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Marker-Assisted Selection:Marker-Assisted Selection:From Agriculture to Aquaculture
Ross HoustonRoss Houston
Outline• Introduction to selective breeding and
marker-assisted selection (MAS)marker-assisted selection (MAS)• Identifying markers
candidate gene approachcandidate gene approachQTL mapping approachgenome-wide selectiong
• Example from pig industry • Application of MAS in aquacultureApplication of MAS in aquaculture
Introduction• Selective breeding is a powerful tool
Introduction• Genetic improvement in agriculture
– success using ‘traditional’ breeding approach
Van der Steen et al. 2005
Introduction• Selection on quantitative traits
‘Infinitesimal model’: large number of genes withInfinitesimal model : large number of genes with minor effects on trait Effective at estimating genetic merit of animals, based on performance and pedigreeGenome seen as ‘black box’
IntroductionTrait Measurements + Pedigree = Genetics + Environment
Combined effect of all influential Genes (G1+G2 + G3 +…)
Courtesy of Huw Jones, Genesis Faraday
Introduction• Marker-assisted selection (MAS)
• Genetic markers throughout genome can giveGenetic markers throughout genome can give information on individual gene effects
Genes Markers
Introduction• Marker-assisted selection – 3 main phases:
Detection:Genotype markers for population of animalsLook at association with traits of interest (e.g. resistance to disease)
Verification:Verify effects in appropriate commercial lines
Utilisation:Genotype selection candidatesIncorporate marker information into selection program (complementary to existing program)
Introduction• Advantages of MAS:
Major gene explaining large % variation in traitMajor gene explaining large % variation in traitDifficult or expensive to measure traits
disease resistancemeat quality traits
Traits with low heritabilityI d f l tiImproved accuracy of selection
Identifying Markers• Candidate genes
look for variation in specific geneslook for variation in specific genesgene predicted to affect trait
affect of mutation in other speciesknowledge of physiology of protein
association between variation in gene and variation in traitgene and variation in trait
Identifying Markers• QTL Mapping
markers throughout genomemarkers throughout genome statistical association between markers and traits of interest
QTL Location
focus in on most significant regions of the genome
k fi inew markers, fine mappingcandidate genes
Identifying Markers• Genome-wide selection
thousands of markers acrossthousands of markers across genomeutilise information from all markers in calculating genomic EBVimproved accuracy over
SNP Chip: Tens of thousands of markersimproved accuracy over
traditional selection method
Utilising Markers• Selecting animals for breeding based on
DNA sequence at markersDNA sequence at markerssupplement to traditional breeding program in calculating EBVextra information on selection candidate = improved accuracy of selectionparticularly useful for difficult to measure traitsparticularly useful for difficult to measure traits
Examples of MASp1. Candidate Gene Approach in Pigs:
- The MC4R example- The MC4R example 2. QTL Mapping Approach in Salmon:
- The IPN exampleThe IPN example
Detection of markersDetection of markersVerification of effectsUtilisation in breeding programsUtilisation in breeding programs
MC4R in Pigsg
Mutant mouse Does a MC4R mutationand full-sib exist in this pig?and full sib exist in this pig?
Courtesy of Graham Plastow, University of Alberta
MC4R in Pigs
Barsh et al. 2000, Nature
PT1 - A Single Nucleotide DifferencePT1 - A Single Nucleotide DifferenceMC4R: Single Nucleotide Differencegg
Ginstead
of
MC4R: Single Nucleotide Difference
C N S I I D P L I Y
C N S I I N P L I Y
Allele 1homozygotesequence
Allele 2
293 295 297 299 300
A
Transmembranedmains
homozygotesequence
NH2 COOHI II III IV V VI VII
MC4R gene
Kim, K. S., N. Larsen, T. H. Short, G. S. Plastow and M. F. R th hild 2000 M li G 11 131 135
PICmarq™ Technology
Rothschild. 2000. Mammalian Genome, 11:131-135.
