Evidence map›Paper›PMID 41171134›Full record

ArticleNucleic acids research2026

gcMeta 2025: a global repository of metagenome-assembled genomes enabling cross-ecosystem microbial discovery and function research.

Yan Sun, Qi Chen, Guomei Fan, Qinglan Sun, Qing Zhou, Jiaqing Zhang, Jingyi Nie, Juncai Ma, Linhuan Wu

Abstract read
In one paragraph

Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 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

9 authors.

Yan SunMicrobial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.
Qi ChenMicrobial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.
Guomei FanMicrobial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.
Qinglan SunMicrobial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.
Qing ZhouMicrobial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.
Jiaqing ZhangMicrobial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.
Jingyi NieMicrobial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.
Juncai MaMicrobial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.
Linhuan WuMicrobial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.ORCID 0000-0002-5255-1846

Funding

Chinese Academy of Science 153211KYSB201900211Chinese Academy of SciencesChinese Academy of Sciences XDB0830000National Key R&D Program of China 2021YFA0717001
6 · The paper itself

Abstract

The rapid growth of metagenomic sequencing has generated an unprecedented wealth of metagenome-assembled genomes (MAGs), transforming opportunities for microbial discovery and functional characterization. Yet, full utilization of these resources has been constrained by heterogeneous data generation practices and inconsistent analytical pipelines. The gcMeta database addresses this gap by compiling MAGs through both public acquisition and de novo assembly. This release integrates over 2.7 million MAGs from 104 266 samples spanning various biomes, covering human, animal, plant, marine, freshwater, and extreme environments. It establishes 50 biome-specific MAG catalogues comprising 109 586 species-level clusters, of which 63% (69 248) represents previously uncharacterized taxa, and annotates >74.9 million novel genes. By linking functional traits with microbial co-occurrence networks, gcMeta identifies keystone taxa central to biogeochemical cycling and environmental adaptation. The platform further supports cross-ecosystem functional comparisons, revealing niche-specific metabolic pathways and stress-response genes. Moreover, gcMeta provides standardized, AI-ready datasets encompassing microbial enzymes, anti-phage defense systems, and other functional modules, enabling advanced machine learning applications. By bridging microbial "sequence discovery" with "functional utilization," gcMeta establishes a foundation for ecological research, industrial biotechnology, and novel gene mining. The platform is freely accessible at https://gcmeta.wdcm.org/.

Indexed as

Databases, GeneticEcosystemMetagenomeMetagenomicsAnimalsBacteriaHumansMolecular Sequence Annotation

Identifiers

PMID41171134
PMCPMC12807734

What OpenQuestion holds

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Registered trials

None linked

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.