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Multi-Breed Genetic Evaluations Lessons from UK Dairy evaluations

Multi-Breed Genetic Evaluations Lessons from UK Dairy evaluations. Marco Winters. DairyCo Breeding+. Responsible for Genetic Evaluation in UK Independent and Paid for by dairy farmers All breeds and crosses : Production traits SCC Lifespan Fertility Index Type (excl. B&W) Calving Ease.

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Multi-Breed Genetic Evaluations Lessons from UK Dairy evaluations

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  1. Multi-Breed Genetic EvaluationsLessons from UK Dairy evaluations Marco Winters

  2. DairyCo Breeding+ Responsible for Genetic Evaluation in UK Independent and Paid for by dairy farmers All breeds and crosses : Production traits SCC Lifespan Fertility Index Type (excl. B&W) Calving Ease

  3. Who do we work with? Breed Societies Milk Recording Service partner Critical success factors; Recording (ICAR accredited) Collaboration – (inter)nationally

  4. The Breeders ‘toolbox’ • Dairy breeding has never been so easy ! • Many bulls on offer from many breeds • Many genetic indexes available to use • However, they only add value if they are used ! • Regardless of heritability

  5. Yield 1977 – 2006 (Year of Birth)(Milk Genetics vs. 1st Lact. yields)

  6. Impact of Genetics – lower h2 Daughter average – Lactation SCC

  7. Standardised Genetic Gains(based on insemination data)

  8. Future Challenges - Competitiveness • What are the future genetic needs ? • Consider future economic conditions • Consider different ‘non-economic’ demands • E.g. environment, welfare, consumer • Consider ever-widening range of production systems • What are implications for Genetic evaluations ? • Are we making best use of available data?

  9. Genetic Evaluations Performance = Genetics + Environment Genetic evaluations based on: Pedigree information (Genomic information) Performance recording (e.g. Milk, SCC) Correcting for environmental effects Progeny performance Proper adjustment for genetic merit of mate Genetic gain improves with higher accuracy (but there is a trade-off with Generation Interval) Time & Accuracy

  10. UK situation – Pre 2010 Aim: How can we maximise the accuracy of evaluations? Using all existing data Without bias to existing evaluations Not all recorded data was being used Some breeds excluded altogether Crossbreds largely excluded Not all breeds had full set of traits evaluated Not all data was being used optimally Split proofs for the same bulls across breeds Suboptimal use of pedigree contributions Herdmate contemporaries not always included Growing interest in crossbreeding

  11. Breed proportion - Changes

  12. Breed proportions 2013 – Live cows 20% of cows not pure (>87.5% purity) Most are result of breed replacement 89% are >75% ‘pure’ 5.3% are 1st generation crosses Up 1.5% during last five years

  13. Dealing with mixed breed data • Correction for difference in variance • Fitting full pedigree • Separate groups for unknown parents by breed • Widespread use of AI has established many links • Correction for Heterosis / Recombination • Crosses between four main breed groups considered • Holstein • British Friesian • Reds (Ayrshire, Shorthorn, Brown Swiss, Montbeliarde) • Other (Jersey, Guernsey, rest)

  14. Example animal - 11779014 Animal Breed Code %Breed Origin 11779014 68 50.00 NZ Jersey 11779014 76 12.50 N. American Jersey 11779014 04 6.25 UK Jersey 11779014 66 6.25 Danish Jersey 11779014 78 25.00 NZ Ayrshire

  15. Heterosis of 5% Offspring better than average of its parents

  16. Useful Heterosis Offspring are better than either of their parents

  17. All breed evaluations- background Already routinely used in other countries: E.g. Ireland, The Netherlands, New Zealand, and USA DairyCo commissioned feasibility study (‘07/08) Results of feasibility were promising EGENES undertook further development work (08/09) International validation run in August 2009 (interbull) Implementation in January 2010

  18. Impact Largest changes for: Bulls used heavily in crossbreeding Bulls with limited information Few daughters Few herds Therefore; Smaller breed populations relatively more change But also have largest gains in reliability

  19. All-breed evaluations Best use of all data; Two examples Morwick Sand Ranger (Red Holstein) Pure-bred analysis; 399 daughters in Holstein proof 392 daughters in Ayrshire proof 12 daughters in Shorthorn proof All-breed  837dtrs in combined proof B Jurist (Swedish Red) Pure-bred analysis; 0 dtrs in Holstein proof (not allowed) 127 dtrs in Ayrshire proof 21 dtrs in Shorthorn proof All-breed  766dtrs in combined proof

  20. Presentation of proofs Each animal receives only one proof Post evaluation Animals get assigned to breed groups Each breed group has own genetic base Reset in January 2010 to average of cows born in 2005 Example: £PLI index applied to all breeds (Guernsey has own Merit Index)

  21. On-going requirements Accurate data needed (lots of it !) Currently >100M records used Accurate animal identification Harmonised trait definitions (ICAR) Sharing (pooling) of Data Internationally

  22. Conclusion and Future All-breed evaluations implemented in 2010 Improved Accuracy of evaluations – within and across breeds New breed and trait evaluations added Industry response has been positive Separate breed lists helped this situation However, one single list would help those x-breeding Future possibly All-breed genomic evaluations Within breed genomics for Holstein - 2012 More R&D needed to ‘translate’ DNA info to other breeds

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