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Items: 1 to 50 of 151

1.

Genetic parameters for atypical reproductive patterns in dairy cows estimated from in-line milk progesterone profiles.

van Binsbergen R, Bouwman AC, Veerkamp RF.

J Dairy Sci. 2019 Oct 9. pii: S0022-0302(19)30890-2. doi: 10.3168/jds.2019-16348. [Epub ahead of print]

PMID:
31606217
2.

Inbreeding depression due to recent and ancient inbreeding in Dutch Holstein-Friesian dairy cattle.

Doekes HP, Veerkamp RF, Bijma P, de Jong G, Hiemstra SJ, Windig JJ.

Genet Sel Evol. 2019 Sep 27;51(1):54. doi: 10.1186/s12711-019-0497-z.

3.

Comparing regression, naive Bayes, and random forest methods in the prediction of individual survival to second lactation in Holstein cattle.

van der Heide EMM, Veerkamp RF, van Pelt ML, Kamphuis C, Athanasiadis I, Ducro BJ.

J Dairy Sci. 2019 Oct;102(10):9409-9421. doi: 10.3168/jds.2019-16295. Epub 2019 Aug 22.

4.

Invited review: Determination of large-scale individual dry matter intake phenotypes in dairy cattle.

Seymour DJ, Cánovas A, Baes CF, Chud TCS, Osborne VR, Cant JP, Brito LF, Gredler-Grandl B, Finocchiaro R, Veerkamp RF, de Haas Y, Miglior F.

J Dairy Sci. 2019 Sep;102(9):7655-7663. doi: 10.3168/jds.2019-16454. Epub 2019 Jun 27.

PMID:
31255263
5.

Significance testing and genomic inflation factor using high-density genotypes or whole-genome sequence data.

van den Berg S, Vandenplas J, van Eeuwijk FA, Lopes MS, Veerkamp RF.

J Anim Breed Genet. 2019 Jun 19. doi: 10.1111/jbg.12419. [Epub ahead of print]

PMID:
31215703
6.

Imputation to whole-genome sequence using multiple pig populations and its use in genome-wide association studies.

van den Berg S, Vandenplas J, van Eeuwijk FA, Bouwman AC, Lopes MS, Veerkamp RF.

Genet Sel Evol. 2019 Jan 24;51(1):2. doi: 10.1186/s12711-019-0445-y.

7.

Genomic prediction for numerically small breeds, using models with pre-selected and differentially weighted markers.

Raymond B, Bouwman AC, Wientjes YCJ, Schrooten C, Houwing-Duistermaat J, Veerkamp RF.

Genet Sel Evol. 2018 Oct 10;50(1):49. doi: 10.1186/s12711-018-0419-5.

8.

Prediction of slaughter age in pigs and assessment of the predictive value of phenotypic and genetic information using random forest.

Alsahaf A, Azzopardi G, Ducro B, Hanenberg E, Veerkamp RF, Petkov N.

J Anim Sci. 2018 Dec 3;96(12):4935-4943. doi: 10.1093/jas/sky359.

PMID:
30239725
9.

Value of the Dutch Holstein Friesian germplasm collection to increase genetic variability and improve genetic merit.

Doekes HP, Veerkamp RF, Bijma P, Hiemstra SJ, Windig J.

J Dairy Sci. 2018 Nov;101(11):10022-10033. doi: 10.3168/jds.2018-15217. Epub 2018 Sep 13.

10.

Utility of whole-genome sequence data for across-breed genomic prediction.

Raymond B, Bouwman AC, Schrooten C, Houwing-Duistermaat J, Veerkamp RF.

Genet Sel Evol. 2018 May 18;50(1):27. doi: 10.1186/s12711-018-0396-8.

11.

Genetic covariance components within and among linear type traits differ among contrasting beef cattle breeds.

Doyle JL, Berry DP, Walsh SW, Veerkamp RF, Evans RD, Carthy TR.

J Anim Sci. 2018 May 4;96(5):1628-1639. doi: 10.1093/jas/sky076.

12.

Trends in genome-wide and region-specific genetic diversity in the Dutch-Flemish Holstein-Friesian breeding program from 1986 to 2015.

Doekes HP, Veerkamp RF, Bijma P, Hiemstra SJ, Windig JJ.

Genet Sel Evol. 2018 Apr 11;50(1):15. doi: 10.1186/s12711-018-0385-y.

13.

Improving accuracy of bulls' predicted genomic breeding values for fertility using daughters' milk progesterone profiles.

Tenghe AMM, Bouwman AC, Berglund B, de Koning DJ, Veerkamp RF.

J Dairy Sci. 2018 Jun;101(6):5177-5193. doi: 10.3168/jds.2016-12304. Epub 2018 Mar 7.

