Evidence map›Paper›PMID 38507653›Full record

ArticleMolecular biology and evolution2024

Adaptation in Unstable Environments and Global Gene Losses: Small but Stable Gene Networks by the May-Wigner Theory.

Shaohua Xu, Shao Shao, Xiao Feng, Sen Li, Lingjie Zhang, Weihong Wu, Min Liu, Miles E Tracy, Cairong Zhong, Zixiao Guo and 3 more

Abstract read
In one paragraph

Article in Molecular biology and evolution, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Genome-Wide Investigation ofInternational journal of molecular sciences · 2025
    Article
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

13 authors.

Shaohua XuState Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China.ORCID 0000-0002-4379-2621
Shao ShaoState Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China.
Xiao FengState Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China.
Sen LiState Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China.
Lingjie ZhangState Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China.ORCID 0000-0002-6506-4457
Weihong WuState Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China.
Min LiuState Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China.
Miles E TracyState Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China.
Cairong ZhongInstitute of Wetland Research, Hainan Academy of Forestry (Hainan Academy of Mangrove), Haikou, China.
Zixiao GuoState Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China.
Chung-I WuState Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China.
Suhua ShiState Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China.ORCID 0000-0003-2809-5999
Ziwen HeState Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China.

Funding

Guangdong Basic and Applied Basic Research Foundation 2022A1515010962Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory 311021006National Natural Science Foundation of China 32170230
6 · The paper itself

Abstract

Although gene loss is common in evolution, it remains unclear whether it is an adaptive process. In a survey of seven major mangrove clades that are woody plants in the intertidal zones of daily environmental perturbations, we noticed that they generally evolved reduced gene numbers. We then focused on the largest clade of Rhizophoreae and observed the continual gene set reduction in each of the eight species. A great majority of gene losses are concentrated on environmental interaction processes, presumably to cope with the constant fluctuations in the tidal environments. Genes of the general processes for woody plants are largely retained. In particular, fewer gene losses are found in physiological traits such as viviparous seeds, high salinity, and high tannin content. Given the broad and continual genome reductions, we propose the May-Wigner theory (MWT) of system stability as a possible mechanism. In MWT, the most effective solution for buffering continual perturbations is to reduce the size of the system (or to weaken the total genic interactions). Mangroves are unique as immovable inhabitants of the compound environments in the land-sea interface, where environmental gradients (such as salinity) fluctuate constantly, often drastically. Extending MWT to gene regulatory network (GRN), computer simulations and transcriptome analyses support the stabilizing effects of smaller gene sets in mangroves vis-à-vis inland plants. In summary, we show the adaptive significance of gene losses in mangrove plants, including the specific role of promoting phenotype innovation and a general role in stabilizing GRN in unstable environments as predicted by MWT.

Indexed as

Gene Regulatory NetworksGenomeGene Expression ProfilingPlantsadaptive evolutiongene lossgenomemangrovenetwork stabilityunstable environment

Identifiers

PMID38507653
PMCPMC10991078

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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.