%0 Journal Article %1 Fragomeni20154090 %A Fragomeni, B.O. %A Lourenco, D.A.L. %A Tsuruta, S. %A Masuda, Y. %A Aguilar, I. %A Legarra, A. %A Lawlor, T.J. %A Misztal, I. %D 2015 %J Journal of Dairy Science %K 2015 APY dairy_cattle genomics %N 6 %P 4090 - 4094 %R http://dx.doi.org/10.3168/jds.2014-9125 %T Hot topic: Use of genomic recursions in single-step genomic best linear unbiased predictor (BLUP) with a large number of genotypes %U http://www.sciencedirect.com/science/article/pii/S0022030215002386 %V 98 %X Abstract The purpose of this study was to evaluate the accuracy of genomic selection in single-step genomic \BLUP\ (ssGBLUP) when the inverse of the genomic relationship matrix (G) is derived by the “algorithm for proven and young animals” (APY). This algorithm implements genomic recursions on a subset of “proven” animals. Only a relationship matrix for animals treated as “proven” needs to be inverted, and the extra costs of adding animals treated as “young” are linear. Analyses involved 10,102,702 final scores on 6,930,618 Holstein cows. Final score, which is a composite of type traits, is popular trait in the United States and was easily available for this study. A total of 100,000 animals with genotypes were used in the analyses and included 23,000 sires (16,000 with >5 progeny), 27,000 cows, and 50,000 young animals. Genomic \EBV\ (GEBV) were calculated with a regular inverse of G, and with the G inverse approximated by APY. Animals in the proven subset included only sires (23,000), sires + cows (50,000), only cows (27,000), or sires with >5 progeny (16,000). The correlations of \GEBV\ with \APY\ and regular \GEBV\ for young genotyped animals were 0.994, 0.995, 0.992, and 0.992, respectively Later, animals in the proven subset were randomly sampled from all genotyped animals in sets of 2,000, 5,000, 10,000, 15,000, and 20,000; each sample was replicated 4 times. Respective correlations were 0.97 (5,000 sample), 0.98 (10,000 sample), and 0.99 (20,000 sample), with minimal difference between samples of the same size. Genomic \EBV\ with \APY\ were accurate when the number of animals used in the subset is between 10,000 and 20,000, with little difference between the ways of creating the subset. Due to the approximately linear cost of APY, ssGBLUP with \APY\ could support any number of genotyped animals without affecting accuracy.

@article{Fragomeni20154090, abstract = {Abstract The purpose of this study was to evaluate the accuracy of genomic selection in single-step genomic \{BLUP\} (ssGBLUP) when the inverse of the genomic relationship matrix (G) is derived by the “algorithm for proven and young animals” (APY). This algorithm implements genomic recursions on a subset of “proven” animals. Only a relationship matrix for animals treated as “proven” needs to be inverted, and the extra costs of adding animals treated as “young” are linear. Analyses involved 10,102,702 final scores on 6,930,618 Holstein cows. Final score, which is a composite of type traits, is popular trait in the United States and was easily available for this study. A total of 100,000 animals with genotypes were used in the analyses and included 23,000 sires (16,000 with >5 progeny), 27,000 cows, and 50,000 young animals. Genomic \{EBV\} (GEBV) were calculated with a regular inverse of G, and with the G inverse approximated by APY. Animals in the proven subset included only sires (23,000), sires + cows (50,000), only cows (27,000), or sires with >5 progeny (16,000). The correlations of \{GEBV\} with \{APY\} and regular \{GEBV\} for young genotyped animals were 0.994, 0.995, 0.992, and 0.992, respectively Later, animals in the proven subset were randomly sampled from all genotyped animals in sets of 2,000, 5,000, 10,000, 15,000, and 20,000; each sample was replicated 4 times. Respective correlations were 0.97 (5,000 sample), 0.98 (10,000 sample), and 0.99 (20,000 sample), with minimal difference between samples of the same size. Genomic \{EBV\} with \{APY\} were accurate when the number of animals used in the subset is between 10,000 and 20,000, with little difference between the ways of creating the subset. Due to the approximately linear cost of APY, ssGBLUP with \{APY\} could support any number of genotyped animals without affecting accuracy. }, added-at = {2016-05-14T05:31:25.000+0200}, author = {Fragomeni, B.O. and Lourenco, D.A.L. and Tsuruta, S. and Masuda, Y. and Aguilar, I. and Legarra, A. and Lawlor, T.J. and Misztal, I.}, biburl = {https://www.bibsonomy.org/bibtex/203dfeafdb8644c7f397bbe213b802f8d/uga.abgg}, doi = {http://dx.doi.org/10.3168/jds.2014-9125}, interhash = {e9d60de4c563f97c227ef30f118b1ba5}, intrahash = {03dfeafdb8644c7f397bbe213b802f8d}, issn = {0022-0302}, journal = {Journal of Dairy Science }, keywords = {2015 APY dairy_cattle genomics}, number = 6, pages = {4090 - 4094}, timestamp = {2016-05-14T18:04:51.000+0200}, title = {Hot topic: Use of genomic recursions in single-step genomic best linear unbiased predictor (BLUP) with a large number of genotypes }, url = {http://www.sciencedirect.com/science/article/pii/S0022030215002386}, volume = 98, year = 2015 }