Genomic dominance variance analysis of health and milk production traits in German Holstein cattle.
German Holstein
dairy cattle
dominance
health traits
non-additivity
Journal
Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie
ISSN: 1439-0388
Titre abrégé: J Anim Breed Genet
Pays: Germany
ID NLM: 100955807
Informations de publication
Date de publication:
Jul 2023
Jul 2023
Historique:
received:
13
09
2022
accepted:
12
02
2023
medline:
16
6
2023
pubmed:
7
3
2023
entrez:
6
3
2023
Statut:
ppublish
Résumé
Genomic analyses commonly explore the additive genetic variance of traits. The non-additive variance, however, is usually small but often significant in dairy cattle. This study aimed at dissecting the genetic variance of eight health traits that recently entered the total merit index in Germany and the somatic cell score (SCS), as well as four milk production traits by analysing additive and dominance variance components. The heritabilities were low for all health traits (between 0.033 for mastitis and 0.099 for SCS), and moderate for the milk production traits (between 0.261 for milk energy yield and 0.351 for milk yield). For all traits, the contribution of dominance variance to the phenotypic variance was low, varying between 0.018 for ovarian cysts and 0.078 for milk yield. Inbreeding depression, inferred from the SNP-based observed homozygosity, was significant only for the milk production traits. The contribution of dominance variance to the genetic variance was larger for the health traits, ranging from 0.233 for ovarian cysts to 0.551 for mastitis, encouraging further studies that aim at discovering QTLs based on their additive and dominance effects.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
390-399Subventions
Organisme : Deutsche Forschungsgemeinschaft
Informations de copyright
© 2023 The Authors. Journal of Animal Breeding and Genetics published by John Wiley & Sons Ltd.
Références
Aliloo, H., Pryce, J. E., González-Recio, O., Cocks, B. G., Goddard, M. E., & Hayes, B. J. (2017). Including nonadditive genetic effects in mating programs to maximize dairy farm profitability. Journal of Dairy Science, 100(2), 1203-1222. https://doi.org/10.3168/jds.2016-11261
Aliloo, H., Pryce, J. E., González-Recio, O., Cocks, B. G., & Hayes, B. J. (2016). Accounting for dominance to improve genomic evaluations of dairy cows for fertility and milk production traits. Genetics Selection Evolution, 48, 8. https://doi.org/10.1186/s12711016-0186-0
Alves, K., Brito, L. F., Baes, C., Sargolzaei, M., Robinson, J. A. B., & Schenkel, F. S. (2020). Estimation of additive and non-additive genetic effects for fertility and reproduction traits in north American Holstein cattle using genomic information. Journal of Animal Breeding and Genetics, 137(3), 316-330. https://doi.org/10.1111/jbg.12466
Bennewitz, J., Edel, C., Fries, R., Meuwissen, T. H., & Wellmann, R. (2017). Application of a Bayesian dominance model improves power in quantitative trait genome-wide association analysis. Genetics Selection Evolution, 49(1), 7. https://doi.org/10.1186/s12711-017-0284-7
Berry, D. P., Wall, E., & Pryce, J. E. (2014). Genetics and genomics of reproductive performance in dairy and beef cattle. Animal, 8(Suppl 1), 105-121. https://doi.org/10.1017/S1751731114000743
Boettcher, P. J., Jairath, L. K., & Dekkers, J. C. (1999). Comparison of methods for genetic evaluation of sires for survival of their daughters in the first three lactations. Journal of Dairy Science, 82(5), 1034-1044. https://doi.org/10.3168/jds.S0022-0302(99)75324-5
Bolormaa, S., Pryce, J. E., Zhang, Y., Reverter, A., Barendse, W., Hayes, B. J., & Goddard, M. E. (2015). Non-additive genetic variation in growth, carcass and fertility traits of beef cattle. Genetics Selection Evolution, 47, 26. https://doi.org/10.1186/s12711-015-0114-8
Carlén, E., Strandberg, E., & Roth, A. (2004). Genetic parameters for clinical mastitis, somatic cell score, and production in the first three lactations of Swedish Holstein cows. Journal of Dairy Science, 87(9), 3062-3070. https://doi.org/10.3168/jds.S00220302(04)73439-6
Dempster, E. R., & Lerner, I. M. (1950). Heritability of threshold characters. Genetics, 35(2), 212-236. https://doi.org/10.1093/genetics/35.2.212
Doekes, H. P., Bijma, P., Veerkamp, R. F., de Jong, G., Wientjes, Y. C. J., & Windig, J. J. (2020). Inbreeding depression across the genome of Dutch Holstein Friesian dairy cattle. Genetics Selection Evolution, 52(1), 64. https://doi.org/10.1186/s12711-020-00583-1
Doekes, H. P., Bijma, P., & Windig, J. J. (2021). How depressing is inbreeding? A meta analysis of 30 years of research on the effects of inbreeding in livestock. Genes, 12(6), 926. https://doi.org/10.3390/genes12060926
Dolecheck, K. A., Overton, M. W., Mark, T. B., & Bewley, J. M. (2019). Use of a stochastic simulation model to estimate the cost per case of digital dermatitis, sole ulcer, and white line disease by parity group and incidence timing. Journal of Dairy Science, 102(1), 715-730. https://doi.org/10.3168/jds.2018-14901
Ertl, J., Legarra, A., Vitezica, Z. G., Varona, L., Edel, C., Emmerling, R., & Götz, K.-U. (2014). Genomic analysis of dominance effects on milk production and conformation traits in Fleckvieh cattle. Genetics Selection Evolution, 46, 40. https://doi.org/10.1186/12979686-46-40
Falconer, D. S., & Mackay, T. F. C. (2009). Introduction to quantitative genetics (Fourth ed., p. 119). Pearson.
