1
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Moody ERR, Álvarez-Carretero S, Mahendrarajah TA, Clark JW, Betts HC, Dombrowski N, Szánthó LL, Boyle RA, Daines S, Chen X, Lane N, Yang Z, Shields GA, Szöllősi GJ, Spang A, Pisani D, Williams TA, Lenton TM, Donoghue PCJ. The nature of the last universal common ancestor and its impact on the early Earth system. Nat Ecol Evol 2024:10.1038/s41559-024-02461-1. [PMID: 38997462 DOI: 10.1038/s41559-024-02461-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Accepted: 06/04/2024] [Indexed: 07/14/2024]
Abstract
The nature of the last universal common ancestor (LUCA), its age and its impact on the Earth system have been the subject of vigorous debate across diverse disciplines, often based on disparate data and methods. Age estimates for LUCA are usually based on the fossil record, varying with every reinterpretation. The nature of LUCA's metabolism has proven equally contentious, with some attributing all core metabolisms to LUCA, whereas others reconstruct a simpler life form dependent on geochemistry. Here we infer that LUCA lived ~4.2 Ga (4.09-4.33 Ga) through divergence time analysis of pre-LUCA gene duplicates, calibrated using microbial fossils and isotope records under a new cross-bracing implementation. Phylogenetic reconciliation suggests that LUCA had a genome of at least 2.5 Mb (2.49-2.99 Mb), encoding around 2,600 proteins, comparable to modern prokaryotes. Our results suggest LUCA was a prokaryote-grade anaerobic acetogen that possessed an early immune system. Although LUCA is sometimes perceived as living in isolation, we infer LUCA to have been part of an established ecological system. The metabolism of LUCA would have provided a niche for other microbial community members and hydrogen recycling by atmospheric photochemistry could have supported a modestly productive early ecosystem.
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Affiliation(s)
- Edmund R R Moody
- Bristol Palaeobiology Group, School of Earth Sciences, University of Bristol, Bristol, UK.
| | | | - Tara A Mahendrarajah
- Department of Marine Microbiology and Biogeochemistry, NIOZ, Royal Netherlands Institute for Sea Research, Den Burg, The Netherlands
| | - James W Clark
- Milner Centre for Evolution, Department of Life Sciences, University of Bath, Bath, UK
| | - Holly C Betts
- Bristol Palaeobiology Group, School of Earth Sciences, University of Bristol, Bristol, UK
| | - Nina Dombrowski
- Department of Marine Microbiology and Biogeochemistry, NIOZ, Royal Netherlands Institute for Sea Research, Den Burg, The Netherlands
| | - Lénárd L Szánthó
- Department of Biological Physics, Eötvös University, Budapest, Hungary
- MTA-ELTE 'Lendulet' Evolutionary Genomics Research Group, Budapest, Hungary
- Institute of Evolution, HUN-REN Center for Ecological Research, Budapest, Hungary
| | | | - Stuart Daines
- Global Systems Institute, University of Exeter, Exeter, UK
| | - Xi Chen
- Department of Earth Sciences, University College London, London, UK
| | - Nick Lane
- Department of Genetics, Evolution and Environment, University College London, London, UK
| | - Ziheng Yang
- Department of Genetics, Evolution and Environment, University College London, London, UK
| | - Graham A Shields
- Department of Earth Sciences, University College London, London, UK
| | - Gergely J Szöllősi
- MTA-ELTE 'Lendulet' Evolutionary Genomics Research Group, Budapest, Hungary
- Institute of Evolution, HUN-REN Center for Ecological Research, Budapest, Hungary
- Model-Based Evolutionary Genomics Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan
| | - Anja Spang
- Department of Marine Microbiology and Biogeochemistry, NIOZ, Royal Netherlands Institute for Sea Research, Den Burg, The Netherlands
- Department of Evolutionary & Population Biology, Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, Amsterdam, The Netherlands
| | - Davide Pisani
- Bristol Palaeobiology Group, School of Earth Sciences, University of Bristol, Bristol, UK.
- Bristol Palaeobiology Group, School of Biological Sciences, University of Bristol, Bristol, UK.
| | - Tom A Williams
- Bristol Palaeobiology Group, School of Biological Sciences, University of Bristol, Bristol, UK.
| | | | - Philip C J Donoghue
- Bristol Palaeobiology Group, School of Earth Sciences, University of Bristol, Bristol, UK.
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2
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List JM. Open Problems in Computational Historical Linguistics. OPEN RESEARCH EUROPE 2024; 3:201. [PMID: 38357681 PMCID: PMC10864822 DOI: 10.12688/openreseurope.16804.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 05/30/2024] [Indexed: 02/16/2024]
Abstract
Problems constitute the starting point of all scientific research. The essay reflects on the different kinds of problems that scientists address in their research and discusses a list of 10 problems for the field of computational historical linguistics, that was proposed throughout 2019 in a series of blog posts (see http://phylonetworks.blogspot.com/). In contrast to problems identified in different contexts, these problems were considered to be solvable, but no solution could be proposed back then. By discussing the problems in the light of developments that have been made in the field during the past five years, a modified list is proposed that takes new insights into account but also finds that the majority of the problems has not yet been solved.
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Affiliation(s)
- Johann-Mattis List
- Chair of Multilingual Computational Linguistics, University of Passau, Passau, Bavaria, 94032, Germany
- Department of Linguistic and Cultural Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, 04103, Germany
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3
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van der Gulik PTS, Hoff WD, Speijer D. The contours of evolution: In defence of Darwin's tree of life paradigm. Bioessays 2024; 46:e2400012. [PMID: 38436469 DOI: 10.1002/bies.202400012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 02/12/2024] [Accepted: 02/15/2024] [Indexed: 03/05/2024]
Abstract
Both the concept of a Darwinian tree of life (TOL) and the possibility of its accurate reconstruction have been much criticized. Criticisms mostly revolve around the extensive occurrence of lateral gene transfer (LGT), instances of uptake of complete organisms to become organelles (with the associated subsequent gene transfer to the nucleus), as well as the implications of more subtle aspects of the biological species concept. Here we argue that none of these criticisms are sufficient to abandon the valuable TOL concept and the biological realities it captures. Especially important is the need to conceptually distinguish between organismal trees and gene trees, which necessitates incorporating insights of widely occurring LGT into modern evolutionary theory. We demonstrate that all criticisms, while based on important new findings, do not invalidate the TOL. After considering the implications of these new insights, we find that the contours of evolution are best represented by a TOL.
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Affiliation(s)
| | - Wouter D Hoff
- Department of Microbiology and Molecular Genetics, Oklahoma State University, Stillwater, Oklahoma, USA
| | - Dave Speijer
- Department of Medical Biochemistry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
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4
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Holland B, Huber KT, Moulton V. A distance-based model for convergent evolution. J Math Biol 2024; 88:17. [PMID: 38238584 PMCID: PMC10796574 DOI: 10.1007/s00285-023-02038-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 11/28/2023] [Accepted: 12/10/2023] [Indexed: 01/22/2024]
Abstract
Convergent evolution is an important process in which independent species evolve similar features usually over a long period of time. It occurs with many different species across the tree of life, and is often caused by the fact that species have to adapt to similar environmental niches. In this paper, we introduce and study properties of a distance-based model for convergent evolution in which we assume that two ancestral species converge for a certain period of time within a collection of species that have otherwise evolved according to an evolutionary clock. Under these assumptions it follows that we obtain a distance on the collection that is a modification of an ultrametric distance arising from an equidistant phylogenetic tree. As well as characterising when this modified distance is a tree metric, we give conditions in terms of the model's parameters for when it is still possible to recover the underlying tree and also its height, even in case the modified distance is not a tree metric.
