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Research Article| Volume 98, ISSUE 5, P3508-3513, May 2015

Short communication: Improving accuracy of Jersey genomic evaluations in the United States and Denmark by sharing reference population bulls1

Open ArchivePublished:March 12, 2015DOI:https://doi.org/10.3168/jds.2014-8874
Short communication: Improving accuracy of Jersey genomic evaluations in the United States and Denmark by sharing reference population bulls1
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      Abstract

      The effect on prediction accuracy for Jersey genomic evaluations of Danish and US bulls from using a larger reference population was assessed. Each country contributed genotypes from 1,157 Jersey bulls to the reference population of the other. Data were separated into reference (US only, Danish only, and combined US–Danish) and validation (US only and Danish only) populations. Depending on trait (milk, fat, and protein yields and component percentages; productive life; somatic cell score; daughter pregnancy rate; 14 conformation traits; and net merit), the US reference population included 2,720 to 4,772 bulls and cows with traditional evaluations as of August 2009; the Danish reference population included 635 to 996 bulls. The US validation population included 442 to 712 bulls that gained a traditional evaluation between August 2009 and December 2013; the Danish validation population included 105 to 196 bulls with multitrait across-country evaluations on the US scale by December 2013. Genomic predicted transmitting abilities (GPTA) were calculated on the US scale using a selection index that combined direct genomic predictions with either traditional predicted transmitting ability for the reference population or traditional parent averages (PA) for the validation population and a traditional evaluation based only on genotyped animals. Reliability for GPTA was estimated from the reference population and August 2009 traditional PA and PA reliability. For prediction of December 2013 deregressed daughter deviations on the US scale, mean August 2009 GPTA reliability for Danish validation bulls was 0.10 higher when based on the combined US–Danish reference population than when the reference population included only Danish bulls; for US validation bulls, mean reliability increased by 0.02 when Danish bulls were added to the US reference population. Exchanging genotype data to increase the size of the reference population is an efficient approach to increasing the accuracy of genomic prediction when the reference population is small.