Garcia-Baccino, C. A., Lourenco, D. A. L., Miller, S., Cantet, R. J. C., & Vitezica, Z. G. (2020). Estimating dominance genetic variances for growth traits in American Angus males using genomic models. Journal of Animal Science, 98(1), skz384. https://doi.org/10.1093/jas/skz384
Gianola, D., & Foulley, J. (1983). Sire evaluation for ordered categorical data with a threshold model. Genetique, selection, evolution, 15(2), 201-224. https://doi.org/10.1186/1297-9686-15-2-201
González-Diéguez, D., Tusell, L., Bouquet, A., Legarra, A., & Vitezica, Z. G. (2020). Purebred and crossbred genomic evaluation and mate allocation strategies to exploit dominance in pig crossbreeding schemes. G3, 10(8), 2829-2841. https://doi.org/10.1534/g3.120.401376
Hadfield, J. D. (2010). MCMC methods for multi-response generalized linear mixed models: The MCMCglmmR package. Journal of Statistical Software. https://doi.org/10.18637/jss.v033.i02
Heringstad, B., Egger-Danner, C., Charfeddine, N., Pryce, J. E., Stock, K. F., Kofler, J., Sogstad, A. M., Holzhauer, M., Fiedler, A., Müller, K., Nielsen, P., Thomas, G., Gengler, N., de Jong, G., Ødegård, C., Malchiodi, F., Miglior, F., Alsaaod, M., & Cole, J. B. (2018). Invited review: Genetics and claw health: Opportunities to enhance claw health by genetic selection. Journal of Dairy Science, 101(6), 4801-4821. https://doi.org/10.3168/jds.2017-13531
Hoeschele, I. (1991). Additive and nonadditive genetic variance in female fertility of Holsteins. Journal of Dairy Science, 74(5), 1743-1752. https://doi.org/10.3168/jds.S00220302(91)78337-9
Jamrozik, J., Fatehi, J., Kistemaker, G. J., & Schaeffer, L. R. (2005). Estimates of genetic parameters for Canadian Holstein female reproduction traits. Journal of Dairy Science, 88, 2199-2208. https://doi.org/10.3168/jds.S0022-0302(05)72895-2
Jiang, J., Ma, L., Prakapenka, D., VanRaden, P. M., Cole, J. B., & Da, Y. (2019). A large-scale genome-wide association study in U.S. Holstein cattle. Frontiers in Genetics, 10, 412. https://doi.org/10.3389/fgene.2019.0041
Jiang, J., Shen, B., O'Connell, J. R., VanRaden, P. M., Cole, J. B., & Ma, L. (2017). Dissection of additive, dominance, and imprinting effects for production and reproduction traits in Holstein cattle. BMC Genomics, 18(1), 425. https://doi.org/10.1186/s12864-017-38214
König, S., Wu, X. L., Gianola, D., Heringstad, B., & Simianer, H. (2008). Exploration of relationships between claw disorders and milk yield in Holstein cows via recursive linear and threshold models. Journal of Dairy Science, 91(1), 395-406. https://doi.org/10.3168/jds.2007-0170
Liu, Y., Xu, L., Wang, Z., Xu, L., Chen, Y., Zhang, L., Xu, L., Gao, X., Gao, H., Zhu, B., & Li, J. (2019). Genomic prediction and association analysis with models including dominance effects for important traits in chinese simmental beef cattle. Animals: An Open Access Journal from MDPI, 9(12), 1055. https://doi.org/10.3390/ani9121055
Maltecca, C., Tiezzi, F., Cole, J. B., & Baes, C. (2020). Symposium review: Exploiting homozygosity in the era of genomics-selection, inbreeding, and mating programs. Journal of Dairy Science, 103(6), 5302-5313. https://doi.org/10.3168/jds.2019-17846
Mao, X., Sahana, G., Johansson, A. M., Liu, A., Ismael, A., Løvendahl, P., De Koning, D. J., & Guldbrandtsen, B. (2020). Genome-wide association mapping for dominance effects in female fertility using real and simulated data from Danish Holstein cattle. Scientific Reports, 10(1), 2953. https://doi.org/10.1038/s41598-020-59788-5
Mark, T. (2004). Applied genetic evaluations for production and functional traits in dairy cattle. Journal of Dairy Science, 87, 2641-2652. https://doi.org/10.3168/jds.S0022-0302(04)73390-1
