Algal genomes reveal evolutionary mosaicism and the fate of nucleomorphs

Journal name:
Nature
Volume:
492,
Pages:
59–65
Date published:
DOI:
doi:10.1038/nature11681
Received
Accepted
Published online

Abstract

Cryptophyte and chlorarachniophyte algae are transitional forms in the widespread secondary endosymbiotic acquisition of photosynthesis by engulfment of eukaryotic algae. Unlike most secondary plastid-bearing algae, miniaturized versions of the endosymbiont nuclei (nucleomorphs) persist in cryptophytes and chlorarachniophytes. To determine why, and to address other fundamental questions about eukaryote–eukaryote endosymbiosis, we sequenced the nuclear genomes of the cryptophyte Guillardia theta and the chlorarachniophyte Bigelowiella natans. Both genomes have >21,000protein genes and are intron rich, and B. natans exhibits unprecedented alternative splicing for a single-celled organism. Phylogenomic analyses and subcellular targeting predictions reveal extensive genetic and biochemical mosaicism, with both host- and endosymbiont-derived genes servicing the mitochondrion, the host cell cytosol, the plastid and the remnant endosymbiont cytosol of both algae. Mitochondrion-to-nucleus gene transfer still occurs in both organisms but plastid-to-nucleus and nucleomorph-to-nucleus transfers do not, which explains why a small residue of essential genes remains locked in each nucleomorph.

At a glance

Figures

  1. Cryptophyte and chlorarachniophyte cell biology.
    Figure 1: Cryptophyte and chlorarachniophyte cell biology.

    The cryptophyte alga G. theta and the chlorarachniophyte alga B. natans have plastids bound by four membranes. In cryptophytes, the outermost plastid membrane is continuous with the nuclear envelope and its surface is studded with ribosomes, which co-translationally insert nucleus-encoded, organelle-targeted proteins. Between the inner and outer membrane pairs is the periplastidial compartment (PPC), which contains the nucleomorph (NM), the relict nucleus of the eukaryotic endosymbiont. The predicted numbers of protein-coding genes in the plastid, mitochondrial (MT), nucleomorph and nuclear genomes of G. theta and B. natans are shown. Additional abbreviations: C, carbohydrate; PY, pyrenoid.

  2. Complexity of the periplastidial compartment in cryptophytes and chlorarachniophytes.
    Figure 2: Complexity of the periplastidial compartment in cryptophytes and chlorarachniophytes.

    a, Histogram showing the number of proteins predicted to be targeted to the PPC of G. theta and B. natans broken down by KOG functional category. For each KOG category, nucleomorph (NM)- and nucleus (NU)-encoded proteins are shown (PPC proteins predicted to be targeted to more than one subcellular compartment were removed; see Supplementary Fig. 1.9.4.1.2). b, Histogram showing the diversity of protein functions in the G. theta and B. natans PPC relative to free-living organisms (colour-coding as in a). Numbers of distinct KOG identifiers (IDs) in the PPC proteomes are plotted as a percentage of the average number of KOG IDs across 25KOG categories for 6organisms: Chlamydomonas reinhardtii, Ostreococcus tauri, Arabidopsis lyrata, Emiliania huxleyi, Dictyostelium purpureum and Phaeodactylum tricornutum (see Supplementary Information 1.9.4.3). Plastid and mitochondrial proteins were removed before calculating the averages (see Supplementary Information). KOG categories are as follows: A, RNA processing and modification; B, chromatin structure and dynamics; C, energy production and conversion; D, cell cycle control, cell division and chromosome partitioning; E, amino acid transport and metabolism; F, nucleotide transport and metabolism; G, carbohydrate transport and metabolism; H, coenzyme transport and metabolism; I, lipid transport and metabolism; J, translation, ribosomal structure and biogenesis; K, transcription; L, replication, recombination and repair; M, cell wall, membrane or envelope biogenesis; N, cell motility; O, post-translational modification, protein turnover, chaperones; P, inorganic ion transport and metabolism; Q, secondary metabolites biosynthesis, transport and catabolism; R, general function prediction only; S, function unknown; T, signal transduction; U, intracellular trafficking, secretion and vesicular transport; V, defence mechanisms; W, extracellular structures; Y, nuclear structure; Z, cytoskeleton. Higher KOG categories are as follows: CP, cellular processing and signalling; Hyp, poorly characterized; Inf, information storage and processing; Met, metabolism.

