Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Analysis
  • Published:

Systematic evaluation of horizontal gene transfer between eukaryotes and viruses

Nature Microbiology volume 7, pages 327–336 (2022)Cite this article

Subjects

Abstract

Gene exchange between viruses and their hosts acts as a key facilitator of horizontal gene transfer and is hypothesized to be a major driver of evolutionary change. Our understanding of this process comes primarily from bacteria and phage co-evolution, but the mode and functional importance of gene transfers between eukaryotes and their viruses remain anecdotal. Here we systematically characterized viral–eukaryotic gene exchange across eukaryotic and viral diversity, identifying thousands of transfers and revealing their frequency, taxonomic distribution and projected functions. Eukaryote-derived viral genes, abundant in the Nucleocytoviricota, highlighted common strategies for viral host-manipulation, including metabolic reprogramming, proteolytic degradation and extracellular modification. Furthermore, viral-derived eukaryotic genes implicate genetic exchange in the early evolution and diversification of eukaryotes, particularly through viral-derived glycosyltransferases, which have impacted structures as diverse as algal cell walls, trypanosome mitochondria and animal tissues. These findings illuminate the nature of viral–eukaryotic gene exchange and its impact on the evolution of viruses and their eukaryotic hosts.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: The mode and taxonomic distribution of viral–eukaryotic gene exchange.
Fig. 2: Gene function is related to transfer direction.
Fig. 3: Predicted subcellular localizations and functions of eukaryote-derived viral genes.
Fig. 4: Recurrent acquisition of viral glycosyltransferases across the eukaryotic tree of life.

Similar content being viewed by others

Data availability

All data, including proteomes, protein families, annotations, alignments, phylogenies and summaries of detected HGTs (both before and after contamination filtering) are available from Dryad (https://datadryad.org/stash/dataset/doi:10.5061/dryad.z08kprrc9).

Code availability

All the code used for phylogenetic interpretation, contamination scoring, and functional enrichments and analyses are available from Dryad (https://datadryad.org/stash/dataset/doi:10.5061/dryad.z08kprrc9).

References

  1. Zimmerman, A. E. et al. Metabolic and biogeochemical consequences of viral infection in aquatic ecosystems. Nat. Rev. Microbiol. 18, 21–34 (2019).

    Article  PubMed  Google Scholar 

  2. Koonin, E. V. & Krupovic, M. The depths of virus exaptation. Curr. Opin. Virol. 31, 1–8 (2018).

    Article  CAS  PubMed  Google Scholar 

  3. Frank, J. A. & Feschotte, C. Co-option of endogenous viral sequences for host cell function. Curr. Opin. Virol. 25, 81–89 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Moreira, D. & Brochier-Armanet, C. Giant viruses, giant chimeras: the multiple evolutionary histories of Mimivirus genes. BMC Evol. Biol. 8, 12 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Filée, J., Pouget, N. & Chandler, M. Phylogenetic evidence for extensive lateral acquisition of cellular genes by Nucleocytoplasmic large DNA viruses. BMC Evol. Biol. 8, 320 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Monier, A. et al. Host-derived viral transporter protein for nitrogen uptake in infected marine phytoplankton. Proc. Natl Acad. Sci. USA 114, E7489–E7498 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Monier, A. et al. Horizontal gene transfer of an entire metabolic pathway between a eukaryotic alga and its DNA virus. Genome Res. 1441–1449 (2009).https://doi.org/10.1101/gr.091686.109

  8. Schulz, F. et al. Giant virus diversity and host interactions through global metagenomics. Nature 578, 432–436 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Aswad, A. & Katzourakis, A. Cell-derived viral genes evolve under stronger purifying selection in rhadinoviruses. J. Virol. 92, e00539-18 (2018).

    Article  Google Scholar 

  10. Schulz, F. et al. Giant viruses with an expanded complement of translation system components. Science 356, 82–85 (2017).

