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6 results for “eukaryogenesis”
Dominant contribution of Asgard archaea to eukaryogenesis (2024) Tobiasson, V., Koonin, E. PROCESSED DATA AND METADATA
<h1>Main data deposit for "Dominant contribution of Asgard archaea to eukaryogenesis". </h1> <p>Victor Tobiasson, Jacob Luo, Yuri I Wolf, Eugene V Koonin</p> <p>Computational Biology Branch, Division of Intramural Research, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA</p> <p><strong>The Origin of eukaryotes is one of the key problems in evolutionary biology. The demonstration that the Last Eukaryotic Common Ancestor (LECA) already contained the mitochondrion, an endosymbiotic organelle derived from an alphaproteobacterium, and the discovery of Asgard archaea, the closest archaeal relatives of eukaryotes inform and constrain evolutionary scenarios of eukaryogenesis. We undertook a comprehensive analysis of the origins of the core eukaryotic genes tracing to the LECA within a rigorous statistical framework centered around evolutionary hypotheses testing using constrained phylogenetic trees. The results reveal dominant contributions of Asgard archaea to the origin of most of the conserved eukaryotic functional systems and pathways. A limited contribution from Alphaproteobacteria was identified, primarily relating to the energy transformation systems and Fe-S cluster biogenesis, whereas ancestry from other bacterial phyla was scattered across the eukaryotic functional landscape, without consistent trends. These findings suggest a model of eukaryogenesis in which key features of eukaryotic cell organization evolved in the Asgard ancestor, followed by the capture of the Alphaproteobacterial endosymbiont, and augmented by numerous but sporadic horizontal acquisition of genes from other bacteria both before and after endosymbiosis. </strong></p> <div> <div> <div>Version 0.3, updated 180325</div> <div> </div> <div> </div> <div>Main data repository for:</div> <div>Dominant contribution of Asgard archaea to eukaryogenesis (2024) </div> <div>Tobiasson, V., Koonin, E.</div> <div> </div> <div>Contains all final parsed data from the main Eukaryogenesis project </div> <div>investigating the evolutionary ancetries of eukaryotic protein families. </div> <div> </div> <div>Currently (non-static) available at: </div> <div>https://www.biorxiv.org/content/10.1101/2024.10.14.618318v2</div> <div>https://assets-eu.researchsquare.com/files/rs-5352492/v1/2f9c68ae-cf3e-420a-8d29-867b6fb1a878.pdf</div> <div> </div> <div>All code used to generate the data present within this repository available at: </div> <div>https://github.com/VictorTobiasson/eukgen </div> <div> </div> <div> </div> <div>### General information</div> <div> </div> <div>To identify associations between prokaryotic and eukaryotic protein families, separate</div> <div>hidden Markov model (HMM) databases for prokaryotes and eukaryotes were constructed </div> <div>using a custom, cascaded, sequence-to-profile clustering pipeline, implemented using </div> <div>mmseqs2, followed by a multistep data-reduction and multiple sequence alignment (MSA) </div> <div>procedure to generate HMM profiles using hhsuite. </div> <div> </div> <div>A prokaryotic database of 37 million protein sequences was curated from prokaryotic </div> <div>genomes obtained from the NCBI GenBank in November 2023 and supplemented with proteins </div> <div>extracted from 146 Asgard genome assemblies. To avoid inclusion of genes present only </div> <div>within a narrow subset of species, possibly resulting from horizontal transfer from </div> <div>eukaryotes post LECA, we reconstructed the “soft-core” pangenome for each of the 26 </div> <div>curated prokaryotic taxonomic classes. These pangenomes include only those genes that </div> <div>are present in at least 67% of the families within each class of Bacteria and Archaea. </div> <div>The initial eukaryotic database consisted of 30 million protein sequences from 993 </div> <div>species taken from EukprotV3 and cleaned using mmseqs2 to remove likely prokaryotic </div> <div>contaminants. </div> <div> </div> <div>Both databases were clustered and MSAs constructed for all non, singleton clusters </div> <div>and HMM profiles created. The resulting eukaryotic HMM dataset was queried against </div> <div>the prokaryotic dataset using hhblits to identify sets of homologous protein sequences. </div> <div>Each