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Affiliation(s)
- Barbara Holland
- School of Natural Sciences, University of Tasmania, ARC Centre of Excellence for Plant Success, Hobart, Tasmania, Australia
| | - Katharina T Huber
- School of Computing Sciences, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, Norfolk, UK
| | - Vincent Moulton
- School of Computing Sciences, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, Norfolk, UK.
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5
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Colson P, Bader W, Fantini J, Dudouet P, Levasseur A, Pontarotti P, Devaux C, Raoult D. From viral democratic genomes to viral wild bunch of quasispecies. J Med Virol 2023; 95:e29209. [PMID: 37937701 DOI: 10.1002/jmv.29209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 10/05/2023] [Accepted: 10/19/2023] [Indexed: 11/09/2023]
Abstract
The tremendous majority of RNA genomes from pathogenic viruses analyzed and deposited in databases are consensus or "democratic" genomes. They represent the genomes most frequently found in the clinical samples of patients but do not account for the huge genetic diversity of coexisting genomes, which is better described as quasispecies. A viral quasispecies is defined as the dynamic distribution of nonidentical but closely related mutants, variants, recombinant, or reassortant viral genomes. Viral quasispecies have collective behavior and dynamics and are the subject of internal interactions that comprise interference, complementation, or cooperation. In the setting of SARS-CoV-2 infection, intrahost SARS-CoV-2 genetic diversity was recently notably reported for immunocompromised, chronically infected patients, for patients treated with monoclonal antibodies targeting the viral spike protein, and for different body compartments of a single patient. A question that deserves attention is whether such diversity is generated postinfection from a clonal genome in response to selection pressure or is already present at the time of infection as a quasispecies. In the present review, we summarize the data supporting that hosts are infected by a "wild bunch" of viruses rather than by multiple virions sharing the same genome. Each virion in the "wild bunch" may have different virulence and tissue tropisms. As the number of viruses replicated during host infections is huge, a viral quasispecies at any time of infection is wide and is also influenced by host-specific selection pressure after infection, which accounts for the difficulty in deciphering and predicting the appearance of more fit variants and the evolution of epidemics of novel RNA viruses.
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Affiliation(s)
- Philippe Colson
- IHU Méditerranée Infection, Marseille, France
- Aix-Marseille Université., Institut de Recherche pour le Développement (IRD), Microbes Evolution Phylogeny and Infections (MEPHI), Marseille, France
- Assistance Publique-Hôpitaux de Marseille (AP-HM), Marseille, France
| | - Wahiba Bader
- IHU Méditerranée Infection, Marseille, France
- Aix-Marseille Université., Institut de Recherche pour le Développement (IRD), Microbes Evolution Phylogeny and Infections (MEPHI), Marseille, France
| | - Jacques Fantini
- INSERM UMR_S 1072, Aix-Marseille Université, Marseille, France
| | - Pierre Dudouet
- IHU Méditerranée Infection, Marseille, France
- Aix-Marseille Université., Institut de Recherche pour le Développement (IRD), Microbes Evolution Phylogeny and Infections (MEPHI), Marseille, France
| | - Anthony Levasseur
- IHU Méditerranée Infection, Marseille, France
- Aix-Marseille Université., Institut de Recherche pour le Développement (IRD), Microbes Evolution Phylogeny and Infections (MEPHI), Marseille, France
| | - Pierre Pontarotti
- IHU Méditerranée Infection, Marseille, France
- Department of Biological Sciences, Centre National de la Recherche 16 Scientifique (CNRS)-SNC5039, Marseille, France
| | - Christian Devaux
- IHU Méditerranée Infection, Marseille, France
- Department of Biological Sciences, Centre National de la Recherche 16 Scientifique (CNRS)-SNC5039, Marseille, France
| | - Didier Raoult
- IHU Méditerranée Infection, Marseille, France
- Aix-Marseille Université., Institut de Recherche pour le Développement (IRD), Microbes Evolution Phylogeny and Infections (MEPHI), Marseille, France
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6
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Donoghue PCJ, Kay C, Spang A, Szöllősi G, Nenarokova A, Moody ERR, Pisani D, Williams TA. Defining eukaryotes to dissect eukaryogenesis. Curr Biol 2023; 33:R919-R929. [PMID: 37699353 DOI: 10.1016/j.cub.2023.07.048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/14/2023]
Abstract
The origin of eukaryotes is among the most contentious debates in evolutionary biology, attracting multiple seemingly incompatible theories seeking to explain the sequence in which eukaryotic characteristics were acquired. Much of the controversy arises from differing views on the defining characteristics of eukaryotes. We argue that eukaryotes should be defined phylogenetically, and that doing so clarifies where competing hypotheses of eukaryogenesis agree and how we may test among aspects of disagreement. Some hypotheses make predictions about the phylogenetic origins of eukaryotic genes and are distinguishable on that basis. However, other hypotheses differ only in the order of key evolutionary steps, like mitochondrial endosymbiosis and nuclear assembly, which cannot currently be distinguished phylogenetically. Stages within eukaryogenesis may be made identifiable through the absolute dating of gene duplicates that map to eukaryotic traits, such as in genes of host or mitochondrial origin that duplicated and diverged functionally prior to emergence of the last eukaryotic common ancestor. In this way, it may finally be possible to distinguish heat from light in the debate over eukaryogenesis.
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Affiliation(s)
- Philip C J Donoghue
- Bristol Palaeobiology Group, School of Earth Sciences, Life Sciences Building, University of Bristol, Bristol BS8 1TQ, UK.
| | - Chris Kay
- Bristol Palaeobiology Group, School of Earth Sciences, Life Sciences Building, University of Bristol, Bristol BS8 1TQ, UK
| | - Anja Spang
- Department of Marine Microbiology and Biogeochemistry, NIOZ, Royal Netherlands Institute for Sea Research, Utrecht University, Den Burg 1790 AB, The Netherlands
| | - Gergely Szöllősi
- Department of Biological Physics, Eötvös Lorand University, H-1117 Budapest, Hungary; MTA-ELTE "Lendü let" Evolutionary Genomics Research Group, H-1117 Budapest, Hungary; Institute of Evolution, Centre for Ecological Research, H-1113 Budapest, Hungary
| | - Anna Nenarokova
- Bristol Palaeobiology Group, School of Earth Sciences, Life Sciences Building, University of Bristol, Bristol BS8 1TQ, UK
| | - Edmund R R Moody
- Bristol Palaeobiology Group, School of Earth Sciences, Life Sciences Building, University of Bristol, Bristol BS8 1TQ, UK
| | - Davide Pisani
- Bristol Palaeobiology Group, School of Earth Sciences, Life Sciences Building, University of Bristol, Bristol BS8 1TQ, UK; Bristol Palaeobiology Group, School of Biological Sciences, Life Sciences Building, University of Bristol, Bristol BS8 1TQ, UK.
| | - Tom A Williams
- Bristol Palaeobiology Group, School of Biological Sciences, Life Sciences Building, University of Bristol, Bristol BS8 1TQ, UK.