    Article  CAS  PubMed  Google Scholar 

  11. Guglielmini, J., Woo, A. C., Krupovic, M., Forterre, P. & Gaia, M. Diversification of giant and large eukaryotic dsDNA viruses predated the origin of modern eukaryotes. Proc. Natl Acad. Sci. USA 116, 19585–19592 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Enav, H., Mandel-Gutfreund, Y. & Béjà, O. Comparative metagenomic analyses reveal viral-induced shifts of host metabolism towards nucleotide biosynthesis. Microbiome 2, 9 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Vardi, A. et al. Host-virus dynamics and subcellular controls of cell fate in a natural coccolithophore population. Proc. Natl Acad. Sci. USA 109, 19327–19332 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Biémont, C. A brief history of the status of transposable elements: from junk DNA to major players in evolution. Genetics 186, 1085–1093 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Gornik, S. G. et al. Loss of nucleosomal DNA condensation coincides with appearance of a novel nuclear protein in dinoflagellates. Curr. Biol. 22, 2303–2312 (2012).

    Article  CAS  PubMed  Google Scholar 

  16. Medina, E. M., Turner, J. J., Gordân, R., Skotheim, J. M. & Buchler, N. E. Punctuated evolution and transitional hybrid network in an ancestral cell cycle of fungi. Elife 5, e09492 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Pastuzyn, E. D. et al. The neuronal gene Arc encodes a repurposed retrotransposon Gag protein that mediates intercellular RNA transfer. Cell 172, 275–288 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Mi, S. et al. Syncytin is a captive retroviral envelope protein involved in human placental morphogenesis. Nature 403, 785–789 (2002).

    Article  Google Scholar 

  19. Cornelis, G. et al. An endogenous retroviral envelope syncytin and its cognate receptor identified in the viviparous placental Mabuya lizard. Proc. Natl Acad. Sci. USA 114, E10991–E11000 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Irwin, N. A. T. et al. Viral proteins as a potential driver of histone depletion in dinoflagellates. Nat. Commun. 9, 1535 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Forterre, P. & Prangishvili, D. The major role of viruses in cellular evolution: facts and hypotheses. Curr. Opin. Virol. 3, 558–565 (2013).

    Article  CAS  PubMed  Google Scholar 

  22. Delaroque, N., Maier, L., Knippers, R. & Müller, D. G. Persistent virus integration into the genome of its algal host, Ectocarpus siliculosus (Phaeophyceae). J. Gen. Virol. 80, 1367–1370 (1999).

    Article  CAS  PubMed  Google Scholar 

  23. Blanc, G., Gallot-Lavallée, L. & Maumus, F. Provirophages in the Bigelowiella genome bear testimony to past encounters with giant viruses. Proc. Natl Acad. Sci. USA 112, E5318–E5326 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Leonard, G. et al. Comparative genomic analysis of the ‘pseudofungus’ Hyphochytrium catenoides. Open Biol. 8, 170184 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  25. McCrone, J. T. & Lauring, A. S. Genetic bottlenecks in intraspecies virus transmission. Curr. Opin. Virol. 28, 20–25 (2018).

    Article  PubMed  Google Scholar 

  26. Awadalla, P. The evolutionary genomics of pathogen recombination. Nat. Rev. Genet. 4, 50–60 (2003).

    Article  CAS  PubMed  Google Scholar 

  27. Koonin, E. V. & Yutin, N. Origin and evolution of eukaryotic large nucleo-cytoplasmic DNA viruses. Intervirology 53, 284–292 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Koonin, E. V., Dolja, V. V. & Krupovic, M. Origins and evolution of viruses of eukaryotes: the ultimate modularity. Virology 479–480, 2–25 (2015).

    Article  PubMed  Google Scholar 

  29. Filée, J. & Chandler, M. Gene exchange and the origin of giant viruses. Intervirology 53, 354–361 (2010).

    Article  PubMed  Google Scholar 

  30. Sun, T.-W. et al. Host range and coding potential of eukaryotic giant viruses. Viruses 12, 1337 (2020).

    Article  PubMed Central  Google Scholar 

  31. Fraser, M. J., Smith, G. E. & Summers, M. D. Acquisition of host cell DNA sequences by Baculoviruses: relationship between host DNA insertions and FP mutants of Autographa californica and Galleria mellonella nuclear polyhedrosis viruses. J. Virol. 47, 287–300 (1983).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Liu, H. et al. Widespread horizontal gene transfer from double-stranded RNA viruses to eukaryotic nuclear genomes. J. Virol. 84, 11876–11887 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Bordenstein, S. R. & Bordenstein, S. R. Eukaryotic association module in phage WO genomes from Wolbachia. Nat. Commun. 7, 13155 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Richards, T. A., Hirt, R. P., Williams, B. A. P. & Embley, T. M. Horizontal gene transfer and the evolution of parasitic Protozoa. Protist 154, 17–32 (2003).

