Machine learning reveals biocontrol agents shaping disease outcome in natural Arabidopsis populations ->Nature | More info at BigEarthData.ai | #Disease #Health #MachineLearning
Machine learning reveals biocontrol agents shaping disease outcome in natural Arabidopsis populationsAlbugo infection reduces the diversity of microbial community in the phyllosphere of A. thaliana To investigate the diversity and compositional dynamics of the phyllosphere microbiome in relation to leaf infection by the obligate biotrophic pathogen Albugo (Oomycota phylum), we obtained the microbiome data from an A. thaliana collection, on which we have previously performed amplicon sequencing and described the microbiome9. Shoot samples (n = 351) were collected from six sites near Tübingen, Germany (48.52° N, 9.06° E, Fig. 1a), over six years (2014–2019). Microbiome data were obtained from epiphytic and endophytic leaf fractions using amplicon sequencing, and the host genotype was determined using whole genome sequencing (Fig. 1b)9. Here, we further analyzed endophytic microbiome due to their tight association with the host25. Since Albugo was the major pathogen in A. thaliana leaves at the time of sampling, samples were categorized as infected with observable symptoms or uninfected without observable symptoms based on the presence of characteristic white blisters on leaves (Supplementary Table 1). We first conducted diversity analysis to compare the leaf-associated microbial communities between infected and uninfected plants. Alpha diversity (within-sample diversity, measured by Shannon’s index) demonstrated that, on average, bacterial and nonfungal eukaryotic (NFEuk) communities in infected plants...www.nature.com