Genetic Data Analysis for Plant and Animal Breeding
September 23-27, 2019, Montepulciano, Tuscany, Italy
Organized by:
North Carolina State University, USA
Organizing committee:
Dr. Francesco Tiezzi (NC State University), Email: f_tiezzi@ncsu.edu
Dr. Riccardo Bozzi, (University of Florence), Email: riccardo.bozzi@unifi.it
Instructors:
Christian Maltecca (NC State University, Animal breeding), Francesco Tiezzi (NC State University, Animal breeding), Fikret Isik (NC State University, Forest Tree Breeding), Guest lecturer (NC State University, Crop Breeding).
Registration:
Workshop registration cost is $1150 USD. Registration includes lunches, two coffee breaks per day, a welcome and a farewell dinner. It does not include lodging and travel expenses.
About the Workshop:
The workshop will be taught at an intermediate to advanced level. Participants are expected to have some understanding of the theory of mixed models.
This is a hands-on workshop. Participants are expected to work on exercises related to crops, animal and forest trees. You may bring your own laptop and your own data to work on after lectures.
Workshop format: Four sets of lecture + exercise per day. Each set will be a about 30-minute lecture and 60- minute exercise. See example below.
Software:
The exercises will demonstrate use of ASReml, R packages, and additional tools for data analysis. Some familiarity with R syntax will be expected. A temporary free license for ASReml will available at the time of workshop.
Workshop outline:
The workshop will mostly follow the textbook Isik-Holland-Maltecca (2017) Genetic data Analysis for Plant and Animal Breeding with hands-on examples.
The tentative outline is as follows:
Theory of linear mixed models ASReml software basics and options Breeding values and genetic values
Multi environmental trials using factor analytic models Spatial analysis of field test data
Explanatory marker data analysis
Imputing missing genotypes
Realized genomic relationships matrix and GBLUP Marker-trait associations
Genome-wide selection