Selección Genómica: Una Nueva Era para la Producción Porcina Dr

Genomic Selection: A
New Era for Sustainable
Pork Production
Dr. Armand Sánchez. Director de Vetgenomics S.L.
Universidad Autónoma de Barcelona
1-3 October 2013 - Isla de la Toja - Spain
The future of Genomic Technologies in Animal
Breeding: HTS and genotyping platforms and their
use in Genomic Selection of farm animals
“A major challenge in current biology is to understand the genetic basis of
variation for quantitative traits.
We are currently in the midst of a genomic revolution, which enables us to
incorporate genetic variation in transcript abundance and other
intermediate molecular phenotypes into a quantitative trait locus mapping
framework.
This systems genetics approach enables us to understand the biology
inside the 'black box' that lies between genotype and phenotype in terms
of causal networks of interacting genes”.
Trudy F. C. Mackay et al. 2009. Nature Review Genetics 10, 565-577.
Genetics and animal breeding
• The majority of economically important traits in
livestock are typical multifactorial traits.
• Spectacular genetic progress has been obtained
using conventional breeding programs.
(Quantitative Genetics)
• Using proven selection techniques, it is possible
to genetically improve economically important
traits at the rate of about 2 to 3% per year.
Pig industry improvement
1962
14 pigs/year
410 Kg of feed/pig
34 Kg of lean/pig
71% more pigs
38% less feed
33% more lean
2009
23 pigs/year
273 Kg of feed/pig
47 Kg of lean/pig
Aproximately 60% of improvement
has come from genetic improvement
Past and Current Selection for
Quantitative traits in animals
Genotype
Many genes
(infinitesimal model)
(polygenes)
Estimated
Breeding
Value
BLUP
Phenotype
Environment
Phenotype
of relatives
SELECTION
OMICS - ERA
Large-scale, high-throughput analysis
- Genomics
- Transcriptomics
- Proteomics
- Pharmacogenomics
- Toxicogenomics
- Cellomics
- Metabolomics etc…
Farm Animal Genomics
Aims
Scientific
• To understand genetic control of complex traits
infinitesimal / major gene models, epistasis,
networks, gene discovery
• To predict consequence from sequence
Strategic
• To improve:
• health and welfare of farmed animals
• the sustainability of animal production systems
• the quality and safety of animal products
• the knowledge base in animal biology
Principles of QTL mapping
• Co-segregation of QTL alleles and
linked marker alleles in pedigrees
Q
M
q
m
Unobserved QTL alleles
pair of
chromosomes
Observed marker alleles
Informative pedigree
X
qq
QQ
QQ Qq qq
There are 8935 QTLs in the database from 371 publications
representing 644 different traits (Sept. 2013).
Number of QTL by publishing year
Trait Classs
QTLs Found
Year
QTLs Found
1994
1995
5
5
1996
6
1997
11
Exterior
786
1998
102
Health
883
1999
49
Meat Quality
5755
2000
102
2001
279
2002
195
2003
661
2004
223
2005
2006
2007
2008
2009
519
520
492
1831
833
Production
708
Reproduction
803
http://www.animalgenome.org/QTLdb/
2010
2011
2012
768
1380
953
From QTL to QTN…
Problems with linkage mapping
Process is very slow…
- 10 years or more to find causative mutation
- One limitation has been the density of markers
- Probably to be solved in the future…
The SNP revolution!
The Revolution…
As a result of sequencing animal genomes, have a huge
amount of information on variation in the genome
- at the DNA level
Most abundant form of variation are Single Nucleotide
polymorphisms (SNPs)
The Revolution…
Can we use SNP information to greatly
accelerate the application of marker
assisted selection in the livestock
industries?
Some porcine QTNs actually in use…
• HAL : Meat quality
• IGF2 : Growth, meat quality
• RN : Meat quality
• ESR : Reproduction
• PRLR : Reproduction
• RBP4 : Reproduction
• KIT : Colour
• MC1R : Colour
• MC4R : Growth, fat
• AFABP, HFABP : Intramuscular fat
• .......
Genome Wide Association Studies (GWAS)
Use of SNP genotyping chips
Actually can genotype up to 5
millions of SNPs in a sample
“SNP
chips”
Infinium
Assay
GeneChip
Array
PorcineSNP60. A total of 64,232
SNPs were included on the
Beadchip.
Ramos AM et al. (2009) Design of a High Density SNP
Genotyping Assay in the Pig Using SNPs Identified and
Characterized by Next Generation Sequencing Technology.
