← Papers

Paper record

Identification of a bio-signature for barley resistance against Pyrenophora teres infection based on physiological, molecular and sensor-based phenotyping.

Chandana Pandey · Dominik K. Großkinsky · Jesper Cairo Westergaard · Hans Jørgen Lyngs Jørgensen · Jesper Svensgaard · Svend Christensen · Alexander Schulz · Thomas Roitsch

Plant Science · 29 Sept 2021 · 10.1016/j.plantsci.2021.111072

Abstract

Necrotic and chlorotic symptoms induced during Pyrenophora teres infection in barley leaves indicate a compatible interaction that allows the hemi-biotrophic fungus Pyrenophora teres to colonise the host. However, it is unexplored how this fungus affects the physiological responses of resistant and susceptible cultivars during infection. To assess the degree of resistance in four different cultivars, we quantified visible symptoms and fungal DNA and performed expression analyses of genes involved in plant defence and ROS scavenging. To obtain insight into the interaction between fungus and host, we determined the activity of 19 key enzymes of carbohydrate and antioxidant metabolism. The pathogen impact was also phenotyped non-invasively by sensor-based multireflectance and -fluorescence imaging. Symptoms, regulation of stress-related genes and pathogen DNA content distinguished the cultivar Guld as being resistant. Severity of net blotch symptoms was also strongly correlated with the dynamics of enzyme activities already within the first day of infection. In contrast to the resistant cultivar, the three susceptible cultivars showed a higher reflectance over seven spectral bands and higher fluorescence intensities at specific excitation wavelengths. The combination of semi high-throughput physiological and molecular analyses with non-invasive phenotyping enabled the identification of bio-signatures that discriminates the resistant from susceptible cultivars.

Code and data availability

The supplied blocks describe multispectral/fluorescence imaging, enzyme activity profiling, and qRT-PCR analyses, but contain no public phenotype dataset, image repository, analysis code, or trained model with an authors' public URL. Supplementary material is only referenced via the article DOI, and no data or code-av­

No evidence-backed public reproduction asset is currently recorded.