Evidence map›Paper›PMID 37322057›Full record

ArticleScientific data2023

A dataset of micro biodiversity in benthic sediment at a global scale.

Xumei Sun, Danni Jiang, Yina Shao, Siyuan Zhang

Abstract readDataset
In one paragraph

Article in Scientific data, 2023. 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. Review
  3. 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

4 authors.

Xumei SunSchool of Marine Sciences, Ningbo University, Ningbo, 315211, People's Republic of China.ORCID 0000-0002-7063-7184
Danni JiangSchool of Marine Sciences, Ningbo University, Ningbo, 315211, People's Republic of China.
Yina ShaoSchool of Marine Sciences, Ningbo University, Ningbo, 315211, People's Republic of China.
Siyuan ZhangSchool of Marine Sciences, Ningbo University, Ningbo, 315211, People's Republic of China. zhangsiyuan@nbu.edu.cn.

Funding

China Postdoctoral Science Foundation 2022M721727Natural Science Foundation of Ningbo (Ningbo Natural Science Foundation) 2022J125Natural Science Foundation of Zhejiang Province (Zhejiang Provincial Natural Science Foundation) LY23C190004
6 · The paper itself

Abstract

Microorganisms, occupying the largest biomass in deep sea, play essential roles in deep-sea ecosystem. It is believed that the microbes in deep-sea sediments are more representative of deep-sea microbial communities, the microbial composition of which is seldom affected by ocean currents. However, the community of benthic microbes on a global scale has not been adequately explored. Herein, we build a comprehensive global dataset determined by 16S rRNA gene sequencing to characterize the biodiversity of microorganisms in benthic sediment. The dataset comprised 212 records from 106 sites, included sequencing of bacteria and archaea for each site and yielded 4,766,502 and 1,562,989 reads, respectively. Through annotation, a total of 110,073 and 15,795 OTUs of bacteria and archaea were obtained, and 61 bacterial phyla and 15 archaeal phyla were identified, of which the dominant phyla were Proteobacteria and Thaumarchaeota in deep-sea sediment. Therefore, our findings provided a biodiversity data of microbial communities in deep-sea sediment at global-scale and laid a foundation to further reveal the structures of microorganism communities in deep sea.

Indexed as

MicrobiotaRNA, Ribosomal, 16SArchaeaBacteriaBiodiversityPhylogenySeawaterRNA, Ribosomal, 16S

Identifiers

PMID37322057
PMCPMC10272205

What OpenQuestion holds

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LicenceCC BY
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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.