DOI: 10.5281/zenodo.14002645
title: Dominant contribution of Asgard archaea to eukaryogenesis (2024) Tobiasson, V., Koonin, E. PROCESSED DATA AND METADATA

description: Main data deposit for "Dominant contribution of Asgard archaea to eukaryogenesis". 

Victor Tobiasson, Jacob Luo, Yuri I Wolf, Eugene V Koonin

Computational Biology Branch, Division of Intramural Research, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA

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. 

 

 

Version 0.1, updated 281024

Main data repository for Dominant contribution of Asgard archaea to eukaryogenesis (2024) Tobiasson, V., Koonin, E.

Contains all final parsed data from the main Eukaryogenesis project investigating the evolutionary ancetries of eukaryotic protein families. 

Currently available at: https://www.biorxiv.org/content/10.1101/2024.10.14.618318v2

All code used to generate the data present within this repository available at: https://github.com/VictorTobiasson/eukgen 

All intermediate data files, including full EPOC data available at 



10.5281/zenodo.14004407



 



 

### General information

To identify associations between prokaryotic and eukaryotic protein families, separate hidden Markov model (HMM) databases for prokaryotes and eukaryotes were constructed using a custom, cascaded, sequence-to-profile clustering pipeline, implemented using mmseqs2, followed by a multistep data-reduction and multiple sequence alignment (MSA) procedure to generate HMM profiles using hhsuite. 

 

A prokaryotic database of 37 million protein sequences was curated from prokaryotic genomes obtained from the NCBI GenBank in November 2023 and supplemented with proteins extracted from 146 Asgard genome assemblies. To avoid inclusion of genes present only within a narrow subset of species, possibly resulting from horizontal transfer from eukaryotes post LECA, we reconstructed the “soft-core” pangenome for each of the 26 curated prokaryotic taxonomic classes. These pangenomes include only those genes that are present in at least 67% of the families within each class of Bacteria and Archaea. The initial eukaryotic database consisted of 30 million protein sequences from 993 species taken from EukprotV3 and cleaned using mmseqs2 to remove likely prokaryotic contaminants. 

 

Both databases were clustered and MSAs constructed for all non, singleton clusters and HMM profiles created. The resulting eukaryotic HMM dataset was queried against the prokaryotic dataset using hhblits to identify sets of homologous protein sequences. Each eukaryotic cluster and all its significant prokaryotic hits constituted an individual sequence set, hereinafter referred to as an Eukaryotic/Prokaryotic Orthologous Cluster (EPOC). The EPOCs constitute groups of homologous proteins from eukaryotes and prokaryotes (each EPOC contains a unique set of eukaryotic proteins, but some clusters of prokaryotic proteins can be present in multiple EPOCs) that were used for phylogenetic tree construction, annotation, and evolutionary hypothesis testing. 

 

To infer the most likely prokaryotic ancestry of the eukaryotic proteins in each EPOC, rather than relying on the tree topology directly, we employed a probabilistic approach for evolutionary hypothesis testing using constraint trees. We exhaustively sampled all arrangements of likely sister clades and obtained Expected Likelihood Weights (ELW) for the set of possible sister clade models. As the ELW metric is analogous to model selection confidence, here we take it to be proportional to the probability of a sampled prokaryotic clade to be the true sister group of the given eukaryotic clade among a set of competing sister clades. For each EPOC, our analysis dynamically accounts for long branch outliers and is robust to phylogenetically non-homogenous clades. This analysis is further capable of resolving eukaryotic paraphyly, treating each eukaryotic clade within a EPOC as a single datapoint for downstream analysis. Our resulting data contains EPOCs annotated using profiles generated from KEGG Orthology Groups (KOGs), each with an MSA generated using muscle5, a maximum likelihood tree inferred using IQtree2 and associated ELW values for all candidate prokaryotic sister phyla. The analysis of prokaryotic ancestry was performed only for those eukaryotic clades that included more than 5 distinct taxonomic labels, with at least one coming from Amorphea and one from Diaphoretickes, the two expansive eukaryotic clades considered to represent either the first or the second bifurcation in the evolution of eukaryotes. Thus, these clades likely represent genes mapping back to the LECA.

 

For further details please see main publication or contact victor.tobiasson@nih.gov

https://www.biorxiv.org/content/10.1101/2024.10.14.618318v2

 

### Included files

Unless otherwise stated all files contained are tab separated and utf-8 encoded with the first row containing header information. All data entries encoding lists are “|” (pipe) separated. Fields without data values are filled with string entries of “none”.

 

euk72_ep.tar.gz

prok2311.tar.gz

NCBI_taxonomy_species_addendum.tsv

NCBI_taxonomy_class_addendum.tsv

Euk72Ep_Prok2311As_final_classes.tsv

Prok2311As_final_clusters.tsv

Euk72Ep_final_clusters.tsv

EPOC_data_prok2311As.tsv

EPOC_annotation_KEGG.tsv

KEGG_category_mapping.tsv 

KEGG_metadata.tsv

 

# NCBI_taxonomy_species_addendum.tsv

Taxonomy mapping file with manually curated ‘class’ level annotation for poorly annotated species. 

 

taxid: NCBI taxid 

proposed_class_id: Manually assigned NCBI taxid

proposed_class_label: NCBI class name 

org_name: NCBI organism name

 

# NCBI_taxonomy_class_addendum.tsv

Class revision file mapping poorly populated class level entries to higher order manually curated labels. Also includes information for small classes with shallow taxonomy which are deleted from the EPOC analysis at the level of tree construction.

