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A phylogenetic and proteomic reconstruction of eukaryotic chromatin evolution

Nature Ecology & Evolution volume 6, pages 1007–1023 (2022)Cite this article

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Abstract

Histones and associated chromatin proteins have essential functions in eukaryotic genome organization and regulation. Despite this fundamental role in eukaryotic cell biology, we lack a phylogenetically comprehensive understanding of chromatin evolution. Here, we combine comparative proteomics and genomics analysis of chromatin in eukaryotes and archaea. Proteomics uncovers the existence of histone post-translational modifications in archaea. However, archaeal histone modifications are scarce, in contrast with the highly conserved and abundant marks we identify across eukaryotes. Phylogenetic analysis reveals that chromatin-associated catalytic functions (for example, methyltransferases) have pre-eukaryotic origins, whereas histone mark readers and chaperones are eukaryotic innovations. We show that further chromatin evolution is characterized by expansion of readers, including capture by transposable elements and viruses. Overall, our study infers detailed evolutionary history of eukaryotic chromatin: from its archaeal roots, through the emergence of nucleosome-based regulation in the eukaryotic ancestor, to the diversification of chromatin regulators and their hijacking by genomic parasites.

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Fig. 1: Diversity of post-translational modifications in eukaryotic canonical and variant histones.
Fig. 2: Archaeal histone diversity and post-translational modifications.
Fig. 3: Taxonomic distribution of chromatin-associated gene classes.
Fig. 4: Origin and evolution of chromatin-associated gene families.
Fig. 5: Evolution of chromatin readers and capture of chromatin proteins by TEs and viruses.
Fig. 6: Chromatin evolution and eukaryogenesis.

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Data availability

The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD031991.

Code availability

Code for reproducing the analysis is available in our laboratory Github repository (https://github.com/sebepedroslab/chromatin-evolution-analysis).

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Acknowledgements

We thank A. de Mendoza for critical input on the analysis of TE fusions. We also thank J. Casacuberta for P. patens samples, H. J. G. Meijer for P. infestans samples, M. Adamska for S. ciliatum samples and A. Simpson for access to the G. okellyi culture (made possible by his funding from NSERC, Canada). Research in the A.S.-P. group was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation Programme (grant agreement no. 851647) and the Spanish Ministry of Science and Innovation (PGC2018-098210-A-I00). We also acknowledge support of the Spanish Ministry of Science and Innovation to the EMBL partnership, the Centro de Excelencia Severo Ochoa and the CERCA Programme (Generalitat de Catalunya). C.N. is supported by an FPI PhD fellowship from the Spanish Ministry of Economy, Industry and Competitiveness (MEIC). X.G.-B. is supported by a Juan de la Cierva fellowship (FJC2018-036282-I) from MEIC. I.R.-T. was supported by a European Research Council (grant no. 616960). B.F.L. was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC; RGPIN-2017-05411) and by the ‘Fonds de Recherche Nature et Technologie’, Quebec. P.L.-G. and D.M. were supported by a Moore and Simons foundations grant (GBMF9739) and by European Research Council advanced grants (322669, 787904). Research in the C.S. group was supported by the ERC through project TACKLE (advanced grant no. 695192).

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Authors and Affiliations

  1. Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain

    Xavier Grau-Bové, Cristina Navarrete, Eduard Sabidó & Arnau Sebé-Pedrós

  2. Universitat Pompeu Fabra (UPF), Barcelona, Spain

    Xavier Grau-Bové, Cristina Navarrete, Cristina Chiva, Eduard Sabidó & Arnau Sebé-Pedrós

  3. Department of Functional and Evolutionary Ecology, Archaea Biology Unit, University of Vienna, Vienna, Austria

    Thomas Pribasnig & Christa Schleper

  4. Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Barcelona, Spain

    Meritxell Antó & Iñaki Ruiz-Trillo

  5. Unité d’Ecologie Systématique et Evolution, CNRS, Université Paris-Saclay, AgroParisTech, Orsay, France

    Guifré Torruella, Luis Javier Galindo, David Moreira & Purificación López-Garcia

  6. Robert Cedergren Centre in Bioinformatics and Genomics, Department of Biochemistry, Université de Montréal, Montréal, Quebec, Canada

    Bernd Franz Lang

  7. Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain

    Iñaki Ruiz-Trillo

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  1. Xavier Grau-Bové
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Contributions

A.S.-P. conceived the project. X.G.-B., C.C., I.R.-T., C.S., E.S. and A.S.-P. designed experiments and analytical strategies. C.N., T.P., M.A. and A.S.-P. performed experiments. X.G.-B., C.C. and A.S.-P. analysed the data. T.P., G.T., L.J.G., D.M., P.L.-G. and B.F.L. provided biological samples/cultures and genomic data. All authors contributed to data interpretation. X.G.-B. and A.S.-P. wrote the manuscript with input from all authors.

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Correspondence to Arnau Sebé-Pedrós.

