Evidence map›Paper›PMID 30046166›Full record

ArticleThe ISME journal2018

Genetic correlation network prediction of forest soil microbial functional organization.

Bin Ma, Kankan Zhao, Xiaofei Lv, Weiqin Su, Zhongmin Dai, Jack A Gilbert, Philip C Brookes, Karoline Faust, Jianming Xu

Abstract read
In one paragraph

Article in The ISME journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

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  5. Biogeographic patterns and drivers of soil viromes.Nature ecology & evolution · 2024
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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.

Bin MaInstitute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
Kankan ZhaoInstitute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
Xiaofei LvInstitute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
Weiqin SuInstitute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
Zhongmin DaiInstitute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
Jack A GilbertThe Microbiome Center, Department of Surgery, University of Chicago, Chicago, IL, 60637, USA.
Philip C BrookesInstitute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
Karoline FaustDepartment of Microbiology and Immunology, Rega Institute, KU Leuven, Campus Gasthuisberg, Leuven, Belgium.ORCID http://orcid.org/0000-0001-7129-2803
Jianming XuInstitute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China. jmxu@zju.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Soil ecological functions are largely determined by the activities of soil microorganisms, which, in turn, are regulated by relevant interactions between genes and their corresponding pathways. Therefore, the genetic network can theoretically elucidate the functional organization that supports complex microbial community functions, although this has not been previously attempted. We generated a genetic correlation network based on 5421 genes derived from metagenomes of forest soils, identifying 7191 positive and 123 negative correlation relationships. This network consisted of 27 clusters enriched with sets of genes within specific functions, represented with corresponding cluster hubs. The clusters revealed a hierarchical architecture, reflecting the functional organization in the soil metagenomes. Positive correlations mapped functional associations, whereas negative correlations often mapped regulatory processes. The potential functions of uncharacterized genes were predicted based on the functions of located clusters. The global genetic correlation network highlights the functional organization in soil metagenomes and provides a resource for predicting gene functions. We anticipate that the genetic correlation network may be exploited to comprehensively decipher soil microbial community functions.

Indexed as

ForestsSoil MicrobiologyGene Regulatory NetworksMetagenomeMicrobiotaSoilSoil

Identifiers

PMID30046166
PMCPMC6155114

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.