 

taxid: NCBI taxid 

ncbi_class: NCBI taxid of rank corresponding to ‘class’ following manual amendment as per NCBI_taxonomy_species_addendum.tsv

revised_class_id: Manually assigned NCBI taxid of rank corresponding to ‘class’

revised_class_label: Proposed cleartext name of manually revised revised_class_id 

 

# Euk72Ep_Prok2311As_final_classes.tsv

Final taxonomy at NCBI rank ‘class’ following revisions for all sequences in Euk72Ep or Prok2311As. These taxonomic labels are used for EPOC tree annotation. 

 

acc: mmseqs database header in either prok2311_as or euk72_ep databases

taxid: NCBI taxid for organism 

superkingdom: Top level NCBI taxonomy classification Bacteria, Archaea or Eukarya, used to define Eukaryotic outgroups in EPOC analysis

class: Cleartext name of manually revised NCBI rank ‘class’ identifier for annotation

 

# euk72_ep.tar.gz

Gzip-ed .tar archive containing a single directory with 10 files constituting the initial eukaryotic mmseqs2 database with taxonomy annotation. Constructed from a pre-selected list of 72 eukaryotic proteomes downloaded from NCBI as well as a “clean” version of Eukprot, lacking highly prokaryotic-like contaminant sequences. 

 

# prok2311.tar.gz

Gzip-ed .tar archive containing a single directory with 10 files constituting the initial prokaryotic mmseqs2 database with taxonomy annotation. Constructed from 47, 545 complete genomes retrieved from NCBI in November 2023. 

 

# Prok2311As_final_clusters.tsv

Cluster mapping file for accessions within the initial Prok2311A database to the final clusters used for HMM creation 

 

cluster_acc: cluster representative

acc: cluster member

 

# Euk72Ep_final_clusters.tsv

Cluster mapping file for accessions within the initial Prok2311A database to the final clusters used for HMM creation

 

cluster_acc: cluster representative

acc: cluster member

 

# EPOC_data_prok2311As.tsv

Main resulting data from all Eukaryotic/Prokaryotic Orthologous Clusters (EPOCs). Contains information regarding tree breakdown, LCA membership and phylogenetic distances between all detected LCAs. 

 

tree_name: unique index for each EPOC  

euk_clade_rep: unique index for each annotated eukaryotic clade within each tree_name

euk_clade_size: number of original sequences represented by euk_clade_rep

euk_clade_weight: metric for taxonomic purity for each euk_clade_rep

euk_leaf_clade: boolean indicating whether euk_clade_rep contains a single leaf

euk_LCA: lowest taxa spanning all members in euk_clade_rep

euk_scope: list of all taxonomic classes in euk_clade_rep

euk_scope_len: length of euk_scope list

prok_clade_rep: unique index for each annotated prokaryotic clade for each euk_clade_rep

prok_clade_size: number of original sequences represented by prok_clade_rep

prok_clade_weight: metric for taxonomic purity for each prok_clade_rep

prok_leaf_clade: boolean indicating whether prok_clade_rep contains a single leaf

prok_taxa: lowest taxa spanning all members in prok_clade_rep

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

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

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

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

stem_length: raw_stem_length/median_euk_leaf_dist

logL: log likelihood of best constraint tree constructed

deltaL: log likelihood difference between constraint tree for prok_clade_rep and best constraint tree constructed

bp-RELL: validation metric from IQtree -trees, see iqtree.org

bp-RELL_accept: as above

p-KH: as above

p-KH_accept: as above

p-SH: as above

p-SH_accept: as above

c-ELW: as above

c-ELW_accept: as above

p-AU: as above

p-AU_accept: as above

 

# EPOC_annotation_KEGG.tsv

Parsed HHblits output of HMM profiles generated from KEGG KOGs (KEGG Orthologous Groups) against eukaryotic profiles constituting each EPOC

 

Query: query name equal to tree_name from EPOC_data

Target: target name equal to kogid in KEGG_category_mapping and KEGG_metadata

Prob: data from HHblits, see https://github.com/soedinglab/hh-suite/wiki

E-value : as above

P-value : as above

Score: as above

SS: as above

Cols: as above

Identities: as above

Similarity: as above

Sum_probs: as above

Query-HMM-start: as above

Query-HMM-end: as above

Template-HMM-start: as above

Template-HMM-end: as above

Template_columns: as above

Template_Neff : as above

Pairwise_cov: calculated pairwise coverage from Query and Target start and end

Description: category_name from KEGG_category_mapping

 

# KEGG_category_mapping.tsv

kogid: unique KOG identifier

category_id: KEGG map, module, or reaction number, see https://www.kegg.jp/kegg/pathway.html

category_name: cleartext name for KOG identifier

 

# KEGG_metadata.tsv

kogid: unique KOG identifier

name: cleartext name for KOG identifier

brite_A: list of BRITE-A sets including KOG 

brite_B: list of BRITE-A sets including KOG

brite_C: list of BRITE-A sets including KOG

EC: list of Enzyme commission numbers associated with KOG, see https://enzyme.expasy.org/

TC: list of transporter classification numbers associated with KOG, see https://www.tcdb.org/

RN: list of KEGG reaction numbers associated with KOG

CA: list of CAZY numbers associated with KOG, see http://www.cazy.org/

GO: list of GO terms associated with KOG, see https://geneontology.org/