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7
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Forterre P. Carl Woese: Still ahead of our time. MLIFE 2022; 1:359-367. [PMID: 38818481 PMCID: PMC10989812 DOI: 10.1002/mlf2.12049] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 11/14/2022] [Accepted: 11/17/2022] [Indexed: 06/01/2024]
Affiliation(s)
- Patrick Forterre
- Institut Pasteur, Departement de MicrobiologieParisFrance
- Institute for Integrative Biology of the Cell, équipeBiologie Cellulaire des Archées, Département de MicrobiologieGif sur YvetteFrance
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8
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Sengupta S, Azad RK. Reconstructing horizontal gene flow network to understand prokaryotic evolution. Open Biol 2022; 12:220169. [PMID: 36446404 PMCID: PMC9708380 DOI: 10.1098/rsob.220169] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022] Open
Abstract
Horizontal gene transfer (HGT) is a major source of phenotypic innovation and a mechanism of niche adaptation in prokaryotes. Quantification of HGT is critical to decipher its myriad roles in microbial evolution and adaptation. Advances in genome sequencing and bioinformatics have augmented our ability to understand the microbial world, particularly the direct or indirect influence of HGT on diverse life forms. Methods for detecting HGT can be classified into phylogenetic-based and parametric or composition-based approaches. Here, we exploited the complementary strengths of both the approaches to construct a high confidence horizontal gene flow network. Our network is unique in its ability to detect the transfer of native genes of a genome to genomes from other taxa, thus establishing donor and recipient organisms (taxa), rather than through a post hoc analysis as is the practice with several other approaches. The scale-free horizontal gene flow network presented here provides new insights into modes of transfer for the exchange of genetic information and also illuminates differential gene flow across phyla.
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Affiliation(s)
- Soham Sengupta
- Department of Biological Sciences and BioDiscovery Institute, University of North Texas, Denton, TX 76203, USA
| | - Rajeev K. Azad
- Department of Biological Sciences and BioDiscovery Institute, University of North Texas, Denton, TX 76203, USA,Department of Mathematics, University of North Texas, Denton, TX 76203, USA
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9
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Sengupta S, Azad RK. Reconstructing horizontal gene flow network to understand prokaryotic evolution. Open Biol 2022. [PMID: 36446404 DOI: 10.6084/m9.figshare.c.6307519] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022] Open
Abstract
Horizontal gene transfer (HGT) is a major source of phenotypic innovation and a mechanism of niche adaptation in prokaryotes. Quantification of HGT is critical to decipher its myriad roles in microbial evolution and adaptation. Advances in genome sequencing and bioinformatics have augmented our ability to understand the microbial world, particularly the direct or indirect influence of HGT on diverse life forms. Methods for detecting HGT can be classified into phylogenetic-based and parametric or composition-based approaches. Here, we exploited the complementary strengths of both the approaches to construct a high confidence horizontal gene flow network. Our network is unique in its ability to detect the transfer of native genes of a genome to genomes from other taxa, thus establishing donor and recipient organisms (taxa), rather than through a post hoc analysis as is the practice with several other approaches. The scale-free horizontal gene flow network presented here provides new insights into modes of transfer for the exchange of genetic information and also illuminates differential gene flow across phyla.
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Affiliation(s)
- Soham Sengupta
- Department of Biological Sciences and BioDiscovery Institute, University of North Texas, Denton, TX 76203, USA
| | - Rajeev K Azad
- Department of Biological Sciences and BioDiscovery Institute, University of North Texas, Denton, TX 76203, USA.,Department of Mathematics, University of North Texas, Denton, TX 76203, USA
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10
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Susko E. Complex statistical modelling for phylogenetic inference. CAN J STAT 2022. [DOI: 10.1002/cjs.11741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Edward Susko
- Department of Mathematics and Statistics Dalhousie University Halifax Nova Scotia Canada B3H 3J5
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11
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Bell PJL. Eukaryogenesis: The Rise of an Emergent Superorganism. Front Microbiol 2022; 13:858064. [PMID: 35633668 PMCID: PMC9130767 DOI: 10.3389/fmicb.2022.858064] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 04/15/2022] [Indexed: 12/11/2022] Open
Abstract
Although it is widely taught that all modern life descended via modification from a last universal common ancestor (LUCA), this dominant paradigm is yet to provide a generally accepted explanation for the chasm in design between prokaryotic and eukaryotic cells. Counter to this dominant paradigm, the viral eukaryogenesis (VE) hypothesis proposes that the eukaryotes originated as an emergent superorganism and thus did not evolve from LUCA via descent with incremental modification. According to the VE hypothesis, the eukaryotic nucleus descends from a viral factory, the mitochondrion descends from an enslaved alpha-proteobacteria and the cytoplasm and plasma membrane descend from an archaeal host. A virus initiated the eukaryogenesis process by colonising an archaeal host to create a virocell that had its metabolism reprogrammed to support the viral factory. Subsequently, viral processes facilitated the entry of a bacterium into the archaeal cytoplasm which was also eventually reprogrammed to support the viral factory. As the viral factory increased control of the consortium, the archaeal genome was lost, the bacterial genome was greatly reduced and the viral factory eventually evolved into the nucleus. It is proposed that the interaction between these three simple components generated a superorganism whose emergent properties allowed the evolution of eukaryotic complexity. If the radical tenets of the VE hypothesis are ultimately accepted, current biological paradigms regarding viruses, cell theory, LUCA and the universal Tree of Life (ToL) should be fundamentally altered or completely abandoned.
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12
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Kong S, Pons JC, Kubatko L, Wicke K. Classes of explicit phylogenetic networks and their biological and mathematical significance. J Math Biol 2022; 84:47. [PMID: 35503141 DOI: 10.1007/s00285-022-01746-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 01/18/2022] [Accepted: 03/31/2022] [Indexed: 11/24/2022]
Abstract
The evolutionary relationships among organisms have traditionally been represented using rooted phylogenetic trees. However, due to reticulate processes such as hybridization or lateral gene transfer, evolution cannot always be adequately represented by a phylogenetic tree, and rooted phylogenetic networks that describe such complex processes have been introduced as a generalization of rooted phylogenetic trees. In fact, estimating rooted phylogenetic networks from genomic sequence data and analyzing their structural properties is one of the most important tasks in contemporary phylogenetics. Over the last two decades, several subclasses of rooted phylogenetic networks (characterized by certain structural constraints) have been introduced in the literature, either to model specific biological phenomena or to enable tractable mathematical and computational analyses. In the present manuscript, we provide a thorough review of these network classes, as well as provide a biological interpretation of the structural constraints underlying these networks where possible. In addition, we discuss how imposing structural constraints on the network topology can be used to address the scalability and identifiability challenges faced in the estimation of phylogenetic networks from empirical data.
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Affiliation(s)
- Sungsik Kong
- Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH, USA
| | - Joan Carles Pons
- Department of Mathematics and Computer Science, University of the Balearic Islands, Palma, 07122, Spain
| | - Laura Kubatko
- Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH, USA.,Department of Statistics, The Ohio State University, Columbus, OH, USA
| | - Kristina Wicke
- Department of Mathematics, The Ohio State University, Columbus, OH, USA.