Martin, P., Barkema, H. W., Brito, L. F., Narayana, S. G., & Miglior, F. (2018). Symposium review: Novel strategies to genetically improve mastitis resistance in dairy cattle. Journal of Dairy Science, 101(3), 2724-2736. https://doi.org/10.3168/jds.2017-13554
Meijering, A., & Gianola, D. (1985). Observations on sire evaluation with categorical data using heteroscedastic mixed linear models. Journal of Dairy Science, 68, 1226-1232. https://doi.org/10.3168/jds.S0022-0302(85)80950-4
Misztal, I., Gianola, D., & Foulley, J. L. (1989). Computing aspects for a nonlinear method of sire evaluation for categorical traits. Journal of Dairy Science, 72, 1557-1568. https://doi.org/10.3168/jds.S0022-0302(89)79267-5
Misztal, I., Lawlor, T. J., & Gengler, N. (1997). Relationships among estimates of inbreeding depression, dominance and additive variance for linear traits in Holsteins. Genetics Selection Evolution, 29(3), 319. https://doi.org/10.1186/1297-9686-29-3-319
Misztal, I., Varona, L., Culbertson, M. S., Bertrand, J. K., Mabry, J. W., Lawlor, T. J., Van Tassell, C. P., & Gengler, N. (1998). Studies on the value of incorporating the effect of dominance in genetic evaluations of dairy cattle, beef cattle and swine. Biotechnology, Agronomy and Society and Environment, 2, 227-233.
Moghaddar, N., & van der Werf, J. H. J. (2017). Genomic estimation of additive and dominance effects and impact of accounting for dominance on accuracy of genomic evaluation in sheep populations. Journal of Animal Breeding and Genetics, 134(6), 453-462. https://doi.org/10.1111/jbg.12287
Mostert, P. F., van Middelaar, C. E., de Boer, I. J. M., & Bokkers, E. A. M. (2018). The impact of foot lesions in dairy cows on greenhouse gas emissions of milk production. Agricultural Systems, 167, 206-212. https://doi.org/10.1016/j.agsy.2018.09.006
Neuenschwander, T. F.-O., Miglior, F., Jamrozik, J., Berke, O., Kelton, D. F., & Schaeffer, L. R. (2012). Genetic parameters for producer-recorded health data in Canadian Holstein cattle. Animal, 6(4), 571-578. https://doi.org/10.1017/S1751731111002059
Nostitz, B., & Mielke, H. (1995). Vergleich verschiedener Methoden der Bestimmung des Milchenergiegehaltes beim Schwarzbunten Milchrind. Journal of Animal Physiology and Animal Nutrition, 73(1-5), 9-18. https://doi.org/10.1111/j.14390396.1995.tb00398.x
Palucci, V., Schaeffer, L. R., Miglior, F., & Osborne, V. (2007). Non-additive genetic effects for fertility traits in Canadian Holstein cattle. Genetics Selection Evolution, 39(2), 181-193. https://doi.org/10.1186/1297-9686-39-2-181
Pryce, J. E., Haile-Mariam, M., Goddard, M. E., & Hayes, B. J. (2014). Identification of genomic regions associated with inbreeding depression in Holstein and Jersey dairy cattle. Genetics Selection Evolution, 46(1), 71. https://doi.org/10.1186/s12711-014-0071-7
Rantala, M. J., & Roff, D. A. (2006). Analysis of the importance of genotypic variation, metabolic rate, morphology, sex and development time on immune function in the cricket, Gryllus firmus. Journal of Evolutionary Biology, 19(3), 834-843. https://doi.org/10.1111/j.1420-9101.2005.01048.x
Sahana, G., Nielsen, U. S., Aamand, G. P., Lund, M. S., & Guldbrandtsen, B. (2013). Novel harmful recessive haplotypes identified for fertility traits in Nordic Holstein cattle. PLoS One, 8(12), e82909. https://doi.org/10.1371/journal.pone.0082909
Schneider, H., Segelke, D., Tetens, J., Thaller, G., & Bennewitz, J. (2022). A genomic assessment of the correlation between milk production traits and claw and udder health traits in Holstein dairy cattle. Journal of Dairy Science, 106(2), 1190-1205. https://doi.org/10.3168/jds.2022-22312
Stock, J., Bennewitz, J., Hinrichs, D., & Wellmann, R. (2020). A review of genomic models for the analysis of livestock crossbred data. Frontiers in Genetics, 11, 568. https://doi.org/10.3389/fgene.2020.00568
