The first year of the programme has a professional orientation and includes lectures, practicals, study, individual and group projects, and technical visits.
Unit 1: Agricultural systems and plant breeding (4.5 ECTS)
Historical perspective of agriculture and plant breeding. The plant breeding framework. Introduction to agricultural systems. Big data and digitalization in agriculture. Physiological determinants of crop production. Agriculture and climate change. Environmental characterization and crop modelling.
Unit 2: Plant genetics (6 ECTS)
Plant reproduction system. Genetic structure of plant populations. Genetic diversity and the domestication of crop plants. Detecting genetic diversity. Linkage analysis and genetic mapping. Essentials of quantitative genetics (D, R, H2, breeding values). Gene identification and validation: forward and reverse genetics.
Unit 3: Structural and functional genomics (3 ECTS)
Plant genome sequencing, Genome structure. Reference genomes. Pangenomes. Transcriptomics and functional genomics.
Unit 4: Introduction to data science for plant breeding (7.5 ECTS)*
Scripting (BASH, R, Python). Experimental design. Introduction to multivariate methods. Genotype x environment interaction: adaptation, stability and resilience. Selection theory.
Unit 5: Bioinformatics (3 ECTS)*
Bioinformatics resources and databases. Data filtering, imputation, phasing, formatting and exporting. Alignment and mapping. Variant calling and effect prediction. Comparative genomics: orthology, collinearity.
Unit 6: Breeding methods and variety development (12 ECTS)*
Breeding methods. Germplasm diversity and development. Legal aspects of plant breeding. In vitro techniques. Double haploids. Juvenility management. Genetic transformation technologies.
Unit 7: Marker enabled prediction and selection (6 ECTS)*
IBD, IBS, genetic distance, population structure. QTL mapping and GWAS (estimation of positions and allelic effects). Evaluation of selection strategies. Cross validation, prediction error, training-test set construction. Penalized regression, ridge, GBLUP, Lasso. Dimension reduction, PCR, PLS. GxE, QTLxE, factorial regression, selecting environmental covariables for predicting phenotypes. Genomic prediction and GxE, genomic prediction for genotypic intercepts and sensitivities, Jarquin approach (double ridge); environmental classification, subdividing TPE.
Unit 8: Phenomics and analysis of -omics data (3 ECTS)*
Introduction to Phenotyping. Introduction to HTP data indoor & outdoor phenotyping. Data annotation and organization. Phenotyping VL – Spectral data LAB. Choosing the design for phenotyping experiments: Procedure and examples of indoor experiments designs. Feature extraction. Correcting for design factors and spatial modelling. Modelling dependence on environment gradients. Target trait prediction. Integrating phenotyping, machine learning, crop growth, modelling and satellite imagery in plant breeding programs.
Unit 9: Applied breeding programmes (9 ECTS)
Breeding crops on a climate change framework. Breeding for abiotic stress. Breeding for biotic stress. Quality and novel traits. Case studies: Maize, Winter cereals, Vegetables, Fruit trees.
Unit 10: Individual Project: Design of Plant Breeding Programmes (6 ECTS)
Individual design of a plant breeding project chosen by the student. This training activity provides the student with practical experience on planning breeding programmes with certain objectives and which respond to specific agronomic, environmental, social and economic conditions, by applying the principles and methodology presented throughout the different units of the course.
* Units 4 to 8 are also open for applicants who wish to take one or several units as independent modules and participants can attend face-to-face or online.