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