  3. Algal genes in the Bigelowiella natans and Guillardia theta nuclear genomes and the predicted subcellular locations of their protein products.
    Figure 3: Algal genes in the Bigelowiella natans and Guillardia theta nuclear genomes and the predicted subcellular locations of their protein products.

    a, Histogram showing the proportion of ‘algal’ genes or proteins and their inferred origin by automated tree sorting and manual curation; bar height is relative to the total number of trees built for each organism and the raw counts are indicated on the bars (Supplementary Fig. 1.12.3). Exclusive affiliations are those in which the B. natans or G. theta homologue forms a clade solely with the group in question (for example, red algae), whereas inclusive affiliations enable sequences from other secondary and/or tertiary plastid-bearing algae within the clade to be present. ‘Green’ is defined as chlorophyte and/or streptophyte algae (including land plants). ‘Only plantae’ means trees containing only sequences from green algae and/or red algae and/or glaucophytes; algal origin therefore cannot be inferred with confidence. Only trees in the ‘red’, ‘green’ and ‘glaucophyte’ categories provide unambiguous information on the specific evolutionary origin of the B. natans or G. theta proteins. b, Pie charts showing the predicted locations of the algal proteins presented in a. Endoplasmic reticulum and Golgi proteins are those identified at the level of 75% confidence (see Supplementary Information 1.9.3). The ‘cytosolic’ category includes all proteins with no positive prediction for any of the four proteomes investigated.

Accession codes

Primary accessions

GenBank/EMBL/DDBJ

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Author information

Affiliations

  1. Department of Biochemistry and Molecular Biology, Dalhousie University, Halifax, Nova Scotia B3H 4R2, Canada

    • Bruce A. Curtis,
    • Goro Tanifuji,
    • Shinichiro Maruyama,
    • Gillian H. Gile,
    • Julia F. Hopkins,
    • Robert J. M. Eveleigh,
    • Takuro Nakayama,
    • Shehre-Banoo Malik,
    • Naoko T. Onodera,
    • Claudio H. Slamovits,
    • David F. Spencer,
    • Christopher E. Lane,
    • Michael W. Gray &
    • John M. Archibald
  2. Centre for Comparative Genomics and Evolutionary Bioinformatics, Dalhousie University, Halifax, Nova Scotia B3H 4R2, Canada

    • Bruce A. Curtis,
    • Goro Tanifuji,
    • Shinichiro Maruyama,
    • Gillian H. Gile,
    • Julia F. Hopkins,
    • Robert J. M. Eveleigh,
    • Takuro Nakayama,
    • Shehre-Banoo Malik,
    • Naoko T. Onodera,
    • Claudio H. Slamovits,
    • David F. Spencer,
    • Christopher E. Lane,
    • Michael W. Gray &
    • John M. Archibald
  3. Integrated Microbial Biodiversity Program, Canadian Institute for Advanced Research, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada

    • Bruce A. Curtis,
    • Goro Tanifuji,
    • Fabien Burki,
    • Shinichiro Maruyama,
    • Gillian H. Gile,
    • Yoshihisa Hirakawa,
    • Julia F. Hopkins,
    • Takuro Nakayama,
    • Adrian Reyes-Prieto,
    • Shehre-Banoo Malik,
    • Naoko T. Onodera,
    • Claudio H. Slamovits,
    • David F. Spencer,
    • Christopher E. Lane,
    • Patrick J. Keeling,
    • Michael W. Gray &
    • John M. Archibald
  4. Department of Botany, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada

    • Fabien Burki,
    • Yoshihisa Hirakawa,
    • Naomi M. Fast,
    • Beverley R. Green,
    • Cameron J. Grisdale &
    • Patrick J. Keeling
  5. Fachbereich Biologie, Universität Konstanz, 78457 Konstanz, Germany

    • Ansgar Gruber &
    • Peter G. Kroth
  6. Banting and Best Department of Medical Research and Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada

    • Manuel Irimia
  7. Unité de Glycobiologie Structurale et Fonctionnelle, UMR 8576 CNRS-USTL, Université des Sciences et Technologies de Lille, 59655 Villeneuve d’Ascq Cedex, France