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13
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Moody ERR, Mahendrarajah TA, Dombrowski N, Clark JW, Petitjean C, Offre P, Szöllősi GJ, Spang A, Williams TA. An estimate of the deepest branches of the tree of life from ancient vertically-evolving genes. eLife 2022; 11:66695. [PMID: 35190025 PMCID: PMC8890751 DOI: 10.7554/elife.66695] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 02/07/2022] [Indexed: 11/30/2022] Open
Abstract
Core gene phylogenies provide a window into early evolution, but different gene sets and analytical methods have yielded substantially different views of the tree of life. Trees inferred from a small set of universal core genes have typically supported a long branch separating the archaeal and bacterial domains. By contrast, recent analyses of a broader set of non-ribosomal genes have suggested that Archaea may be less divergent from Bacteria, and that estimates of inter-domain distance are inflated due to accelerated evolution of ribosomal proteins along the inter-domain branch. Resolving this debate is key to determining the diversity of the archaeal and bacterial domains, the shape of the tree of life, and our understanding of the early course of cellular evolution. Here, we investigate the evolutionary history of the marker genes key to the debate. We show that estimates of a reduced Archaea-Bacteria (AB) branch length result from inter-domain gene transfers and hidden paralogy in the expanded marker gene set. By contrast, analysis of a broad range of manually curated marker gene datasets from an evenly sampled set of 700 Archaea and Bacteria reveals that current methods likely underestimate the AB branch length due to substitutional saturation and poor model fit; that the best-performing phylogenetic markers tend to support longer inter-domain branch lengths; and that the AB branch lengths of ribosomal and non-ribosomal marker genes are statistically indistinguishable. Furthermore, our phylogeny inferred from the 27 highest-ranked marker genes recovers a clade of DPANN at the base of the Archaea and places the bacterial Candidate Phyla Radiation (CPR) within Bacteria as the sister group to the Chloroflexota.
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Affiliation(s)
- Edmund R R Moody
- School of Biological Sciences, University of Bristol, Bristol, United Kingdom
| | - Tara A Mahendrarajah
- Department of Marine Microbiology and Biogeochemistry, Royal Netherlands Institute for Sea Research, Den Burg, Netherlands
| | - Nina Dombrowski
- Department of Marine Microbiology and Biogeochemistry, Royal Netherlands Institute for Sea Research, Den Burg, Netherlands
| | - James W Clark
- School of Biological Sciences, University of Bristol, Bristol, United Kingdom
| | - Celine Petitjean
- School of Biological Sciences, University of Bristol, Bristol, United Kingdom
| | - Pierre Offre
- Department of Marine Microbiology and Biogeochemistry, Royal Netherlands Institute for Sea Research, Den Burg, Netherlands
| | - Gergely J Szöllősi
- Department of Biological Physics, Eötvös Loránd University, Budapest, Hungary
| | - Anja Spang
- Department of Marine Microbiology and Biogeochemistry, Royal Netherlands Institute for Sea Research, Den Burg, Netherlands
| | - Tom A Williams
- School of Biological Sciences, University of Bristol, Bristol, United Kingdom
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14
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Morel B, Schade P, Lutteropp S, Williams TA, Szöllősi GJ, Stamatakis A. SpeciesRax: A tool for maximum likelihood species tree inference from gene family trees under duplication, transfer, and loss. Mol Biol Evol 2022; 39:6503503. [PMID: 35021210 PMCID: PMC8826479 DOI: 10.1093/molbev/msab365] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Species tree inference from gene family trees is becoming increasingly popular because it can account for discordance between the species tree and the corresponding gene family trees. In particular, methods that can account for multiple-copy gene families exhibit potential to leverage paralogy as informative signal. At present, there does not exist any widely adopted inference method for this purpose. Here, we present SpeciesRax, the first maximum likelihood method that can infer a rooted species tree from a set of gene family trees and can account for gene duplication, loss, and transfer events. By explicitly modeling events by which gene trees can depart from the species tree, SpeciesRax leverages the phylogenetic rooting signal in gene trees. SpeciesRax infers species tree branch lengths in units of expected substitutions per site and branch support values via paralogy-aware quartets extracted from the gene family trees. Using both empirical and simulated data sets we show that SpeciesRax is at least as accurate as the best competing methods while being one order of magnitude faster on large data sets at the same time. We used SpeciesRax to infer a biologically plausible rooted phylogeny of the vertebrates comprising 188 species from 31,612 gene families in 1 h using 40 cores. SpeciesRax is available under GNU GPL at https://github.com/BenoitMorel/GeneRax and on BioConda.
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Affiliation(s)
- Benoit Morel
- Computational Molecular Evolution group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany.,Institute for Theoretical Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Paul Schade
- Institute for Theoretical Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Sarah Lutteropp
- Computational Molecular Evolution group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany
| | - Tom A Williams
- School of Biological Sciences, University of Bristol, Bristol, UK
| | - Gergely J Szöllősi
- ELTE-MTA "Lendület" Evolutionary Genomics Research Group, Pázmány P. stny. 1A., H-1117 Budapest, Hungary.,Dept. Biological Physics, Eötvös University, Pázmány P. stny. 1A., H-1117 Budapest, Hungary.,Institute of Evolution, Centre for Ecological Research, Konkoly-Thege M. út 29-33. H-1121 Budapest, Hungary
| | - Alexandros Stamatakis
- Computational Molecular Evolution group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany.,Institute for Theoretical Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany
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15
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Harris BJ, Sheridan PO, Davín AA, Gubry-Rangin C, Szöllősi GJ, Williams TA. Rooting Species Trees Using Gene Tree-Species Tree Reconciliation. Methods Mol Biol 2022; 2569:189-211. [PMID: 36083449 DOI: 10.1007/978-1-0716-2691-7_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Interpreting phylogenetic trees requires a root, which provides the direction of evolution and polarizes ancestor-descendant relationships. But inferring the root using genetic data is difficult, particularly in cases where the closest available outgroup is only distantly related, which are common for microbes. In this chapter, we present a workflow for estimating rooted species trees and the evolutionary history of the gene families that evolve within them using probabilistic gene tree-species tree reconciliation. We illustrate the pipeline using a small dataset of prokaryotic genomes, for which the example scripts can be run using modest computer resources. We describe the rooting method used in this work in the context or other rooting strategies and discuss some of the limitations and opportunities presented by probabilistic gene tree-species tree reconciliation methods.
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Affiliation(s)
- Brogan J Harris
- School of Biological Sciences, University of Bristol, Bristol, UK
| | - Paul O Sheridan
- School of Biological Sciences, University of Bristol, Bristol, UK
- School of Biological Sciences, University of Aberdeen, Aberdeen, UK
| | - Adrián A Davín
- Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia
| | | | - Gergely J Szöllősi
- Dept. of Biological Physics, Eötvös Loránd University, Budapest, Hungary
- MTA-ELTE "Lendület" Evolutionary Genomics Research Group, Budapest, Hungary
- Institute of Evolution, Centre for Ecological Research, Budapest, Hungary
| | - Tom A Williams
- School of Biological Sciences, University of Bristol, Bristol, UK.
