Evidence map›Paper›PMID 39597587›Full record

ArticleMicroorganisms2024

Comparative Genomics Reveal Distinct Environment Preference and Functional Adaptation Among Lineages of Gemmatimonadota.

Jiangtao Du, Zhixuan Wang, Lin Hu, Li Wang, Jiasong Fang, Rulong Liu

Abstract read
In one paragraph

Article in Microorganisms, 2024. 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. Mechanisms ofFrontiers in plant science · 2026
    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

6 authors.

Jiangtao DuCollege of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai 201306, China.
Zhixuan WangCollege of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai 201306, China.
Lin HuCollege of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai 201306, China.
Li WangCollege of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai 201306, China.
Jiasong FangCollege of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai 201306, China.
Rulong LiuCollege of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai 201306, China.

Funding

National Natural Science Foundation of China 42276149, 92251303
6 · The paper itself

Abstract

Bacteria in the phylum Gemmatimonadota are globally distributed and abundant in microbial communities of various environments, playing an important role in driving biogeochemical cycling on Earth. Although high diversities in taxonomic composition and metabolic capabilities have been reported, little is known about the environmental preferences and associated functional features that facilitate adaptation among different Gemmatimonadota lineages. This study systematically analyzed the relationships between the environments, taxonomy, and functions of Gemmatimonadota lineages, by using a comparative genomics approach based on 1356 Gemmatimonadota genomes (213 high-quality and non-redundant genomes) available in a public database (NCBI). The taxonomic analysis showed that the 99.5% of the genomes belong to the class Gemmatimonadetes, and the rest of the genomes belong to the class Glassbacteria. Functional profiling revealed clear environmental preference among different lineages of Gemmatimonadota, and a marine group and two non-marine groups were identified and tested to be significantly different in functional composition. Further annotation and statistical comparison revealed a large number of functional genes (e.g.,

Indexed as

functional profileGemmatimonadotagenomic featuresmarine environment

Identifiers

PMID39597587
PMCPMC11596202

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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.