      Key words

      Short Communication

      An important factor that affects the accuracy of genomic evaluations is the size of the reference population (
      • Daetwyler H.D.
      • Villanueva B.
      • Woolliams J.A.
      Accuracy of predicting the genetic risk of disease using a genome-wide approach.
      PLoS ONE. 2008; 3: e3395
      ;
      • Goddard M.
      Genomic selection: Prediction of accuracy and maximisation of long term response.
      Genetica. 2009; 136: 245-257
      ). In dairy cattle, reference populations are composed primarily of progeny-tested bulls because they have reliable phenotypic information from a large group of daughters. However, for a single country and for breeds other than Holstein, the number of progeny-tested bulls may be too small to achieve reliabilities for genomic evaluations near those for Holsteins. One effective approach to increase the size of the reference population has been to share animal genotypes (
      • Schenkel F.S.
      • Sargolzaei M.
      • Kistemaker G.
      • Jansen G.B.
      • Sullivan P.
      • Van Doormaal B.J.
      • VanRaden P.M.
      • Wiggans G.R.
      Reliability of genomic evaluation of Holstein cattle in Canada.
      Interbull Bull. 2009; 39: 51-58
      ;
      • VanRaden P.M.
      • Van Tassell C.P.
      • Wiggans G.R.
      • Sonstegard T.S.
      • Schnabel R.D.
      • Taylor J.F.
      • Schenkel F.
      Genomic data and cooperation result in faster progress.
      ICAR Tech. Ser. 2009; 13 (a): 341-346
      ,
      • VanRaden P.M.
      • Wiggans G.R.
      • Van Tassell C.P.
      • Sonstegard T.S.
      • Schenkel F.
      Benefits from cooperation in genomics.
      Interbull Bull. 2009; 39 (c): 67-72
      ;
      • Jorjani H.
      • Jakobsen J.
      • Nilforooshan M.A.
      • Hjerpe E.
      • Zumbach B.
      • Palucci V.
      • Dürr J.
      Genomic evaluation of BSW populations, InterGenomics: Results and deliverables.
      Interbull Bull. 2011; 43: 5-8
      ;
      • Lund M.S.
      • de Roos A.P.W.
      • de Vries A.G.
      • Druet T.
      • Ducrocq V.
      • Fritz S.
      • Guillaume F.
      • Guldbrandtsen B.
      • Liu Z.
      • Reents R.
      • Schrooten C.
      • Seefried F.
      • Su G.
      A common reference population from four European Holstein populations increases reliability of genomic predictions.
      Genet. Sel. Evol. 2011; 43: 43
      ;
      • VanRaden P.M.
      • Olson K.M.
      • Null D.J.
      • Sargolzaei M.
      • Winters M.
      • van Kaam J.B.C.H.M.
      Reliability increases from combining 50,000- and 777,000-marker genotypes from four countries.
      Interbull Bull. 2012; 46: 75-79
      ;
      • Zhou L.
      • Ding X.
      • Zhang Q.
      • Wang Y.
      • Lund M.S.
      • Su G.
      Consistency of linkage disequilibrium between Chinese and Nordic Holsteins and genomic prediction for Chinese Holsteins using a joint reference population.
      Genet. Sel. Evol. 2013; 45: 7
      ;
      • Lund M.S.
      • Su G.
      • Janss L.
      • Guldbrandtsen B.
      • Brøndum R.F.
      Genomic evaluation of cattle in a multi-breed context.
      Livest. Sci. 2014; 166: 101-110
      ). Canada and the United States have shared genotypes for all dairy cattle breeds since 2007 (
      • Wiggans G.R.
      • Sonstegard T.S.
      • VanRaden P.M.
      • Matukumalli L.K.
      • Schnabel R.D.
      • Taylor J.F.
      • Chesnais J.P.
      • Schenkel F.S.
      • Van Tassell C.P.
      Genomic evaluations in the United States and Canada: A collaboration.
      ICAR Tech. Ser. 2009; 13: 347-353
      ). Since then, those North American collaborators have also shared Holstein genotypes with the United Kingdom and Italy (
      • VanRaden P.M.
      • Olson K.M.
      • Null D.J.
      • Sargolzaei M.
      • Winters M.
      • van Kaam J.B.C.H.M.
      Reliability increases from combining 50,000- and 777,000-marker genotypes from four countries.
      Interbull Bull. 2012; 46: 75-79
      ) and Brown Swiss genotypes with Germany, Austria, and Switzerland (

      Wiggans, G. R., T. A. Cooper, P. M. VanRaden, and M. V. Silva. 2010a. Increased reliability of genetic evaluations for dairy cattle in the United States from use of genomic information. Proc. 9th World Congr. Genet. Appl. Livest. Prod., Leipzig, Germany, Comm. 0476. Gesellschaft für Tierzuchtwissenschaften e. V., Gießen, Germany. Accessed Jan. 28, 2015. http://www.kongressband.de/wcgalp2010/assets/pdf/0476.pdf

      ,
      • Wiggans G.R.
      • VanRaden P.M.
      • Cooper T.A.
      The genomic evaluation system in the United States: Past, present, future.
      J. Dairy Sci. 2011; 94: 3202-3211
      ) and later with other Interbull participants through the InterGenomics project (
      • Jorjani H.
      • Jakobsen J.
      • Nilforooshan M.A.
      • Hjerpe E.
      • Zumbach B.
      • Palucci V.
      • Dürr J.
      Genomic evaluation of BSW populations, InterGenomics: Results and deliverables.
      Interbull Bull. 2011; 43: 5-8
      ). EuroGenomics was formed to facilitate sharing Holstein genotypes for predictor populations among European partners (
      • Lund M.S.
      • de Roos A.P.W.
      • de Vries A.G.
      • Druet T.
      • Ducrocq V.
      • Fritz S.
      • Guillaume F.
      • Guldbrandtsen B.
      • Liu Z.
      • Reents R.
      • Schrooten C.
      • Seefried F.
      • Su G.
      A common reference population from four European Holstein populations increases reliability of genomic predictions.
      Genet. Sel. Evol. 2011; 43: 43
      ).
      Danish Jersey is a small dairy cattle population. Only about 1,200 to 1,400 progeny-tested bulls (depending on trait) are used as a reference population for genomic evaluation (

