Deep phenotyping platform for microscopic plant-pathogen interactions

The increasing availability of genetic and genomic resources has underscored the need for automated microscopic phenotyping in plant-pathogen interactions to identify genes involved in disease resistance. Building on accumulated experience and leveraging automated microscopy and software, we developed <i>BluVision Micro</i>, a modular, machine learning-aided system designed for high-throughput microscopic phenotyping. This system is adaptable to various image data types and extendable with modules for additional phenotypes and pathogens. <i>BluVision Micro</i> was applied to screen 196 genetically diverse barley genotypes for interactions with powdery mildew fungi, delivering accurate, sensitive, and reproducible results. This enabled the identification of novel genetic loci and marker-trait associations in the barley genome. The system also facilitated high-throughput studies of labor-intensive phenotypes, such as precise colony area measurement. Additionally, <i>BluVision</i>'s open-source software supports the development of specific modules for various microscopic phenotypes, including high-throughput transfection assays for disease resistance-related genes.

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Publication Details

Journal
Frontiers in Plant Science
Published
2025-02-03
DOI
https://doi.org/10.3389/fpls.2025.1462694
Citations
5
Primary Topic
Plant Pathogens and Fungal Diseases
Type
article
Field-Weighted Citation Impact
5.76

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article

Deep phenotyping platform for microscopic plant-pathogen interactions

Salim Bourras, Dimitar Douchkov, Stefanie Lück
5 citations
Frontiers in Plant Science
Plant Pathogens and Fungal Diseases
5.76
article

Deep phenotyping platform for microscopic plant-pathogen interactions

Salim Bourras, Dimitar Douchkov, Stefanie Lück
article en
5 citations

Abstract

The increasing availability of genetic and genomic resources has underscored the need for automated microscopic phenotyping in plant-pathogen interactions to identify genes involved in disease resistance. Building on accumulated experience and leveraging automated microscopy and software, we developed <i>BluVision Micro</i>, a modular, machine learning-aided system designed for high-throughput microscopic phenotyping. This system is adaptable to various image data types and extendable with modules for additional phenotypes and pathogens. <i>BluVision Micro</i> was applied to screen 196 genetically diverse barley genotypes for interactions with powdery mildew fungi, delivering accurate, sensitive, and reproducible results. This enabled the identification of novel genetic loci and marker-trait associations in the barley genome. The system also facilitated high-throughput studies of labor-intensive phenotypes, such as precise colony area measurement. Additionally, <i>BluVision</i>'s open-source software supports the development of specific modules for various microscopic phenotypes, including high-throughput transfection assays for disease resistance-related genes.

Frontiers in Plant ScienceVol. 16
Swedish University of Agricultural Sciences (SE), Leibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung (IPK) (DE)
Bundesministerium für Bildung und Forschung
Openalex Percentile: Top 5%
Plant Pathogens and Fungal Diseases
5.76
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