Evidence map›Paper›PMID 41814663›Full record

ReviewPlant communications2026

From triangle to pyramid: Understanding host-pathogen-microniome-environment interplay for sustainable, enviromics-empowered management of plant diseases.

Taotao Wang, Wenjing Hu, Weifeng Song, Xiwen Liao, Hongjian Zheng, Xingping Zhang, Xiufang Xin, Pawan Kumar Singh, Yuan Chen, Yunbi Xu

Abstract readReview
In one paragraph

Review in Plant communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

10 authors.

Taotao WangState Key Laboratory of Wheat Improvement, Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Shandong 261325, China.
Wenjing HuYangzhou Academy of Agricultural Sciences, Yangzhou 225007, China.
Weifeng SongState Key Laboratory of Wheat Improvement, Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Shandong 261325, China.
Xiwen LiaoState Key Laboratory of Wheat Improvement, Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Shandong 261325, China.
Hongjian ZhengCIMMYT-China Specialty Maize Research Center, Shanghai Academy of Agricultural Sciences, Shanghai 201400, China.
Xingping ZhangState Key Laboratory of Wheat Improvement, Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Shandong 261325, China.
Xiufang XinCenter for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai 200032, China.
Pawan Kumar SinghCIMMYT (International Maize and Wheat Improvement Center), El Batan, Texcoco CP 56130, Mexico.
Yuan ChenState Key Laboratory of Wheat Improvement, Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Shandong 261325, China. Electronic address: yuan.chen@pku-iaas.edu.cn.
Yunbi XuState Key Laboratory of Wheat Improvement, Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Shandong 261325, China; State Key Laboratory of Crop Gene Resources and Breeding, National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China; BGI Bioverse, Shenzhen 518083, China. Electronic address: yunbi.xu@pku-iaas.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding plant disease development requires moving beyond the classic disease triangle, which considers the host, pathogen, and environment. Recent advances in multi-omics have highlighted the importance of a disease pyramid that integrates the host, pathogen, microbiome, and environment to capture the complex interactions among these core biological/ecological components. This pyramid framework emphasizes how host genetic architecture, pathogen traits, microbiome dynamics, and environmental conditions collectively and interactively shape disease outcomes, plant phenotypes, and adaptive potential. The conceptual expansion from the disease triangle to a pyramid model reflects this shift, providing a more holistic and dynamic view of plant disease ecology. Environmental factors regulate host susceptibility and restructure both pathogenic and non-pathogenic microbial communities, thereby influencing infection severity and disease progression. Multi-omics approaches-encompassing hostomics, pathomics, microbiomics, and enviromics-hold strong promise for dissecting these interactions, enabling predictive disease modeling and the development of sustainable management strategies. Moreover, integrating enviromics data into resistance breeding enables the identification of key environmental variables and their interactions with host genotypes and pathogenic and non-pathogenic microbes, thereby supporting the deployment of durable resistance across diverse agroecosystems. Together, these perspectives advance a systems-level understanding of plant health and open new avenues for disease management through omics-driven breeding, microbiome-informed strategies, and environmentally responsive interventions.

Indexed as

Host-Pathogen InteractionsMicrobiotaPlant DiseasesPlantsEnvironmentMultiomicsdisease pyramid networkenviromicshostomicsmicrobiomicspathomicsplant disease management

Identifiers

PMID41814663
PMCPMC13174238

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.