Evidence map›Paper›PMID 38014007›Full record

ArticlebioRxiv : the preprint server for biology2023

Inference of the demographic histories and selective effects of human gut commensal microbiota over the course of human history.

Jonathan C Mah, Kirk E Lohmueller, Nandita Garud

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Jonathan C MahBioinformatics Interdepartmental Program, University of California, Los Angeles.ORCID 0000-0003-3027-3141
Kirk E LohmuellerDepartment of Ecology and Evolutionary Biology, University of California, Los Angeles.ORCID 0000-0002-3874-369X
Nandita GarudDepartment of Ecology and Evolutionary Biology, University of California, Los Angeles.ORCID 0000-0003-4217-4407

Funding

Systems in Integrative BiologyT32GM008185 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI CHOU, TOM · 1987 to 2022
$4.6M
Population genomics of the selective effects of new mutationsR35GM119856 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LOHMUELLER, KIRK · 2016 to 2025
$3.4M
Evolutionary Dynamics of the Human Gut Microbiome During ColonizationR35GM151023 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Nandita Garud · 2023 to 2026
$1.5M
NIGMS NIH HHS R35 GM119856NIGMS NIH HHS R35 GM151023NIGMS NIH HHS T32 GM008185
6 · The paper itself

Abstract

Despite the importance of gut commensal microbiota to human health, there is little knowledge about their evolutionary histories, including their population demographic histories and their distributions of fitness effects (DFE) of new mutations. Here, we infer the demographic histories and DFEs of 27 of the most highly prevalent and abundant commensal gut microbial species in North Americans over timescales exceeding human generations using a collection of lineages inferred from a panel of healthy hosts. We find overall reductions in genetic variation among commensal gut microbes sampled from a Western population relative to an African rural population. Additionally, some species in North American microbiomes display contractions in population size and others expansions, potentially occurring at several key historical moments in human history. DFEs across species vary from highly to mildly deleterious, with accessory genes experiencing more drift compared to core genes. Within genera, DFEs tend to be more congruent, reflective of underlying phylogenetic relationships. Taken together, these findings suggest that human commensal gut microbes have distinct evolutionary histories, possibly reflecting the unique roles of individual members of the microbiome.

Identifiers

PMID38014007
PMCPMC10680615

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.