14.

Meta-analysis of genome-wide association studies for cattle stature identifies common genes that regulate body size in mammals.

Bouwman AC, Daetwyler HD, Chamberlain AJ, Ponce CH, Sargolzaei M, Schenkel FS, Sahana G, Govignon-Gion A, Boitard S, Dolezal M, Pausch H, Brøndum RF, Bowman PJ, Thomsen B, Guldbrandtsen B, Lund MS, Servin B, Garrick DJ, Reecy J, Vilkki J, Bagnato A, Wang M, Hoff JL, Schnabel RD, Taylor JF, Vinkhuyzen AAE, Panitz F, Bendixen C, Holm LE, Gredler B, Hozé C, Boussaha M, Sanchez MP, Rocha D, Capitan A, Tribout T, Barbat A, Croiseau P, Drögemüller C, Jagannathan V, Vander Jagt C, Crowley JJ, Bieber A, Purfield DC, Berry DP, Emmerling R, Götz KU, Frischknecht M, Russ I, Sölkner J, Van Tassell CP, Fries R, Stothard P, Veerkamp RF, Boichard D, Goddard ME, Hayes BJ.

Nat Genet. 2018 Mar;50(3):362-367. doi: 10.1038/s41588-018-0056-5. Epub 2018 Feb 19.

PMID:
29459679
15.

Genome-wide association analyses based on a multiple-trait approach for modeling feed efficiency.

Lu Y, Vandehaar MJ, Spurlock DM, Weigel KA, Armentano LE, Connor EE, Coffey M, Veerkamp RF, de Haas Y, Staples CR, Wang Z, Hanigan MD, Tempelman RJ.

J Dairy Sci. 2018 Apr;101(4):3140-3154. doi: 10.3168/jds.2017-13364. Epub 2018 Feb 1.

16.

Adjusting for heterogeneity of experimental data in genetic evaluation of dry matter intake in dairy cattle.

Uddin ME, Meuwissen T, Veerkamp RF.

J Anim Breed Genet. 2018 Feb;135(1):28-36. doi: 10.1111/jbg.12300. Epub 2017 Nov 20.

PMID:
29152841
17.

Accuracies of breeding values for dry matter intake using nongenotyped animals and predictor traits in different lactations.

Manzanilla-Pech CIV, Veerkamp RF, de Haas Y, Calus MPL, Ten Napel J.

J Dairy Sci. 2017 Nov;100(11):9103-9114. doi: 10.3168/jds.2017-12741. Epub 2017 Aug 31.

18.

The genetic and biological basis of feed efficiency in mid-lactation Holstein dairy cows.

Hardie LC, VandeHaar MJ, Tempelman RJ, Weigel KA, Armentano LE, Wiggans GR, Veerkamp RF, de Haas Y, Coffey MP, Connor EE, Hanigan MD, Staples C, Wang Z, Dekkers JCM, Spurlock DM.

J Dairy Sci. 2017 Nov;100(11):9061-9075. doi: 10.3168/jds.2017-12604. Epub 2017 Aug 23.

19.

Validation of a mathematical model of the bovine estrous cycle for cows with different estrous cycle characteristics.

Boer HMT, Butler ST, Stötzel C, Te Pas MFW, Veerkamp RF, Woelders H.

Animal. 2017 Nov;11(11):1991-2001. doi: 10.1017/S175173111700026X. Epub 2017 Feb 15.

PMID:
28196547
20.

Use of genotype × environment interaction model to accommodate genetic heterogeneity for residual feed intake, dry matter intake, net energy in milk, and metabolic body weight in dairy cattle.

Yao C, de Los Campos G, VandeHaar MJ, Spurlock DM, Armentano LE, Coffey M, de Haas Y, Veerkamp RF, Staples CR, Connor EE, Wang Z, Hanigan MD, Tempelman RJ, Weigel KA.

J Dairy Sci. 2017 Mar;100(3):2007-2016. doi: 10.3168/jds.2016-11606. Epub 2017 Jan 18.

21.
22.

Opportunities for genomic prediction for fertility using endocrine and classical fertility traits in dairy cattle.

Tenghe AM, Berglund B, Wall E, Veerkamp RF, de Koning DJ.

J Anim Sci. 2016 Sep;94(9):3645-3654. doi: 10.2527/jas.2016-0555.

PMID:
27898905
23.

Genomewide association study of methane emissions in Angus beef cattle with validation in dairy cattle.

Manzanilla-Pech CI, De Haas Y, Hayes BJ, Veerkamp RF, Khansefid M, Donoghue KA, Arthur PF, Pryce JE.

J Anim Sci. 2016 Oct;94(10):4151-4166. doi: 10.2527/jas.2016-0431.

