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On the Age of Eukaryotes: Evaluating Evidence from Fossils and Molecular Clocks

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On the Age of Eukaryotes: Evaluating Evidence from Fossils and Molecular Clocks Downloaded from http://cshperspectives.cshlp.org/ on October 6, 2021 - Published by Cold Spring Harbor Laboratory Press On the Age of Eukaryotes: Evaluating Evidence from Fossils and Molecular Clocks Laura Eme, Susan C. Sharpe, Matthew W. Brown1, and Andrew J. Roger Centre for Comparative Genomics and Evolutionary Bioinformatics, Department of Biochemistry and Molecular Biology, Dalhousie University, Halifax B3H 4R2, Canada Correspondence: [email protected] Our understanding of the phylogenetic relationships among eukaryotic lineages has im- proved dramatically over the few past decades thanks to the development of sophisticated phylogenetic methods and models of evolution, in combination with the increasing avail- ability of sequence data for a variety of eukaryotic lineages. Concurrently, efforts have been made to infer the age of major evolutionary events along the tree of eukaryotes using fossil- calibrated molecular clock-based methods. Here, we review the progress and pitfalls in estimating the age of the last eukaryotic common ancestor (LECA) and major lineages. After reviewing previous attempts to date deep eukaryote divergences, we present the results of a Bayesian relaxed-molecular clock analysis of a large dataset (159 proteins, 85 taxa) using 19 fossil calibrations. We show that for major eukaryote groups estimated dates of divergence, as well as their credible intervals, are heavily influenced by the relaxed molec- ular clock models and methods used, and by the nature and treatment of fossil calibrations. Whereas the estimated age of LECA varied widely, ranging from 1007 (943–1102) Ma to 1898 (1655–2094) Ma, all analyses suggested that the eukaryotic supergroups subsequently diverged rapidly (i.e., within 300 Ma of LECA). The extreme variability of these and previ- ously published analyses preclude definitive conclusions regarding the age of major eukary- ote clades at this time. As more reliable fossil data on eukaryotes from the Proterozoic become available and improvements are made in relaxed molecular clock modeling, we may be able to date the age of extant eukaryotes more precisely. ur conception of the tree of eukaryotes has came clear that the deep structure of the rRNA Ochanged dramatically over the last few tree was the result of a methodological artifact decades. In the 1980s and early 1990s, prevailing known as long branch attraction (LBA) (Budin views were based on small subunit ribosomal and Philippe 1998; Roger et al. 1999; Philippe RNA (SSU rRNA) gene phylogenies (e.g., Sogin et al. 2000a,b). Analyses based on multiple pro- 1991). However, as multiple protein-coding tein genes instead hinted at the existence of gene datasets were developed and more sophis- higher-level eukaryotic “supergroups” that en- ticated phylogenetic methods were used, it be- compassed both protistan and multicellular eu- 1Current address: Department of Biological Sciences, Mississippi State University, Mississippi State, MS. Editors: Patrick J. Keeling and Eugene V. Koonin Additional Perspectives on The Origin and Evolution of Eukaryotes available at www.cshperspectives.org Copyright # 2014 Cold Spring Harbor Laboratory Press; all rights reserved; doi: 10.1101/cshperspect.a016139 Cite this article as Cold Spring Harb Perspect Biol 2014;6:a016139 1 Downloaded from http://cshperspectives.cshlp.org/ on October 6, 2021 - Published by Cold Spring Harbor Laboratory Press L. Eme et al. karyotic lineages (Baldauf et al. 2000). More THE EUKARYOTIC TREE OF LIFE recently, a better understanding of protistan ultrastructural diversity and the development Estimates of divergence dates from molecular of phylogenomic approaches have refined this clock analyses are only meaningful if the phy- picture and further delineated these groups (see logeny on which they are based is correct. How- also Fig. 1) (Bapteste et al. 2002; Burki et al. ever, recovering deep phylogenetic relationships 2007; Hampl et al. 2009; Brown et al. 2012; among eukaryotes has proven to be an extreme- Zhao et al. 2012). ly challenging task. As our understanding of eukaryote phylog- The most recent conceptions of the eukary- eny improved, fossil-calibrated molecularclock- otic tree of life feature five or six “supergroups” based methods were beginning to be applied to (Keeling et al. 2005; Roger and Simpson 2009; date the major diversification events in this do- Burki 2014) including Opisthokonta, Amoebo- main (Hedges et al. 2001; Douzery et al. 2004; zoa, Excavata, the SAR group, Archaeplastida, Hedges and Kumar 2004; Berney and Pawlowski and Hacrobia (Haptophyta and Cryptophyta). 