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Extended data

Extended Data Fig. 1 Histone classification and evolution.

a, Primary and secondary alignments of histone-fold containing proteins classified as canonical H2A, H2B, H3 and H4, based on identity to reference sequences in HistoneDB. Pie plots represent the number of alignments to HistoneDB-annotated sequences, for the entire dataset (prokaryotic, eukary-otic and viral sequences, large pie plots in the inset) and the eukaryotic subset (smaller plots in the inset). For those proteins that align to more than one canonical histone or major variant (macroH2A, H2A.Z or cenH3), the scatter plots represent the relative identity between the primary (horizontal axis) and secondary alignment(s) (vertical axis). b, Aggregated counts of histone gene pairs, classified ac-cording to histone type and orientation. c, Presence of histone variants (left) and number of collinear pairs of histone-encoding genes (right) per species, classified according to their histone types and rela-tive orientation (head-to-head, hh; head-to-tail, ht; and tail-to-tail, tt). Source data available in Supple-mentary Data 2. Histone variant classification is based on the highest-scoring HMM profile from His-toneDB. Asterisks colors in the macroH2A column indicate species where histone-less Macro do-mains orthologous to the macroH2A genes are found (see panel d). Lighter colors in the variant classi-fication indicate ambiguously classified histones (i.e. cases in which the highest-scoring HMM profile exhibited a low bitscore, defined as a probability below 0.05 in the profile-wise distribution function of scaled bitscores; or cases in which the first-to-second ratio between high scoring profiles was below 1.01). d, Alignments of putatively conserved histone N-tails in archaea. Conserved amino-acids are color-coded according to chemical properties. Dots next to species names are color-coded according to taxonomy (same as Fig. 2c). e, Phylogenetic analysis of the Macro motif of macroH2A histones across eukaryotes, highlighting the macroH2A ortholog group (green), and, within this group, Macro-containing genes lacking histone domains (orange), and their protein domain architectures.

Extended Data Fig. 2 Histone post-translational modifications.

a, Proteomics detection coverage (% of amino acids), number of hPTMs and number of hPTMs per covered position, for the best-covered histone in each species in our proteomics survey. b, Number of samples in which each histone-matching peptide with post-translational modifications (peptide spectral matches defined by Proteome Discoverer) has been identified, per species. For each species, we report the percentage of modified peptides found in more than one replicate. c, Number of samples in which histone-matching modified peptide has been identified, across all the samples from this study. The tree pie charts represent these distributions for all hPTMs, acetylations, and methylations. d, Evidence of hPTM conservation in the major histone variants H2A.Z and macroH2A (conserved positions only), as well as any position in the linker histones H1.

Extended Data Fig. 3 Gene family counts.

a-c, Number of taxa within each lineage that contain chromatin-associated genes, for archaeal, bacterial (per phyla) or viral (per family) genomes. Numbers indicate the exact number of taxa. d, Number of genes encoding core domains that define chromatin-associated gene families per eukaryotic genome/transcriptome. Numbers indicate exact number of proteins.

Extended Data Fig. 4 Evolutionary reconstruction and domain architecture conservation.

a, Species tree of eukaryotes used in the ancestral reconstruction analysis, with branch lengths calibrated to the gain/loss rates of Pfam domains (see Methods). Available in Supplementary Table 1. b, Conservation of archetypical protein domain architectures across orthogroups, in acetylases, deacetylases, methyltransferases, demethylases, remodellers and chaperones. In each heatmap, we indicate the fraction of genes within an orthogroup (rows) that contain a specific protein domain (columns). Domains in bold are catalytic (black) or reader (purple) functions. At the right of each heatmap, we summarize the presence/absence profile of each orthogroup across eukaryotic lineages (as listed in Fig. 1a).

Extended Data Fig. 5 Evolution of the hPTM reader toolkit.

a, Pie plot representing the number of genes classified as part of the catalytic (acetylases, deacetylases, methyltransferases, demethylases, remodellers or chaperones) or reader families or as both. The barplot at the right shows the most common reader domains in genes classified with both reader and catalytic functions. b, Pie plot representing the number of reader domain-encoding genes classified according to whether they contain one type of reader domain (for example, PHD) or more than one (for example, PHD + PWWP). The barplot at the right shows the most common combinations of reader domains among genes with multiple reader domains. c, Summary of gene family gains per reader family, with example cases highlighted in selected nodes. Node size is proportional to number of gains at 90% probability.

Extended Data Fig. 6 Transposon–chromatin gene fusions.

a, Number of candidate fusion genes classified by the level of gene model validation evidence, based on contiguity of the gene model over the genome assembly (that is lack of poly-N stretches in the genomic region between the TE- and chromatin-associated domains), evidence of expression, and evidence of contiguous expression (see inset at the right). b, Summary of candidate gene fusions within each chromatin-associated gene family, divided by gene family. For each gene, we indicate their similarity to known TE families, presence of TE-associated domains, the evidence of gene model validity, and information on their gene structure (whether they are monoexonic or are located in clusters with other fusion genes). Source data available in Supplementary Table 6. c, Number of species with at least one valid fusion, divided by gene family. d, Mapping positions of RNA-seq reads supporting candidate gene-transposon fusions (selected examples from Fig. 5e). For each fusion, we show reads spanning the region along the spliced transcript that fully covers the transposon-associated domains (highlighted in green), the chromatin-associated domains, and the inter-domain region. Uninterrupted stretches of mapped positions between domains indicate the validity of a domain co-occurrence. For clarity purposes, reads mapping entirely within a single domain have been excluded from this visualization.

