Fokkerij in genomics tijdperk

Johan van ArendonkAnimal Breeding and Genomics CentreWageningen University

Animal Breeding and Genomics Centre (WU)

Our Mandate: training and research on the role and sustainable utilisation of genetic variation in farm and companion animals.

Expertise in quantitative and molecular genetics. Staff: Scientists, 8 Postdocs and 25 PhD students

37%

26%

37%

Science Foundation University Industry and EU

Funding

• Strong scientific position

• Partnership with industry

• International orientation

B

G

A

Genomics and bioinformatics

Statistical Genetics

Animal Breeding

Expertise

Animal Breeding and Genomics centre

BiodiversityProductivity, healthand welfare

Quality

Farm animalsAquatic species

Companionanimals Natural

populations

Jobs

Industry

Research

Extension

Breeding: utilizing genetic variation

Creating genetic change Selecting the best animals Using the best animals to produce next generation

Aim: produce animals that perform better

Challenges: Understanding the impact of genetic variation Developing tools to find the genetically best animals

Current breeding schemes

BLUP breeding values: Evolved from sire models to animal model From single to multiple trait analysis

Optimally combines phenotypic information

Emphasis on traits that can be recorded relatively easy (growth rate, milk production, longevity)

Application of Molecular genetics

Objective

Finding genes (QTL) that contribute to genetic variation

Molecular Markers

• Differences in DNA

•Can be measured

Principle QTL mapping

Sire AB

50% A 50% B

Difference: information on location and size of QTL

Genetic markers:make it possible to follow

transmission fromparent to offspring

bad good

QTL mapping: central role in gene detection

QTL

Development of molecular tools

Phenotypes andGenotypes

Candidate genes:•Comparative Mapping•Data mining•Physiology•Gene expression

QTL analysis

Gene Identification

Genome sequence: increase in molecular tools

Large increase in number of markersChicken genome sequence: 2.8 million SNPs

identified based

Improvement of comparative mapOpportunity to exploit knowledge from other

species

Chicken – human comparative maps

Genomics and breeding for

product quality

Milk Genomics Initiative: started in 2004

Goal: Determine opportunities to change milk composition through breeding

Three activities

1. Measure milk composition of 2000 cows

2. Determine the amount of genetic variation

3. Mapping QTL/genes involved in some components

Partners:

Design of experiment

5 large

families

50 small

families

1000 heifers

50*20

1000 heifers

5*200

Collection of samples on 400 farms:

1. 3 milk samples

2. Blood sample for DNA analysis

Finding genes using molecular genetic information

Measure

performance

Analysis of DNA

Family structure Collection of information

Results on milk fat composition

Verschillen tussen koeien in C16:0

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C16:0 gehalte van melkvet (in gewichtsprocenten)

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Verschillen tussen bedrijven in C16:0

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C16:0 gehalte van melkvet (in gewichtsprocenten)

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1. Substantial variation in milk fat composition

2. Large genetic variation between cows

3. DGAT1: gene with a large contribution to genetic variation

Milk Genomics Initiative

Unique combination of: Disciplines: from dairy

science to genomics

Industry and University: science for impact

Partners in the chain: from cow to product

Milk Genomics Initiative=Team effort

Utilization of genomic information

1. Gene technology: production of GM animals Application to livestock hindered by many factors including

technology Break through needed to enable site-specific insertion

2. Use genomic information to better exploit natural genetic variation

Marker assisted selection Genomic selection Pedigree reconstruction (e.g. high health chip in pigs)

High health chip

Pig production chain: no information on pedigree of finishing pigs

Large number of DNA markers: opportunity to trace line and father of origin

Opportunities to improve selection for improved health and carcass quality

Research infrastructure

Maintaining up-to-date research infrastructure

ABI 3730 sequencer Illumina BeadXpressX-tractor Gene

Large scale genotyping: outsourced (Utrecht) External funding essential

Successful collaboration with Industry

Long-term partnership important (no quick wins) Recognition of the interest of industry and

university (understand the driving forces) Contributes to publications in leading journals

Thank you