Evidence map›Paper›PMID 34493731›Full record

ArticleNPJ biofilms and microbiomes2021

Network mapping of root-microbe interactions in Arabidopsis thaliana.

Xiaoqing He, Qi Zhang, Beibei Li, Yi Jin, Libo Jiang, Rongling Wu

Open access · goldAbstract read
In one paragraph

Article in NPJ biofilms and microbiomes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
7.3field-weighted citation impact, top 3% of its field
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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.

  1. Pooled it
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  14. Disentangling leaf-microbiome interactions inFrontiers in plant science · 2022
    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

6 authors at 2 institutions in 2 countries.

Xiaoqing HeBeijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China.ORCID http://orcid.org/0000-0001-9098-9980
Qi ZhangCenter for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China.ORCID http://orcid.org/0000-0001-7016-3954
Beibei LiCenter for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China.ORCID http://orcid.org/0000-0003-2493-8792
Yi JinCenter for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China.ORCID http://orcid.org/0000-0001-6412-0835
Libo JiangBeijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China.ORCID http://orcid.org/0000-0003-4703-9220
Rongling WuBeijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China. rwu@bjfu.edu.cn.ORCID http://orcid.org/0000-0002-2334-6421
Beijing Forestry University · CNPennsylvania State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding how plants interact with their colonizing microbiota to determine plant phenotypes is a fundamental question in modern plant science. Existing approaches for genome-wide association studies (GWAS) are often focused on the association analysis between host genes and the abundance of individual microbes, failing to characterize the genetic bases of microbial interactions that are thought to be important for microbiota structure, organization, and function. Here, we implement a behavioral model to quantify various patterns of microbe-microbe interactions, i.e., mutualism, antagonism, aggression, and altruism, and map host genes that modulate microbial networks constituted by these interaction types. We reanalyze a root-microbiome data involving 179 accessions of Arabidopsis thaliana and find that the four networks differ structurally in the pattern of bacterial-fungal interactions and microbiome complexity. We identify several fungus and bacterial hubs that play a central role in mediating microbial community assembly surrounding A. thaliana root systems. We detect 1142 significant host genetic variants throughout the plant genome and then implement Bayesian networks (BN) to reconstruct epistatic networks involving all significant SNPs, of which 91 are identified as hub QTLs. Results from gene annotation analysis suggest that most of the hub QTLs detected are in proximity to candidate genes, executing a variety of biological functions in plant growth and development, resilience against pathogens, root development, and abiotic stress resistance. This study provides a new gateway to understand how genetic variation in host plants influences microbial communities and our results could help improve crops by harnessing soil microbes.

Indexed as

MicrobiotaArabidopsisBacteriaBayes TheoremGenome-Wide Association StudyHost Microbial InteractionsMicrobial ConsortiaMicrobial InteractionsPlant RootsSoilSoil MicrobiologyStress, PhysiologicalSymbiosisSoil

Identifiers

PMID34493731
PMCPMC8423736
OpenAlexW3198867525

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.