Extended Data Fig. 7 Chromatin proteins in viruses.

a-c, Selected gene trees highlighting examples of eukaryotic- and prokaryotic-like viral homologues. d, Number of viral genes of each chromatin-associated gene family, classified according to their closest neighbours from cellular clades in gene tree analyses based on phylogenetic affinity scores (see Methods). Within each gene family, viral sequences are classified according to their PFAM domain architecture – the most common architecture being single domain in most gene families except for remodellers and BIR readers. e, Id. but classifying viral genes according to their phylogenetic affinity to eukaryotic orthology groups. Source data available in Supplementary Table 6.

Supplementary information

Reporting Summary

Supplementary Data 1

Taxon sampling. a, List of eukaryotic species used in the comparative genomic analyses, including species abbreviations, data sources for genome or transcriptome assemblies and annotations and their taxonomic classification. b, List of gene expression datasets (SRA accession numbers) used for gene model validation analyses of candidate fusion genes. c, List of histone post-translational modification proteomics datasets used in this study (PRIDE accession numbers).

Supplementary Data 2

Histone clusters and classification. a, Pairs of collinear histone-encoding genes, including their genomic coordinates and relative orientation. b, List and sequences of archaeal HMfB histones with N-terminal tails (at least ten amino acids before a complete globular domain). c, Classification of histone variants across eukaryotes.

Supplementary Data 3

hPTM conservation. a–g, Table of hPTMs identified in histones of the 26 eukaryotic species used in the comparative proteomics analysis, separated by histone type (canonical and major variants: H2A, H2B, H3, H4, macroH2A, H2A.Z and H1). Each entry corresponds to a modified peptide, for which we specify modification coordinates along the peptide and relative to the consensus histone sequence (if available). We also indicate whether each peptide can be uniquely mapped to a conserved or non-conserved region in a canonical histone or to specific histone variants. These tables also include entries for hPTMs reported in the literature (indicated as a cited source or as a specific UNIPROT entry; see Methods for a list of sources); in these cases, source peptides and associated data may not be available. h, hPTMs in archaea.

Supplementary Data 4

Gene family analysis. a, List of gene classes analysed in the comparative genomics analyses, including the PFAM protein domains used to retrieve homologues and search parameters. b, List of transposon-associated PFAM domains surveyed in the analyses of transposon–chromatin gene fusions.

Supplementary Data 5

Evolution of the chromatin machinery in eukaryotes. a, Summary of gene family evolutionary patterns in eukaryotes (n = 1,713 orthogroups). For each orthogroup, we indicate its gene and functional class, the number of members, species where it is present and major eukaryotic lineages (Amoebozoa, Opisthokonta + Breviatea + Apusozoa, CRuMs, Ancyromonadida, Malawimonadidae, Archaeplastida + Cryptista, SAR + Haptista, Hemimastigophora, Discoba and Metamonada), the probability of presence at the last eukaryotic common ancestor, the phylogenetic affinity of their closest homologues (other eukaryotic orthogroups, bacteria, archaea or viruses) and their average frequency amongst the ten nearest neighbours of its member gene in phylogenetic trees (‘Phylogenetic affinity score’, Methods); as well as its consensus protein domain architecture (present in at least 25% of its members). We also indicate the gene symbols of members from four model species: H. sapiens, D. melanogaster, S. cerevisiae and A. thaliana. b,c, Probability of gain and loss of each gene family at extant and ancestral nodes along the eukaryotic phylogeny. d, Orthogroup assignments per gene.

Supplementary Data 6

Transposon fusions and viral homology. a, List of candidate fusions between chromatin-associated genes and transposons, including the phylogenetic classification of each gene (orthogroup), protein domain architectures and the transcriptomics-level and gene model-level evidence supporting each fusion. b, List of chromatin-associated genes encoded by viral genomes, including their species of origin and a summary of their phylogenetic embedding among cellular species (specifically, which are its closest homologues in cellular genomes and the fraction of phylogenetic nearest neighbours they represent, the closest eukaryotic gene family among those close to eukaryotic genes in the gene trees and the distance to the closest cellular homologue).

Supplementary Data 7

Phylogenetic analyses. Collection of gene trees used to identify orthology groups for the eukaryotic chromatin toolkit. UFBS bootstrap supports rare indicated at each node. An annotated eukaryotic species tree is also included.

Supplementary Data 8

Peptide sequences. Collection of peptide sequences used to build gene trees of the eukaryotic chromatin toolkit.

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Grau-Bové, X., Navarrete, C., Chiva, C. et al. A phylogenetic and proteomic reconstruction of eukaryotic chromatin evolution. Nat Ecol Evol 6, 1007–1023 (2022). https://doi.org/10.1038/s41559-022-01771-6

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