Evidence map›Paper›PMID 38365793›Full record

ArticleNature communications2024

A genome and gene catalog of the aquatic microbiomes of the Tibetan Plateau.

Mingyue Cheng, Shuai Luo, Peng Zhang, Guangzhou Xiong, Kai Chen, Chuanqi Jiang, Fangdian Yang, Hanhui Huang, Pengshuo Yang, Guanxi Liu and 6 more

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 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

16 authors.

Mingyue Cheng *Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular Imaging, Center of Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.ORCID 0000-0003-1243-5039
Shuai Luo *Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China.
Peng Zhang *Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China.ORCID 0000-0002-0239-3923
Guangzhou XiongKey Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular Imaging, Center of Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.ORCID 0000-0001-5792-3664
Kai ChenInstitute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China.ORCID 0009-0006-8037-736X
Chuanqi JiangInstitute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China.
Fangdian YangInstitute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China.
Hanhui HuangKey Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular Imaging, Center of Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
Pengshuo YangKey Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular Imaging, Center of Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
Guanxi LiuKey Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular Imaging, Center of Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
Yuhao ZhangKey Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular Imaging, Center of Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
Sang BaLaboratory of Tibetan Plateau Wetland and Watershed Ecosystem, College of Science, Tibet University, Lhasa, China.
Ping YinNational Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China.ORCID 0000-0001-8001-221X
Jie XiongInstitute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China. xiongjie@ihb.ac.cn.ORCID 0000-0001-8923-0424
Wei MiaoInstitute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China. miaowei@ihb.ac.cn.ORCID 0000-0003-3440-8322
Kang NingKey Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular Imaging, Center of Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China. ningkang@hust.edu.cn.ORCID 0000-0003-3325-5387

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Tibetan Plateau supplies water to nearly 2 billion people in Asia, but climate change poses threats to its aquatic microbial resources. Here, we construct the Tibetan Plateau Microbial Catalog by sequencing 498 metagenomes from six water ecosystems (saline lakes, freshwater lakes, rivers, hot springs, wetlands and glaciers). Our catalog expands knowledge of regional genomic diversity by presenting 32,355 metagenome-assembled genomes that de-replicated into 10,723 representative genome-based species, of which 88% were unannotated. The catalog contains nearly 300 million non-redundant gene clusters, of which 15% novel, and 73,864 biosynthetic gene clusters, of which 50% novel, thus expanding known functional diversity. Using these data, we investigate the Tibetan Plateau aquatic microbiome's biogeography along a distance of 2,500 km and >5 km in altitude. Microbial compositional similarity and the shared gene count with the Tibetan Plateau microbiome decline along with distance and altitude difference, suggesting a dispersal pattern. The Tibetan Plateau Microbial Catalog stands as a substantial repository for high-altitude aquatic microbiome resources, providing potential for discovering novel lineages and functions, and bridging knowledge gaps in microbiome biogeography.

Indexed as

MicrobiotaHumansLakesRiversTibetWaterWater

Identifiers

PMID38365793
PMCPMC10873407

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