PLoS ONE 4(8): e6524.
Cost of Whole Genome Sequencing
(mammal)
1.000 $ genome
Genome sequencing in domestic species
2004
2005
2009
2012
Completed
Groenen MA. et al., Nature 491, 393–398 (15 November 2012).
Total length of the genome : 2,596,639,456
Number of protein coding genes: 21,627
The Revolution…
Can we use SNP information to greatly
accelerate the application of marker
assisted selection in the livestock
industries?
- Omit linkage mapping
- Straight to genome wide LD mapping
- Breeding values directly ftom markers?
GENOMIC SELECTION
(Meuwissen et al. 2001)
ANIMAL GENOMICS enables Identification of
(most) SNPs Affecting Quantitative Traits:
GENOMIC SELECTION
GENOMIC SELECTION
Unknown genes
(polygenes)
Gene Assisted Selection
Marker Assisted Selection
Informative SNPs
EBV
GENOMIC SELECTION
chromosome
Chromosome
segment i
Chromosome
segment effects gi
GENOMIC SELECTION
Predict genomic breeding values as sum of effects
over all segments (Meuwissen et al. 2001)
p
GEBV =
∑ Xi gi
^
i
Number of chromosome segments
GENOMIC SELECTION
• Genomic selection can be implemented
• with marker haplotypes within chromosome segments
p
GEBV =
∑ Xi gi
i
^
1_1
0,3
1_2
0,0
2 _ 1 -0,2
2 _ 2 -0,1
GENOMIC SELECTION
• Genomic selection exploits linkage disequilibrium
• Assumption is that effect of haplotypes or markers
within chromosome segments will have same effects
across the whole population.
• Possible within
available.
dense
marker
maps
1_1
0,3
1_2
0,0
2 _ 1 -0,2
2 _ 2 -0,1
now
GENOMIC SELECTION
GENOMIC SELECTION
Optimal breeding program design
• With genomic selection, we can predict GEBV
with an accuracy of 0,8 for selection candidates
at birth.
• How does this change the optimal breeding
program design?
• Breed from animals as early as possible.
Abe Huisman (Hendrix Genetics in the Netherlands) and Patrick Charagu (Hypor Inc., Canada).
A genomic future. London Swine Conference – Managing For Production March 27 and March 28, 2013
Rate of genetic progress is determined by four factors:
1. Accuracy of the breeding values
2. Selection intensity–how big is the group of potential selection
candidates and how many do I select?
3. genetic variability of the trait
4. The generation interval–how long does it take before I can use the
selected animals as parents.
Genomic selection potentially impacts three of those, and certainly
has an impact on accuracy (1) and generation interval (4).
Genomic selection can offer anywhere between 20-50%
greater genetic progress in pig breeding programs.
Abe Huisman (Hendrix Genetics in the Netherlands) and Patrick Charagu (Hypor Inc., Canada).
A genomic future. London Swine Conference – Managing For Production March 27 and March 28, 2013
Genomic Selection provides unique opportunities to
enhance pig breeding programs
By removing limitations on when, where, and on whom
phenotypes are recorded
With opportunities to:
- increase / maintaining response to selection
- reduce rates of inbreeding and / or generation intervals
- enhance selection for “difficult” traits (disease, field performance)
Successful implementation requires:
- Large training data sets and continous re-training
- Strategic use of low-density panels to reduce costs
- Redesign of breeding programs to reduce costs
Host-pathogen interactions
Environmental
factors
Host genetic
factors
Disease
development
interactions
Pathogen genetic
factors
Host genes influencing susceptibility to infectious
disease and disease development
•
•
•
•
•
•
•
•
Attachment and entry of micro-organism
Innate immunity (based on general patterns)
Antigen processing and presentation
Regulation of immune and inflammatory response
Lymphocyte function
Effector cell function
Tissue function and integrity
Others, for example bloodgroups...
Conclusions
Genomic Selection provides unique opportunities to
enhance pig breeding programs
The genomic (r)evolution in Animal Breeding
• Today: High density panels of SNPs genotyping
• Next future: (re)sequencing of genomes and
transcriptomes im domestic animals
TOWARDS A PARADIGME CHANGE…
DNA seq + RNA seq
Opening the “black box”
Before: infinitesimal model
¿How many QTLs?
¿Effects of QTLs?
¿QTNs?
Now: genomic
information
Thanks for your attention !
Evolution never stops....