Evidence map›Paper›PMID 40862604›Full record

ArticlemBio2025

Rethinking large-scale phylogenomics with EukPhylo v.1.0, a flexible toolkit to enable phylogeny-informed data curation and analyses of diverse eukaryotic lineages.

Laura A Katz, Marie Leleu, Godwin Ani, Rebecca Gawron, Auden Cote-L'Heureux

Abstract read
In one paragraph

Article in mBio, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Laura A Katz *Department of Biological Sciences, Smith College, Northampton, Massachusetts, USA.ORCID 0000-0002-9138-4702
Marie Leleu *Department of Biological Sciences, Smith College, Northampton, Massachusetts, USA.
Godwin AniDepartment of Biological Sciences, Smith College, Northampton, Massachusetts, USA.
Rebecca GawronDepartment of Biological Sciences, Smith College, Northampton, Massachusetts, USA.
Auden Cote-L'Heureux *Department of Biological Sciences, Smith College, Northampton, Massachusetts, USA.ORCID 0000-0001-5793-7695

Funding

Assessing evolutionary patterns in uncultivable ciliates and their microbiomes by combining single-cell transcriptomics and single-cell genomicsR15HG010409 · NHGRI · SMITH COLLEGE · PI KATZ, LAURA ALINE · 2019 to 2019
$400k
National Science Foundation DEB-2230391National Science Foundation OCE-1924570NHGRI NIH HHS R15 HG010409NIH HHS R15HG010409
6 · The paper itself

Abstract

Eukaryotic diversity is largely microbial, with macroscopic lineages (plants, animals, and fungi) nesting among a plethora of diverse protists. Our understanding of the evolutionary relationships among eukaryotes is rapidly advancing through 'omics analyses, but phylogenomic analyses 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 data sets and methods that are challenging for other research groups to replicate. To address these challenges, we present EukPhylo v.1.0, 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. For the GF assignment, we provide the "Hook Database" of ~15,000 ancient GFs, which users can easily replace with a set of gene families of interest. We demonstrate the power of EukPhylo, including a suite of stand-alone utilities, through phylogenomic 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). The flexibility and transparency of EukPhylo set new standards for curation of 'omics data for future studies.IMPORTANCEIlluminating the diversity of microbial lineages is essential for estimating the tree of life and characterizing principles of genome evolution. However, analyses of microbial eukaryotes (e.g., flagellates, amoebae) are complicated by both the paucity of reference genomes and the prevalence of contamination (e.g., by symbionts, microbiomes). EukPhylo v.1.0 enables taxon-rich analyses "on the fly" as users can choose optimal gene families for their focal taxa and then use replicable approaches to curate data in estimating both gene and species trees. With multiple entry points and curated data sets from up to 15,000 gene families from 1,000 taxa ready for use, EukPhylo provides a powerful launching point for researchers interested in the evolution of eukaryotes.

Indexed as

Computational BiologyData CurationEukaryotaGenomicsPhylogenySoftwarecontaminationeukaryotic tree of lifemicrobiomephylogeneticsphylogenomic standardsprotistssingle-cell transcriptomes

Identifiers

PMID40862604
PMCPMC12506077

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.