Evidence map›Paper›PMID 32245390›Full record

ArticleMicrobiome2020

MetaEuk-sensitive, high-throughput gene discovery, and annotation for large-scale eukaryotic metagenomics.

Eli Levy Karin, Milot Mirdita, Johannes Söding

Open access · goldAbstract readVideo-Audio Media
In one paragraph

Article in Microbiome, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 183 papers.

0numbers the graph read from it
0cells of the map it votes in
183citing papers in PubMed
20.2field-weighted citation impact, top 1% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

183 citing papers in PubMed, 311 citations in OpenAlex.

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  6. Evolutionary dynamics of the arthropod molting machinery.Molecular biology and evolution · 2026
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123 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Eli Levy KarinQuantitative and Computational Biology, Max-Planck Institute for Biophysical Chemistry, 37077, Göttingen, Germany. eli.levy.karin@gmail.com.
Milot MirditaQuantitative and Computational Biology, Max-Planck Institute for Biophysical Chemistry, 37077, Göttingen, Germany.
Johannes SödingQuantitative and Computational Biology, Max-Planck Institute for Biophysical Chemistry, 37077, Göttingen, Germany. soeding@mpibpc.mpg.de.
Max Planck Institute for Biophysical Chemistry · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMetagenomics is revolutionizing the study of microorganisms and their involvement in biological, biomedical, and geochemical processes, allowing us to investigate by direct sequencing a tremendous diversity of organisms without the need for prior cultivation. Unicellular eukaryotes play essential roles in most microbial communities as chief predators, decomposers, phototrophs, bacterial hosts, symbionts, and parasites to plants and animals. Investigating their roles is therefore of great interest to ecology, biotechnology, human health, and evolution. However, the generally lower sequencing coverage, their more complex gene and genome architectures, and a lack of eukaryote-specific experimental and computational procedures have kept them on the sidelines of metagenomics.

resultsMetaEuk is a toolkit for high-throughput, reference-based discovery, and annotation of protein-coding genes in eukaryotic metagenomic contigs. It performs fast searches with 6-frame-translated fragments covering all possible exons and optimally combines matches into multi-exon proteins. We used a benchmark of seven diverse, annotated genomes to show that MetaEuk is highly sensitive even under conditions of low sequence similarity to the reference database. To demonstrate MetaEuk's power to discover novel eukaryotic proteins in large-scale metagenomic data, we assembled contigs from 912 samples of the Tara Oceans project. MetaEuk predicted >12,000,000 protein-coding genes in 8 days on ten 16-core servers. Most of the discovered proteins are highly diverged from known proteins and originate from very sparsely sampled eukaryotic supergroups.

conclusionThe open-source (GPLv3) MetaEuk software (https://github.com/soedinglab/metaeuk) enables large-scale eukaryotic metagenomics through reference-based, sensitive taxonomic and functional annotation. Video abstract.

Indexed as

AlgorithmsMicrobiotaComputational BiologyDatabases, GeneticEukaryotaHigh-Throughput Screening AssaysMetagenomeMetagenomicsMolecular Sequence AnnotationSequence Analysis, DNAAnnotationContigsEukaryotesHomology detectionMarineMetaEukPrediction

Identifiers

PMID32245390
PMCPMC7126354
OpenAlexW3014607123

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.