    Article  PubMed  Google Scholar 

  35. Hayward, A., Cornwallis, C. K. & Jern, P. Pan-vertebrate comparative genomics unmasks retrovirus macroevolution. Proc. Natl Acad. Sci. USA 112, 464–469 (2015).

    Article  CAS  PubMed  Google Scholar 

  36. Cock, J. M. et al. The Ectocarpus genome and the independent evolution of multicellularity in brown algae. Nature 465, 617–621 (2010).

    Article  CAS  PubMed  Google Scholar 

  37. Moniruzzaman, M., Weinheimer, A. R., Martinez-Gutierrez, C. A. & Aylward, F. O. Widespread endogenization of giant viruses shapes genomes of green algae. Nature 588, 141–145 (2020).

    Article  CAS  PubMed  Google Scholar 

  38. Maumus, F. & Blanc, G. Study of gene trafficking between Acanthamoeba and giant viruses suggests an undiscovered family of amoeba-infecting viruses. Genome Biol. Evol. 8, 3351–3363 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Fischer, M. G. & Hackl, T. Host genome integration and giant virus-induced reactivation of the virophage mavirus. Nature 540, 288–291 (2016).

    Article  CAS  PubMed  Google Scholar 

  40. Maumus, F., Epert, A., Nogué, F. & Blanc, G. Plant genomes enclose footprints of past infections by giant virus relatives. Nat. Commun. 5, 4268 (2014).

    Article  CAS  PubMed  Google Scholar 

  41. Patel, M. R., Emerman, M. & Malik, H. S. Paleovirology – ghosts and gifts of viruses past. Curr. Opin. Virol. 1, 304–309 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Williams, T. A., Embley, T. M. & Heinz, E. Informational gene phylogenies do not support a fourth domain of life for nucleocytoplasmic large DNA viruses. PLoS ONE 6, e21080 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Tonetti, M., Sturla, L., Bisso, A., Benatti, U. & de Flora, A. Synthesis of GDP-L-fucose by the human FX protein. J. Biol. Chem. 271, 27274–27279 (1996).

    Article  CAS  PubMed  Google Scholar 

  44. Forterre, P., Gribaldo, S., Gadelle, D. & Serre, M. C. Origin and evolution of DNA topoisomerases. Biochimie 89, 427–446 (2007).

    Article  CAS  PubMed  Google Scholar 

  45. Malik, S. S., Azem-e-Zahra, S., Kim, K. M., Caetano-Anollés, G. & Nasir, A. Do viruses exchange genes across superkingdoms of life? Front. Microbiol. 8, 2110 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Gilbert, C. & Cordaux, R. Viruses as vectors of horizontal transfer of genetic material in eukaryotes. Curr. Opin. Virol. 25, 16–22 (2017).

    Article  CAS  PubMed  Google Scholar 

  47. Chen, J. et al. Genome hypermobility by lateral transduction. Science 362, 207–212 (2018).

    Article  CAS  PubMed  Google Scholar 

  48. Touchon, M., Moura de Sousa, J. A. & Rocha, E. P. Embracing the enemy: the diversification of microbial gene repertoires by phage-mediated horizontal gene transfer. Curr. Opin. Microbiol. 38, 66–73 (2017).

    Article  CAS  PubMed  Google Scholar 

  49. Krupovic, M. & Koonin, E. V. Multiple origins of viral capsid proteins from cellular ancestors. Proc. Natl Acad. Sci. USA 114, E2401–E2410 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Moreira, D. & López-García, P. Ten reasons to exclude viruses from the tree of life. Nat. Rev. Microbiol. 7, 306–311 (2009).

    Article  CAS  PubMed  Google Scholar 

  51. Almagro Armenteros, J. J., Sønderby, C. K., Sønderby, S. K., Nielsen, H. & Winther, O. DeepLoc: prediction of protein subcellular localization using deep learning. Bioinformatics 33, 3387–3395 (2017).