      Su, G., U. S. Nielsen, G. Wiggans, G. P. Aamand, B. Guldbrandtsen, and M. S. Lund. 2014. Improving genomic prediction for Danish Jersey using a joint Danish-US reference population. Proc. 10th World Congr. Genet. Appl. Livest. Prod., Vancouver, BC, Canada, Comm. 060. Accessed Jan. 28, 2015. https://asas.org/docs/default-source/wcgalp-proceedings-oral/060_paper_8823_manuscript_396_0.pdf

      ). Because of the small size of the reference population, accuracy of genomic prediction for Danish Jerseys (
      • Thomasen J.R.
      • Guldbrandtsen B.
      • Su G.
      • Brøndum R.F.
      • Lund M.S.
      Reliabilities of genomic estimated breeding values in Danish Jersey.
      Animal. 2012; 6: 789-796
      ) is much lower than that for Danish Holstein (
      • Su G.
      • Guldbrandtsen B.
      • Gregersen V.R.
      • Lund M.S.
      Preliminary investigation on reliability of genomic estimated breeding values in the Danish Holstein population.
      J. Dairy Sci. 2010; 93: 1175-1183
      ) and Nordic Red Cattle populations (
      • Su G.
      • Madsen P.
      • Nielsen U.S.
      • Mäntysaari E.A.
      • Aamand G.P.
      • Christensen O.F.
      • Lund M.S.
      Genomic prediction for Nordic Red Cattle using one-step and selection index blending.
      J. Dairy Sci. 2012; 95: 909-917
      ). At the beginning of December 2013, the reference population in the United States for predicting Jersey SNP effects included 3,041 bulls and 15,662 cows from the United States and Canada, which is substantially smaller than the corresponding Holstein reference population (24,547 bulls and 60,658 cows). Later in December 2013, genotypes for Jersey bulls were exchanged between Denmark, the United States, and Canada to create larger reference populations for genomic prediction in each country (
      • Wiggans G.R.
      • Cooper T.A.
      • VanRaden P.M.
      • Null D.J.
      • Hutchison J.L.
      • Meland O.M.
      • Tooker M.E.
      • Norman H.D.
      Calculation and delivery of US genomic evaluations for dairy cattle.
      J. Dairy Sci. 2014; 92 (b (Abstr.)): 77-78
      ). The objective of this study was to determine the effect on prediction accuracy of US and Danish genomic evaluations for performance on the US scale from using the larger Jersey reference population.
      The United States and Denmark contributed genotypes from 1,157 Jersey bulls to the reference population of the other. Jersey bulls and cows with genotypes in the US genomic database had been genotyped with the Illumina BovineSNP50 (SNP50;

      Illumina Inc. 2011a. BovineSNP50 Genotyping BeadChip. Accessed Jan. 28, 2015. http://res.illumina.com/documents/products/datasheets/datasheet_bovine_snp5o.pdf

      ), Illumina Bovine3K (

      Illumina Inc. 2011b. GoldenGate Bovine3K Genotyping BeadChip. Accessed Jan. 28, 2015. http://support.illumina.com/content/dam/illumina-marketing/documents/products/datasheets/datasheet_bovine3k.pdf

      ), Illumina BovineHD (

      Illumina Inc. 2010. BovineHD Genotyping BeadChip. Accessed Jan. 28, 2015. http://res.illumina.com/documents/products/datasheets/datasheet_bovinehd.pdf

