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Comparison of methods for predicting genomic breeding values for growth traits in Nellore cattle

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Abstract

The objective of this study was to evaluate the accuracy of genomic predictions of growth traits in Nellore cattle. Data from 5064 animals belonging to farms that participate in the Conexão DeltaGen and PAINT breeding programs were used. Genotyping was performed with the Illumina BovineHD BeadChip (777,962 SNPs). After quality control of the genomic data, 412,993 SNPs were used. Deregressed EBVs (DEBVs) were calculated using the estimated breeding values (EBVs) and accuracies of birth weight (BW), weight gain from birth to weaning (GBW), postweaning weight gain (PWG), yearling height (YH), and cow weight (CW) provided by GenSys. Three models were used to estimate marker effects: genomic best linear unbiased prediction (GBLUP), BayesCπ, and improved Bayesian least absolute shrinkage and selection operator (IBLASSO). The prediction ability of genomic estimated breeding value (GEBVs) was estimated by the average Pearson correlation between DEBVs and GEBVs, predicted with the different methodologies in the validation populations. The regression coefficients of DEBVs on GEBVs in the validation population were calculated and used as indicators of prediction bias of GEBV. In general, the Bayesian methods provided slightly more accurate predictions of genomic breeding values than GBLUP. The BayesCπ and IBLASSO were similar for all traits (BW, GBW, PWG, and YH), except for CW. Thus, there does not seem to be a more suitable method for the estimation of SNP effects and genomic breeding values. Bayesian regression models are of interest for future applications of genomic selection in this population, but further improvements are needed to reduce deflation of their predictions.

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References

  • Almeida IF, Cruz CD, Resende MDV 2016. Validação e correção de fenótipos na seleção genômica ampla. Pesq. agropec. bras., Brasília, v.51, n. 12, p. 1973-1982

  • Boerner V, Johnston DJ, Tier B. Accuracies of genomically estimated breeding values from pure-breed and across-breed predictions in Australian beef cattle. Genet Sel Evol. 2014 Oct 24;46(1):61. https://doi.org/10.1186/s12711-014-0061-9.

  • Bolormaa S, Hayes BJ, Savin KHR, Barendse W, Arthur PF, Herd RM and Goddard ME 2011. Genome-wide association studies for feedlot and growth traits in cattle. Journal Of Animal Science, v. 89, p. 1684-1697.

    Article  CAS  Google Scholar 

  • Chen L, Schenkel F, Vinsky M, Crews DH Jr, Li C. Accuracy of predicting genomic breeding values for residual feed intake in Angus and Charolais beef cattle. J Anim Sci. 2013 Oct;91(10):4669-78. https://doi.org/10.2527/jas.2013-5715.

  • Colombani C, Legarra A, Fritz S, Guillaume F, Croiseau P, Ducrocq V and Robert-Granié C 2013. Application of Bayesian least absolute shrinkage and selection operator (LASSO) and BayesCπ methods for genomic selection in French Holstein and Montbéliarde breeds. Journal of Dairy Science, v. 96, p. 575–591.

    Article  CAS  Google Scholar 

  • Costa Raphael Bermal, Natalia Irano, Iara Del Pilar Solar Diaz, Luciana Takada, Isis da Costa Hermisdorff, Roberto Carvalheiro, Fernando Baldi, Henrique Nunes de Oliveira, Humberto Tonhati, Lucia Galvão de Albuquerque, Prediction of genomic breeding values for reproductive traits in Nellore heifers, Theriogenology, 125, (2019). https://doi.org/10.1016/j.theriogenology.2018.10.014.

  • CRV Lagoa 2013. Programa de Melhoramento Genético para Bovinos de corte da CRV Lagoa. Retrieved September 10, 2013, from http://www.crvlagoa.com.br/index.asp

  • Espigolan, R., Baldi, F., Boligon, A.A. et al. Study of whole genome linkage disequilibrium in Nellore cattle. BMC Genomics 14, 305 (2013). https://doi.org/10.1186/1471-2164-14-305.

  • Fernandes Júnior, G.A., Rosa, G.J.M., Valente, B.D. et al. Genomic prediction of breeding values for carcass traits in Nellore cattle. Genet Sel Evol 48, 7 (2016). https://doi.org/10.1186/s12711-016-0188-y

  • Gredler B, Nirea KG, Solberg TR, Egger-Danner C, Meuwissen T and Solkner J 2009. A Comparison of methods for genomic selection in Australian dual purpose Simmental cattle. Procedings. Association of Advancement. Animal Breeding Genetics, v. 18, p. 568-571.

    Google Scholar 

  • Habier D, Fernando RL, Kizilkaya K and Garrick DJ 2011. Extension of the Bayesian alphabet for genomic selection. BMC Bioinformatics. v. 12, p. 186.

    Article  Google Scholar 

  • Hayes, B.J., Bowman, P.J., Chamberlain, A.C. et al. Accuracy of genomic breeding values in multi-breed dairy cattle populations. Genet Sel Evol 41, 51 (2009). https://doi.org/10.1186/1297-9686-41-51

  • Illumina Inc., 9885 Towne Centre Drive, San Diego, CA 92121, USA. rshen@illumina.com

  • Lee J, Kachman SD, Spangler ML. The impact of training strategies on the accuracy of genomic predictors in United States Red Angus cattle. J Anim Sci. 2017 Aug;95(8):3406-3414. https://doi.org/10.2527/jas.2017.1604.

