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