      ), Illumina BovineLD (

      Illumina Inc. 2013. BovineLD v1.1 Genotyping BeadChip. Accessed Jan. 28, 2015. http://res.illumina.com/documents/products/datasheets/datasheet_bovineld.pdf

      ), GeneSeek Genomic Profiler (versions 1 and 2;

      Neogen Corporation. 2013a. GeneSeek Genomic Profiler for dairy cattle. Accessed Jan. 28, 2015. http://www.neogen.com/Agrigenomics/pdf/Slicks/GGP-LD_Dairy.pdf

      ), or GeneSeek Genomic Profiler HD (

      Neogen Corporation. 2013b. GeneSeek Genomic Profiler HD for dairy cattle. Accessed Jan. 28, 2015. http://www.neogen.com/Agrigenomics/pdf/Slicks/GGP_HD_Dairy.pdf

      ) BeadChips; Danish Jersey bulls had been genotyped with the SNP50 chip. All genotypes were imputed using the findhap.f90 program (

      VanRaden, P. M. 2015. findhap.f90, Find haplotypes and impute genotypes using multiple chip sets and sequence data. Accessed Feb. 20, 2015. http://aipl.arsusda.gov/software/findhap/

      ) to the common set of 61,013 SNP (45,195 from the SNP50 chip plus 15,818 from the GeneSeek Genomic Profiler HD chip) described by

      Wiggans, G. R., T. A. Cooper, D. J. Null, and P. M. VanRaden. 2014a. Increasing the number of single nucleotide polymorphisms used in genomic evaluations of dairy cattle. Proc. 10th World Congr. Genet. Appl. Livest. Prod., Vancouver, Canada, Comm. 301. Accessed Jan. 28, 2015. https://asas.org/docs/default-source/wcgalp-proceedings-oral/301_paper_9522_manuscript_742_0.pdf

      ). That SNP set had been chosen based on SNP performance criteria such as minor allele frequency, parent-progeny conflicts, call rate, and correlation with other SNP (
      • Wiggans G.R.
      • VanRaden P.M.
      • Bacheller L.R.
      • Tooker M.E.
      • Hutchison J.L.
      • Cooper T.A.
      • Sonstegard T.S.
      Selection and management of DNA markers for use in genomic evaluation.
      J. Dairy Sci. 2010; 93 (b): 2287-2292
      ,

      Wiggans, G. R., T. A. Cooper, D. J. Null, and P. M. VanRaden. 2014a. Increasing the number of single nucleotide polymorphisms used in genomic evaluations of dairy cattle. Proc. 10th World Congr. Genet. Appl. Livest. Prod., Vancouver, Canada, Comm. 301. Accessed Jan. 28, 2015. https://asas.org/docs/default-source/wcgalp-proceedings-oral/301_paper_9522_manuscript_742_0.pdf

