Dataset Information

Inference and reconstruction of the heimdallarchaeial ancestry of eukaryotes.

ABSTRACT: In the ongoing debates about eukaryogenesis-the series of evolutionary events leading to the emergence of the eukaryotic cell from prokaryotic ancestors-members of the Asgard archaea play a key part as the closest archaeal relatives of eukaryotes¹. However, the nature and phylogenetic identity of the last common ancestor of Asgard archaea and eukaryotes remain unresolved^2-4. Here we analyse distinct phylogenetic marker datasets of an expanded genomic sampling of Asgard archaea and evaluate competing evolutionary scenarios using state-of-the-art phylogenomic approaches. We find that eukaryotes are placed, with high confidence, as a well-nested clade within Asgard archaea and as a sister lineage to Hodarchaeales, a newly proposed order within Heimdallarchaeia. Using sophisticated gene tree and species tree reconciliation approaches, we show that analogous to the evolution of eukaryotic genomes, genome evolution in Asgard archaea involved significantly more gene duplication and fewer gene loss events compared with other archaea. Finally, we infer that the last common ancestor of Asgard archaea was probably a thermophilic chemolithotroph and that the lineage from which eukaryotes evolved adapted to mesophilic conditions and acquired the genetic potential to support a heterotrophic lifestyle. Our work provides key insights into the prokaryote-to-eukaryote transition and a platform for better understanding the emergence of cellular complexity in eukaryotic cells.

SUBMITTER: Eme L

PROVIDER: S-EPMC10307638 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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Inference and reconstruction of the heimdallarchaeial ancestry of eukaryotes.

Eme Laura L Tamarit Daniel D Caceres Eva F EF Stairs Courtney W CW De Anda Valerie V Schön Max E ME Seitz Kiley W KW Dombrowski Nina N Lewis William H WH Homa Felix F Saw Jimmy H JH Lombard Jonathan J Nunoura Takuro T Li Wen-Jun WJ Hua Zheng-Shuang ZS Chen Lin-Xing LX Banfield Jillian F JF John Emily St ES Reysenbach Anna-Louise AL Stott Matthew B MB Schramm Andreas A Kjeldsen Kasper U KU Teske Andreas P AP Baker Brett J BJ Ettema Thijs J G TJG

Nature 20230614 7967

In the ongoing debates about eukaryogenesis-the series of evolutionary events leading to the emergence of the eukaryotic cell from prokaryotic ancestors-members of the Asgard archaea play a key part as the closest archaeal relatives of eukaryotes<sup>1</sup>. However, the nature and phylogenetic identity of the last common ancestor of Asgard archaea and eukaryotes remain unresolved<sup>2-4</sup>. Here we analyse distinct phylogenetic marker datasets of an expanded genomic sampling of Asgard arch ...[more]

PMID: 37316666

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Project description:MotivationLocal ancestry inference (LAI) is the high resolution prediction of ancestry labels along a DNA sequence. LAI is important in the study of human history and migrations, and it is beginning to play a role in precision medicine applications including ancestry-adjusted genome-wide association studies (GWASs) and polygenic risk scores (PRSs). Existing LAI models do not generalize well between species, chromosomes or even ancestry groups, requiring re-training for each different setting. Furthermore, such methods can lack interpretability, which is an important element in each of these applications.ResultsWe present SALAI-Net, a portable statistical LAI method that can be applied on any set of species and ancestries (species-agnostic), requiring only haplotype data and no other biological parameters. Inspired by identity by descent methods, SALAI-Net estimates population labels for each segment of DNA by performing a reference matching approach, which leads to an interpretable and fast technique. We benchmark our models on whole-genome data of humans and we test these models' ability to generalize to dog breeds when trained on human data. SALAI-Net outperforms previous methods in terms of balanced accuracy, while generalizing between different settings, species and datasets. Moreover, it is up to two orders of magnitude faster and uses considerably less RAM memory than competing methods.Availability and implementationWe provide an open source implementation and links to publicly available data at github.com/AI-sandbox/SALAI-Net. Data is publicly available as follows: https://www.internationalgenome.org (1000 Genomes), https://www.simonsfoundation.org/simons-genome-diversity-project (Simons Genome Diversity Project), https://www.sanger.ac.uk/resources/downloads/human/hapmap3.html (HapMap), ftp://ngs.sanger.ac.uk/production/hgdp/hgdp_wgs.20190516 (Human Genome Diversity Project) and https://www.ncbi.nlm.nih.gov/bioproject/PRJNA448733 (Canid genomes).Supplementary informationSupplementary data are available from Bioinformatics online.

Dataset Information

Inference and reconstruction of the heimdallarchaeial ancestry of eukaryotes.

Publications

Inference and reconstruction of the heimdallarchaeial ancestry of eukaryotes.

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