Evidence map›Paper›PMID 35710651›Full record

ArticleScientific data2022

500 metagenome-assembled microbial genomes from 30 subtropical estuaries in South China.

Lei Zhou, Shihui Huang, Jiayi Gong, Peng Xu, Xiande Huang

Abstract readDataset
In one paragraph

Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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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

5 authors.

Lei ZhouJoint Laboratory of Guangdong Province and Hong Kong Region on Marine Bioresource Conservation and Exploitation, College of Marine Sciences, South China Agricultural University, Guangzhou, China.
Shihui HuangJoint Laboratory of Guangdong Province and Hong Kong Region on Marine Bioresource Conservation and Exploitation, College of Marine Sciences, South China Agricultural University, Guangzhou, China.
Jiayi GongJoint Laboratory of Guangdong Province and Hong Kong Region on Marine Bioresource Conservation and Exploitation, College of Marine Sciences, South China Agricultural University, Guangzhou, China.
Peng XuGuangxi Key Laboratory of Beibu Gulf Marine Biodiversity Conservation, College of Marine Sciences, Beibu Gulf University, Qinzhou, 535011, China. pxu@bbgu.edu.cn.
Xiande HuangJoint Laboratory of Guangdong Province and Hong Kong Region on Marine Bioresource Conservation and Exploitation, College of Marine Sciences, South China Agricultural University, Guangzhou, China. huangxd@scau.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As a unique geographical transition zone, the estuary is considered as a model environment to decipher the diversity, functions and ecological processes of microbial communities, which play important roles in the global biogeochemical cycle. Here we used surface water metagenomic sequencing datasets to construct metagenome-assembled genomes (MAGs) from 30 subtropical estuaries at a large scale along South China. In total, 500 dereplicated MAGs with completeness ≥ 50% and contamination ≤ 10% were obtained, among which more than one-thirds (n = 207 MAGs) have a completeness ≥ 70%. These MAGs are dominated by taxa assigned to the phylum Proteobacteria (n = 182 MAGs), Bacteroidota (n = 110) and Actinobacteriota (n = 104). These draft genomes can be used to study the diversity, phylogenetic history and metabolic potential of microbiota in the estuary, which should help improve our understanding of the structure and function of these microorganisms and how they evolved and adapted to extreme conditions in the estuarine ecosystem.

Indexed as

Genome, MicrobialMetagenomeMicrobiotaChinaEstuariesMetagenomics

Identifiers

PMID35710651
PMCPMC9203525

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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.