eukaryotic cluster and all its significant prokaryotic hits constituted an individual</div> <div> sequence set, hereinafter referred to as an Eukaryotic/Prokaryotic Orthologous Cluster </div> <div>(EPOC). The EPOCs constitute groups of homologous proteins from eukaryotes and prokaryotes </div> <div>(each EPOC contains a unique set of eukaryotic proteins, but some clusters of prokaryotic </div> <div>proteins can be present in multiple EPOCs) that were used for phylogenetic tree </div> <div>construction, annotation, and evolutionary hypothesis testing. </div> <div> </div> <div>To infer the most likely prokaryotic ancestry of the eukaryotic proteins in each EPOC, </div> <div>rather than relying on the tree topology directly, we employed a probabilistic approach </div> <div>for evolutionary hypothesis testing using constraint trees. We exhaustively sampled all </div> <div>arrangements of likely sister clades and obtained Expected Likelihood Weights (ELW) for </div> <div>the set of possible sister clade models. As the ELW metric is analogous to model selection </div> <div>confidence, here we take it to be proportional to the probability of a sampled prokaryotic </div> <div>clade to be the true sister group of the given eukaryotic clade among a set of competing </div> <div>sister clades. For each EPOC, our analysis dynamically accounts for long branch outliers </div> <div>and is robust to phylogenetically non-homogenous clades. This analysis is further capable </div> <div>of resolving eukaryotic paraphyly, treating each eukaryotic clade within a EPOC as a </div> <div>single datapoint for downstream analysis. Our resulting data contains EPOCs annotated </div> <div>using profiles generated from KEGG Orthology Groups (KOGs), each with an MSA generated </div> <div>using muscle5, a maximum likelihood tree inferred using IQtree2 and associated ELW values </div> <div>for all candidate prokaryotic sister phyla. The analysis of prokaryotic ancestry was </div> <div>performed only for those eukaryotic clades that included more than 5 distinct taxonomic </div> <div>labels, with at least one coming from Amorphea and one from Diaphoretickes, the two </div> <div>expansive eukaryotic clades considered to represent either the first or the second </div> <div>bifurcation in the evolution of eukaryotes. Thus, these clades likely represent genes </div> <div>mapping back to the LECA.</div> <div> </div> <div>For further details please see main publication or contact</div> <div>victor.tobiasson@nih.gov</div> <div>eugene.koonin@nih.gov</div> <div> </div> <div> </div> <div>### Included files</div> <div> </div> <div>Unless otherwise stated all files contained are tab separated and utf-8 encoded </div> <div>with the first row containing header information. </div> <div>All data entries encoding lists are “|” (pipe) separated. </div> <div>Fields without data values are filled with string entries of “none”.</div> <div> </div> <div>--- Databases ---</div> <div>euk72_ep.tar.gz</div> <div>prok2311_as.tar.gz</div> <div>Prok2311As_final_clusters.tsv</div> <div>Euk72Ep_final_clusters.tsv</div> <div>prok2311_as.hmmDB.tar.gz</div> <div>euk72_ep.hmmDB.tar.gz</div> <div> </div> <div>--- Annotation and Curation ---</div> <div>NCBI_taxonomy_species_addendum.tsv</div> <div>NCBI_taxonomy_class_addendum.tsv</div> <div>Euk72Ep_Prok2311As_final_classes.tsv</div> <div>Euk72Ep_Prok2311As_final_classes.GTDB.tsv</div> <div>KEGG_category_mapping.tsv</div> <div>KEGG_metadata.tsv</div> <div> </div> <div>--- EPOC data ---</div> <div>EPOC_data.tar.gz</div> <div>EPOC_annotation_KEGG.tsv</div> <div>EPOC_data.tsv</div> <div>EPOC_data.pangenomes_s10.tsv</div> <div>EPOC_data.pangenomes_s25.tsv</div> <div>EPOC_data.pangenomes_s67.tsv</div> <div>EPOC_data.GTDB.tsv</div> <div> </div> <div># euk72_ep.tar.gz</div> <div>Gunzip-ed .tar archive containing a single directory with 10 files </div> <div>constituting the initial eukaryotic mmseqs2 database with taxonomy annotation. </div> <div>Constructed from a pre-selected list of 72 eukaryotic proteomes downloaded from </div> <div>NCBI as well as a “clean” version of Eukprot, lacking highly prokaryotic-like </div> <div>contaminant sequences. </div> <div> </div> <div># prok2311_as.tar.gz</div> <div>Gunzip-ed .tar archive containing a single directory with 10 files constituting the </div> <div>initial prokaryotic mmseqs2 database with taxonomy annotation. Constructed from </div> <div>47545 complete genomes retrieved from NCBI in November 2023. </div> <div> </div> <div># prok2311_as.hmmDB.tar.gz</div> <div>Gunzip-ed .tar archive containing 6 files. Comprises an HHSuite Databse formatted </div> <div>from prok2311_as non--singleton clusters, contains 26286 profiles.