Multibreed evaluation. Multibreed evaluation. Obstacles to full Multibreed. Multibreed Obstacles. Outline

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How should we be predicting breed differences in multibreed genetic evaluation? Larry Kuehn Multibreed evaluation What is it? Depends on the goal Genetic evaluation incorporating data from and generating predictions on crossbred animals Evaluation that results in accurate comparisons of additive genetic merit across breeds/composites Provide estimates of nonadditive effects such as heterosis/sire x dam breed interactions Multibreed evaluation As implemented currently, primary goal is to include crossbred and composite records Ultimate goal to be able to compare all animals of any breed as seedstock Starting to occur more often Relates to a full multibreed analysis Obstacles to full Multibreed Merger of multiple breed databases Structures are often very different IDs duplicated in several breeds (but not known as duplicates) Difficult to resolve Standardized ID system would help Cooperation between database curators Breed associations Genetic prediction centers Individual producers/commercial entities Multibreed Obstacles Estimating population parameters Direct and maternal heterosis Direct and maternal additive breed effects Field data usually not suitable Contemporary groups structure Will discuss further Confounding between heterosis and breed Less crossbred data relative to purebred (depends on classification of purebred ) Research data useful here Outline Review current multibreed methods Contemporary group structure and importance Research data for breed differences ABEPD update Update on 2, bull project prediction equations 1

Multibreed model Current Multibreed Methodology Primarily descended from Arnold et al. () animal model Elzo et al., 1983, 199 sire model y = Xb + ZQg + Za + WSd + WTδ + e Includes Additive breed effects and heterosis Additive animal effects Animal x breed interaction (dominance) Likely difficult to fit in most data sets Multibreed model Variance assumption Scale additive/residual variance according to breed/breed percentage Segregation variance not accounted for (Lo et al., 1993; Cardoso and Tempelman, 24) Field data generally not adequate Rodriquez-Almeida et al. (1997) Why is field data inadequate? Trying to predict multiple effects from crossbred progeny relative to purebreds Heterosis, maternal breed effect, direct breed effect, maternal heterosis, etc. All comparisons must take place within contemporary groups Contemporary group definition is key Review Contemporary Groups Formed to evaluate animals that have been in similar environmental conditions Herd Year Recording date Management Location (including different pastures) All comparisons used to calculate EPDs, breed differences, and heterosis take place within contemporary groups Review Contemporary Groups Some of the factors in contemporary groups are intuitive year, season, herd Want to be sure that environmental factors are not incorrectly attributed to genetics Pasture: grass quality differences, creep Weigh date: stomach contents (water, feed) Pen: bunk space, animal hierarchy 2

Review Contemporary Groups Desirable properties Reasonable size If herd is small try to make 1 group Compare as many animals as possible at once Weigh on the same date Multiple sires Always try to use more than one sire When only one sire is used, none of the progeny data contributes to that sire s EPD Generally, sires are our main goal in selection Contemporary Groups (CG) Desirable properties Connectedness especially when size is limited (e.g. due to pasture, etc. in definition) Bulls: 26 27 A B C C D E Bull C used both years Across Herd EPDs Across Herd EPDs Herd1 Herd 2 Herd 1 Herd 2 Sire A: 55 lb Sire D: 66 lb +1 Sire A: 55 lb Sire D: 66 lb +6 Sire B: 65 lb Sire E: 65 lb +8 Sire B: 62 lb Sire E: 64 lb -1 Sire C: 54 lb Sire F: 6 lb + Sire C: 54 lb Same Bull Sire C: 65 lb + Which sire is the best? Which sire is the best? Contemporary Groups In order to estimate breed differences from field data, we need contemporary groups that include purebreds of the same breed Rarely occurs; often breeds are in different groups Even when crossbreds and purebreds are in the same group, direct comparisons are not possible without adjusting for heterosis (requires good estimates of heterosis) Estimation of Heterosis In order to estimate heterosis from field data, we need groups with crossbreds and purebreds of both parental breeds Rarely occurs; usually crossbreds are in a different groups Even when crossbreds and purebreds are in the same group, typically purebreds of only one of the breeds are present 3

Estimating breed differences Contemporary group Sire 1: Limousin WW Avg: 65 lb Sire 2: Angus WW Avg: 675 lb Sire 3: Lim-Flex WW Avg: 67 lb All mated to mature purebred Limousin cows What was the cause of the different averages? Heterosis Sire breeding YES value (and no) Breed differences Estimating breed differences Problem can be improved with more sires in group still other considerations that are difficult to address Reciprocal matings Biased sampling of sires from other breeds Heterosis still difficult to separate from breed Were calves really treated the same? Multibreed model Prior estimates of breed effects and heterosis essentially required Source of information most likely from research data Published studies Current/ongoing projects Research Data as Prior Information Breed comparison research Too many studies to count None compare all breeds that we are interested in (minimum 2 x 2) Breed specific heterosis impossible to obtain from literature for most crosses Data has to be mined/combined from multiple studies Studies of combined data Williams et al. (28) Least squares means from studies published to Combined data by modeling fixed class effect (study) and percentage breed covariates Roughsedge et al. (21) Studies performed in 197s and 198s Weighted analysis for sire sampling 4

