Data-Driven Breeding and Genetics course

2021, on-line

DDBG 2021

The principles of animal and plant breeding are increasingly coalescing due to advances in technology and increasing demands and opportunities for agriculture. This two-week graduate-level course of integrated lectures and practicals is designed to equip students, academics, and practitioners with theoretical and applied knowledge, skills and tools to design, optimise, and deploy Data-Driven Breeding and Genetics techniques for Animals and Plants. It was jointly delivered by scientists and teachers from the University of Edinburgh and colleagues from the Swedish University of Agricultural Sciences and the CGIAR’s Excellence in Breeding Platform, with guest lectures from various academic and industry collaborators.

Due to the pandemic, the course took place in virtual format from the 20th Sep and 1st Oct 2021. The course lectures were pre-recorded to enable asynchronous worldwide delivery. Course participants engaged with the lectures and practicals at their own pace. They engaged with course instructors and other participants via Slack and daily Zoom sessions (one in the UK morning and one in the UK afternoon time).

Lecturers:

  • Gregor Gorjanc (University of Edinburgh, Roslin Institute)
  • Giovanny Eduardo Covarrubias-Pazaran (CGIAR Excellence in Breeding)
  • Martin Johnsson (Swedish University of Agricultural Sciences)
  • Ivan Pocrnić (University of Edinburgh, Roslin Institute)
  • Daniel J.Tolhurst (University of Edinburgh, Roslin Institute)

Course statistics:

  •  45 participants from more than 15 countries around the globe
  •  12 internal participants
  • 21 guest lecturers from internal and external partner institutions (AbacusBio, Agricultural Institute of Slovenia, Aviagen, Bayer CropScience, Beta Bugs, Geno SA, The Kennel Club, Scion, University of Edinburgh, University of Guelph, Wageningen University & Research).

Day 1 - Introduction to breeding 

  • Welcome and Introduction (Gregor Gorjanc)
  • Introduction to breeding programme modelling (Gregor Gorjanc)
  • AlphaSimR MOOC - Introduction (Gregor Gorjanc)
  • AlphaSimR MOOC - Relationship between DNA & traits (Gregor Gorjanc)
  • R crash course on using ggplot and tidyverse (Thiago Paula Oliveira)
  • The role of livestock in global food security (Geoff Simm)

Day 2 - Breeding programme design

  • AlphaSimR  MOOC - DNA lottery (Gregor Gorjanc)
  • AlphaSimR MOOC - Response to selection (Gregor Gorjanc)
  • AlphaSimR MOOC - Modelling complex breeding programmes (Gregor Gorjanc)
  • How does a major multinational animal breeding programme operate in the 21st century (Andreas Kranis)
  • How does a major multinational plant breeding programme operate in the 21st century (Brian Gardunia)

Day 3 - Genomic data in breeding 

  • Genomic data, SNP array genotyping and sequencing, and Strategies to generate genomic data in breeding programmes  (Gregor Gorjanc)
  • Phasing genomic data with heuristic and probabilistic methods (Gregor Gorjanc)
  • Imputation of genomic data (Gregor Gorjanc)
  • AlphaPeel practical - probabilistic genotype calling, phasing, and imputation of genomic data in pedigreed populations (Jana Obsteter)
  • AlphaImpute2 practical - fast phasing and imputation (Jana Obsteter)
  • AlphaFamImpute practical - genotype calling, phasing, and imputation algorithm for large full-sib families (Jana Obsteter)
  • AlphaAssign practical - parentage assignment (Jana Obsteter)
  • Breeding in aquaculture (Ross Houston)
  • Tea breeding and a genomic selection outlook (Nelson Lubanga)

Day 4 - Modelling phenotype data to estimate environmental effects

  • Introduction to experimental design of field trials (Daniel Tolhurst)
  • Introduction to linear mixed models for plant breeding (Daniel Tolhurst)
  • Analysis of phenotype data, including data collected from i) single field trials (with spatial) and ii) field trials across multiple (Daniel Tolhurst)
  • ASReml practicals (Daniel Tolhurst & Thiago Paula Oliveira)
  • Overview of forest tree breeding (Jaroslav Klapste)
  • Genomic selection provides new opportunities for intercrop breeding (Jon Bancic)

Day 5 - Population and Quantitative genetics for breeding

  • Introduction to population and quantitative genetics for breeding (Martin Johnsson)
  • Change in frequencies with drift (Martin Johnsson)
  • Change in frequencies with mutation, migration and selection (Martin Johnsson)
  • Additive effects (Martin Johnsson)
  • Non-additive effects (Martin Johnsson)
  • Inbreeding depression and heterosis (Martin Johnsson)
  • Practicals (Martin Johnsson)
  • Genetic evaluation in a multinational plant breeding programme AND/OR CGIAR Excellence in Breeding platforms (Eduardo Covarrubias-Pazaran)
  • Roadmap for black soldier fly breeding (Leticia de Castro Lara)

Day 6 - Quantitative genetics for breeding II 

  • Variance, covariance, correlation and heritability (Eduardo Covarrubias-Pazaran)
  • Correlated response to selection (Eduardo Covarrubias-Pazaran)
  • Recurrent selection strategies (Eduardo Covarrubias-Pazaran)
  • Practicals (Eduardo Covarrubias-Pazaran)
  • National breeding programme for the Norwegian Red dairy cattle (Janez Jenko)
  • Breeding a man's best friend (Joanna Ilska)

Day 7 - Modelling phenotype data to estimate genetic effects

  • Genetic evaluations with focus on pedigree-based BLUP (Ivan Pocrnic)
  • Introduction to genome-wide association studies (Ivan Pocrnic)
  • Genomic evaluations (Ivan Pocrnic)
  • Practicals (Ivan Pocrnic)
  • A multipart breeding strategy for introgression of exotic germplasm in elite breeding programs using genomic selection (Irene Breider)
  • Population genetics tools with perspective in dog research (Mateja Janes)

Day 8 - Sustainable breeding

  • Management of genetic diversity in breeding programmes - Breeders' dilemma (Gregor Gorjanc)
  • Management of genetic diversity in breeding programmes - Optimal contribution selection (Gregor Gorjanc)
  • Management of genetic diversity in breeding programmes - Optimal cross selection (Gregor Gorjanc)
  • AlphaMate practical - optimising selection, management of diversity, and mate allocation in breeding programs (Gregor Gorjanc)
  • A walk-through of three examples (Gregor Gorjanc)
  • AlphaPart - quantifying the drivers of genetic change (Jana Obsteter & Thiago Paula Oliveira)
  • Recursive models in animal breeding (Maria Martinez Castillero)
  • Economic objectives in animal and plant breeding (Cheryl Quinton)

Day 9 - Exploiting modern technologies in breeding programmes

  • The role of reproductive technologies to boost animal breeding (Gabriela Mafra Fortuna & Gerson Oliveira)
  • Breeding for disease resistance in animals (Andrea Doeschel-Wilson)
  • Editing livestock genomes (Simon Lillico)
  • Evaluating the use of gene drives to limit the spread of invasive populations (Nicky Faber)
  • The potential of genome editing and gene drives for improving complex traits (Gregor Gorjanc)

Day 10 - Open-ended work on topics of participants' interest

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