Accuracy of genomic prediction for milk production traits with different approaches in a small population of Slovenian Brown bulls

Špehar, Marija; Potočnik, Klemen

doi:10.1016/j.livsci.2013.08.008

Cited by 3 publications

(3 citation statements)

References 6 publications

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“…Further, some phenotyping resources could be diverted to genotyping to maximize return on investment. A comparable level of accuracy can be achieved with international reference populations (Jorjani, 2012;Špehar et al, 2013) or a combination of national and international reference populations (Vandenplas and Gengler, 2015;Vandenplas et al, 2017Vandenplas et al, , 2018. When this level of accuracy is combined with a reduced generation interval, small populations can achieve substantially larger genetic gains than with progeny testing.…”

Section: Genetic Gain With Genomic Truncation Selectionmentioning

confidence: 97%

Efficient use of genomic information for sustainable genetic improvement in small cattle populations

Obšteter

Jenko

Hickey

2019

Journal of Dairy Science

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In this study, we compared genetic gain, genetic variation, and the efficiency of converting variation into gain under different genomic selection scenarios with truncation or optimum contribution selection in a small dairy population by simulation. Breeding programs have to maximize genetic gain but also ensure sustainability by maintaining genetic variation. Numerous studies have shown that genomic selection increases genetic gain. Although genomic selection is a well-established method, small populations still struggle with choosing the most sustainable strategy to adopt this type of selection. We developed a simulator of a dairy population and simulated a model after the Slovenian Brown Swiss population with ~10,500 cows. We compared different truncation selection scenarios by varying (1) the method of sire selection and their use on cows or bull-dams, and (2) selection intensity and the number of years a sire is in use. Furthermore, we compared different optimum contribution selection scenarios with optimization of sire selection and their usage. We compared scenarios in terms of genetic gain, selection accuracy, generation interval, genetic and genic variance, rate of coancestry, effective population size, and conversion efficiency. The results showed that early use of genomically tested sires increased genetic gain compared with progeny testing, as expected from changes in selection accuracy and generation interval. A faster turnover of sires from year to year and higher intensity increased the genetic gain even further but increased the loss of genetic variation per year. Although maximizing intensity gave the lowest conversion efficiency, faster turnover of sires gave an intermediate conversion efficiency. The largest conversion efficiency was achieved with the simultaneous use of genomically and progeny-tested sires that were used over several years. Compared with truncation selection, optimizing sire selection and their usage increased the conversion efficiency by achieving either comparable genetic gain for a smaller loss of genetic variation or higher genetic gain for a comparable loss of genetic variation. Our results will help breeding organizations implement sustainable genomic selection.

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Section: Genetic Gain With Genomic Truncation Selectionmentioning

confidence: 97%

Efficient use of genomic information for sustainable genetic improvement in small cattle populations

Obšteter

Jenko

Hickey

2019

Journal of Dairy Science

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“…Further, 346 some phenotyping resources could be diverted to genotyping to maximize return on investment. A 347 comparable level of accuracy can be also achieved with international reference populations (Jorjani, 348 2012;Špehar et al, 2013) or a combination of national and international reference populations 349 (Vandenplas and Gengler, 2015;Vandenplas et al, 2017;Vandenplas et al, 2018). When this level 350 of accuracy is combined with a reduced generation interval, small populations can achieve 351 substantially larger genetic gains than with progeny testing.…”

Section: Genetic Gain With Genomic Truncation Selection 326mentioning

confidence: 98%

Efficient use of genomic information for sustainable genetic improvement in small cattle populations

Obšteter

Jenko

Hickey

2019

Preprint

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17This paper compares genetic gain, genetic variation, and the efficiency of converting variation into 18 gain under different genomic selection scenarios with truncation or optimum contribution selection 19 in a small dairy population by simulation. Breeding programs have to maximize genetic gain but 20 also ensure sustainability by maintaining genetic variation. Numerous studies showed that genomic 21 selection increases genetic gain. Although genomic selection is a well-established method, small 22 populations still struggle with choosing the most sustainable strategy to adopt this type of selection. 23We developed a simulator of a dairy population and simulated a model after the Slovenian Brown 24Swiss population with ~10,500 cows. We compared different truncation selection scenarios by 25 varying i) the method of sire selection and their use on cows or bull-dams, and ii) selection intensity 26 and the number of years a sire is in use. Furthermore, we compared different optimum contribution 27 selection scenarios with optimization of sire selection and their usage. We compared the scenarios 28 in terms of genetic gain, selection accuracy, generation interval, genetic and genic variance, the rate 29 of coancestry, effective population size, and the conversion efficiency. The results show that early 30 use of genomically tested sires increased genetic gain compared to progeny testing as expected from 31 changes in selection accuracy and generation interval. A faster turnover of sires from year to year 32 and higher intensity increased the genetic gain even further but increased the loss of genetic 33 variation per year. While maximizing intensity gave the lowest conversion efficiency, a faster turn-34 over of sires gave an intermediate conversion efficiency. The largest conversion efficiency was 35 achieved with the simultaneous use of genomically and progeny tested sires that were used over 36 several years. Compared to truncation selection optimizing sire selection and their usage increased 37 the conversion efficiency by either achieving comparable genetic gain for a smaller loss of genetic 38 variation or achieving higher genetic gain for a comparable loss of genetic variation. Our results 39 will help breeding organizations to implement sustainable genomic selection. 40Key words: small population, sustainability, genomic selection, optimum contribution selection 41 progeny testing with genomic pre-selection prior to progeny testing or direct genomic selection for 59 widespread use without progeny testing (de Roos et al., 2011;Lillehammer et al., 2011; Pryce et al., 60 2010). These studies reported up to 30% increase in genetic gain with the genomic pre-selection and 61 up to 195% increase with the direct genomic selection. Thomasen et al. (2014) deterministically 62 evaluated hybrid schemes that use both progeny and young genomically tested sires in populations 63 of different size. They concluded that genomic selection gives higher genetic gain than conventional 64 progeny testing irrespective of popu...

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“…Another approach calculated pseudo-records and associated weights from DGVs and included them in conventional genetic evaluations as a correlated trait. As done by Mäntysaari and Strandén (2010), DGVs were considered as pseudo-records with a heritability equal or close to 1 (e.g., Johnston et al, 2009;Kachman, 2008;Špehar et al, 2013). In contrast, Stoop et al (2011) proposed including pseudo-records derived from DGV with a heritability equal to predictive reliability of the prediction equation and a genetic correlation with the trait of interest equal to 1.…”

Section: Combinations In Genomic Selectionmentioning

confidence: 99%

Strategies for comparing and combining different genetic and genomic evaluations: A review

Vandenplas

Gengler

2015

Livestock Science

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Accuracy of genomic prediction for milk production traits with different approaches in a small population of Slovenian Brown bulls

Cited by 3 publications

References 6 publications

Efficient use of genomic information for sustainable genetic improvement in small cattle populations

Efficient use of genomic information for sustainable genetic improvement in small cattle populations

Efficient use of genomic information for sustainable genetic improvement in small cattle populations

Strategies for comparing and combining different genetic and genomic evaluations: A review

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