Rethinking large scale phylogenomics with PhyloToL 6, a flexible toolkit to enable phylogeny-informed data curation and analysis
Cote-L'Heureux, A. E.; Leleu, M.; Ani, G.; Gawron, R.; Katz, L. A.
Show abstract
Eukaryotic diversity is largely microbial, with macroscopic lineages (plant, animals and fungi) nesting among a plethora of diverse protists. Understanding the evolutionary relationships among eukaryotes is rapidly advancing through omics analyses, but phylogenomics are challenging for microeukaryotes, particularly uncultivable lineages, as single-cell sequencing approaches generate a mixture of sequences from hosts, associated microbiomes, and contaminants. Moreover, many analyses of eukaryotic gene families and phylogenies rely on boutique datasets and methods that are challenging for other research groups to replicate. To address these challenges, we present EukPhylo v1.0, a modular, user-friendly pipeline that enables effective data curation through phylogeny-informed contamination removal, estimation of homologous gene families (GFs), and generation of both multisequence alignments and gene trees. Analyses can use a hook database of [~]15k ancient GFs or users can easily replace this hook with a set of gene families of interest. We demonstrate the power of EukPhylo, including a suite of stand-alone utilities, through analyses of 500 conserved GFs sampled from 1,000 diverse species of eukaryotes, bacteria and archaea. We show improvements in estimates of the eukaryotic tree of life, recovering clades that are well established in the literature, through successive rounds of curation using the EukPhylo contamination loop. The final trees corroborate numerous hypotheses in the literature (e.g. Opisthokonta, Rhizaria, Amoebozoa) while challenging others (e.g. CRuMs, Obazoa, Diaphoretickes). We believe that the flexibility and transparency of EukPhylo sets standards for curation of omics data for future studies. AUTHOR SUMMARYThe majority of eukaryotic lineages are microbial, with plants and animals nesting among diverse amoeba, flagellates, and other predominantly-microbial clades. Yet analyses of the evolution of microbial eukaryotes is hampered by the lack of tools for efficient analysis of genome-scaled data, especially in light of the genome complexity and high levels of contamination associated with these microorganism. Furthermore, many existing analyses rely on boutique datasets and decision making that lacks transparency and are thus difficult for others to repeat. To address these challenges, we present EukPhylo as an easy-to-use toolkit that fills a gap in phylogenomic methods, and we analyze of 500 gene families from 1,000 species to demonstrate the power of this approach in estimating the eukaryotic tree of life. EukPhylo enables exploration of eukaryotic evolution in a manner that is both transparent and easily repeatable, and hence can be used to illuminate the origin and diversification of eukaryotic life on Earth.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Accurate, scalable, and fully automated inference of species trees from raw genome assemblies using ROADIES 94%
- Compensatory Relationship between Low Complexity Regions and Gene Paralogy in the Evolution of Prokaryotes 94%
- Estimating maximal microbial growth rates from cultures, metagenomes, and single cells via codon usage patterns 93%
Similar papers in this journal
Similar papers in this journal
- Comparison of gene clustering criteria reveals intrinsic uncertainty in pangenome analyses 95%
- A k-mer-based maximum likelihood method for estimating distances of reads to genomes enables genome-wide phylogenetic placement. 95%
- GUNC: Detection of Chimerism and Contamination in Prokaryotic Genomes 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.