    Article  PubMed  Google Scholar 

  52. Duffy, S., Shackelton, L. A. & Holmes, E. C. Rates of evolutionary change in viruses: patterns and determinants. Nat. Rev. Genet. 9, 267–276 (2008).

    Article  CAS  PubMed  Google Scholar 

  53. Jung, J. U., Stäger, M. & Desrosiers, R. C. Virus-encoded cyclin. Mol. Cell. Biol. 14, 7235–7244 (1994).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Erives, A. J. Phylogenetic analysis of the core histone doublet and DNA topo II genes of Marseilleviridae: evidence of proto-eukaryotic provenance. Epigenetics Chromatin 10, 55 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  55. Schvarcz, C. R. & Steward, G. F. A giant virus infecting green algae encodes key fermentation genes. Virology 518, 423–433 (2018).

    Article  CAS  PubMed  Google Scholar 

  56. Pagarete, A., Allen, M. J., Wilson, W. H., Kimmance, S. A. & De Vargas, C. Host-virus shift of the sphingolipid pathway along an Emiliania huxleyi bloom: survival of the fattest. Environ. Microbiol. 11, 2840–2848 (2009).

    Article  CAS  PubMed  Google Scholar 

  57. Schneider-Schaulies, J. & Schneider-Schaulies, S. Sphingolipids in viral infection. Biol. Chem. 396, 585–595 (2015).

    Article  CAS  PubMed  Google Scholar 

  58. Fernández de Castro, I., Tenorio, R. & Risco, C. Virus assembly factories in a lipid world. Curr. Opin. Virol. 18, 20–26 (2016).

    Article  PubMed  Google Scholar 

  59. Hiramatsu, S., Ishihara, M., Fujie, M. & Usami, S. Expression of a chitinase gene and lysis of the host cell wall during Chlorella virus CVK2 infection. Virology 260, 308–315 (1999).

    Article  CAS  PubMed  Google Scholar 

  60. Klenk, H. D. & Garten, W. Host cell proteases controlling virus pathogenicity. Trends Microbiol. 2, 39–43 (1994).

    Article  CAS  PubMed  Google Scholar 

  61. Thaker, S. K., Ch’ng, J. & Christofk, H. R. Viral hijacking of cellular metabolism. BMC Biol. 17, 59 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  62. Mahalingam, S., Meanger, J., Foster, P. S. & Lidbury, B. A. The viral manipulation of the host cellular and immune environments to enhance propagation and survival: a focus on RNA viruses. J. Leukoc. Biol. 72, 429–439 (2002).

    Article  CAS  PubMed  Google Scholar 

  63. Ravindran, M. S., Bagchi, P., Cunningham, C. N. & Tsai, B. Opportunistic intruders: how viruses orchestrate ER functions to infect cells. Nat. Rev. Microbiol. 14, 407–420 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. de Chassey, B., Meyniel-Schicklin, L., Vonderscher, J., André, P. & Lotteau, V. Virus–host interactomics: new insights and opportunities for antiviral drug discovery. Genome Med. 6, 115 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  65. Puschnik, A. S., Majzoub, K., Ooi, Y. S. & Carette, J. E. A CRISPR toolbox to study virus–host interactions. Nat. Rev. Microbiol. 15, 351–364 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Michel, G., Tonon, T., Scornet, D., Cock, J. M. & Kloareg, B. Central and storage carbon metabolism of the brown alga Ectocarpus siliculosus: insights into the origin and evolution of storage carbohydrates in eukaryotes. New Phytol. 188, 67–81 (2010).

    Article  CAS  PubMed  Google Scholar 

  67. Durak, G. M. et al. A role for diatom-like silicon transporters in calcifying coccolithophores. Nat. Commun. 7, 10543 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Armstrong, P. B., Armstrong, M. T., Pardy, R. L., Child, A. & Wainwright, N. Immunohistochemical demonstration of a lipopolysaccharide in the cell wall of a eukaryote, the green alga, Chlorella. Biol. Bull. 203, 203–204 (2002).

    Article  PubMed  Google Scholar 

  69. Laurent, T. C. & Fraser, J. R. E. Hyaluronan. FASEB 6, 2397–2404 (1992).

    Article  CAS  Google Scholar 

  70. Loomis, W. F., Wheeler, S. A., Springer, W. R. & Barondes, S. H. Adhesion mutants of Dictyostelium discoideum lacking the saccharide determinant recognized by two adhesion-blocking monoclonal antibodies. Dev. Biol. 109, 111–117 (1985).