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16
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Hasan CM, Dutta D, Nguyen ANT. Revisiting Antibiotic Resistance: Mechanistic Foundations to Evolutionary Outlook. Antibiotics (Basel) 2021; 11:antibiotics11010040. [PMID: 35052917 PMCID: PMC8773413 DOI: 10.3390/antibiotics11010040] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 11/22/2021] [Accepted: 11/23/2021] [Indexed: 12/12/2022] Open
Abstract
Antibiotics are the pivotal pillar of contemporary healthcare and have contributed towards its advancement over the decades. Antibiotic resistance emerged as a critical warning to public wellbeing because of unsuccessful management efforts. Resistance is a natural adaptive tool that offers selection pressure to bacteria, and hence cannot be stopped entirely but rather be slowed down. Antibiotic resistance mutations mostly diminish bacterial reproductive fitness in an environment without antibiotics; however, a fraction of resistant populations 'accidentally' emerge as the fittest and thrive in a specific environmental condition, thus favouring the origin of a successful resistant clone. Therefore, despite the time-to-time amendment of treatment regimens, antibiotic resistance has evolved relentlessly. According to the World Health Organization (WHO), we are rapidly approaching a 'post-antibiotic' era. The knowledge gap about antibiotic resistance and room for progress is evident and unified combating strategies to mitigate the inadvertent trends of resistance seem to be lacking. Hence, a comprehensive understanding of the genetic and evolutionary foundations of antibiotic resistance will be efficacious to implement policies to force-stop the emergence of resistant bacteria and treat already emerged ones. Prediction of possible evolutionary lineages of resistant bacteria could offer an unswerving impact in precision medicine. In this review, we will discuss the key molecular mechanisms of resistance development in clinical settings and their spontaneous evolution.
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Affiliation(s)
- Chowdhury M. Hasan
- School of Biological Sciences, University of Queensland, Brisbane 4072, Australia
- Department of Clinical Infection, Microbiology and Immunology, Institute of Infection, Veterinary & Ecological Sciences (IVES), University of Liverpool, Liverpool L7 3EA, UK;
- School of Biological Sciences, Monash University, Melbourne 3800, Australia;
- Correspondence:
| | - Debprasad Dutta
- Department of Clinical Infection, Microbiology and Immunology, Institute of Infection, Veterinary & Ecological Sciences (IVES), University of Liverpool, Liverpool L7 3EA, UK;
- Department of Human Genetics, National Institute of Mental Health & Neurosciences (NIMHANS), Bangalore 560029, India
| | - An N. T. Nguyen
- School of Biological Sciences, Monash University, Melbourne 3800, Australia;
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17
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Floridia-Yapur N, Rusman F, Diosque P, Tomasini N. Genome data vs MLST for exploring intraspecific evolutionary history in bacteria: Much is not always better. INFECTION, GENETICS AND EVOLUTION : JOURNAL OF MOLECULAR EPIDEMIOLOGY AND EVOLUTIONARY GENETICS IN INFECTIOUS DISEASES 2021; 93:104990. [PMID: 34224899 DOI: 10.1016/j.meegid.2021.104990] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 06/27/2021] [Accepted: 06/30/2021] [Indexed: 06/13/2023]
Abstract
Genome-based phylogeny has been proposed to be more accurate than phylogeny based in a few genes as MLST-based phylogeny. However, much is not always better. Here we analyzed 368 complete genomes corresponding to 9 bacterial species in order to address intraspecific phylogeny. The studied species were: Burkholderia pseudomallei, Campylobacter jejuni, Chlamydia trachomatis, Helicobacter pylori, Klebsiella pneumoniae, Listeria monocytogenes, Salmonella enterica, Staphylococcus aureus and Streptococcus pyogenes. The intra-specific phylogenies were inferred using the complete genome sequences of different strains of these species and their MLST schemes. A supermatrix approach was used to infer maximum likelihood phylogenies in both cases. The phylogenetic incongruence between the supermatrix-based genome or MLST tree and individual trees (constructed from genome fragments or MLST genes, respectively) was analyzed. In supermatrix-based trees for genomes, most branches showed a high branch support; however, a high number of branches also showed high percentage of topologically incongruent individual trees. Interestingly, genome and MLST trees showed similar levels of incongruence in the phylogeny for each bacteria specie. Both genome and MLST approaches showed that C. trachomatis and S. aureus have a tree-like evolutionary history (low levels of internal incongruence). Instead, B. pseudomallei and S. pyogenes show high levels of incongruence (network-like evolutionary story) probably caused by HGT (horizontal gene transfer). Concluding, our analysis showed that: high branch supports obtained in genome phylogenies could be an artifact probably caused by data size; MLST is valid to address intraspecific phylogenetic structure; and, each species has its own evolutionary history, which could be affected by HGT to different extents.
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Affiliation(s)
- Noelia Floridia-Yapur
- Instituto de Patología Experimental (IPE), UNSa-CONICET, Av. Bolivia 5150, Salta, Argentina
| | - Fanny Rusman
- Instituto de Patología Experimental (IPE), UNSa-CONICET, Av. Bolivia 5150, Salta, Argentina
| | - Patricio Diosque
- Instituto de Patología Experimental (IPE), UNSa-CONICET, Av. Bolivia 5150, Salta, Argentina
| | - Nicolás Tomasini
- Instituto de Patología Experimental (IPE), UNSa-CONICET, Av. Bolivia 5150, Salta, Argentina.
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18
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Rangel LT, Soucy SM, Setubal JC, Gogarten JP, Fournier GP. An efficient, non-phylogenetic method for detecting genes sharing evolutionary signals in phylogenomic datasets. Genome Biol Evol 2021; 13:6352501. [PMID: 34390574 PMCID: PMC8483891 DOI: 10.1093/gbe/evab187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/11/2021] [Indexed: 11/25/2022] Open
Abstract
Assessing the compatibility between gene family phylogenies is a crucial and often computationally demanding step in many phylogenomic analyses. Here, we describe the Evolutionary Similarity Index (IES), a means to assess shared evolution between gene families using a weighted orthogonal distance regression model applied to sequence distances. The utilization of pairwise distance matrices circumvents comparisons between gene tree topologies, which are inherently uncertain and sensitive to evolutionary model choice, phylogenetic reconstruction artifacts, and other sources of error. Furthermore, IES enables the many-to-many pairing of multiple copies between similarly evolving gene families. This is done by selecting non-overlapping pairs of copies, one from each assessed family, and yielding the least sum of squared residuals. Analyses of simulated gene family data sets show that IES’s accuracy is on par with popular tree-based methods while also less susceptible to noise introduced by sequence alignment and evolutionary model fitting. Applying IES to an empirical data set of 1,322 genes from 42 archaeal genomes identified eight major clusters of gene families with compatible evolutionary trends. The most cohesive cluster consisted of 62 genes with compatible evolutionary signal, which occur as both single-copy and multiple homologs per genome; phylogenetic analysis of concatenated alignments from this cluster produced a tree closely matching previously published species trees for Archaea. Four other clusters are mainly composed of accessory genes with limited distribution among Archaea and enriched toward specific metabolic functions. Pairwise evolutionary distances obtained from these accessory gene clusters suggest patterns of interphyla horizontal gene transfer. An IES implementation is available at https://github.com/lthiberiol/evolSimIndex.