      ).
      The data were separated into reference and validation populations based on the availability of a traditional evaluation as of August 2009 (Table 1). Not all bulls with exchanged genotypes had a traditional evaluation as of August 2009. Depending on trait (milk, fat, and protein yields and component percentages; productive life; SCS; daughter pregnancy rate; 14 conformation traits; and net merit), the US reference population included 2,720 to 4,772 bulls and cows with traditional evaluations as of August 2009; the Danish reference population included 635 to 996 bulls. The US validation population included 442 to 712 bulls (depending on trait) that gained a traditional evaluation between August 2009 and December 2013 and had ≥10 daughters; the Danish validation population included 105 to 196 bulls with multitrait across-country evaluations from the Interbull Centre (Uppsala, Sweden) on the US scale by December 2013 and daughters in ≥10 herds.
      Table 1Numbers of Jersey bulls and cows in the US, Danish, and combined US–Danish reference populations and numbers of Jersey bulls in the US and Danish validation populations by trait
      TraitReference populationValidation population
      USDanishUS–DanishUSDanish
      Milk yield4,7729965,768712196
      Fat yield4,7729965,768712196
      Protein yield4,7589965,754712196
      Fat percentage4,7729965,768712196
      Protein percentage4,7589965,754712196
      Productive life2,7209823,702712181
      SCS4,6969755,671712196
      Daughter pregnancy rate3,2049884,192672196
      Final score4,2349655,199607105
      Stature4,2349825,216608196
      Strength4,2339835,216608196
      Dairy form4,2369815,217606196
      Foot angle4,2229805,202608187
      Rear legs (side view)4,2169835,199600196
      Rump angle4,2299835,212608196
      Rump width4,2339825,215605178
      Fore udder attachment4,3799835,362682196
      Rear udder height4,2546354,889593196
      Udder depth4,4329815,413442196
      Udder cleft4,2309835,213608196
      Front teat placement4,2349835,217607196
      Teat length4,2359815,216605196
      Net merit index4,7879925,779670196
      Genomic predictions were calculated using an algorithm that solved directly for marker effects using the Bayes A approximation of
      • VanRaden P.M.
      Efficient methods to compute genomic predictions.
      J. Dairy Sci. 2008; 91: 4414-4423
      ). The dependent variable for analysis was the deregressed daughter deviation, where the deregression factor was computed from total daughter equivalents minus daughter equivalents from parent average (PA;
      • VanRaden P.M.
      • Van Tassell C.P.
      • Wiggans G.R.
      • Sonstegard T.S.
      • Schnabel R.D.
      • Taylor J.F.
      • Schenkel F.
      Invited review: Reliability of genomic predictions for North American Holstein bulls.
      J. Dairy Sci. 2009; 92 (b): 16-24
      ). The SNP accounted for 90% of total additive genetic variance; 10% was assigned to residual additive genetic variance. Genomic PTA (GPTA) were calculated using a selection index that combined direct genomic predictions with either traditional PTA for the reference population or traditional PA for the validation population and a traditional evaluation based on only genotyped animals (
      • VanRaden P.M.
      • Van Tassell C.P.
      • Wiggans G.R.
      • Sonstegard T.S.
      • Schnabel R.D.
      • Taylor J.F.
      • Schenkel F.
      Invited review: Reliability of genomic predictions for North American Holstein bulls.
      J. Dairy Sci. 2009; 92 (b): 16-24
      ). Maximum weights for the direct genomic predictions were limited to 0.80 for yield traits, 0.85 for health and fertility traits, and 0.90 for type traits to improve regression of later performance on earlier prediction.
      Following
      • VanRaden P.M.
      • Van Tassell C.P.
      • Wiggans G.R.
      • Sonstegard T.S.
      • Schnabel R.D.
      • Taylor J.F.
      • Schenkel F.
      Invited review: Reliability of genomic predictions for North American Holstein bulls.
      J. Dairy Sci. 2009; 92 (b): 16-24
      ), genomic reliabilities were calculated from coefficients of determination for 2013 daughter deviations with 2009 predictions after adjusting for error variance in the daughter deviations and for prior selection on pedigree. Coefficients for regression of December 2013 daughter deviations on August 2009 GPTA (
      • VanRaden P.M.
      Efficient methods to compute genomic predictions.
      J. Dairy Sci. 2008; 91: 4414-4423
      ) were also calculated.
      The addition of Danish bulls to the US reference population changed the mean coefficient for regression of deregressed daughter deviations on GPTA only slightly (from 0.94 to 0.95) for the US validation population (Table 2); deviation from the expected value of 1.00 increased from 0.10 to 0.11. However, the addition of US bulls to the Danish reference population reduced the mean regression coefficient for the Danish validation population from 1.11 to 1.06 and the deviation from expected from 0.29 to 0.19.