2006; Parfrey et al. 2011). Molecular clock anal- Whereas phylogenomic analyses robustly re- yses were first introduced by Zuckerkandl and cover the monophyly of Opisthokonta, Amoe- Pauling (1965). Theyshowed that the differences bozoa and SAR, the phylogenetic coherence of between homologous proteins of different spe- Excavata, Archaeplastida, and Hacrobia is less cies are approximately proportional to their di- certain (see also Fig. 1) (Burki et al. 2008, 2012; vergence time. Since then, sophisticated RMC Hampl et al. 2009; Parfrey et al. 2010; Brown methods have been developed that combine fos- et al. 2012; Zhao et al. 2012; Burki 2014). sil data with molecular phylogenies for the in- Another challenge inherent to dating an- ference of divergence times. However, attempts cient events in eukaryotic evolution is the cur- to estimate the age of deep divisions within rent uncertainty regarding the location of the eukaryotes using these methods have yielded root (Stechmann and Cavalier-Smith 2002, vastly different estimates (e.g., see Douzery et al. 2003a,b; Cavalier-Smith 2010; Derelle and 2004 vs. Hedges et al. 2004). These discrepan- Lang 2012; Katz et al. 2012). Tackling this ques- cies can be explained by a myriad of sources of tion is made especially difficult by the absence variability and error including (1) the assumed of closely related outgroups to eukaryotes. The phylogeny of eukaryotes, (2) the sparse fossil large phylogenetic distance between sequences record of protists and other organisms lacking from eukaryotes and their archaeal or bacterial hard structures for fossilization, (3) how fossil orthologs makes their use as outgroups highly constraints are applied to phylogenetic trees, prone to phylogenetic artefacts like LBA (Fel- (4) methods and models used in RMC analysis, senstein 1978; Roger and Hug 2006). Conse- and (5) the selection of taxa and genes included. quently, various alternative methods have been Here, we review the progress and pitfalls in used in the last decade, yielding different results estimating the age of the last eukaryotic com- regarding the placement of the root; between mon ancestor (LECA) and supergroups using Amorphea (or “unikonts”) and all othereukary- molecular clock-based analyses. We first discuss otes (i.e., “bikonts”) (Richards and Cavalier- recent progress in our understanding of eukary- Smith 2005; Roger and Simpson 2009; Cava- otic phylogeny and the ancient eukaryotic fos- lier-Smith 2010), which, despite being the cur- sil record, and then we review the development rent leading working hypothesis, is challenged of molecular clock-based methods and how by several lines of evidence (Arisue et al. 2005; fossil constraints are treated. Next, we describe Roger and Simpson 2009): at the base of an attempts to date ancient eukaryotic divergences Excavata lineage, Euglenozoa (Cavalier-Smith using RMC methods. Finally, we present an 2010); between Archaeplastida and other eu- RMC analysis of a very large dataset comprised karyotes (Rogozin et al. 2009; Koonin 2010); of 159 proteins and 85 taxa, using 19 fossil cal- and between Opisthokonta and other eukary- ibrations. otes (Katz et al. 2012). Therefore, although the 2 Cite this article as Cold Spring Harb Perspect Biol 2014;6:a016139 Downloaded from http://cshperspectives.cshlp.org/ on October 6, 2021 - Published by Cold Spring Harbor Laboratory Press Evaluating Evidence from Fossils Schizosaccharomyces pombe Coprinus cinereus Blastocladiella emersonii Allomyces macrogynus Batrachochytrium dendrobatidis Spizellomyces punctatus Fonticula alba Amoebidium parasiticum Sphaeroforma arctica 97 Ministeria vibrans Capsaspora owczarzaki Salpingoeca rosetta Opisthokonta Monosiga brevicollis Amphimedon queenslandica Nematostella vectensis Obazoa Apis mellifera Amorphea 52 Drosophila melanogaster Caenorhabditis elegans Taenia solium 99 Schistosoma mansoni Branchiostoma floridae 99 Gallus gallus Homo sapiens Thecamonas trahens Pygsuia biforma Amorphea Mastigamoeba balamuthi Physarum polycephalum Dictyostelium discoideum Polysphondylium pallidum Amoebozoa Acanthamoeba castellanii Copromyxa protea Trimastix pyriformis 93 Giardia lamblia Trichomonas vaginalis Sawyeria marylandensis 92 Naegleria gruberi Euglena gracilis Bodo saltans 99 Trypanosoma brucei Excavata Andalucia incarcerata 54 99 Reclinomonas americana Jakoba libera Malawimonas californiana Malawimonas jakobiformis Gromia sphaerica Bigelowiella natans Guttulinopsis vulgaris Rhizaria Paulinella chromatophora Tetrahymena thermophila Excavata Paramecium tetraurelia Perkinsus marinus Alveolata Oxyrrhis marina 97 Symbiodinium sp. k8 Alexandrium minutum Cryptosporidium parvum SAR 82 Toxoplasma gondii Blastocystis hominis Phaeodactylum tricornutum 75 Thalassiosira pseudonana Pelagophyceae CCMP2097 Stramenopiles Ectocarpus siliculosus 76 Ochromonas sp. CCMP1393 Chyrsophyceae CCMP2298 55 Phytophthora infestans Guillardia theta Roombia truncata Cryptophyta Micromonas
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