Evidence map›Paper›PMID 39338431›Full record

ArticleMicroorganisms2024

Rhizosphere Microbiome Co-Occurrence Network Analysis across a Tomato Domestication Gradient.

Mary M Dixon, Antisar Afkairin, Daniel K Manter, Jorge Vivanco

Abstract read
In one paragraph

Article in Microorganisms, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Article
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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

4 authors.

Mary M DixonDepartment of Horticulture and Landscape Architecture, Colorado State University, Fort Collins, CO 80523, USA.
Antisar AfkairinDepartment of Horticulture and Landscape Architecture, Colorado State University, Fort Collins, CO 80523, USA.ORCID 0009-0001-6164-2635
Daniel K ManterUnited States Department of Agriculture-Agricultural Research Service, Soil Management and Sugar Beet Research, Fort Collins, CO 80526, USA.ORCID 0000-0001-7729-7197
Jorge VivancoDepartment of Horticulture and Landscape Architecture, Colorado State University, Fort Collins, CO 80523, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

When plant-available phosphorus (P) is lost from a soil solution, it often accumulates in the soil as a pool of unavailable legacy P. To acquire legacy P, plants employ recovery strategies, such as forming associations with soil microbes. However, the degree to which plants rely on microbial associations for this purpose varies with crop domestication and subsequent breeding. Here, by generating microbial co-occurrence networks, we sought to explore rhizosphere bacterial interactions in low-P conditions and how they change with tomato domestication and breeding. We grew wild tomato, traditional tomato (developed circa 1900), and modern tomato (developed circa 2020) in high-P and low-P soil throughout their vegetative developmental stage. Co-occurrence network analysis revealed that as the tomatoes progressed along the stages of domestication, the rhizosphere microbiome increased in complexity in a P deficit. However, with the addition of P fertilizer, the wild tomato group became more complex, surpassing the complexity of traditional and modern tomato, suggesting a high degree of responsiveness in the rhizosphere microbiome to P fertilizer by wild tomato relatives. By illustrating these changing patterns of network complexity in the tomato rhizosphere microbiome, we can further understand how plant domestication and breeding have shaped plant-microbe interactions.

Indexed as

co-occurrence networkcrop domesticationphosphorustomato

Identifiers

PMID39338431
PMCPMC11434442

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.