    • Maria C. Arias &
    • Steven G. Ball
  8. US Department of Energy Joint Genome Institute, Walnut Creek, California 94598, USA

    • Alan Kuo,
    • Jeremy Schmutz,
    • Kerrie Barry,
    • Jane Grimwood,
    • Erika Lindquist,
    • Susan Lucas,
    • Asaf Salamov &
    • Igor V. Grigoriev
  9. Faculty of Biology and BIOSS Centre for Biological Signalling Studies, University of Freiburg, 79085 Freiburg, Germany

    • Stefan A. Rensing &
    • Aikaterini Symeonidi
  10. HudsonAlpha Genome Sequencing Center, 601 Genome Way, Huntsville, Alabama 35806, USA

    • Jeremy Schmutz &
    • Jane Grimwood
  11. University of Ostrava, Faculty of Science, Department of Biology and Ecology, Life Science Research Centre, 710 00 Ostrava, Czech Republic

    • Marek Elias
  12. Genome Quebec, 740 Docteur-Penfield Avenue, Montreal, Quebec H3A 1A4, Canada

    • Robert J. M. Eveleigh
  13. Department of Cell Biology, University of Alberta, Edmonton, Alberta T6G 2H7, Canada

    • Emily K. Herman,
    • Mary J. Klute &
    • Joel B. Dacks
  14. University of South Bohemia, Faculty of Science, Branišovská 31, 37005 České Budějovice, Czech Republic

    • Miroslav Oborník &
    • Luděk Kořený
  15. Biology Centre, Academy of Sciences of the Czech Republic, Institute of Parasitology, Branišovská 31, 37005 České Budějovice, Czech Republic

    • Miroslav Oborník &
    • Luděk Kořený
  16. Institute of Microbiology, Academy of Sciences of the Czech Republic, 37981 Třeboň, Czech Republic

    • Miroslav Oborník
  17. Department of Biology, University of New Brunswick, Fredericton, New Brunswick E3B 5A3, Canada

    • Adrian Reyes-Prieto,
    • Dion G. Durnford &
    • Jonathan A. D. Neilson
  18. School of Oceanography, University of Washington, Seattle, Washington 98195-7940, USA

    • E. Virginia Armbrust &
    • Gabrielle Rocap
  19. Biosciences, College of Life and Environmental Sciences, University of Exeter, Stocker Road, Exeter EX4 4QD, UK

    • Stephen J. Aves &
    • Yuan Liu
  20. Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia B3H 4R2, Canada

    • Robert G. Beiko
  21. Architecture et Fonction des Macromolécules Biologiques, Aix-Marseille Université, CNRS UMR 7257, 163 avenue de Luminy, 13228 Marseille, France

    • Pedro Coutinho &
    • Bernard Henrissat
  22. LOEWE-Zentrum für Synthetische Mikrobiologie (Synmikro), Hans-Meerwein-Straße, D-35032 Marbug, Germany

    • Franziska Hempel,
    • Uwe G. Maier &
    • Stefan Zauner
  23. Science for Life Laboratory, Department of Medical Biochemistry and Microbiology Uppsala University, SE-751 23 Uppsala, Sweden

    • Marc P. Höppner
  24. Graduate School of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Ibaraki 305-8572, Japan

    • Ken-Ichiro Ishida,
    • Chihiro Sarai,
    • Shu Shirato &
    • Shigekatsu Suzuki
  25. American Museum of Natural History, Division of Invertebrate Zoology, New York, New York 10024, USA

    • Eunsoo Kim
  26. The Natural History Museum, Cromwell Road, London SW7 5BD, UK

    • Yuan Liu &
    • Thomas A. Richards
  27. Monterey Bay Aquarium Research Institute (MBARI), 7700 Sandholdt Road, Moss Landing, California 95039, USA

    • Darcy McRose &
    • Alexandra Z. Worden
  28. School of Environmental Sciences, University of East Anglia, Norwich Research Park, Norwich NR47TJ, UK

    • Thomas Mock
  29. Biomolecular Interaction Centre & School of Biological Sciences, University of Canterbury, Christchurch 8140, New Zealand

    • Anthony M. Poole
  30. Eccles Institute of Human Genetics, Salt Lake City, Utah 84112, USA

    • Ellen J. Pritham
  31. San Francisco State University, San Francisco, California 94132, USA

