: 06/30/2020] [Accepted: 07/09/2020] [Indexed: 11/25/2022] Open
Abstract
Current phylogenetic comparative methods modeling quantitative trait evolution generally assume that, during speciation, phenotypes are inherited identically between the two daughter species. This, however, neglects the fact that species consist of a set of individuals, each bearing its own trait value. Indeed, because descendent populations after speciation are samples of a parent population, we can expect their mean phenotypes to randomly differ from one another potentially generating a "jump" of mean phenotypes due to asymmetrical trait inheritance at cladogenesis. Here, we aim to clarify the effect of asymmetrical trait inheritance at speciation on macroevolutionary analyses, focusing on model testing and parameter estimation using some of the most common models of quantitative trait evolution. We developed an individual-based simulation framework in which the evolution of phenotypes is determined by trait changes at the individual level accumulating across generations, and cladogenesis occurs then by separation of subsets of the individuals into new lineages. Through simulations, we assess the magnitude of phenotypic jumps at cladogenesis under different modes of trait inheritance at speciation. We show that even small jumps can strongly alter both the results of model selection and parameter estimations, potentially affecting the biological interpretation of the estimated mode of evolution of a trait. Our results call for caution when interpreting analyses of trait evolution, while highlighting the importance of testing a wide range of alternative models. In the light of our findings, we propose that future methodological advances in comparative methods should more explicitly model the intraspecific variability around species mean phenotypes and how it is inherited at speciation.
Collapse
Affiliation(s)
- Pablo Duchen
- Department of Computational Biology, University of Lausanne, Quartier Sorge, 1015 Lausanne, Switzerland
| | - Michael L Alfaro
- University of California Los Angeles (UCLA). College Life Sciences - Ecology and Evolutionary Biology. Los Angeles, CA, USA
| | - Jonathan Rolland
- Department of Computational Biology, University of Lausanne, Quartier Sorge, 1015 Lausanne, Switzerland
- Department of Zoology, University of British Columbia, #4200-6270 University Blvd, Vancouver, BC, Canada
| | - Nicolas Salamin
- Department of Computational Biology, University of Lausanne, Quartier Sorge, 1015 Lausanne, Switzerland
| | - Daniele Silvestro
- Department of Biology, University of Fribourg, 1700 Fribourg, Switzerland Nicolas Salamin and Daniele Silvestro contributed equally to this article
| |
Collapse
|