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Affiliation(s)
- Luiz Thibério Rangel
- Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Corresponding author: E-mail:
| | - Shannon M Soucy
- Department of Biomedical Data Science, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, USA
| | - João C Setubal
- Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, Brasil
| | - Johann Peter Gogarten
- Department of Molecular and Cell Biology, University of Connecticut, USA
- Institute for Systems Genomics, University of Connecticut, USA
| | - Gregory P Fournier
- Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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19
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CHOPRA MEENU, BANDYOPADHYAY SAMIRAN, BHATTACHARYA DEBARAJ, BANERJEE JAYDEEP, SINGH RAVIKANT, SWARNKAR MOHIT, SINGH ANILKUMAR, DE SACHINANDAN. Genome based phylogeny and virulence factor analysis of mastitis causing Escherichia coli isolated from Indian cattle. THE INDIAN JOURNAL OF ANIMAL SCIENCES 2021; 90:1577-1583. [DOI: https:/doi.org/10.56093/ijans.v90i12.113165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/30/2023]
Abstract
Mastitis is a highly infectious disease prevalent in dairy cattle and it is majorly caused by Escherichia coli (E. coli). The objective of present study is to investigate the occurrence of virulence genes, antimicrobial susceptibility and comparative analysis of E. coli (IVRI KOL CP4 and CM IVRI KOL-1) isolates from mastitis infected animal. Whole-genome sequencing (WGS) was performed using a PacBio RS II system and de novo assembled using Hierarchical Genome Assembly Process (HGAP3). Bacterial Pan Genome Analysis Pipeline (BPGA) was used for pangenome analysis. A set of 50 E. coli isolates were used for comparative analysis (48 collected from the database and 2 reference sequences). Core genes were further concatenated for phylogenetic analyses. In silico analysis was performed for antibiotic resistance and virulence gene identification. Both of the E. coli isolates carried many resistance genes including, b-lactamase, quinolones, rifampicin, macrolide, aminoglycoside and phenicols resistance. We detected 39 virulence genes in IVRI KOL CP4 and 52 in CM IVRI KOL-1 which include toxins, adhesions, invasins, secretion machineries or iron acquisition system. High prevalence of mastitis strains belongs to phylogroups A, although few isolates were also assigned to phylogenetic groups B1 and B2. In conclusion, the present study reported the presence of genes involved in Adherence, Iron acquisition, secretion system and toxins which shown to be crucial in MPEC pathogenicity. This is the first whole genome analysis of MPEC strains to be carried out in Indian isolate to highlights the spread of resistance and virulence genes in food animals.
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20
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Brueckner J, Martin WF. Bacterial Genes Outnumber Archaeal Genes in Eukaryotic Genomes. Genome Biol Evol 2021; 12:282-292. [PMID: 32142116 PMCID: PMC7151554 DOI: 10.1093/gbe/evaa047] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/02/2020] [Indexed: 12/13/2022] Open
Abstract
Eukaryotes are typically depicted as descendants of archaea, but their genomes are evolutionary chimeras with genes stemming from archaea and bacteria. Which prokaryotic heritage predominates? Here, we have clustered 19,050,992 protein sequences from 5,443 bacteria and 212 archaea with 3,420,731 protein sequences from 150 eukaryotes spanning six eukaryotic supergroups. By downsampling, we obtain estimates for the bacterial and archaeal proportions. Eukaryotic genomes possess a bacterial majority of genes. On average, the majority of bacterial genes is 56% overall, 53% in eukaryotes that never possessed plastids, and 61% in photosynthetic eukaryotic lineages, where the cyanobacterial ancestor of plastids contributed additional genes to the eukaryotic lineage. Intracellular parasites, which undergo reductive evolution in adaptation to the nutrient rich environment of the cells that they infect, relinquish bacterial genes for metabolic processes. Such adaptive gene loss is most pronounced in the human parasite Encephalitozoon intestinalis with 86% archaeal and 14% bacterial derived genes. The most bacterial eukaryote genome sampled is rice, with 67% bacterial and 33% archaeal genes. The functional dichotomy, initially described for yeast, of archaeal genes being involved in genetic information processing and bacterial genes being involved in metabolic processes is conserved across all eukaryotic supergroups.
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Affiliation(s)
- Julia Brueckner
- Institute for Molecular Evolution, Heinrich Heine University Düsseldorf, Germany
| | - William F Martin
- Institute for Molecular Evolution, Heinrich Heine University Düsseldorf, Germany
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21
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Ibrahim A, Colson P, Merhej V, Zgheib R, Maatouk M, Naud S, Bittar F, Raoult D. Rhizomal Reclassification of Living Organisms. Int J Mol Sci 2021; 22:5643. [PMID: 34073251 PMCID: PMC8199106 DOI: 10.3390/ijms22115643] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 05/14/2021] [Accepted: 05/23/2021] [Indexed: 12/11/2022] Open
Abstract
Living organisms interact with each other during their lifetime, leading to genomes rearrangement and sequences transfer. These well-known phenomena give these organisms mosaic genomes, which challenge their classification. Moreover, many findings occurred between the IXXth and XXIst century, especially the discovery of giant viruses and candidate phyla radiation (CPR). Here, we tried to provide an updated classification, which integrates 216 representative genomes of the current described organisms. The reclassification was expressed through a genetic network based on the total genomic content, not on a single gene to represent the tree of life. This rhizomal exploration represents, more accurately, the evolutionary relationships among the studied species. Our analyses show a separated branch named fifth TRUC (Things Resisting Uncompleted Classifications). This taxon groups CPRs together, independently from Bacteria, Archaea (which regrouped also Nanoarchaeota and Asgard members), Eukarya, and the giant viruses (recognized recently as fourth TRUC). Finally, the broadening of analysis methods will lead to the discovery of new organisms, which justify the importance of updating the classification at every opportunity. In this perspective, our pragmatic representation could be adjusted along with the progress of evolutionary studies.
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Affiliation(s)
- Ahmad Ibrahim
- IHU Méditerranée Infection, 13005 Marseille, France; (A.I.); (P.C.); (V.M.); (R.Z.); (M.M.); (S.N.)
- Aix-Marseille Université, IRD, APHM, MEPHI, 13005 Marseille, France
| | - Philippe Colson
- IHU Méditerranée Infection, 13005 Marseille, France; (A.I.); (P.C.); (V.M.); (R.Z.); (M.M.); (S.N.)
- Aix-Marseille Université, IRD, APHM, MEPHI, 13005 Marseille, France
| | - Vicky Merhej
- IHU Méditerranée Infection, 13005 Marseille, France; (A.I.); (P.C.); (V.M.); (R.Z.); (M.M.); (S.N.)
- Aix-Marseille Université, IRD, APHM, MEPHI, 13005 Marseille, France
| | - Rita Zgheib
- IHU Méditerranée Infection, 13005 Marseille, France; (A.I.); (P.C.); (V.M.); (R.Z.); (M.M.); (S.N.)
- Aix-Marseille Université, IRD, APHM, SSA, VITROME, 13005 Marseille, France
| | - Mohamad Maatouk
- IHU Méditerranée Infection, 13005 Marseille, France; (A.I.); (P.C.); (V.M.); (R.Z.); (M.M.); (S.N.)
- Aix-Marseille Université, IRD, APHM, MEPHI, 13005 Marseille, France
| | - Sabrina Naud
- IHU Méditerranée Infection, 13005 Marseille, France; (A.I.); (P.C.); (V.M.); (R.Z.); (M.M.); (S.N.)
- Aix-Marseille Université, IRD, APHM, MEPHI, 13005 Marseille, France
| | - Fadi Bittar
- IHU Méditerranée Infection, 13005 Marseille, France; (A.I.); (P.C.); (V.M.); (R.Z.); (M.M.); (S.N.)
- Aix-Marseille Université, IRD, APHM, MEPHI, 13005 Marseille, France
| | - Didier Raoult
- IHU Méditerranée Infection, 13005 Marseille, France; (A.I.); (P.C.); (V.M.); (R.Z.); (M.M.); (S.N.)