    Article  CAS  PubMed  Google Scholar 

  71. Bandini, G. et al. An essential, kinetoplastid-specific GDP-Fuc: β-D-Gal α-1,2- fucosyltransferase is located in the mitochondrion of Trypanosoma brucei. eLife 10, e70272 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  72. Schrom, M. & Bablanian, R. Altered cellular morphology resulting from cytocidal virus infection. Arch. Virol. 70, 173–187 (1981).

    Article  CAS  PubMed  Google Scholar 

  73. Raaben, M. et al. The ubiquitin-proteasome system plays an important role during various stages of the coronavirus infection cycle. J. Virol. 84, 7869–7879 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Leier, H. C. et al. A global lipid map defines a network essential for Zika virus replication. Nat. Commun. 11, 3652 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Chuong, E. B. The placenta goes viral: retroviruses control gene expression in pregnancy. PLoS Biol. 16, e3000028 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  76. Li, W. & Godzik, A. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22, 1658–1659 (2006).

    Article  CAS  PubMed  Google Scholar 

  77. Keeling, P. J. et al. The Marine Microbial Eukaryote Transcriptome Sequencing Project (MMETSP): illuminating the functional diversity of eukaryotic life in the oceans through transcriptome sequencing. PLoS Biol. 12, e1001889 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  78. Simão, F. A., Waterhouse, R. M., Ioannidis, P., Kriventseva, E. V. & Zdobnov, E. M. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31, 3210–3212 (2015).

    Article  PubMed  Google Scholar 

  79. Enright, A. J., van Dongen, S. & Ouzounis, C. A. An efficient algorithm for large-scale detection of protein families. Nucleic Acids Res. 30, 1575–1584 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Buchfink, B., Xie, C. & Huson, D. H. Fast and sensitive protein alignment using DIAMOND. Nat. Methods 12, 59–60 (2014).

    Article  PubMed  Google Scholar 

  81. Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol. 30, 772–780 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Mistry, J., Finn, R. D., Eddy, S. R., Bateman, A. & Punta, M. Challenges in homology search: HMMER3 and convergent evolution of coiled-coil regions. Nucleic Acids Res. 41, e121 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Capella-Gutiérrez, S., Silla-Martínez, J. M. & Gabaldón, T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25, 1972–1973 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  84. Anisimova, M., Gil, M., Dufayard, J. F., Dessimoz, C. & Gascuel, O. Survey of branch support methods demonstrates accuracy, power, and robustness of fast likelihood-based approximation schemes. Syst. Biol. 60, 685–699 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  85. Shimodaira, H. & Hasegawa, M. Multiple comparisons of log-likelihoods with applications to phylogenetic inference. Mol. Biol. Evol. 16, 1114–1116 (1999).

    Article  CAS  Google Scholar 

  86. Nguyen, L. T., Schmidt, H. A., Von Haeseler, A. & Minh, B. Q. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32, 268–274 (2015).

    Article  CAS  PubMed  Google Scholar 

  87. Tria, F. D. K., Landan, G. & Dagan, T. Phylogenetic rooting using minimal ancestor deviation. Nat. Ecol. Evol. 1, 0193 (2017).

    Article  Google Scholar 

  88. Kalyaanamoorthy, S., Minh, B. Q., Wong, T. K. F., von Haeseler, A. & Jermiin, L. S. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat. Methods 14, 587–589 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Letunic, I. & Bork, P. Interactive Tree of Life (iTOL) v4: recent updates and new developments. Nucleic Acids Res. 47, 256–259 (2019).

    Article  Google Scholar 

  90. Susko, E. & Roger, A. J. On reduced amino acid alphabets for phylogenetic inference. Mol. Biol. Evol. 24, 2139–2150 (2007).

    Article  CAS  PubMed  Google Scholar 

  91. Huerta-Cepas, J., Serra, F. & Bork, P. ETE 3: reconstruction, analysis, and visualization of phylogenomic data. Mol. Biol. Evol. 33, 1635–1638 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Federhen, S. The NCBI Taxonomy database. Nucleic Acids Res. 40, 136–143 (2012).