      Table 2Coefficients for regression of December 2013 deregressed daughter deviations on August 2009 genomic PTA of US and Danish validation bulls on the US scale by reference (Ref) and validation (Val) populations and trait
      TraitRegression coefficient
      Ref: USRef: DanishRef: Combined US–Danish
      Val: USVal: DanishVal: USVal: Danish
      Milk yield0.810.960.811.00
      Fat yield0.820.410.820.61
      Protein yield0.750.570.750.69
      Fat percentage1.051.061.051.11
      Protein percentage1.001.170.991.17
      Productive life1.121.571.101.15
      SCS0.891.700.921.35
      Daughter pregnancy rate0.991.450.981.21
      Final score0.861.450.850.98
      Stature0.951.020.910.97
      Strength0.901.290.870.77
      Dairy form0.741.320.761.17
      Foot angle1.030.651.030.74
      Rear legs (side view)1.221.481.221.27
      Rump angle1.061.051.081.18
      Rump width0.891.190.861.02
      Fore udder attachment1.030.871.031.23
      Rear udder height0.830.760.830.89
      Udder depth1.071.151.091.35
      Udder cleft0.981.321.001.33
      Front teat placement0.981.181.011.15
      Teat length0.850.880.870.90
      Mean0.941.110.951.06
      For August 2009 evaluations of US validation bulls, reliability for traditional PA ranged from 0.23 (udder depth) to 0.39 (milk, fat, and protein yields and fat and protein percentages), with a mean of 0.33 across traits (Table 3). Reliabilities of GPTA for those bulls based on the US reference population ranged from 0.37 [rear legs (side view)] to 0.73 (fat percentage) and averaged 0.51, which was much higher than the mean reliability for PA (0.18). For individual traits, the largest reliability gain for GPTA compared with PA was 0.34 for fat percentage, and the smallest gain was 0.09 for rear legs (side view). The addition of Danish Jerseys to the US reference population increased mean GPTA reliability by 0.02; the magnitude of genomic reliability differences for individual traits generally was ≤0.02, with the exception of a reliability gain of 0.03 for daughter pregnancy rate and rump angle; 0.04 for SCS, rear legs (side view), udder depth, and front teat placement; and 0.05 for teat length.
      Table 3Reliabilities (REL) of traditional parent average (PA) and genomic PTA (GPTA) of US and Danish validation bulls from predictions on the US scale by reference (Ref) and validation (Val) populations and trait
      TraitPA RELGPTA REL
      Ref: —Ref: —Ref: USRef: DanishRef: Combined US–Danish
      Val: USVal: DanishVal: USVal: DanishVal: USVal: Danish
      Milk yield0.390.300.590.500.600.67
      Fat yield0.390.300.550.370.560.51
      Protein yield0.390.300.540.380.550.53
      Fat percentage0.390.300.730.700.740.80
      Protein percentage0.390.300.690.690.710.78
      Productive life0.290.220.540.350.530.35
      SCS0.350.250.510.440.550.51
      Daughter pregnancy rate0.300.250.440.460.470.43
      Final score0.310.180.420.430.420.41
      Stature0.350.280.580.490.590.59
      Strength0.330.240.490.470.490.35
      Dairy form0.330.240.500.340.520.56
      Foot angle0.300.210.500.230.510.29
      Rear legs (side view)0.280.250.370.420.410.47
      Rump angle0.320.270.460.420.490.55
      Rump width0.320.200.480.370.470.45
      Fore udder attachment0.250.240.470.370.480.63
      Rear udder height0.320.240.470.270.490.41
      Udder depth0.230.280.510.460.550.74
      Udder cleft0.310.240.410.390.410.49
      Front teat placement0.320.270.510.460.550.63
      Teat length0.320.290.480.430.530.51
      Mean0.330.260.510.430.530.53
      For August 2009 evaluations of Danish validation bulls on the US scale (Table 3), reliability for traditional PA ranged from 0.18 (final score) to 0.30 (yield and component traits), with a mean of 0.26 across traits. Reliabilities of GPTA for those bulls based on the Danish reference population ranged from 0.23 (foot angle) to 0.70 (fat percentage) and averaged 0.43, which again was much higher than the mean reliability for PA (0.17). For individual traits, the largest reliability gain for GPTA compared with PA was 0.40 for fat percentage, and the smallest gain was 0.02 for foot angle. The addition of US Jerseys to the Danish reference population increased mean GPTA reliability by 0.10 for Danish validation bulls. Most traits had reliability gains [0.05 for rear legs (side view) to 0.28 for udder depth], productive life had no gain, and 3 traits had losses (0.02 for final score, 0.03 for daughter pregnancy rate, and 0.12 for strength). The reliability gain for GPTA on the Danish scale that was observed in Denmark after the exchange of US and Danish Jersey bull genotypes was lower than that shown in Table 3 for performance on the US scale and using a combined US–Danish reference population that included all US bulls and cows.

