4 Deregressed proof (DRP) - genotyped animals Females: Own phenotypic deviation from parent average if animal should have the calculated EBV Bulls: Phenotypic deviation of daughters is used as a phenotype of the bull. Deviation from parent average of the bull if the bull should have the calculated EBV Each phenotype is only included once! 4...
5 Tested cows Females in reference group - information from 10 daughters of a bull with yield in 1. lactation Adjusted phenotype Not tested cows Adjusted phenotype Adjusted phenotype Adjusted phenotype 5...
6 DRP - use of pedigree information for tested animals Previous routine: Sire, MGS Now: Sire, Dam (Animal model) Advantage: DRP are closer to the true yield deviation of the animal 6...
7 DRP - use of pedigree information for tested animals Now Previously Pedigree: 0,5 + 0,25 = 0,75 + genetic group Pedigree: 0,5 + 0,25 + 0, ,0625 = 0, genetic group 7...
8 Calculation of BV Tested cows and proven bulls with DRP DRP = μ + Animal + e Type of output BV depends on pedigree: Genomic pedigree DGV (genomic value) Traditional pedigree EBV (traditional value) 8
9 Pedigree on the basis of SNP Genomic pedigree: 0-1!Bull!Full Sib Traditional pedigree: 0,5 9...
10 Calculation of BV Tested heifers and young bulls without DRP Missing DRP = μ + Animal + e Type of BV depends on used pedigree: Genomic pedigree DGV Traditional pedigree Pedigree index 10...
11 Blending (GEBV) Combines DGV and EBV DGV: Pedigree (genomic), performance (DRP) EBV: Pedigree (traditional), performance (DRP) Combination BUT much overlap of information New method better to avoid double counting makes it possible to include females in reference group 11...
12 Reference population January 2015 Reference population Bulls Cows Holstein a) (8400) RDC 8150 b) Jersey 2450 c) 8550 a) Includes proven bulls from NLD, FRA, DEU, ESP b) Includes proven bulls from NOR c) Includes proven bulls from USA 12
13 Genomic information gives higher reliability for candidates! Reliability for 4 latest birth years of proven bulls compared to reliability on pedigree information Example: Validation reliability on DGV 45% Validation reliability on pedigree 20% Extra reliability 25% 13
14 Extra reliability in addition to pedigree information for RDC Reference population Bulls Bulls and cows Yield 0,13 0,18 Growth 0,13 0,14 Fertility 0,14 0,14 Birth 0,18 0,18 Calving 0,02 0,02 Udder health 0,17 0,23 Other diseases 0,14 0,14 Frame 0,24 0,29 Feet&Legs 0,24 0,33 Udder 0,23 0,30 Milking speed 0,17 0,22 Temperament 0,18 0,21 Longevity 0,07 0,07 Claw health 0,11 0,11 14
15 Extra reliability in addition to pedigree information for HOL Reference population Bulls Bulls and cows Yield 0,33 0,35 Growth 0,24 0,24 Fertility 0,32 0,32 Birth 0,31 0,31 Calving 0,22 0,22 Udder health 0,39 0,41 Other diseases 0,06 0,06 Frame 0,36 0,36 Feet&Legs - - Udder 0,52 0,52 Milking speed 0, Temperament 0, Longevity 0, Claw health (0,00) (0,00) 15
16 Extra reliability in addition to pedigree information for JER Reference population Bulls Bulls and cows Yield 0,16 0,22 Fertility 0,17 0,17 Birth 0,00 0,00 Calving 0,00 0,00 Udder health 0,09 0,16 Other diseases 0,00 0,00 Frame 0,19 0,30 Feet&Legs 0,05 0,13 Udder 0,26 0,29 Milking speed 0,15 0,34 Temperament 0,00 0,00 Longevity 0,11 0,11 16