    Article  Google Scholar 

  93. Walker, P. J. et al. Changes to virus taxonomy and to the international code of virus classification and nomenclature ratified by the international committee on taxonomy of viruses (2021). Arch. Virol. 166, 2633–2648 (2021).

    Article  CAS  PubMed  Google Scholar 

  94. Huerta-Cepas, J. et al. Fast genome-wide functional annotation through orthology assignment by eggNOG-Mapper. Mol. Biol. Evol. 34, 2115–2122 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Jones, P. et al. InterProScan 5: genome-scale protein function classification. Bioinformatics 30, 1236–1240 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Supek, F., Bošnjak, M., Škunca, N. & Šmuc, T. REVIGO summarizes and visualizes long lists of gene ontology terms. PLoS ONE 6, e21800 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Dean, S., Sunter, J. D. & Wheeler, R. J. TrypTag.org: a trypanosome genome-wide protein localisation resource. Trends Parasitol. 33, 80–82 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Aslett, M. et al. TriTrypDB: a functional genomic resource for the Trypanosomatidae. Nucleic Acids Res. 38, 457–462 (2009).

    Article  Google Scholar 

  99. Burki, F., Roger, A. J., Brown, M. W. & Simpson, A. G. B. The new tree of eukaryotes. Trends Ecol. Evol. 35, 43–55 (2020).

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We thank R. Wheeler for providing fluorescent micrographs of Trypanosoma brucei as part of TrypTag. This work was supported by grants from the Natural Sciences and Engineering Research Council of Canada (NSERC, RGPIN-2014-03994) and from the Gordon and Betty Moore Foundation (https://doi.org/10.37807/GBMF9201) to P.J.K. N.A.T.I. was supported by a Junior Research Fellowship from Merton College, Oxford and an NSERC Canadian Graduate Scholarship. A.A.P. was supported by a European Molecular Biology Organization (EMBO) Long-term Fellowship (ALTF 118-2017). T.A.R. is supported by a Royal Society University Research Fellowship (UF130382).

Author information

Authors and Affiliations

  1. Merton College, University of Oxford, Oxford, UK

    Nicholas A. T. Irwin

  2. Department of Zoology, University of Oxford, Oxford, UK

    Nicholas A. T. Irwin & Thomas A. Richards

  3. Department of Botany, University of British Columbia, Vancouver, British Columbia, Canada

    Nicholas A. T. Irwin, Alexandros A. Pittis & Patrick J. Keeling

Authors
  1. Nicholas A. T. Irwin
    View author publications

    Search author on:PubMed Google Scholar

  2. Alexandros A. Pittis
    View author publications

    Search author on:PubMed Google Scholar

  3. Thomas A. Richards
    View author publications

    Search author on:PubMed Google Scholar

  4. Patrick J. Keeling
    View author publications

    Search author on:PubMed Google Scholar

Contributions

N.A.T.I. and A.A.P. conceptualized the project; P.J.K. and T.A.R. acquired funding; N.A.T.I. and A.A.P. conducted the investigations; P.J.K. and T.A.R. provided resources and supervised the project; N.A.T.I. wrote the paper with input from all authors.

Corresponding author

Correspondence to Nicholas A. T. Irwin.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Microbiology thanks Valerian Dolja, Jolien van Hooff and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Dataset assembly and statistics.

a. A schematic representation of the dataset assembly pipeline. b. The numbers of eukaryotic, viral, and prokaryotic genomes and proteins examined and included in the initial and final dataset. The final dataset reflects the dataset upon which the HGT analysis was conducted. c. The representation of viral phyla and other groups (that is, those lacking phyla classifications) in the initial and final datasets. d, e. Summary statistics for the final clustered protein families including the number of sequences present (d) and the trimmed alignment lengths (e). See Methods for additional information.

Extended Data Fig. 2 Phylogenetic pipeline and contamination analysis overview.

a, b. Schematic representation of the HGT identification and phylogenetic analysis pipeline (a) and the contamination scoring protocol (b). c. The distribution of eukaryotic contig lengths that contain viral HGTs. d. The distribution of contamination scores across eukaryotic recipient sequences. e. The number of well-supported HGTs that are identified using different contamination score thresholds. Dashed lines denote the defined scoring threshold (≥ 2). See Methods for additional information.

