Genomic Prediction of Average Daily Gain, Back-Fat Thickness, and Loin Muscle Depth Using Different Genomic Tools in Canadian Swine Populations
نویسندگان
چکیده
منابع مشابه
Accuracy of Genomic Prediction under Different Genetic Architectures and Estimation Methods
The accuracy of genomic breeding value prediction was investigated in various levels of reference population size, trait heritability and the number of quantitative trait locus (QTL). Five Bayesian methods, including Bayesian Ridge regression, BayesA, BayesB, BayesC and Bayesian LASSO, were used to estimate the marker effects for each of 27 scenarios resulted from combining three levels for her...
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The objective of this study was to evaluate the imputation accuracy of parent-offspring trios under different scenarios. By using simulated datasets, the performance Bayesian LASSO in genomic prediction was also examined. The genome consisted of 5 chromosomes and each chromosome was set as 1 Morgan length. The number of SNPs per chromosome was 10000. One hundred QTLs were randomly distributed a...
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Recurrent selection (RS) has been used in plant breeding to successively improve synthetic and other multiparental populations. Synthetics are generated from a limited number of parents [Formula: see text] but little is known about how [Formula: see text] affects genomic selection (GS) in RS, especially the persistency of prediction accuracy ([Formula: see text]) and genetic gain. Synthetics we...
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Genomic prediction is expected to considerably increase genetic gains by increasing selection intensity and accelerating the breeding cycle. In this study, marker effects estimated in 255 diverse maize (Zea mays L.) hybrids were used to predict grain yield, anthesis date, and anthesis-silking interval within the diversity panel and testcross progenies of 30 F(2)-derived lines from each of five ...
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ژورنال
عنوان ژورنال: Frontiers in Genetics
سال: 2021
ISSN: 1664-8021
DOI: 10.3389/fgene.2021.665344