Title : A transcriptome meta-analysis to depict functionalities and biomarkers of the root under pathogen infection
Abstract:
Pathogens affect plant health and stability. However, there is a lack of methodologies to understand the infection progression and its possible outcome, especially in urban environments where plants are needed to provide beneficial ecosystem services and can threaten the environmental safety. Thus, the aim of this work is to identify genes to be used as possible biomarker to monitor the root response to pathogen infections and assess the root health for diagnostic/prognostic purposes.
Accordingly, we seeked literature to identify RNA-seq transcriptomic datasets from plants under pathogen attack to be used in a co-expression meta-analysis. Genes were grouped according to their expression patterns into modules which were undergone to a functional enrichment together with the identified differentially expressed genes. This led the characterization of species-specific and common functional features active under pathogen infection in the root. Furthermore, the co-expression networks were queried to sign the biomarkers which offer a molecular target to monitor the presence and the progression of the pathogen infection. These results may offer novel and advanced tools allowing the identification of the pathogen presence and its possible monitoring in the plants through molecular approaches. These can be based on non-invasive and non-disruptive sampling and are of relevance especially for being applied in urban contexts.
Audience Takeaway:
- The mechanisms underpinning root pathogen infection will be revealed allowing a deeper understanding of their complexity.
- The approach based on a meta-analysis give the possibility to integrate knowledge based on multiple species forecasting insight on species-specific peculiarities, common pathways and main markers pivotally involved in the response of the roots to pathogens’ infection.
- The potential of this approach is high since co-expression meta-analysis offer a wide range of applications, included genetically targeting of identified biomarkers, development of diagnostic/prognostic methods. Additionally, such types of approaches are supported by the increasing amount of transcriptomic data and can be extended including in the analysis knowledge from other species or organs.
- Identified function/biomarkers will provide targets to be used in non-disruptive molecular approaches for diagnostic or prognostic purposes allowing the identification of possible signature of the pathogen presence, particularly desirable for monitoring plants especially in urban environments.
