Role in the project :

The University of Postdam will use for this well established single-trait approaches for genome wide association of single root traits to identify putative loci controlling each trait. Genes selected based on this approach will be used for validation in a reverse genetics approach. For the associated genes, we will also identify orthologs in cocoa.

The University of Postdam will :

 i) address if and to what extent microbiome diversity and composition are associated to coffee genetic diversity, to test the hypothesis that coffee genotypes show differences in recruiting microbes,

 ii) determine the extent to which microbiome diversity and composition contribute to improving the predictability of root traits and their plasticities over genomic data, and

 iii) quantify the predictability of productivity-related traits based on the microbiome features, root traits (including metabolomes and NIRS spectra), and/or the coffee genetic diversity. The models will be used to identify resilient genotypes under unseen environments.

 As a result, the University of Postdam will integrate all data on root traits, microbiomes and genetic variability into predictive models that will be used to select resilient genotypes with desirable root traits.

 The University of Postdam will use classification-based approaches for the categorical traits and regression-based approaches to model traits of choice in terms of selected predictors. The models will also include environmental factors that will be recorded and obtained from the respective  experiments.