- Aix-Marseille Université, IRD, APHM, MEPHI, 13005 Marseille, France
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22
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Coleman GA, Davín AA, Mahendrarajah TA, Szánthó LL, Spang A, Hugenholtz P, Szöllősi GJ, Williams TA. A rooted phylogeny resolves early bacterial evolution. Science 2021; 372:372/6542/eabe0511. [PMID: 33958449 DOI: 10.1126/science.abe0511] [Citation(s) in RCA: 89] [Impact Index Per Article: 29.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 11/05/2020] [Accepted: 04/01/2021] [Indexed: 12/17/2022]
Abstract
A rooted bacterial tree is necessary to understand early evolution, but the position of the root is contested. Here, we model the evolution of 11,272 gene families to identify the root, extent of horizontal gene transfer (HGT), and the nature of the last bacterial common ancestor (LBCA). Our analyses root the tree between the major clades Terrabacteria and Gracilicutes and suggest that LBCA was a free-living flagellated, rod-shaped double-membraned organism. Contrary to recent proposals, our analyses reject a basal placement of the Candidate Phyla Radiation, which instead branches sister to Chloroflexota within Terrabacteria. While most gene families (92%) have evidence of HGT, overall, two-thirds of gene transmissions have been vertical, suggesting that a rooted tree provides a meaningful frame of reference for interpreting bacterial evolution.
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Affiliation(s)
- Gareth A Coleman
- School of Biological Sciences, University of Bristol, Bristol BS8 1TQ, UK
| | - Adrián A Davín
- Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Queensland 4072, Australia
| | - Tara A Mahendrarajah
- Department of Marine Microbiology and Biogeochemistry, NIOZ, Royal Netherlands Institute for Sea Research, 1790 AB Den Burg, Netherlands
| | - Lénárd L Szánthó
- Department of Biological Physics, Eötvös Loránd University, 1117 Budapest, Hungary.,MTA-ELTE "Lendület" Evolutionary Genomics Research Group, 1117 Budapest, Hungary
| | - Anja Spang
- Department of Marine Microbiology and Biogeochemistry, NIOZ, Royal Netherlands Institute for Sea Research, 1790 AB Den Burg, Netherlands.,Department of Cell- and Molecular Biology, Uppsala University, SE-75123 Uppsala, Sweden
| | - Philip Hugenholtz
- Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Queensland 4072, Australia.
| | - Gergely J Szöllősi
- Department of Biological Physics, Eötvös Loránd University, 1117 Budapest, Hungary. .,MTA-ELTE "Lendület" Evolutionary Genomics Research Group, 1117 Budapest, Hungary.,Institute of Evolution, Centre for Ecological Research, 1121 Budapest, Hungary
| | - Tom A Williams
- School of Biological Sciences, University of Bristol, Bristol BS8 1TQ, UK.
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23
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Affiliation(s)
- Laura A Katz
- Department of Biological Sciences, Smith College, Northampton, MA, USA.
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24
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Nasir A, Mughal F, Caetano-Anollés G. The tree of life describes a tripartite cellular world. Bioessays 2021; 43:e2000343. [PMID: 33837594 DOI: 10.1002/bies.202000343] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2020] [Revised: 03/11/2021] [Accepted: 03/15/2021] [Indexed: 12/28/2022]
Abstract
The canonical view of a 3-domain (3D) tree of life was recently challenged by the discovery of Asgardarchaeota encoding eukaryote signature proteins (ESPs), which were treated as missing links of a 2-domain (2D) tree. Here we revisit the debate. We discuss methodological limitations of building trees with alignment-dependent approaches, which often fail to satisfactorily address the problem of ''gaps.'' In addition, most phylogenies are reconstructed unrooted, neglecting the power of direct rooting methods. Alignment-free methodologies lift most difficulties but require employing realistic evolutionary models. We argue that the discoveries of Asgards and ESPs, by themselves, do not rule out the 3D tree, which is strongly supported by comparative and evolutionary genomic analyses and vast genomic and biochemical superkingdom distinctions. Given uncertainties of retrodiction and interpretation difficulties, we conclude that the 3D view has not been falsified but instead has been strengthened by genomic analyses. In turn, the objections to the 2D model have not been lifted. The debate remains open. Also see the video abstract here: https://youtu.be/-6TBN0bubI8.
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Affiliation(s)
- Arshan Nasir
- Theoretical Biology and Biophysics (T-6), Los Alamos National Laboratory, Los Alamos, New Mexico, USA
| | - Fizza Mughal
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Gustavo Caetano-Anollés
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
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25
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Abstract
The advent of comparative genomics in the late 1990s led to the discovery of extensive lateral gene transfer in prokaryotes. The resulting debate over whether life as a whole is best represented as a tree or a network has since given way to a general consensus in which trees and networks co-exist rather than stand in opposition. Embracing this consensus allows us to move beyond the question of which is true or false. The future of the tree of life debate lies in asking what trees and networks can, and should, do for science.
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Affiliation(s)
- Cédric Blais
- Centre for Comparative Genomics and Evolutionary Bioinformatics, Dalhousie University, Halifax, NS, Canada; Department of Biochemistry and Molecular Biology, Dalhousie University, Halifax, NS, Canada.
| | - John M Archibald
- Centre for Comparative Genomics and Evolutionary Bioinformatics, Dalhousie University, Halifax, NS, Canada; Department of Biochemistry and Molecular Biology, Dalhousie University, Halifax, NS, Canada.
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26
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Nasir A, Romero-Severson E, Claverie JM. Investigating the Concept and Origin of Viruses. Trends Microbiol 2020; 28:959-967. [PMID: 33158732 PMCID: PMC7609044 DOI: 10.1016/j.tim.2020.08.003] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 08/25/2020] [Accepted: 08/27/2020] [Indexed: 12/21/2022]
Abstract
The ongoing COVID-19 pandemic has piqued public interest in the properties, evolution, and emergence of viruses. Here, we discuss how these basic questions have surprisingly remained disputed despite being increasingly within the reach of scientific analysis. We review recent data-driven efforts that shed light into the origin and evolution of viruses and explain factors that resist the widespread acceptance of new views and insights. We propose a new definition of viruses that is not restricted to the presence or absence of any genetic or physical feature, detail a scenario for how viruses likely originated from ancient cells, and explain technical and conceptual biases that limit our understanding of virus evolution. We note that the philosophical aspects of virus evolution also impact the way we might prepare for future outbreaks.
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Affiliation(s)
- Arshan Nasir
- Theoretical Biology and Biophysics (T-6), Los Alamos National Laboratory, Los Alamos, NM, USA.
| | - Ethan Romero-Severson
- Theoretical Biology and Biophysics (T-6), Los Alamos National Laboratory, Los Alamos, NM, USA
| | - Jean-Michel Claverie
- Aix Marseille University, CNRS, IGS, Structural and Genomic Information Laboratory (UMR7256), Mediterranean Institute of Microbiology (FR3479), Marseille, France
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27
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Hammerschmidt K, Landan G, Domingues Kümmel Tria F, Alcorta J, Dagan T. The Order of Trait Emergence in the Evolution of Cyanobacterial Multicellularity. Genome Biol Evol 2020; 13:5999801. [PMID: 33231627 PMCID: PMC7937182 DOI: 10.1093/gbe/evaa249] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/19/2020] [Indexed: 01/31/2023] Open
Abstract
The transition from unicellular to multicellular organisms is one of the most significant events in the history of life. Key to this process is the emergence of Darwinian individuality at the higher level: Groups must become single entities capable of reproduction for selection to shape their evolution. Evolutionary transitions in individuality are characterized by cooperation between the lower level entities and by division of labor. Theory suggests that division of labor may drive the transition to multicellularity by eliminating the trade off between two incompatible processes that cannot be performed simultaneously in one cell. Here, we examine the evolution of the most ancient multicellular transition known today, that of cyanobacteria, where we reconstruct the sequence of ecological and phenotypic trait evolution. Our results show that the prime driver of multicellularity in cyanobacteria was the expansion in metabolic capacity offered by nitrogen fixation, which was accompanied by the emergence of the filamentous morphology and succeeded by a reproductive life cycle. This was followed by the progression of multicellularity into higher complexity in the form of differentiated cells and patterned multicellularity.