Stock, J., Esfandyari, H., Hinrichs, D., & Bennewitz, J. (2021). Implementing a genomic rotational crossbreeding scheme to promote local dairy cattle breeds-a simulation study. Journal of Dairy Science, 104(6), 6873-6884. https://doi.org/10.3168/jds.2020-19927
Su, G., Christensen, O. F., Ostersen, T., Henryon, M., & Lund, M. S. (2012). Estimating additive and non-additive genetic variances and predicting genetic merits using genome-wide dense single nucleotide polymorphism markers. PLoS One, 7(9), e45293. https://doi.org/10.1371/journal.pone.0045293
Sun, C., VanRaden, P. M., Cole, J. B., & O'Connell, J. R. (2014). Improvement of prediction ability for genomic selection of dairy cattle by including dominance effects. PLoS One, 9(8), e103934. https://doi.org/10.1371/journal.pone.0103934
Toro, M. A., & Varona, L. (2010). A note on mate allocation for dominance handling in genomic selection. Genetics Selection Evolution, 42(1), 33. https://doi.org/10.1186/1297-9686-42-33
VanRaden, P. M. (2008). Efficient methods to compute genomic predictions. Journal of Dairy Science, 91(11), 4414-4423. https://doi.org/10.3168/jds.2007-0980
Varona, L., Legarra, A., Toro, M. A., & Vitezica, Z. G. (2018). Non-additive effects in genomic selection. Frontiers in Genetics, 9, 78. https://doi.org/10.3389/fgene.2018.00078
Varona, L., & Misztal, I. (1999). Prediction of parental dominance combinations for planned matings, methodology, and simulation results. Journal of Dairy Science, 82(10), 2186-2191. https://doi.org/10.3168/jds.S0022-0302(99)75463-9
Vereinigte Informationssysteme Tierhaltung w. V. (2022). Jahresbericht 2021. https://www.vit.de/fileadmin/Wir-sind-vit/Jahresberichte/vit-JB2021-gesamt.pdf. Accessed 30 Aug 2022
Vitezica, Z. G., Varona, L., Elsen, J. M., Misztal, I., Herring, W., & Legarra, A. (2016). Genomic BLUP including additive and dominant variation in purebreds and F1 crossbreds, with an application in pigs. Genetics Selection Evolution, 48, 6. https://doi.org/10.1186/s12711-016-0185-1
Vitezica, Z. G., Varona, L., & Legarra, A. (2013). On the additive and dominant variance and covariance of individuals within the genomic selection scope. Genetics, 195(4), 1223-1230. https://doi.org/10.1534/genetics.113.155176
Wellmann, R., & Bennewitz, J. (2011). The contribution of dominance to the understanding of quantitative genetic variation. Genetics Research, 93(2), 139-154. https://doi.org/10.1017/S0016672310000649
Wellmann, R., & Bennewitz, J. (2012). Bayesian models with dominance effects for genomic evaluation of quantitative traits. Genetics Research, 94(1), 21-37. https://doi.org/10.1017/S0016672312000018
Xiang, T., Christensen, O. F., Vitezica, Z. G., & Legarra, A. (2016). Genomic evaluation by including dominance effects and inbreeding depression for purebred and crossbred performance with an application in pigs. Genetics Selection Evolution, 48(1), 92. https://doi.org/10.1186/s12711-016-0271-4
Zhang, H., Yin, L., Wang, M., Yuan, X., & Liu, X. (2019). Factors affecting the accuracy of genomic selection for agricultural economic traits in maize, cattle, and pig populations. Frontiers in Genetics, 10, 189. https://doi.org/10.3389/fgene.2019.00189
Zhu, Z., Bakshi, A., Vinkhuyzen, A. A., Hemani, G., Lee, S. H., Nolte, I. M., van Vliet Ostaptchouk, J. V., Snieder, H., LifeLines Cohort Study, Esko, T., Milani, L., Mägi, R., Metspalu, A., Hill, W. G., Weir, B. S., Goddard, M. E., Visscher, P. M., & Yang, J. (2015). Dominance genetic variation contributes little to the missing heritability for human complex traits. American Journal of Human Genetics, 96(3), 377-385. https://doi.org/10.1016/j.ajhg.2015.01.001