Courtesy of Graham Plastow, University of Alberta
MC4R: Effects
• Association between MC4R and performance traits in several breeding lines:
MC4R Genotype
Daily Feed Intake (kg) AA 1.94 (0.07)( )AB 2.03 (0.06) BB 2.11 (0.06) P<0.01 Days to 110kg AA 167 9 (0 9)
AA BB AB AA BB AB
AA 167.9 (0.9)AB 166.9 (0.8) BB 164.6 (0.9) P<0.001 Backfat (mm)Backfat (mm)AA 11.1 (0.2) AB 11.6 (0.2) BB 12.0 (0.2)
Kim et al. 2000, Mamm Genome P<0.001
MC4R: UK Commercial Results
N ccw P2 L% Unselected
sires 1833 72.5kg 11.8mm 57.4%
Sires selected to be
%to be
homozygous + 2137 73.5kg 10.7mm 58.8%Improvement -1.1mm +1.4%
Courtesy of Graham Plastow, University of Alberta
MC4R: Utilisation• PIC: Differentiation of product for customer
leaner pig, less intake, less wasteleaner pig, less intake, less waste higher intake, fattier pork (e.g. Japanese market)
• Allele frequencye e eque cyIntermediate frequency is importantfavourable allele close to fixation is less beneficial
MAS in Pigs: Future• Use of markers in breeding programs
Hundreds of markers currently used in selection– Hundreds of markers currently used in selection – Specific gene tests likely to increase– Denser SNP map → move towards genome-wideDenser SNP map move towards genome wide
selection (using all markers)
IPN QTL in SalmonIPN QTL in Salmon
Can genetic markers be used to improve i t t I f ti P ti N i ?resistance to Infectious Pancreatic Necrosis?
Infectious Pancreatic Necrosis• Viral disease affecting young salmon
– high mortality rate– major economic and welfare problem
genetic improvement of resistance key goal for– genetic improvement of resistance key goal for breeders
IPN GeneticsRanking of families
across sites:across sites:
Low Mortality Rate (resistant)
Intermediate
Full-Sib Salmon Family
Intermediate Mortality Rate
High Mortality Rate (susceptible)
Marine site 1 Marine Site 2 Marine site 3
Courtesy of Derrick Guy, Landcatch Natural Selection
QTL Mappingpp g• 10 large families, intermediate mortality • Markers on all chromosomes• Markers on all chromosomes
Parent
M Q
m q
mm q
M QM Q
M Q
IPN Resistant OffspringIPN Susceptible Offspring
m q
m q
M QM Q
M
m q
Q
QTL Mapping
MarkersQTL
Chromosome 21
QTL
QTL
QTL Mapping: Flanking Markerspp g gFlanking Marker 1
Flanking Marker 2
QTL
Markers
QTL
QTL Mapping: Size of Effect
• Genetic variation explained = 70-80% (confirmed in Norwegian study)g y)
Houston et al. (2008) Dev. Biol.
Application of QTL markers• Full sibs to selection candidates challenged
with IPNwith IPNeffect of QTL markers in family confirmed in sibsfamilies selected according to IPN breeding valuewithin-family decisions based on QTL flanking marker genotype
IPN current and future work• Move towards genes underlying QTL
– Compare gene expression response to IPN challenge of fish carrying resistant and susceptible allelessusceptible alleles
– Apply new markers (e.g. SNPs) for improved MAS– Focus on additional diseases and traits
Overall Summary• MAS in agriculture and aquaculture
S f l l i tSuccessful examples existSupplemental to traditional selective breedingMost useful for difficult to measure traits andMost useful for difficult to measure traits, and genes of major effectImproved genomics resources → move towards genome-wide selection
AcknowledgmentsSteve Bishop Chris Haley Graham Plastow
Derrick GuyAlastair HamiltonAlan Tinch
Chris Haley
David TelfordAlmas Gheyas
John Taggart Brendan McAndrew
Huw Jones