</div> <div> </div> <div># euk72_ep.hmmDB.tar.gz</div> <div>Gunzip-ed .tar archive containing 6 files. Comprises an HHSuite Databse formatted </div> <div>from euk72_ep non-singleton clusters, contains 1631704 profiles.</div> <div> </div> <div># NCBI_taxonomy_species_addendum.tsv</div> <div>Taxonomy mapping file with manually curated ‘class’ level annotation for poorly </div> <div>annotated species. </div> <div> </div> <div>taxid: NCBI taxid</div> <div>proposed_class_id: Manually assigned NCBI taxid</div> <div>proposed_class_label: NCBI class name</div> <div>org_name: NCBI organism name</div> <div> </div> <div># NCBI_taxonomy_class_addendum.tsv</div> <div>Class revision file mapping poorly populated class level entries to higher order </div> <div>manually curated labels. Also includes information for small classes with shallow </div> <div>taxonomy which are deleted from the EPOC analysis at the level of tree construction.</div> <div> </div> <div>taxid: NCBI taxid</div> <div>ncbi_class: NCBI taxid of rank corresponding to ‘class’ following manual </div> <div>amendment as per NCBI_taxonomy_species_addendum.tsv</div> <div>revised_class_id: Manually assigned NCBI taxid of rank corresponding to ‘class’</div> <div>revised_class_label: Proposed cleartext name of manually revised revised_class_id </div> <div> </div> <div># Euk72Ep_Prok2311As_final_classes.tsv</div> <div>Final taxonomy at NCBI rank ‘class’ following revisions for all sequences in Euk72Ep or </div> <div>Prok2311As. These taxonomic labels are used for EPOC tree annotation. </div> <div> </div> <div>acc: mmseqs database header in either prok2311_as or euk72_ep databases</div> <div>taxid: NCBI taxid for organism</div> <div>superkingdom: Top level NCBI taxonomy classification Bacteria, Archaea or Eukarya, </div> <div>used to define Eukaryotic outgroups in EPOC analysis</div> <div>class: Cleartext name of manually revised NCBI rank ‘class’ identifier for annotation</div> <div> </div> <div># Euk72Ep_Prok2311As_final_classes.GTDB.tsv</div> <div>Final taxonomy at GTDB rank ‘phylum’ transferred using marker genes from GTDB release 220</div> <div> </div> <div>acc: mmseqs database header in either prok2311_as or euk72_ep databases</div> <div>taxid: NCBI taxid for organism</div> <div>superkingdom: Top level NCBI taxonomy classification Bacteria, Archaea or Eukarya, </div> <div>used to define Eukaryotic outgroups in EPOC analysis</div> <div>class: Cleartext name of assigne GTDB phylum</div> <div> </div> <div># Prok2311As_final_clusters.tsv</div> <div>Cluster mapping file for accessions within the initial Prok2311A database to the </div> <div>final clusters used for HMM creation </div> <div> </div> <div>cluster_acc: cluster representative</div> <div>acc: cluster member</div> <div> </div> <div># Euk72Ep_final_clusters.tsv</div> <div>Cluster mapping file for accessions within the initial Prok2311A database to the </div> <div>final clusters used for HMM creation</div> <div> </div> <div>cluster_acc: cluster representative</div> <div>acc: cluster member</div> <div> </div> <div># EPOC_data.tar.gz</div> <div>Gunzip-ed directory containing 16035 EPOC folders. Each folder is named corresponding </div> <div>to the eukaryotic cluster representative which generated its profile as an ID </div> <div>Matches the tree_name field in EPOC_data_prok2311As.tsv</div> <div>contains the following files:</div> <div> </div> <div><EPOC_ID>.merged.fasta: sequences for all members of the EPOC</div> <div><EPOC_ID>.merged.fasta.leaf_mapping: tsv separated file containing taxonomy and tree reduction data</div> <div><EPOC_ID>.merged.fasta.muscle: main cropped MSA for tree generation </div> <div><EPOC_ID>.merged.fasta.muscle.iqtree: IQtree2 output from tree generation</div> <div><EPOC_ID>.merged.fasta.muscle.treefile.annot: annotated newick tree file with final tree</div> <div><EPOC_ID>.merged.tree_data.tsv: final parsed tree data with columns matching EPOC_data_prok2311As.tsv</div> <div> </div> <div>EPOCs with more than one possible eukaryotic sister phyla also contains </div> <div>a folder "constraint_analysis" with constraint tree