  • Legarra A, Robert-Granié C, Manfredi E and Elsen JM 2008. Performance of genomic selection in mice. Genetics, v.180, p.611-618.

    Article  Google Scholar 

  • Meuwissen THE 2009. Accuracy of breeding values of ‘unrelated’ individuals predicted by dense SNP genotyping. Genetic Selection Evolution, p. 41–35.

  • Meuwissen THE, Hayes BJ and Goddard ME 2001. Prediction of Total genetic value using genome-wide dense marker maps. Genetics, v. 157, p.1819-1829.

    Article  CAS  Google Scholar 

  • Neves, H.H., Carvalheiro, R., O’Brien, A.M.P. et al. Accuracy of genomic predictions in Bos indicus (Nellore) cattle. Genet Sel Evol 46, 17 (2014). https://doi.org/10.1186/1297-9686-46-17.

  • Pryce JE, Williams YJ, Spelman RJE and Hayes BJ 2011. Accuracy of genomic predictions of residual feed intake and 250-day body weight in growing heifers using 625,000 single nucleotide polymorphism markers. Journal of Dairy Science, v. 95, p. 2108-2119.

    Article  Google Scholar 

  • Saatchi M, Mcclure MC, Mckay S, Rolf MM, Kim J, Decker JE, Taxis TM, Chapple RH, Ramey HR, Northcutt SL, Bauck S, Woodward B, Dekkers JCM, Fernando RL, Schnabel RD, Garrick DJE and Taylor JF 2011. Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation. Genetics Selection Evolution, v. 43, p. 40-56.

    Article  Google Scholar 

  • Tibshirani, R 1996. Regression shrinkage and selection via the Lasso. Journal of the Royal Statistical Society, v. 58, p. 267-288.

    Google Scholar 

  • Vanraden, PM 2008. Efficient methods to compute genomic predictions. Journal of Dairy Science, v. 91, p. 4414-4423.

    Article  CAS  Google Scholar 

  • Wang X, Miao J, Chang T, Xia J, An B, LiY, et al. (2019) Evaluation of GBLUP, BayesB and elastic net for genomic prediction in Chinese Simmental beef cattle. PLoS ONE 14(2): e0210442. https://doi.org/10.1371/journal.pone.0210442.

  • Weber KL, Thallman RM, Keele JW, Snelling WM, Bennett GL, Smith TP, Mcdaneld TG, Allan MF, Van Eenennaam ALE and Kuehn LA 2012 Accuracy of genomic breeding values in multi breed beef cattle populations derived from deregressed breeding values and phenotypes. Journal of Animal Science, v. 90, p. 4177-4190.

    Article  CAS  Google Scholar 

Download references

Funding

This study was supported with the costs associated with genotyping of animals by the thematic project ‘Genomic tools for the genetic improvement of economically important traits in Nelore cattle’ supported by Fundação de Amparo a Pesquisa do Estado de SãoPaulo (FAPESP grant numbers 2009/16118–5).

Author information

Authors and Affiliations

  1. School of Agricultural and Veterinarian Sciences, Sao Paulo State University (UNESP), Jaboticabal, SP, 14884-900, Brazil

    Ana Paula Nascimento Terakado, Natalia Irano, Tiago Bresolin, Henrique Nunes de Oliveira, Roberto Carvalheiro, Fernando Baldi & Lucia Galvão de Albuquerque

  2. School of Veterinary and Animal Sciences, Universidade Federal da Bahia (UFBA), Salvador, BA, 40170-110, Brazil

    Raphael Bermal Costa & Iara Del Pilar Solar Diaz

Authors
  1. Ana Paula Nascimento Terakado
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  2. Raphael Bermal Costa
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  3. Natalia Irano
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  4. Tiago Bresolin
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  5. Henrique Nunes de Oliveira
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  6. Roberto Carvalheiro
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  7. Fernando Baldi
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  8. Iara Del Pilar Solar Diaz
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  9. Lucia Galvão de Albuquerque
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Contributions

Each of the authors contributed to different aspects of the study design, data collection, data analyses, and manuscript preparation. All of the authors commented on the final manuscript.

Corresponding author

Correspondence to Raphael Bermal Costa.

Ethics declarations

Ethics approval

The analyses were executed with records from breeder association registration data. No animals were used in experiments. No ethical statement is needed.

Consent to participate

Breeders consent to the participation of all the data from their animals in CRV Lagoa breeding programs when they enroll in the genetic evaluation.

Consent for publication

Permission for the study and to publish the results was granted by Conexão DeltaGen@ and PAINT@ breeding programs from CRV Lagoa (www.crvlagoa.com.br).

Conflict of interest

The authors declare no competing interests.

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Terakado, A.P.N., Costa, R.B., Irano, N. et al. Comparison of methods for predicting genomic breeding values for growth traits in Nellore cattle. Trop Anim Health Prod 53, 349 (2021). https://doi.org/10.1007/s11250-021-02785-1

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