Evidence map›Paper›PMID 29991352›Full record

ArticleMicrobiome2018

The evolutionary signal in metagenome phyletic profiles predicts many gene functions.

Vedrana Vidulin, Tomislav Šmuc, Sašo Džeroski, Fran Supek

Open access · goldAbstract read
In one paragraph

Article in Microbiome, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.1field-weighted citation impact, top 52% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Using metagenomic data to boost protein structure prediction and discovery.Computational and structural biotechnology journal · 2022
    Review
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

4 authors at 3 institutions in 3 countries.

Vedrana VidulinFaculty of Information Studies, 8000, Novo Mesto, Slovenia.
Tomislav ŠmucDivision of Electronics, Rudjer Boskovic Institute, 10000, Zagreb, Croatia.
Sašo DžeroskiDepartment of Knowledge Technologies, Jozef Stefan Institute, 1000, Ljubljana, Slovenia.
Fran SupekGenome Data Science, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, 08028, Barcelona, Spain. fran.supek@irbbarcelona.org.ORCID 0000-0002-7811-6711
Jožef Stefan Institute · SIInstitute for Research in Biomedicine · ESRuđer Bošković Institute · HR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe function of many genes is still not known even in model organisms. An increasing availability of microbiome DNA sequencing data provides an opportunity to infer gene function in a systematic manner.

resultsWe evaluated if the evolutionary signal contained in metagenome phyletic profiles (MPP) is predictive of a broad array of gene functions. The MPPs are an encoding of environmental DNA sequencing data that consists of relative abundances of gene families across metagenomes. We find that such MPPs can accurately predict 826 Gene Ontology functional categories, while drawing on human gut microbiomes, ocean metagenomes, and DNA sequences from various other engineered and natural environments. Overall, in this task, the MPPs are highly accurate, and moreover they provide coverage for a set of Gene Ontology terms largely complementary to standard phylogenetic profiles, derived from fully sequenced genomes. We also find that metagenomes approximated from taxon relative abundance obtained via 16S rRNA gene sequencing may provide surprisingly useful predictive models. Crucially, the MPPs derived from different types of environments can infer distinct, non-overlapping sets of gene functions and therefore complement each other. Consistently, simulations on > 5000 metagenomes indicate that the amount of data is not in itself critical for maximizing predictive accuracy, while the diversity of sampled environments appears to be the critical factor for obtaining robust models.

conclusionsIn past work, metagenomics has provided invaluable insight into ecology of various habitats, into diversity of microbial life and also into human health and disease mechanisms. We propose that environmental DNA sequencing additionally constitutes a useful tool to predict biological roles of genes, yielding inferences out of reach for existing comparative genomics approaches.

Indexed as

Multigene FamilyEvolution, MolecularGene OntologyGenomicsHumansMetagenomicsPhylogenyRNA, Ribosomal, 16SSequence Analysis, DNAWater MicrobiologyRNA, Ribosomal, 16SComparative genomicsGene functionMachine learningMetagenomesPhyletic profiles

Identifiers

PMID29991352
PMCPMC6040064
OpenAlexW2868054268

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.