Evidence map›Paper›PMID 39872075›Full record

ReviewLife metabolism2022

The metabolic adaptation in wild vertebrates via omics approaches.

Xin Du, Yisi Hu, Guangping Huang, Fuwen Wei

Abstract readReview
In one paragraph

Review in Life metabolism, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
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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.

Xin DuKey Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China.ORCID https://orcid.org/0000-0003-2407-5181
Yisi HuKey Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China.
Guangping HuangKey Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China.
Fuwen WeiKey Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China.ORCID https://orcid.org/0000-0003-3882-5852

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolism is the basis for sustaining life and essential to the adaptive evolution of organisms. With the development of high-throughput sequencing technology, genetic mechanisms of adaptive evolution, including metabolic adaptation, have been extensively resolved by omics approaches, but a deep understanding of genetic and epigenetic metabolic adaptation is still lacking. Exploring metabolic adaptations from genetic and epigenetic perspectives in wild vertebrates is vital to understanding species evolution, especially for the early stages of adaptative evolution. Herein, we summarize the advances in our understanding of metabolic adaptations via omics approaches in wild vertebrates based on three types of cases: extreme environment, periodically changing environment, and changes of species characteristics. We conclude that the understanding of the formation of metabolic adaptations at the genetic level alone can well identify the adaptive genetic variation that has developed during evolution, but cannot resolve the potential impact of metabolic adaptations on the adaptative evolution in the future. Thus, it seems imperative to include epigenomics and metabolomics in the study of adaptation, and that in the future genomic and epigenetic data should be integrated to understand the formation of metabolic adaptation of wild vertebrate organisms.

Indexed as

adaptative evolutioncomparative genomicsepigeneticsmetabolic adaptationmulti-omics

Identifiers

PMID39872075
PMCPMC11749369

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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.