PMID:
27898855
24.

Modeling genetic and nongenetic variation of feed efficiency and its partial relationships between component traits as a function of management and environmental factors.

Lu Y, Vandehaar MJ, Spurlock DM, Weigel KA, Armentano LE, Staples CR, Connor EE, Wang Z, Coffey M, Veerkamp RF, de Haas Y, Tempelman RJ.

J Dairy Sci. 2017 Jan;100(1):412-427. doi: 10.3168/jds.2016-11491. Epub 2016 Nov 17.

25.

Genetic changes of survival traits over the past 25 yr in Dutch dairy cattle.

van Pelt ML, Ducrocq V, de Jong G, Calus MPL, Veerkamp RF.

J Dairy Sci. 2016 Dec;99(12):9810-9819. doi: 10.3168/jds.2016-11249. Epub 2016 Sep 28.

26.

Efficient genomic prediction based on whole-genome sequence data using split-and-merge Bayesian variable selection.

Calus MP, Bouwman AC, Schrooten C, Veerkamp RF.

Genet Sel Evol. 2016 Jun 29;48(1):49. doi: 10.1186/s12711-016-0225-x.

27.
28.

Validation of simultaneous deregression of cow and bull breeding values and derivation of appropriate weights.

Calus MPL, Vandenplas J, Ten Napel J, Veerkamp RF.

J Dairy Sci. 2016 Aug;99(8):6403-6419. doi: 10.3168/jds.2016-11028. Epub 2016 May 18.

29.

Genome-wide association study for endocrine fertility traits using single nucleotide polymorphism arrays and sequence variants in dairy cattle.

Tenghe AMM, Bouwman AC, Berglund B, Strandberg E, de Koning DJ, Veerkamp RF.

J Dairy Sci. 2016 Jul;99(7):5470-5485. doi: 10.3168/jds.2015-10533. Epub 2016 May 4.

30.

Corrigendum to "Genetic parameters between feed-intake-related traits and conformation in 2 separate dairy populations-the Netherlands and United States" (J. Dairy Sci. 99:443-457).

Manzanilla-Pech CIV, Veerkamp RF, Tempelman RJ, van Pelt ML, Weigel KA, VandeHaar M, Lawlor TJ, Spurlock DM, Armentano LE, Staples CR, Hanigan M, De Haas Y.

J Dairy Sci. 2016 May;99(5):4095. doi: 10.3168/jds.2016-99-5-4095. Epub 2016 Apr 20. No abstract available.

31.

An Equation to Predict the Accuracy of Genomic Values by Combining Data from Multiple Traits, Populations, or Environments.

Wientjes YC, Bijma P, Veerkamp RF, Calus MP.

Genetics. 2016 Feb;202(2):799-823. doi: 10.1534/genetics.115.183269. Epub 2015 Dec 4.

32.

Genetic parameters between feed-intake-related traits and conformation in 2 separate dairy populations--the Netherlands and United States.

Manzanilla-Pech CI, Veerkamp RF, Tempelman RJ, van Pelt ML, Weigel KA, VandeHaar M, Lawlor TJ, Spurlock DM, Armentano LE, Staples CR, Hanigan M, De Haas Y.

J Dairy Sci. 2016 Jan;99(1):443-57. doi: 10.3168/jds.2015-9727. Epub 2015 Nov 5.

33.

Predicting direct and indirect breeding values for survival time in laying hens using repeated measures.

Brinker T, Ellen ED, Veerkamp RF, Bijma P.

Genet Sel Evol. 2015 Sep 28;47:75. doi: 10.1186/s12711-015-0152-2.

34.

Genomic prediction using imputed whole-genome sequence data in Holstein Friesian cattle.

van Binsbergen R, Calus MP, Bink MC, van Eeuwijk FA, Schrooten C, Veerkamp RF.

Genet Sel Evol. 2015 Sep 17;47:71. doi: 10.1186/s12711-015-0149-x.

35.

Overlap in genomic variation associated with milk fat composition in Holstein Friesian and Dutch native dual-purpose breeds.

Maurice-Van Eijndhoven MH, Bovenhuis H, Veerkamp RF, Calus MP.

J Dairy Sci. 2015 Sep;98(9):6510-21. doi: 10.3168/jds.2014-9196. Epub 2015 Jul 15.

36.

Genomic prediction of dry matter intake in dairy cattle from an international data set consisting of research herds in Europe, North America, and Australasia.

de Haas Y, Pryce JE, Calus MP, Wall E, Berry DP, Løvendahl P, Krattenmacher N, Miglior F, Weigel K, Spurlock D, Macdonald KA, Hulsegge B, Veerkamp RF.