information used for </div> <div>ELW value calculation. </div> <div> </div> <div># EPOC_data.tsv</div> <div>Main resulting data from all Eukaryotic/Prokaryotic Orthologous Clusters (EPOCs) </div> <div>based on pangenomes defined as including 10% of species per class. This is the main</div> <div>data to be used for genereting the core dataset and for data visualistation</div> <div>Contains information regarding tree breakdown, LCA membership and phylogenetic </div> <div>distances between all detected LCAs. Equivalent to the stacked dataframes from all </div> <div>EPOC directories in EPOC_data </div> <div> </div> <div>tree_name: unique index for each EPOC </div> <div>euk_clade_rep: unique index for each annotated eukaryotic clade within each tree_name</div> <div>euk_clade_size: number of original sequences represented by euk_clade_rep</div> <div>euk_clade_weight: metric for taxonomic purity for each euk_clade_rep</div> <div>euk_leaf_clade: boolean indicating whether euk_clade_rep contains a single leaf</div> <div>euk_LCA: lowest taxa spanning all members in euk_clade_rep</div> <div>euk_scope: list of all taxonomic classes in euk_clade_rep</div> <div>euk_scope_len: length of euk_scope list</div> <div>prok_clade_rep: unique index for each annotated prokaryotic clade for each euk_clade_rep</div> <div>prok_clade_size: number of original sequences represented by prok_clade_rep</div> <div>prok_clade_weight: metric for taxonomic purity for each prok_clade_rep</div> <div>prok_leaf_clade: boolean indicating whether prok_clade_rep contains a single leaf</div> <div>prok_taxa: lowest taxa spanning all members in prok_clade_rep</div> <div>dist: tree-distance from lowest tree node containing all members of prok_clade_rep to lowest tree node containing all members of euk_clade_rep</div> <div>top_dist: graph-distance (node-distance) from lowest tree node containing all members of prok_clade_rep to lowest tree node containing all members of euk_clade_rep</div> <div>raw_stem_length: tree-distance from lowest tree node containing the union of all members of prok_clade_rep and euk_clade_rep to the tree node containing all members of euk_clade_rep</div> <div>median_euk_leaf_dist: median value for all tree distances from the tree node containing all members of euk_clade_rep to the individual leaves</div> <div>stem_length: raw_stem_length/median_euk_leaf_dist</div> <div>logL: log likelihood of best constraint tree constructed</div> <div>deltaL: log likelihood difference between constraint tree for prok_clade_rep and best constraint tree constructed</div> <div>bp-RELL: validation metric from IQtree -trees, see iqtree.org</div> <div>bp-RELL_accept: as above</div> <div>p-KH: as above</div> <div>p-KH_accept: as above</div> <div>p-SH: as above</div> <div>p-SH_accept: as above</div> <div>c-ELW: as above</div> <div>c-ELW_accept: as above</div> <div>p-AU: as above</div> <div>p-AU_accept: as above</div> <div> </div> <div># EPOC_data.pangenomes_s10.tsv</div> <div>Resulting data from all Eukaryotic/Prokaryotic Orthologous Clusters (EPOCs) calculated </div> <div>based on pangenomes defined as including 10% of species per class.</div> <div>Identical file structure to EPOC_data.tsv</div> <div> </div> <div># EPOC_data.pangenomes_s25.tsv</div> <div>Resulting data from all Eukaryotic/Prokaryotic Orthologous Clusters (EPOCs) calculated </div> <div>based on pangenomes defined as including 25% of species per class.</div> <div>Identical file structure to EPOC_data.tsv</div> <div> </div> <div># EPOC_data.pangenomes_s67.tsv</div> <div>Resulting data from all Eukaryotic/Prokaryotic Orthologous Clusters (EPOCs) calculated </div> <div>based on pangenomes defined as including 67% of species per class.</div> <div>Identical file structure to EPOC_data.tsv</div> <div> </div> <div># EPOC_data.GTDB.tsv</div> <div>Resulting data from all Eukaryotic/Prokaryotic Orthologous Clusters (EPOCs) calculated </div> <div>under revised taxonomy from GTDB based on data from Euk72Ep_Prok2311As_final_classes.GTDB.tsv</div> <div>Identical file structure to EPOC_data.tsv</div> <div> </div> <div># EPOC_data.alpha_replicates.tsv</div> <div>Resulting data from 20 repetitions of Eukaryotic/Prokaryotic Orthologous Clusters (EPOCs) calculated </div> <div>from a subset of Alphaproteobacterial-derived EPOCs. </div> <div>Identical file structure to EPOC_data.tsv with the addition of:</div> <div> </div> <div>rep: indicating technical