Roughsedge et al. (21) Weighing for sire sampling Amer et al. () SE( Xc) 1 2 2 3 2 2 2 2 h CV h CV + (1 h ) CV 4 + 4 n s n o n s is the number of sires sampled n a is the number of progeny per sire Weight in analysis was 1/SE(Xc) Studies of combined data Combined studies can be adjusted to account for information content These studies did not account for selection (genetic trend) in the breed May still work if base is adjusted to study periods, but relies on several assumptions Breeds effects are not a constant Adjusting data for trend Possible to rely on genetic trend in the model Assumes that relationships, genetic variances in the multibreed model are accurate and predict trend Want current breed differences Better to adjust study breed estimates Use current EPD of sampled bulls Adjusting sample for current EPD Across-breed EPD program Estimate breed differences from GPE using a sire and dam model (F 1 progeny records) Adjust records for bull EPD Bi = USMARC i / b + ( EPDi YY EPDi,, USMARC EPD i,yy is the breed average EPD (current) EPD i,usmarc weighted average USMARC sire EPD b is a scaling factor to convert USMARC solution to an industry scale ) SIRE BREEDS USED IN THE GERMPLASM EVALUATION PROGRAM AT THE USMARC Cycle I Cycle II Cycle III Cycle IV Cycle V Cycle VI Cycle VII Cycle VIII 7-72 73-74 75-76 86-9 92-94 97-98 99-1-2 F 1 Crosses (Hereford or Angus dams) a Hereford Hereford Hereford Hereford Hereford Hereford Hereford Hereford Angus Angus Angus Angus Angus Angus Angus Angus Jersey Red Poll Brahman Longhorn Tuli Wagyu Red Angus Beefmaster S. Devon Braunvieh Sahiwal Salers Boran Norweg. Red Limousin Brangus Limousin Gelbvieh Pinzgauer Galloway Belg. Blue Sw. Red&Wh. Charolais Bonsmara Simmental Maine Anj. Tarentaise Nellore Brahman Friesian Simmental Romosinuano Charolais Chianina Shorthorn Piedmontese Gelbvieh Piedmontese 3-way crosses Charolais Hereford Hereford Gelbvieh Angus Angus Pinzgauer Brahman Brangus Devon Santa Gertrudis Holstein a Sire breeds mated to Angus and Hereford females, and Composite MARC III (1/4 Angus, Hereford, Red Poll and Pinzgauer) cows in Cycles V, VI, VII and VIII. MARC III Cows 12 1 8 6 4 2-2 -4 Genetic Trends for Birth Weight, lb 198 199 Adapted from Spring 29 Genetic Trends from Breed Associations and 211 AB-EPD factors 2 22 24 26 28 5

7 6 5 4 3 2 1-1 -2 Genetic Trends for Weaning Weight, lb 198 199 2 22 24 26 28 1 75 5 25-25 Genetic Trends for Yearling Weight, lb 198 199 2 22 24 26 28 Adapted from Spring 29 Genetic Trends from Breed Associations and 211 AB-EPD factors Adapted from Spring 29 Genetic Trends from Breed Associations and 211 AB-EPD factors 3 25 2 15 1 5-5 -1-15 Genetic Trends for Maternal Milk, lb 199 2 22 24 26 28 Genetic Trends for Yearling Weight, lb 1 75 Diff = 38 lb 5 Diff =.4 lb 25 Diff = 61 lb -25 198 199 2 22 24 26 28 Adapted from Spring 29 Genetic Trends from Breed Associations and 211 AB-EPD factors Angus Simmental Adapted from Spring 29 Genetic Trends from Breed Associations and 211 AB-EPD factors GPE Target Population Structure AI Sires: AN, HH, SM, CH, AR, LM, GV, SH, BN, BM, MA, BR, CI, SG, SA, BV PB & F 1 Steers PB & F 1 Bulls Dams: AN, HH, SM, CH, AR, LM, GV, SH, BN, BM, MA, BR, CI, SG, SA, BV PB & F 1 Heifers Current breed differences Underlies need for continued research for breed differences USMARC GPE not enough More to the country than central Nebraska Southern location most important Use of common sires between locations will strengthen overall power Natural Service PB, F 1, & F 1 2 Steers & Heifers 6

2, bull project predictions Whole genome selection pilot project in cooperation with breed associations Over 2, industry bulls genotyped with Illumina BovineSNP5 Formed prediction equations using USMARC GPE data as well as deregressed EPDs from the 2,+ bulls Proportion of variance explained Proportion of Variance Explained by MBV.2.16.12.8.4. BWT WWT YWT RIB MRB HCW MARC-trained.134.38.96.68.53.81 2 Bull-trained.168.12.66.68.48 *2, bull predictions excluded the sires of the MARC validation populations 2 Bulls MBV Resulting MBV are being sent to breed associations today Sent by Mark Thallman Contact us with any questions Prediction Equations Equations are available at: https://www.ars.usda.gov/sp2userfiles/place/ 543851/2 Bull Prediction Equations.xlsx Link from www.marc.usda.gov -> Genetics & Breeding -> Documents Special thanks to Kristina Weber Questions 7