17 Difference in reliability between breeds Reliability for RDC and Jersey still 12-15% point lower than HOL but higher than before! Expect increase in reliability when more genotyped RDC and Jersey cows are included in reference populationen 17
18 Correlations - previously (May 2014) and now (since August 2014) RDC Jersey Reference Genotyped animals group: Young bulls and Cows Young bulls and Cows heifers heifers Without cows With cows
19 Genetic level Genetic level for young bulls and heifers has increased RDC: 4 index units for yield and NTM 0-2 index units for other traits with cows in the reference population 19
20 Blue = New, Red = previously 20
21 Summary What is improved? RDC/JER Previous routine New Pedigree Reference population Blending method Sire-Maternal grandsire Animal Model Important for candidates and cows only traits with strong trend Bulls Bulls and cows (8400 HOL), Developed by MTT (2010) Improved by MTT (2013/14) RDC, 8550 JER Better to avoid Double counting 21
22 Challenges Calculation of DRP Method sensitive for traits with low heritability when females are included in reference group or reference group is not uniform Causes instability in DGV Improved method is expected to be introduced in February 2015 Improvement of genomic prediction is a continuous process 22
23 Tested females per country and birth year Year Holstein RDC Jersey DNK FIN SWE DNK FIN SWE DNK FIN SWE Total HOL total : Last year: RDC total : Jersey total :
24 Level of genomic tested Holstein November 2014 Bulls with HB Bulls with out HB Females Born Number NTM Number NTM Number NTM , , , , , , , , , , , , , , , , , , , , ,2
25 Level of genomic tested RDC November 2014 Bulls with HB Bulls without HB Females Born Number NTM Number NTM Number NTM ,0 60 2, , , , , , , , , , , , , , , , , , , ,3
26 Level of genomic tested Jersey November 2014 Bulls with HB Bulls without HB Females Born Number NTM Number NTM Number NTM ,8 33-1, , , , , , , , , , , , , , , , , , ,8
27 Stated from practice First time a bull gets an EBV based on a progeny test it some times deviates/drops significantly from the GEBV but closes in on GEBV in subsequent runs and Top GEBV bulls tend to drop in level when daughters enter production
28 Current thresholds going from GEBV to EBV Trait Reliability EBV Yield, Beef 60% Type traits, temperament, milkability 15 daughters Longivity, calving traits direct 50% Mastitis, claw health, calving traits maternal, young stock survival 40% Fertility, other diseases 35% GEBV reliability are > than EBV reliability threshold
29 How well do the bulls meet expectations? HOL - Official GEBVs/EBVs for Yield Udder health NTM Depending on trait bulls Standard deviations of (EBV GEBV) Do the 1 st indices have larger STDVs
30 GEBV 1 year old genotype GEBV EBVref1 EBVref2 EBVref3 4-5 year old Genotype last evaluation before daughter information 5 year old daughter information 5 year old daughter information 5 year old daughter information
31 Expected results If a bull have GEBV NTM = 30 we do expect EBV NTM < 30! The regression βebv,gebv expected < 1 unless the bull has thousands of daughters. Why? Not Part-Whole, but to some degree independent data in the two evaluations. E(βEBV,GEBV) = r 2 EBV for independent tests
41 How well do the bulls meet expectations? RDC & JER changed genomic model in AUG14. Changed to AM and cows in reference GEBVs calculated for 4 birth years of progeny tested bulls. Bulls own EBVs and daughters EBVs not in reference population.