J Dairy Sci. 2015 Sep;98(9):6522-34. doi: 10.3168/jds.2014-9257. Epub 2015 Jul 15.

37.

Using selection index theory to estimate consistency of multi-locus linkage disequilibrium across populations.

Wientjes YC, Veerkamp RF, Calus MP.

BMC Genet. 2015 Jul 19;16:87. doi: 10.1186/s12863-015-0252-6.

38.

Evaluation of genomic selection for replacement strategies using selection index theory.

Calus MP, Bijma P, Veerkamp RF.

J Dairy Sci. 2015 Sep;98(9):6499-509. doi: 10.3168/jds.2014-9192. Epub 2015 Jul 2.

39.

Estimating genetic parameters for fertility in dairy cows from in-line milk progesterone profiles.

Tenghe AM, Bouwman AC, Berglund B, Strandberg E, Blom JY, Veerkamp RF.

J Dairy Sci. 2015 Aug;98(8):5763-73. doi: 10.3168/jds.2014-8732. Epub 2015 May 23.

40.

The Dutch national breeding programmes have developed to major globally operating companies.

ten Napel J, Veerkamp RF.

J Anim Breed Genet. 2015 Jun;132(3):205-6. doi: 10.1111/jbg.12164. No abstract available.

PMID:
25944710
41.

Genetic analysis of longevity in Dutch dairy cattle using random regression.

van Pelt ML, Meuwissen TH, de Jong G, Veerkamp RF.

J Dairy Sci. 2015 Jun;98(6):4117-30. doi: 10.3168/jds.2014-9090. Epub 2015 Apr 16.

42.

Empirical and deterministic accuracies of across-population genomic prediction.

Wientjes YC, Veerkamp RF, Bijma P, Bovenhuis H, Schrooten C, Calus MP.

Genet Sel Evol. 2015 Feb 6;47:5. doi: 10.1186/s12711-014-0086-0.

43.

Heterogeneity in genetic and nongenetic variation and energy sink relationships for residual feed intake across research stations and countries.

Tempelman RJ, Spurlock DM, Coffey M, Veerkamp RF, Armentano LE, Weigel KA, de Haas Y, Staples CR, Connor EE, Lu Y, VandeHaar MJ.

J Dairy Sci. 2015 Mar;98(3):2013-26. doi: 10.3168/jds.2014.8510. Epub 2015 Jan 9.

44.

A comparison of principal component regression and genomic REML for genomic prediction across populations.

Dadousis C, Veerkamp RF, Heringstad B, Pszczola M, Calus MP.

Genet Sel Evol. 2014 Nov 5;46:60. doi: 10.1186/s12711-014-0060-x.

45.

Consequences of splitting whole-genome sequencing effort over multiple breeds on imputation accuracy.

Bouwman AC, Veerkamp RF.

BMC Genet. 2014 Oct 3;15:105. doi: 10.1186/s12863-014-0105-8.

46.

Genetic analysis of atypical progesterone profiles in Holstein-Friesian cows from experimental research herds.

Nyman S, Johansson K, de Koning DJ, Berry DP, Veerkamp RF, Wall E, Berglund B.

J Dairy Sci. 2014 Nov;97(11):7230-9. doi: 10.3168/jds.2014-7984. Epub 2014 Aug 22.

47.

Consequences for diversity when animals are prioritized for conservation of the whole genome or of one specific allele.

Engelsma KA, Veerkamp RF, Calus MP, Windig JJ.

J Anim Breed Genet. 2014 Feb;131(1):61-70. doi: 10.1111/jbg.12052. Epub 2013 Aug 17.

PMID:
25099790
48.

Evaluation of measures of correctness of genotype imputation in the context of genomic prediction: a review of livestock applications.

Calus MP, Bouwman AC, Hickey JM, Veerkamp RF, Mulder HA.

Animal. 2014 Nov;8(11):1743-53. doi: 10.1017/S1751731114001803. Epub 2014 Jul 21. Review.

PMID:
25045914
49.

Accuracy of imputation to whole-genome sequence data in Holstein Friesian cattle.

van Binsbergen R, Bink MC, Calus MP, van Eeuwijk FA, Hayes BJ, Hulsegge I, Veerkamp RF.

Genet Sel Evol. 2014 Jul 15;46:41. doi: 10.1186/1297-9686-46-41.

50.

Genetic parameters across lactation for feed intake, fat- and protein-corrected milk, and liveweight in first-parity Holstein cattle.

Manzanilla Pech CI, Veerkamp RF, Calus MP, Zom R, van Knegsel A, Pryce JE, De Haas Y.

J Dairy Sci. 2014 Sep;97(9):5851-62. doi: 10.3168/jds.2014-8165. Epub 2014 Jul 11.

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