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Widespread endogenization of giant viruses shapes genomes of green algae

Abstract

Endogenous viral elements (EVEs)—viruses that have integrated their genomes into those of their hosts—are prevalent in eukaryotes and have an important role in genome evolution1,2. The vast majority of EVEs that have been identified to date are small genomic regions comprising a few genes2, but recent evidence suggests that some large double-stranded DNA viruses may also endogenize into the genome of the host1. Nucleocytoplasmic large DNA viruses (NCLDVs) have recently become of great interest owing to their large genomes and complex evolutionary origins3,4,5,6, but it is not yet known whether they are a prominent component of eukaryotic EVEs. Here we report the widespread endogenization of NCLDVs in diverse green algae; these giant EVEs reached sizes greater than 1 million base pairs and contained as many as around 10% of the total open reading frames in some genomes, substantially increasing the scale of known viral genes in eukaryotic genomes. These endogenized elements often shared genes with host genomic loci and contained numerous spliceosomal introns and large duplications, suggesting tight assimilation into host genomes. NCLDVs contain large and mosaic genomes with genes derived from multiple sources, and their endogenization represents an underappreciated conduit of new genetic material into eukaryotic lineages that can substantially impact genome composition.

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Fig. 1: Distribution and general features of the GEVEs.
Fig. 2: Signatures of endogenization.
Fig. 3: Evolutionary history of the GEVEs.

Data availability

Nucleotide and protein sequences specific to each of the GEVEs, hallmark gene set used for phylogenetic analyses, alignments for all phylogenies presented, HMM profiles of the core genes and NCVOG families, and other data products are available at: https://zenodo.org/record/3975964#.XzFj0hl7mfZ.

Code availability

A custom bioinformatic pipeline (ViralRecall) was developed in Python 3.5 for purposes of this study. This code is already publicly available on GitHub for the Aylward lab: https://github.com/faylward/viralrecall. For NCLDV marker gene detection, we also used a custom Python script available on GitHub: https://github.com/faylward/ncldv_markersearch. Other bioinformatic analyses performed in this study were done using publicly available bioinformatic tools and are described in the Methods.

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Acknowledgements

We thank J. Burns from the Bigelow Laboratory of Ocean Sciences and E. Kim from the American Museum of Natural History for providing access to the RNA sequencing data of C. tetramitiformis. We acknowledge use of the Virginia Tech Advanced Research Computing Center for bioinformatic analyses performed in this study. This work was supported by a Simons Early Career Investigator Award in Marine Microbial Ecology and Evolution (grant no. 620443) and NSF grant IIBR-1918271 to F.O.A.

Author information

Authors and Affiliations

Authors

Contributions

F.O.A. and M.M. designed the project and wrote the paper. M.M. curated GEVEs, performed gene annotations and phylogenetic analysis. A.R.W. performed the GEVE protein annotations. C.A.M.-G. performed the dN/dS analysis.

Corresponding author

Correspondence to Frank O. Aylward.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature thanks Chantal Abergel, Matthew Sullivan 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 figures and tables

Extended Data Fig. 1 Workflow for GEVE detection.

Overview of the initial steps to identify virus-like regions in chlorophyte genomes and subsequent steps to curate Giant Endogenous Viral Elements (GEVEs). Steps in the grey box are implemented in the ViralRecall tool; steps outside this box represent additional analyses we performed to validate our findings and further analyse the GEVEs.

Extended Data Fig. 2 General features of additional GEVEs.

Circular genome plots of 6 additional GEVEs (apart from those shown in Fig. 1b) showing NCVOG HMM hits, spliceosomal intron locations, and best LAST hit matches. Black dots atop the outermost track mark the locations of the core genes, while the blue links inside the circles represent duplicated regions. The grey shading demarcates the location of integrated GEVE as determined by ViralRecall in case of Chlorella and Tetradesmus obliquus.

Extended Data Fig. 3 GEVEs have coding potential similar to known giant viruses.

a, Principal component analysis (PCA) of the coding potential of the GEVE genomes, corresponding host genomes and reference giant viruses based on the presence/absence of Nucleocytoplasmic virus orthologous group (NCVOG) specific proteins in these genomes. The plot demonstrates the similarity in coding content of GEVEs and reference giant viruses, whereas the eukaryotic hosts are distinct in terms of coding potential. Nonviral chlorophyte host chromosomes have a much more scattered distribution due to the sporadic occurrence and low abundance of some NCVOGs in these genomes (ankyrin repeat proteins and transposons are represented in NCVOGs and are present in the nonviral portion of host chromosomes, for example). Eukaryotic-specific proteins are not included in NCVOGs, and so the host chlorophyte genomes don’t show tight clustering, since this aspect of their genomic repertoires is not captured by NCVOGs. The prcomp() function in R was used to calculate the values. b, Bipartite network of 18 GEVEs and 126 reference giant viruses based on shared gene content. The network is constructed by profiling the presence of NCVOGs across all the virus and GEVE genomes represented. Large nodes represent NCLDV or GEVE genomes, smaller nodes represent NCVOG protein families and edges denote gene families represented in different genomes.