42 RDC - NTM βebv,gebv a little low Tend to overestimate high GEBV Bulls
43 JER - NTM
44 Conclusion Results generally looks as expected. Average EBV lower as not Part-Whole. βebv,gebv for RDC NTM looks a little low. Quite different population structure. Best GEBV group get best avg. EBV. Action Keep focus that top bulls get expected results
45 Conclusion Lower threshold r 2 EBV than GEBV r 2 Larger STDV for (EBVref1-GEBV) HOL yield Actions NAV will increase thresholds for r 2 EBV breedwise depending on GEBV r 2 Combine daughter information and genomic information (Part-Whole)
46 r2 of mean EBV 5-8 Genomic tested bulls has same expected change in EBV as one progeny tested bull 1,00 0,90 0,80 0,70 0,60 0,50 0, No genomic bulls in calculated mean EBV Focus less on single bulls and more on a group of bulls (5-8)
47 Implemented GEBV in 2014 Date February 2014 March 2014 May 2014 July/August 2014 August 2014 November 2014 Comment Adjustment Holstein longevity US Jersey bulls included in ref population Publication age decreased from 17 month to 10 month Cows in reference populations and revised blending method applied for RDC and Jersey. Results from GMACE routine evaluation published Cows in reference populations and revised blending method applied for Holstein yield traits
48 Implementation plan GEBV 2015 Date February 2015 Spring 2015 Spring 2015 Comment Cows in reference populations and revised blending method applied for Holstein remaining traits All type traits at each evaluation GEBV for females Official GEBV reliabilities Spring/summer 2015 Young stock survival 2015 Weekly evaluations 2015 Cows in ref for more traits fertility, claw health, longevity
49 More frequent genomic prediction Aim GEBV for bull calves available at a younger age than today 1. Efficient registration of animal and collection of DNA (farmer and VG) 2. More frequent and faster genotyping (GenoSkan) 3. More frequent genomic prediction (NAV) Room for improvement in all 3 steps!
50 Steps in routine genomic prediction Step 1. NAV pedigree file Information from all three countries only new animals needed 2. Check of pedigree Has to be solved in the future pedigree assignment program 3. Genotypes from GenoSkan 4. Imputing (FImpute) Check of pedigree done here as well can handle that part until step 2 is solved 5. GBLUP/SNP BLUP 6. Blending 7. Publication
51 More frequent genomic prediction Requirement for weekly evaluations More automatic Establish a simple warning/error detecting system Maybe need for more computer capacity or SNP BLUP (require GMACE test run sept 2015)
52 Work ongoing Kevin Byskov and Martha Bo Almskou in cooperation with Timmy Gregers Madsen, AU built stepwise a system up. Aim to introduce more frequent evaluation during 2015
53 Applied research focus 2015 One step (MTT) Simultaneously use of phenotypes and genotypes in evaluation More optimal use of data Use of extra SNPs added on LD (AU) Include information that some SNPs carry more information than other SNPs
54 (G)MACE MACE use national EBVs based on phenotypes (G) GMACE use national GEBVs based on genotypes 58
55 MACE versus GMACE Breeding values from MACE and GMACE are expressed on the same scale and comparable on each country scale All bulls included in GMACE are expressed on all participating countries scale also scales for countries only participating in MACE.
56 What has to be published from GMACE? All countries participating in MACE have to publish: International EBVs for all Interbull traits Interbull EBVs can be EBVs from MACE or GEBV from GMACE
57 Which countries participate in GMACE? December routine Australia, Belgium, Canada (not Semex bulls), Germany, DFS, France, England, Italy, Holland, Poland
58 Groups of countries (e.g. NLD, FRA, DEU and DFS) exchange genotypes for young AI bulls A bull with a genotype in more countries get an GEBV with the same reliability as national bulls on all country scales within the exchange group. (equivalent to a situation that a bull has daughters in all countries no conversion by use of genetic correlation) and A slightly higher reliability on 3rd country scales than if information from GMACE is coming from one country only.
59 Y-index - MACE and GMACE MACE bulls born after 2007 GMACE bulls born >2010 Australia 97,5 106,0 Canada 101,1 110,9 (without Semex) Germany 101,3 111,4 DFS 104,7 111,3 France 104,3 109,2 England 101,1 109,6 Italia 97,4 107,2 Holland 103,9 111,6
60 Udder health - MACE and GMACE MACE bulls born after 2007 GMACE bulls born >2010 Australia 96,9 - Canada 94,4 109,4 (without Semex) Germany 95,8 110,1 DFS 101,5 110,8 France 95,1 110,7 England 96,6 109,3 Italia 95,7 108,2 Holland 97,0 110,4
61 Interbull GMACE Focus on top lists Proportion of top bulls primary depending on average and number of tested bulls. Results see NAV interbull search tool
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