    • Scott W. Roy
  32. Reed College, Portland, Oregon 97202, USA

    • Sarah Schaack
  33. National Center for Genome Resources, Rodeo Park Drive East, Santa Fe, New Mexico 87505, USA

    • Callum Bell,
    • Arvind K. Bharti,
    • John A. Crow &
    • Robin Kramer
  34. School of Botany, University of Melbourne, Victoria 3010, Australia

    • Geoffrey I. McFadden
  35. University of Rhode Island, Kingston, Rhode Island 02881, USA

    • Christopher E. Lane
  36. Present addresses: Department of Biochemistry and Molecular Biology, Dalhousie University, Halifax, Nova Scotia B3H 4R2, Canada (A.G.); Fachbereich Biologie, Philipps-Universität Marburg, Karl-von-Frisch Straße 8, 35043 Marburg, Germany (S.A.R.).

    • Ansgar Gruber &
    • Stefan A. Rensing

Contributions

Nucleic acid sample preparation: C.E.L., D.F.S. and J.F.H. Genome and transcriptome sequencing and assembly: J.S., J.G., C.B., A.K.B., J.A.C., R.K., E.L. and S.L. Genome annotation and/or analysis: B.A.C., G.T., F.B., A.G., M.I., S.M., M.C.A., S.G.B., G.H.G., Y.H., J.F.H., A.K., S.A.R., J.S., A. Symeonidi, M.E., R.J.M.E., E.K.H., M.J.K., T.N., M.O., A.R.-P., E.V.A., S.J.A., R.G.B., P.C., J.B.D., D.G.D., N.M.F., B.R.G., C.J.G., F.H., B.H., M.P.H., K.-I.I., E.K., L.K., P.G.K., Y.L., S.-B.M., U.G.M., D.M., T.M., J.A.D.N., N.T.O., A.M.P., E.J.P., T.A.R., G.R., S.W.R., C.S., S. Schaack., S. Shirato, C.H.S., S. Suzuki, A.Z.W., S.Z., J.G., A. Salamov, C.E.L., M.W.G. and J.M.A. Project management: K.B., I.V.G. and J.S. Project coordination: J.M.A., M.W.G., P.J.K., C.E.L. and G.I.M. Writing: J.M.A., B.A.C., M.W.G., G.I.M., P.J.K., C.E.L., G.T., F.B., A.G., M.I., S.M., M.C.A., S.G.B., G.H.G., J.F.H., A.K., S.A.R., J.S., A. Symeonidi, R.J.M.E., E.K.H., M.J.K., T.N., A.R.-P., J.B.D., E.K., P.G.K., E.J.P., S.W.R., S.S., A.K.B. and I.V.G.

Competing financial interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to:

The G. theta and B. natans genome sequences and annotations are available through the JGI Genome Portal at http://jgi.doe.gov/Gtheta and http://jgi.doe.gov/Bnatans and have been deposited in GenBank under the accession numbers AEIE00000000 and ADNK00000000, respectively.

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Supplementary information

PDF files

  1. Supplementary Information (10.2M)

    This file contains Supplementary Methods, Data and Analyses for the Guillardia theta and Bigelowiella natans nuclear genome sequences. Supplementary References, 35 Supplementary Figures and 24 Supplementary Tables are also included (see Table of Contents for more details).

Excel files

  1. Supplementary Table S1.9.4.2.1 (79K)

    This file contains datasets used for support vector machine prediction of PPC proteins in Bigelowiella natans and Guillardia theta.

  2. Supplementary Table S1.9.4.2.2 (22K)

    This file contains dataset sizes used for support vector machine prediction of PPC proteins in Bigelowiella natans and Guillardia theta.

  3. Supplementary Table S1.12.1 (107K)

    This file contains a list of taxa used in phylogenomic analyses of the nuclear genomes of Bigelowiella natans and Guillardia theta.

  4. Supplementary Table S2.3.3 (56K)

    This file contains proteins identified in the search for putative carbohydrate-active enzymes in Guillardia theta.

  5. Supplementary Table S2.3.4 (50K)

    This file contains proteins identified in the search for putative carbohydrate-active enzymes in Bigelowiella natans.

  6. Supplementary Table S2.3.4.1 (27K)

    This file contains a list of proteins possibly involved in the ER-localized synthesis of N-glycanes in Guillardia theta and Bigelowiella natans.

Additional data