      Su, G., U. S. Nielsen, G. Wiggans, G. P. Aamand, B. Guldbrandtsen, and M. S. Lund. 2014. Improving genomic prediction for Danish Jersey using a joint Danish-US reference population. Proc. 10th World Congr. Genet. Appl. Livest. Prod., Vancouver, BC, Canada, Comm. 060. Accessed Jan. 28, 2015. https://asas.org/docs/default-source/wcgalp-proceedings-oral/060_paper_8823_manuscript_396_0.pdf

      ) reported gains from 0.016 (fertility) to 0.125 (udder conformation) in genomic reliability over traditional PA when US Jersey bulls were added to the Danish reference population; only longevity had a reliability loss (0.056), and mean change in reliability over all traits was 0.040.
      The substantial gain in reliability for Danish GPTA on the US scale after combining the US and Danish reference populations was likely the result of several factors. The Danish reference population was much smaller than the US reference population and, therefore, affected more by the addition of many new reference animals. The validation bulls selected may also have affected reliability gains. Although the number of Danish validation bulls was much smaller than the number of US validation bulls, the Danish bulls were required to have daughters in ≥10 herds, whereas the US bulls were only required to have ≥10 daughters.
      In January 2014, SNP50 genotypes for 1,168 progeny-tested Danish Jersey bulls that were provided by VikingGenetics (Randers, Denmark) were used in US monthly GPTA updates (

      Cooper, T., G. Wiggans, P. VanRaden, and D. Null. 2014. Changes to monthly genomic evaluations (January 2014). Inclusion of Danish Jersey genotypes. Accessed Jan. 28, 2015. https://www.cdcb.us/reference/changes/eval1401.htm

      ). Correlations between GPTA for young animals with or without Danish genotypes included in the reference population were near 0.99 for most yield and type traits but slightly lower (0.97–0.98) for the less-heritable fitness traits. For all Jersey traits, US means and standard deviations for January 2014 GPTA changed little with the inclusion of Danish genotypes.
      The exchange of 1,157 Jersey bulls doubled the size of the Danish Jersey reference population, led to a large improvement in accuracy of genomic prediction for Danish Jerseys on the US scale, and had a smaller effect for US Jerseys. Exchanging genotype data to increase the size of the reference population is an efficient approach to increasing the accuracy of genomic prediction when the reference population is small.

      Acknowledgments

      The cooperation of the Council on Dairy Cattle Breeding (Reynoldsburg, OH) in supplying North American pedigree, performance, and genotypic data is acknowledged. The Danish study was a Green Development and Demonstration Programme project (grant 3405-10-0137). Nordic Cattle Genetic Evaluation (Aarhus, Denmark) and VikingGenetics (Randers, Denmark) are acknowledged for providing data. The assistance of S. M. Hubbard (Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD) in literature review and technical editing is acknowledged. The assistance of one anonymous reviewer in detecting an error in the analysis is gratefully acknowledged.

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      Article info

      Publication history

      Published online: March 12, 2015
      Accepted: January 30, 2015
      Received: September 18, 2014

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      DOI: https://doi.org/10.3168/jds.2014-8874

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      © 2015 American Dairy Science Association. Published by Elsevier Inc.

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