replicate number, 0-19</div> <div> </div> <div># EPOC_annotation_KEGG.tsv</div> <div>Parsed HHblits output of HMM profiles generated from KEGG KOGs (KEGG Orthologous Groups) </div> <div>against eukaryotic profiles constituting each EPOC</div> <div> </div> <div>Query: query name equal to tree_name from EPOC_data</div> <div>Target: target name equal to kogid in KEGG_category_mapping and KEGG_metadata</div> <div>Prob: data from HHblits, see https://github.com/soedinglab/hh-suite/wiki</div> <div>E-value : as above</div> <div>P-value : as above</div> <div>Score: as above</div> <div>SS: as above</div> <div>Cols: as above</div> <div>Identities: as above</div> <div>Similarity: as above</div> <div>Sum_probs: as above</div> <div>Query-HMM-start: as above</div> <div>Query-HMM-end: as above</div> <div>Template-HMM-start: as above</div> <div>Template-HMM-end: as above</div> <div>Template_columns: as above</div> <div>Template_Neff : as above</div> <div>Pairwise_cov: calculated pairwise coverage from Query and Target start and end</div> <div>Description: category_name from KEGG_category_mapping</div> <div> </div> <div># KEGG_category_mapping.tsv</div> <div>Mapping of relevant KOG identifiers to their higher order categories as </div> <div>"Maps" "Modules" or "Reactions" as per KEGG see https://www.kegg.jp/kegg/pathway.html</div> <div> </div> <div>kogid: unique KOG identifier</div> <div>category_id: KEGG map, module, or reaction number</div> <div>category_name: cleartext name for KOG identifier</div> <div> </div> <div># KEGG_metadata.tsv</div> <div>File mapping KOGs to BRITE classification and to additional databases of chemical properties.</div> <div> </div> <div>kogid: unique KOG identifier</div> <div>name: cleartext name for KOG identifier</div> <div>brite_A: list of BRITE-A sets including KOG</div> <div>brite_B: list of BRITE-A sets including KOG</div> <div>brite_C: list of BRITE-A sets including KOG</div> <div>EC: list of Enzyme commission numbers associated with KOG, see https://enzyme.expasy.org/</div> <div>TC: list of transporter classification numbers associated with KOG, see https://www.tcdb.org/</div> <div>RN: list of KEGG reaction numbers associated with KOG</div> <div>CA: list of CAZY numbers associated with KOG, see http://www.cazy.org/</div> <div>GO: list of GO terms associated with KOG, see https://geneontology.org/</div> </div> <div> </div> </div>
Host-adaptation in Legionellales is 1.9 Gya, coincident with eukaryogenesis
<p>This dataset contains genomes, proteomes and protein alignments mentioned in Hugoson et al (2021). It has been used to analyze the evolution of host-adaptation in the order Legionellales.</p> <p>The data is organized by dataset type, and then by dataset.</p> <p>The four datasets used here are</p> <ul> <li><strong>Gamma105</strong>, comprising 105 <em>Gammaproteobacteria</em> and 5 outgroups;</li> <li><strong>Legio93</strong>, comprising 93 <em>Legionellales</em> and 20 outgroups;</li> <li><strong>Bacteria134</strong>, built on Gamma105, adding 27 genomes from Betts et al. (2018)</li> <li><strong>Bacteria93</strong>, built by removing <em>Legionella</em>, <em>Francisella</em>, <em>Fangia</em> and <em>Piscirickettsia</em> genera from Bacteria134</li> </ul> <p><strong>1_genomes</strong><br> Genomes as downloaded or assembled</p> <ul> <li>1_1_Gamma105</li> <li>1_2_Legio93</li> </ul> <p><strong>2_proteomes</strong><br> Proteomes, as annotated by prokka</p> <ul> <li>2_1_Gamma105</li> <li>2_2_Legio93</li> <li>2_3_Bacteria134</li> </ul> <p><strong>3_alignments</strong></p> <p>In the first three and the fifth folders, the following files are found. All sequence and alignment files are in fasta format:</p> <ul> <li>*_concatenated.fasta: concatenated alignment, trimmed.</li> <li>*.map: map of the files, tab-separated. The first row is a title row. The three first columns give the organism, the marker and the id (as found in the fasta file) for the protein.</li> <li>*_unaligned: non-aligned sequences for each marker.</li> <li>*_aligned: aligned sequences, for each marker. The prefix gives the software used for the alignment.</li> <li>*_trimmed: aligned, trimmed sequences for each marker. The prefix gives the software used to trim the alignment.</li> </ul> <p> </p> <ul> <li><strong>3_1_Gamma105</strong>: Based on the Bact109 set of markers.</li> <li><strong>3_2_Legio93</strong>: Based on the Bact109 set of markers.</li> <li><strong>3_3_Bacteria134</strong>: Based on Gamma105 set and Bact109 set of markers.</li> <li><strong>3_4_Bacteria93</strong>: Based on Bacteria134 (removed fast-evolving genomes).</li> <li><strong>3_5_TB4SS_auto</strong>: Alignment of 12 genes of the T4BSS, automatically detected in all genomes. </li> <li><strong>3_6_TB4SS_manual</strong>: Alignment of 25 genes of the T4BSS, manually curated by collinearity analysis.</li> </ul> <p> </p>