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Affiliation(s)
- Katrin Hammerschmidt
- Genomic Microbiology Group, Institute of Microbiology, Kiel University, Germany,Corresponding author: E-mail:
| | - Giddy Landan
- Genomic Microbiology Group, Institute of Microbiology, Kiel University, Germany
| | | | - Jaime Alcorta
- Department of Molecular Genetics and Microbiology, Biological Sciences Faculty, Pontifical Catholic University of Chile, Santiago, Chile
| | - Tal Dagan
- Genomic Microbiology Group, Institute of Microbiology, Kiel University, Germany
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28
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Nagies FSP, Brueckner J, Tria FDK, Martin WF. A spectrum of verticality across genes. PLoS Genet 2020; 16:e1009200. [PMID: 33137105 PMCID: PMC7660906 DOI: 10.1371/journal.pgen.1009200] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 11/12/2020] [Accepted: 10/16/2020] [Indexed: 12/19/2022] Open
Abstract
Lateral gene transfer (LGT) has impacted prokaryotic genome evolution, yet the extent to which LGT compromises vertical evolution across individual genes and individual phyla is unknown, as are the factors that govern LGT frequency across genes. Estimating LGT frequency from tree comparisons is problematic when thousands of genomes are compared, because LGT becomes difficult to distinguish from phylogenetic artefacts. Here we report quantitative estimates for verticality across all genes and genomes, leveraging a well-known property of phylogenetic inference: phylogeny works best at the tips of trees. From terminal (tip) phylum level relationships, we calculate the verticality for 19,050,992 genes from 101,422 clusters in 5,655 prokaryotic genomes and rank them by their verticality. Among functional classes, translation, followed by nucleotide and cofactor biosynthesis, and DNA replication and repair are the most vertical. The most vertically evolving lineages are those rich in ecological specialists such as Acidithiobacilli, Chlamydiae, Chlorobi and Methanococcales. Lineages most affected by LGT are the α-, β-, γ-, and δ- classes of Proteobacteria and the Firmicutes. The 2,587 eukaryotic clusters in our sample having prokaryotic homologues fail to reject eukaryotic monophyly using the likelihood ratio test. The low verticality of α-proteobacterial and cyanobacterial genomes requires only three partners-an archaeal host, a mitochondrial symbiont, and a plastid ancestor-each with mosaic chromosomes, to directly account for the prokaryotic origin of eukaryotic genes. In terms of phylogeny, the 100 most vertically evolving prokaryotic genes are neither representative nor predictive for the remaining 97% of an average genome. In search of factors that govern LGT frequency, we find a simple but natural principle: Verticality correlates strongly with gene distribution density, LGT being least likely for intruding genes that must replace a preexisting homologue in recipient chromosomes. LGT is most likely for novel genetic material, intruding genes that encounter no competing copy.
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Affiliation(s)
- Falk S. P. Nagies
- Institute for Molecular Evolution, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Julia Brueckner
- Institute for Molecular Evolution, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Fernando D. K. Tria
- Institute for Molecular Evolution, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - William F. Martin
- Institute for Molecular Evolution, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
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DeSalle R, Riley M. Should Networks Supplant Tree Building? Microorganisms 2020; 8:E1179. [PMID: 32756444 PMCID: PMC7466111 DOI: 10.3390/microorganisms8081179] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 07/21/2020] [Accepted: 07/29/2020] [Indexed: 12/15/2022] Open
Abstract
Recent studies suggested that network methods should supplant tree building as the basis of genealogical analysis. This proposition is based upon two arguments. First is the observation that bacterial and archaeal lineages experience processes oppositional to bifurcation and hence the representation of the evolutionary process in a tree like structure is illogical. Second is the argument tree building approaches are circular-you ask for a tree and you get one, which pins a verificationist label on tree building that, if correct, should be the end of phylogenetic analysis as we currently know it. In this review, we examine these questions and suggest that rumors of the death of the bacterial tree of life are exaggerated at best.
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Affiliation(s)
- Rob DeSalle
- Sackler Institute for Comparative Genomics, American Museum of Natural History, Central Park West at 79th Street, New York, NY 10024, USA;
| | - Margaret Riley
- Department of Biology, University of Massachusetts Amherst, 116 North Pleasant Street, Amherst, MA 01003, USA
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How to Study Classification. Cladistics 2020. [DOI: 10.1017/9781139047678.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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31
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Classification. Cladistics 2020. [DOI: 10.1017/9781139047678.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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32
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Systematics Association Special Volumes. Cladistics 2020. [DOI: 10.1017/9781139047678.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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33
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Relationship Diagrams. Cladistics 2020. [DOI: 10.1017/9781139047678.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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34
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The Separation of Classification and Phylogenetics. Cladistics 2020. [DOI: 10.1017/9781139047678.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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35
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Beyond Classification. Cladistics 2020. [DOI: 10.1017/9781139047678.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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36
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The Interrelationships of Organisms. Cladistics 2020. [DOI: 10.1017/9781139047678.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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37
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How to Study Classification. Cladistics 2020. [DOI: 10.1017/9781139047678.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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38
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Modern Artificial Methods and Raw Data. Cladistics 2020. [DOI: 10.1017/9781139047678.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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39
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Further Myths and More Misunderstandings. Cladistics 2020. [DOI: 10.1017/9781139047678.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
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40
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Afterword. Cladistics 2020. [DOI: 10.1017/9781139047678.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
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41
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Systematics: Exposing Myths. Cladistics 2020. [DOI: 10.1017/9781139047678.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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42
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Essentialism and Typology. Cladistics 2020. [DOI: 10.1017/9781139047678.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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43
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Beyond Classification: How to Study Phylogeny. Cladistics 2020. [DOI: 10.1017/9781139047678.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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44
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How to Study Classification: ‘Total Evidence’ vs. ‘Consensus’, Character Congruence vs. Taxonomic Congruence, Simultaneous Analysis vs. Partitioned Data. Cladistics 2020. [DOI: 10.1017/9781139047678.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
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45
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What This Book Is About. Cladistics 2020. [DOI: 10.1017/9781139047678.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
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46
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How to Study Classification. Cladistics 2020. [DOI: 10.1017/9781139047678.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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47
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The Cladistic Programme. Cladistics 2020. [DOI: 10.1017/9781139047678.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
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48
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Index. Cladistics 2020. [DOI: 10.1017/9781139047678.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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49
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Parameters of Classification: Ordo Ab Chao. Cladistics 2020. [DOI: 10.1017/9781139047678.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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50
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Monothetic and Polythetic Taxa. Cladistics 2020. [DOI: 10.1017/9781139047678.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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