Phenotypic and genetic parameters for growth-related traits in the half-smooth tongue sole, Cynoglossus semilaevis, were estimated in 22 full-sib families produced by normal and neo-male breeding stocks. As phenotypic...Phenotypic and genetic parameters for growth-related traits in the half-smooth tongue sole, Cynoglossus semilaevis, were estimated in 22 full-sib families produced by normal and neo-male breeding stocks. As phenotypic males with female genotypes, neo-males are harmful in C. semilaevis aquaculture because they reduce overall production. The present study evaluated the difference in the growth-related traits： total length （TL）, body weight （BW） and square root of body weight （SQ_BW） at the age of 570 days between normal and neo-male offspring （neo-males used as male parents）. The difference in the proportion of females between normal and neo-male offspring was also assessed. Based on the linear mixed model, restricted maximum likelihood （REML） and best linear unbiased prediction （BLUP） were used to estimate various （co）variance components and estimated breeding values （EBVs） of growth-related traits. As a result, all the mean values of the three studied traits were significantly larger in normal offspring than in neo-male offspring. Additionally, the female proportion was significantly larger in normal offspring than in neo-male offspring. Heritability was 0.128＋0.066 2 for TL, 0.128-4-0.065 5 for BW and 0.132~0.062 9 for SQBW, all of which were low level heritabilities. The correlation coefficients of EBVs and phenotypic values of the target traits were 0.516 for TL, 0.524 for BW and 0.506 for SQ_BW, all of which were highly significant （P〈0.01）. Genetic correlations among TL, BW and SQ_BW were positive high （0.921-0.969） and higher than those of phenotype （0.711-0.748）, both of which had low standard errors （0.063-0.123 for genotype, and 0.010-0.018 for phenotype）. Compared with normal offspring, neo-male offspring have lower breeding values for each studied trait through EBVs comparison. Therefore, neo-male offspring should not be used as broodstock in a C. semilaevis breeding programs.展开更多
This paper makes an analysis of the phenotype tendencies of dam populations White Large （WL） and Landrace （L） over the years 2000-2009 after the introduction of Multivariate Best Linear Unbiased Prediction and ani...This paper makes an analysis of the phenotype tendencies of dam populations White Large （WL） and Landrace （L） over the years 2000-2009 after the introduction of Multivariate Best Linear Unbiased Prediction and animal model into the genetic evaluation of pigs in the Slovak Republic. The analysis of slaughter parameters over the years 2000-2009 showed a decreasing tendency concerning the fat thickness in WL from 18.30 （2000） to 12.40 mm （2009）, which represents the reduction by 5.9 mm; in L from 16.40 mm （2000） to 12.10 mm （2009）, which means the reduction by 4.30 mm. There was also observed a positive tendency in the percentage of carcass lean meat in a slaughter body. The overall population average for the years 2000-2009 was as follows： WL 54.36% and L 54.61%. The highest values of meatiness in 2000-2009 were achieved in WL ＋ 1.59% and L ＋ 2.92%. Apart from the daily gains in all parameters, there were also found both highly significant statistical differences and interactions between a period and a breed.展开更多
Recent advances in molecular genetics techniques have made dense marker maps available, and the prediction of breeding value at the genome level has been employed in genetics research. However, an increasingly large n...Recent advances in molecular genetics techniques have made dense marker maps available, and the prediction of breeding value at the genome level has been employed in genetics research. However, an increasingly large number of markers raise both statistical and computational issues in genomic selection （GS）, and many methods have been developed for genomic prediction to address these problems, including ridge regression-best linear unbiased prediction （RR-BLUP）, genomic best linear unbiased prediction, BayesA, BayesB, BayesCπ, and Bayesian LASSO. In this paper, these methods were compared regarding inference under different conditions, using real data from a wheat data set and simulated scenarios with a small number of quantitative trait loci （QTL） （20）, a moderate number of QTL （60, 180） and an extreme number of QTL （540）. This study showed that the genetic architecture of a trait should be fully considered when a GS method is chosen. If a small amount of loci had a large effect on a trait, great differences were found between the predictive ability of various methods and BayesCπ was recommended. Although there was almost no significant difference between the predictive ability of BayesCπ andBayesB, BayesCπ is more feasible than BayesB for real data analysis. If a trait was controlled by a moderate number of genes, the absolute differences between the various methods were small, but BayesA was also found to be the most accurate method. Furthermore, BayesA was widely adaptable and could perform well with different numbers of QTL. If a trait was controlled by an extreme number of minor genes, almost no significant differences were detected between the predictive ability of various methods, but RR-BLUP slightly outperformed the others in both simulated scenarios and real data analysis, thus demonstrating its robustness and indicating that it was quite effective in this case.展开更多