Data from: Obligate endosymbiosis explains genome expansion during eukaryogenesis
<p>The endosymbiosis of an alpha-proteobacterium that gave rise to mitochondria was one of the key events in eukaryogenesis. One striking outcome of eukaryogenesis was a much more complex cell with a large genome. Despite the existence of many alternative hypotheses for this and other patterns potentially related to endosymbiosis, a constructive evolutionary model in which these hypotheses can be studied is still lacking.</p> <p>Here, we present a new theoretical approach in which we focus on the consequences rather than the causes of the mitochondrial endosymbiosis. Using a constructive evolutionary model of cell-cycle regulation, we find that genome expansion and genome size asymmetry arise from emergent host–symbiont cell-cycle coordination. We also find that holobionts with large host and small symbiont genomes perform best on long timescales, and mimic the outcome of eukaryogenesis.</p> <p>By designing and studying a constructive evolutionary model of obligate endosymbiosis, we uncovered some of the forces that may drive the patterns observed in nature. Our results provide a theoretical foundation for patterns related to the mitochondrial endosymbiosis, such as genome size asymmetry, and reveal evolutionary outcomes that have not been considered so far, such as cell-cycle coordination without direct communication.</p>
Data from: Obligate endosymbiosis explains genome expansion during eukaryogenesis
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Data from: Horizontal gene flow from Eubacteria to Archaebacteria and what it means for our understanding of eukaryogenesis
The origin of the eukaryotic cell is considered one of the major evolutionary transitions in the history of life. Current evidence strongly supports a scenario of eukaryotic origin in which two prokaryotes, an archaebacterial host and an α-proteobacterium (the free-living ancestor of the mitochondrion), entered a stable symbiotic relationship. The establishment of this relationship was associated with a process of chimerization, whereby a large number of genes from the α-proteobacterial symbiont were transferred to the host nucleus. A general framework allowing the conceptualization of eukaryogenesis from a genomic perspective has long been lacking. Recent studies suggest that the origins of several archaebacterial phyla were coincident with massive imports of eubacterial genes. Although this does not indicate that these phyla originated through the same process that led to the origin of Eukaryota, it suggests that Archaebacteria might have had a general propensity to integrate into their genomes large amounts of eubacterial DNA. We suggest that this propensity provides a framework in which eukaryogenesis can be understood and studied in the light of archaebacterial ecology. We applied a recently developed supertree method to a genomic dataset composed of 392 eubacterial and 51 archaebacterial genera to test whether large numbers of genes flowing from Eubacteria are indeed coincident with the origin of major archaebacterial clades. In addition, we identified two potential large-scale transfers of uncertain directionality at the base of the archaebacterial tree. Our results are consistent with previous findings and seem to indicate that eubacterial gene imports (particularly from δ-Proteobacteria, Clostridia and Actinobacteria) were an important factor in archaebacterial history. Archaebacteria seem to have long relied on Eubacteria as a source of genetic diversity, and while the precise mechanism that allowed these imports is unknown, we suggest that our results support the view that processes comparable to those through which eukaryotes emerged might have been common in archaebacterial history.
Data from: Horizontal gene flow from Eubacteria to Archaebacteria and what it means for our understanding of eukaryogenesis
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