Extended Data Fig. 3 Eukaryote-to-virus transfers across eukaryotic supergroups.

a-j. Expanded versions of Fig. 1e displaying transfers in the Opisthokonta (a), Archaeplastida (b), Rhodophyta (c), SAR (d), Cryptophyceae (e), Haptista (f), Metamonada (g), Amoebozoa (h), Diplomonada (i), and Apusozoa (j). Bar charts represent HGTs present in an individual genome, whereas pie charts present inferred ancestral HGTs. Bar height and pie diameter reflect transfer frequency and colours denote viral taxonomy. For clarity, viral taxa were mapped to their nearest family, phylum, or higher-level classification. Because of this, multiple families from the same phylum are shown, such as the NCLDV lineages, which are denoted with an asterisk (note that some unclassified viruses include candidate NCLDV lineages without formal taxonomic descriptions). Taxonomic information and phylogenies are based on the NCBI (National Center for Biotechnology Information) Taxonomy database92.

Extended Data Fig. 4 Virus-to-eukaryote transfers across eukaryotic supergroups.

a-j. Expanded versions of Fig. 1f displaying transfers in the Opisthokonta (a), Archaeplastida (b), Rhodophyta (c), SAR (d), Cryptophyceae (e), Haptista (f), Metamonada (g), Amoebozoa (h), Diplomonada (i), and Apusozoa (j). Bar charts represent HGTs present in an individual genome, whereas pie charts present inferred ancestral HGTs. Bar height and pie diameter reflect transfer frequency and colours denote viral taxonomy. For clarity, viral taxa were mapped to their nearest family, phylum, or higher-level classification. Because of this, multiple families from the same phylum are shown, such as the NCLDV lineages, which are denoted with an asterisk (note that some unclassified viruses include candidate NCLDV lineages without formal taxonomic descriptions). Taxonomic information and phylogenies are based on the NCBI (National Center for Biotechnology Information) Taxonomy database92.

Extended Data Fig. 5 Examples of ancient viral-eukaryotic gene transfers occurring prior to the last eukaryotic common ancestor.

Phylogenetic analyses were conducted in IQ-Tree after recoding alignments with a 4-bin Dayhoff matrix. The number of sequences within collapsed clades are noted and more recent HGTs were removed for clarity but did not affect the tree topologies. Statistical support was assessed using SH-aLRT (n = 1,000) and substitution models were selected using ModelFinder and included GTR+F+ASC+R10 (a), GTR+F+R10 (b), GTR+F+R7 (c), GTR+F+R8 (d), and GTR+F+R8 (e).

Extended Data Fig. 6 Gene origin identification and transduction examples.

a. A schematic illustrating how viral gene origins were approximated by moving up through the phylogeny from the donor towards the root until a cellular lineage was encountered. The pie chart reflects the proportion of well supported virus-to-eukaryote HGTs that were assigned a given origin. b, c. Example phylogenies illustrating cases of eukaryote-to-eukaryote and prokaryote-to-eukaryote transduction. The number of sequences within collapsed clades are noted. Phylogenies were generated in IQ-Tree using the LG+R7 (b) or LG+R9 (c) substitution models as selected using ModelFinder and statistical support was assessed using SH-aLRT (n = 1,000)86,88.

Extended Data Fig. 7 Phylogenies for glycosyltransferases denoted in Fig. 4.

Phylogenetic analyses were conducted in IQ-Tree with statistical support assessed using SH-aLRT (n = 1,000). The number of sequences within collapsed clades are noted. Substitution models were selected using ModelFinder and included LG+R10 (a), LG+F+R10 (b), LG+R9 (c), LG+F+R8 (d, e), LG+R6 (f), LG+F+R7 (g), LG+F+G4 (h), LG+F+R5 (i, j), and LG+I+G4 (k).

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Irwin, N.A.T., Pittis, A.A., Richards, T.A. et al. Systematic evaluation of horizontal gene transfer between eukaryotes and viruses. Nat Microbiol 7, 327–336 (2022). https://doi.org/10.1038/s41564-021-01026-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41564-021-01026-3

This article is cited by

Search

Advanced search

Quick links

Nature Briefing Microbiology

Sign up for the Nature Briefing: Microbiology newsletter — what matters in microbiology research, free to your inbox weekly.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing: Microbiology