Multi-Breed Genetic Evaluations Lessons from UK Dairy evaluations Marco Winters.
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Transcript of Multi-Breed Genetic Evaluations Lessons from UK Dairy evaluations Marco Winters.
Multi-Breed Genetic EvaluationsLessons 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
Who do we work with?Breed Societies Milk Recording
Service partner
Critical success factors;• Recording (ICAR accredited)• Collaboration – (inter)nationally
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
Yield 1977 – 2006 (Year of Birth)(Milk Genetics vs. 1st Lact. yields)
-3500 -3000 -2500 -2000 -1500 -1000 -500 0 5003000
3500
4000
4500
5000
5500
6000
6500
7000
7500
8000
HOL
SHO
AYR
JER
GUE
FRI
Impact of Genetics – lower h2
-35 -25 -15 -5 5 15 25 350
50
100
150
200
250
300
Lact.1Linear (Lact.1)Lact.2Linear (Lact.2)Lact.3
Sire PTA
Dtr
Lac
tati
on
Avg
. SC
C
• Daughter average – Lactation SCC
Standardised Genetic Gains(based on insemination data)
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?
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
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
Breed proportion - Changes
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
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)
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
Heterosis of 5%• Offspring better than average of its parents
0100020003000400050006000700080009000
Breed 1 Offspring Breed 2
Useful Heterosis• Offspring are better than either of their parents
0100020003000400050006000700080009000
Breed 1 Offspring Breed 2
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
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
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 837 dtrs 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 766 dtrs in combined proof
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)
Bull name Original PTA Re-based PTA Milk SCC Base Milk SCCRosedale Advantage-Red -269 11 HOL -269 11T-Bruno -279 -6 AYR 414 -4Lakemead Rancher -275 7 FRI 406 13
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
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