Extended Data Fig. 4 Example of gene prediction approach within the GEVEs.

Genes predicted by AUGUSTUS (outer ring, brown) and non-overlapping Prodigal predicted genes (middle ring, green) in the GEVEs within Chlamydomoans eustigma and Tetrabaena socialis are shown as examples. In most cases, Prodigal predicted many genes that were not detected by eukaryotic gene prediction algorithms. Many of the Prodigal predicted genes originally missed by AUGUSTUS have hits to NCVOGs (innermost right, purple) - including NCLDV core genes.

Extended Data Fig. 5 Level of duplications and core gene copy numbers in GEVE genomes versus reference giant virus genomes.

The left panel shows duplication level (repeated genomic regions at >90% nucleotide similarity) as estimated using RECON 1.08. The right panel shows copy numbers of NCLDV core genes in each of the GEVEs and reference genomes (see Methods for details).

Extended Data Fig. 6 Signature of relaxed selection in the GEVEs compared to free viruses.

Violin plot representing median dN/dS values of endogenized and free reference giant viruses. Statistical significance of differences between dN/dS values of the compared groups according to a non-paired, one-sided Mann–Whitney Wilcoxon test is denoted by: ***P < 0.0001. ‘W’ denotes the Wilcoxon test statistic. For this test 79 values were for GEVE-GEVE dN/dS values and 775 were for comparisons between free viruses. The IDs of the reference genomes used for calculating the dN/dS values are provided in Supplementary Data 6.

Extended Data Fig. 7 Expression profiles of GEVE genes.

Selected set of expressed genes in 6 of the GEVEs. For each GEVE, up to 15 genes with highest expressions are shown, with exception of Tetrabaena socialis GEVE_1, for which all genes having >1 expression coverage are presented. For a particular gene, expression is measured as the average read mapping coverage of the CDS(s) in that gene. Genes having putative functions (based on PFAM or COG annotations) are shown in red, while mobile elements are shown in blue.

Extended Data Fig. 8 Functional potential coded by the GEVEs.

Functional profiles (EggNOG) of the GEVEs normalized across all the NOG functional categories except category S (Function unknown). No gene was found to be in category R (General function prediction only). Number of genes having no hits or in category S (Function unknown) are shown in the table on the right.

Extended Data Table 1 NCLDV hallmark genes in diverse chlorophyte genomes without GEVEs
Extended Data Table 2 GEVE feature summaries

Supplementary information

Supplementary Information

This file contains the following: a) Supplementary results and discussion with references. b) Supplementary figures with captions describing each figure. c) Supplementary tables with captions describing each table.

Reporting Summary

Supplementary Data

Supplementary Data 1: Information on the genomes analysed in this study. FTP download link are provided for each of the genomes.

Supplementary Data

Supplementary Data 2: Summary statistics for individual contigs in each of the viral elements (GEVEs) analysed.

Supplementary Data

Supplementary Data 3: Average amino acid identities (AAI) between each pair of GEVEs.

Supplementary Data

Supplementary Data 4: Functional annotation for each of the GEVEs obtained using a number of protein family databases. Databases used are: COG, PFam, EggNOG, VOG, TIGR and EggVOG. See ‘Methods’ for references for all these databases.

Supplementary Data

Supplementary Data 5: Annotation and expression values of the expressed genes in six of the GEVEs. Annotations are only provided for the genes which had hits to different databases (as specified in Supplementary Data 4).

Supplementary Data

Supplementary Data 6: Genome IDs of the reference NCLDVs that were used to calculate dN/dS values in the Phycodnaviridae and Mimiviridae group. The reference genomes can be accessed from the study cited in the ‘Calculation of dN/dS ratios’ sub-section in the ‘Methods’.

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Moniruzzaman, M., Weinheimer, A.R., Martinez-Gutierrez, C.A. et al. Widespread endogenization of giant viruses shapes genomes of green algae. Nature 588, 141–145 (2020). https://doi.org/10.1038/s41586-020-2924-2

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