基金Supported by the National High Technology Research and Development Program of China(863 Program)(No.2012AA10A403-2)the Taishan Scholar Project of Shandong Province of China
文摘Phenotypic and genetic parameters for growth-related traits in the half-smooth tongue sole, Cynoglossus semilaevis, were estimated in 22 full-sib families produced by normal and neo-male breeding stocks. As phenotypic males with female genotypes, neo-males are harmful in C. semilaevis aquaculture because they reduce overall production. The present study evaluated the difference in the growth-related traits： total length （TL）, body weight （BW） and square root of body weight （SQ_BW） at the age of 570 days between normal and neo-male offspring （neo-males used as male parents）. The difference in the proportion of females between normal and neo-male offspring was also assessed. Based on the linear mixed model, restricted maximum likelihood （REML） and best linear unbiased prediction （BLUP） were used to estimate various （co）variance components and estimated breeding values （EBVs） of growth-related traits. As a result, all the mean values of the three studied traits were significantly larger in normal offspring than in neo-male offspring. Additionally, the female proportion was significantly larger in normal offspring than in neo-male offspring. Heritability was 0.128＋0.066 2 for TL, 0.128-4-0.065 5 for BW and 0.132~0.062 9 for SQBW, all of which were low level heritabilities. The correlation coefficients of EBVs and phenotypic values of the target traits were 0.516 for TL, 0.524 for BW and 0.506 for SQ_BW, all of which were highly significant （P〈0.01）. Genetic correlations among TL, BW and SQ_BW were positive high （0.921-0.969） and higher than those of phenotype （0.711-0.748）, both of which had low standard errors （0.063-0.123 for genotype, and 0.010-0.018 for phenotype）. Compared with normal offspring, neo-male offspring have lower breeding values for each studied trait through EBVs comparison. Therefore, neo-male offspring should not be used as broodstock in a C. semilaevis breeding programs.
文摘This paper makes an analysis of the phenotype tendencies of dam populations White Large （WL） and Landrace （L） over the years 2000-2009 after the introduction of Multivariate Best Linear Unbiased Prediction and animal model into the genetic evaluation of pigs in the Slovak Republic. The analysis of slaughter parameters over the years 2000-2009 showed a decreasing tendency concerning the fat thickness in WL from 18.30 （2000） to 12.40 mm （2009）, which represents the reduction by 5.9 mm; in L from 16.40 mm （2000） to 12.10 mm （2009）, which means the reduction by 4.30 mm. There was also observed a positive tendency in the percentage of carcass lean meat in a slaughter body. The overall population average for the years 2000-2009 was as follows： WL 54.36% and L 54.61%. The highest values of meatiness in 2000-2009 were achieved in WL ＋ 1.59% and L ＋ 2.92%. Apart from the daily gains in all parameters, there were also found both highly significant statistical differences and interactions between a period and a breed.
基金supported by the National Basic Research Program of China(2011CB100100)the Priority Academic Program Development of Jiangsu Higher Education Institutions+4 种基金the National Natural Science Foundations(31391632,31200943,and31171187)the National High-tech R&D Program(863 Program)(2014AA10A601-5)the Natural Science Foundations of Jiangsu Province(BK2012261)the Natural Science Foundation of the Jiangsu Higher Education Institutions(14KJA210005)the Innovative Research Team of Universities in Jiangsu Province
文摘Recent advances in molecular genetics techniques have made dense marker maps available, and the prediction of breeding value at the genome level has been employed in genetics research. However, an increasingly large number of markers raise both statistical and computational issues in genomic selection （GS）, and many methods have been developed for genomic prediction to address these problems, including ridge regression-best linear unbiased prediction （RR-BLUP）, genomic best linear unbiased prediction, BayesA, BayesB, BayesCπ, and Bayesian LASSO. In this paper, these methods were compared regarding inference under different conditions, using real data from a wheat data set and simulated scenarios with a small number of quantitative trait loci （QTL） （20）, a moderate number of QTL （60, 180） and an extreme number of QTL （540）. This study showed that the genetic architecture of a trait should be fully considered when a GS method is chosen. If a small amount of loci had a large effect on a trait, great differences were found between the predictive ability of various methods and BayesCπ was recommended. Although there was almost no significant difference between the predictive ability of BayesCπ andBayesB, BayesCπ is more feasible than BayesB for real data analysis. If a trait was controlled by a moderate number of genes, the absolute differences between the various methods were small, but BayesA was also found to be the most accurate method. Furthermore, BayesA was widely adaptable and could perform well with different numbers of QTL. If a trait was controlled by an extreme number of minor genes, almost no significant differences were detected between the predictive ability of various methods, but RR-BLUP slightly outperformed the others in both simulated scenarios and real data analysis, thus demonstrating its robustness and indicating that it was quite effective in this case.
