1. Precision animal breeding
Workshop "Animal genomics and breeding for sustainable production"
Precision animal breeding
Theo Meuwissen
Norwegian University of Life Sciences, Ås, Norway.
Workshop "Animal genomics and breeding for sustainable production"
Norwegian University of Life Sciences

2. Introduction
Priorities for research needs in animal genomics and breeding?
What are our future goals?
Challenges to agriculture?
Question is different from:
How to more fully apply genomics in animal breeding
(i.e. we choose the tool to address the challenges)
Tittel på presentasjon
Norwegian University of Life Sciences

3. Future challenges to livestock production
Global warming
Direct problem in south; indirect problem in north (feed prices)
Costs on GHG emissions
Food/feed shortage (population growth, biofuels, etc)
Feed prices surge (livestock products become elite products?)
Animals robust to alternative feeds
Energy, water, land and other shortages
Efficient use of (feed) resources
Reducing environmental footprint (idem)
Institute for Animal and Aquacultural Sciences

4. Animal Breeding & the challenges
AB is one of the tools to address these challenges
can affect an improvement of 2% annually
Important due to accumulation of these improvements
20% improvement in 10 years
Challenges demand:
Efficient use of critical resources
Rapid genetic change/improvements
Robustness:
Efficient production under changing circumstances
Institute for Animal and Aquacultural Sciences

5. Efficient use of critical resources
is aim of precision agriculture
In animal breeding context:
Precision (animal) breeding
Tittel på presentasjon
Norwegian University of Life Sciences

6. Precision breeding (Flint & Woolliams, 2007)
Accurate GEBV
Avoid deleterious side effects from breeding
Select for broad breeding goal
Manage genetic variation
Maintain genetic resources
Realize precision breeding also into the future
Tittel på presentasjon
Norwegian University of Life Sciences

7. Ad 1: Accurate GEBV Accuracy > 90%
For broad spectrum of traits (see Ad 2)
Large scale genotyping and phenotyping
In the age of GS phenotype is king (Mike Coffey)
Make GS work accross large genetic distances
Rapid genetic improvement
Efficient allocation of animals to environments/markets
Tittel på presentasjon
Norwegian University of Life Sciences

8. GEBV with 90+% accuracy Within breed genomic prediction
Game of big numbers: many phenotyped and genotyped animals
Big breeds win this game
No need for high density genotyping / whole genome sequencing
Methods for genomic prediction : G-BLUP or SNP-BLUP
Problematic for traits with large-scale recording difficulties
Limited number of records => low accuracy
Not a broad breeding goal => no precision breeding
Tittel på presentasjon
Norwegian University of Life Sciences

9. GEBV with 90+% accuracy (cont.)
Across breed genomic prediction
Reference population: cooperation across breeds /breedcrosses
High density genotyping / whole genome sequence data needed
discover of causal variants or small segments
Biological knowledge
Non-linear methods for genomic prediction
Small reference populations per breed
Works for traits that are difficult to record on a large scale
Broad breeding goal
Utilises and nurtures AnGR
Tittel på presentasjon
Norwegian University of Life Sciences

10. Genomic selection (GS)
Speeds up selection process dramatically
When generation interval can be reduced
Whith strong selection at young age
Reproductive technology: parents produce many embryos at young age
Especially if trait not recorded on selection candidates
Can address GxE issues
production under low-input/practical environment
Traits not measured on elite animals: slaughter quality, disease resistance
GS can select elite animals that are best under practical conditions
Institute for Animal and Aquacultural Sciences

11. Ad 2: Broad breeding goal
Phenomics to predict many traits
Use of novel recording technologies
On a large scale on practical data
E.g: IR, CT, gene-expression data, automatic milking systems
Combine with genotypes to get GEBV
For broad spectrum of traits for all animals
Robustness:
Maintain production as circumstances change
Tittel på presentasjon
Norwegian University of Life Sciences

12. Ad 3: manage genetic variation
Optimum Contribution Selection:
Maximises genetic progress
Manages the inbreeding
At the level of the DNA (Sonesson et al, 2012)
Using high density SNP data
Maintain ability for fast genetic change
Tittel på presentasjon
Norwegian University of Life Sciences

13. Fast genetic change Breed or cross substitution Genomic selection (GS)
High accuracy;
short generation intervals (using novel reproductive techniques)
GS-intogression (combination of GS and AnGR)
Animal genetic resources (AnGR)
Within breed
Across breeds
Widespread trait recording
Phenomics
Tittel på presentasjon
Norwegian University of Life Sciences

14. __Tradit. Selection; _ _ _Genomic selection
GS-introgression
Introgression of trait(s) from donor breed
Donor breed better for e.g. disease resistance but inferior for Total Merit
Pure line
breeding
Total Merit
Cross with donor breed
__Tradit. Selection; _ _ _Genomic selection
Odegard et al. 2008
Genetic Conservation

15. Widespread trait recording
Calls for ‘phenomics’:
large scale in-line recording of a large spectrum of traits
e.g. infra-red spectroscopy, automatic milking systems, CT etc.
payment-systems to farmers => incentive to select for traits
traits may be indicator traits instead of actual trait:
But genetic correlation should be high
Low heritability may be compensated by large scale recording
Assumes genotyping is widespread ie. recorded animals are genotyped (or pedigree recorded)
Tittel på presentasjon
Norwegian University of Life Sciences

16. Take home messages… Livestock production is facing urgent challenges
-efficient use of critical (environmental) resources
Robust production system => (genetically) robust animals
Rapid adaptations => fast genetic improvements
Precision animal breeding:
Accurate GEBV (>90%)
Selection for broad breeding goal
Maintain genetic variation / AnGR
Tittel på presentasjon
Norwegian University of Life Sciences

17. Take home messages (2) Fast genetic change Genomic selection
Breed or crossbreed substitution (relying on AnGR)
GS-introgression (introgression of few traits)
Phenomics (large scale recording)
Tittel på presentasjon
Norwegian University of Life Sciences

18. Take home messages (3) within breed Genomic Selection (wbGS)
Game of large numbers: many phenotypes and genotypes
Problems with traits that cannot be recorded on large scale
Problems with really broad breeding goal
across breed Genomic Selection (abGS)
Reference population consists of several breeds/crossbreds
Handles traits with limited recording opportunities
abGS focusses on causal variants
WGS data
Biological information
Nonlinear methods for genomic prediction
Tittel på presentasjon
Norwegian University of Life Sciences