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  • 1
    ISSN: 1432-2242
    Keywords: Key words Age-age genetic correlations ; Phenotypic correlations ; Conifers ; Tree breeding ; Woody perennials
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract  A meta-analysis of 520 parents and 51,439 individuals was used to develop two equations for predicting age-age genetic correlations in Pinus taeda L. Genetic and phenotypic family mean correlations and heritabilities were estimated for ages ranging from 2 to 25 years on 31 sites in the southern U.S. and Zimbabwe. Equations for predicting age-age correlations based on P. taeda populations from west and east of the Mississippi River proved statistically different. Both predictive equations proved conservative for validation datasets consisting of younger tests in the U.S. and Zimbabwe. Age-dependent log-linear predictive equations were favored over growth-dependent equations. All P. taeda predictive equations based on genetic correlations favored earlier selection when compared to a generalized conifer predictive equation based on phenotypic correlations. The age-age correlations structure showed stability independent of planting density and across a wide range of family sizes.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Theoretical and applied genetics 93 (1996), S. 1090-1097 
    ISSN: 1432-2242
    Keywords: Key words Estimation ; Gibbs-sampling ; Major-gene ; Selection ; Dominance
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract A method for estimating major gene effects using Gibbs sampling to infer genotype of individuals with unknown values, was compared with a standard mixed-model analysis. The purpose of this study was to evaluate the effect of including information of individuals with unknown genotypes on the estimates and their error variances (Ve) of the single-gene effects. When genotypes were known for all the individuals, results using the Gibbs method (GS) were similar to those obtained with the mixed model (MM). In the absence of selection, when information from individuals with unknown genotypes was included, GS yielded unbiased estimates of the major gene effects while reducing the Ve associated with them. This reduction in Ve depended on the gene frequency and mode of action of the major locus. For the additive effect, the reduction in Ve ranged from 29 to 69% of the total reduction which would have been obtained if all individuals had had a known genotype. Similarly the reduction in Ve found for the dominance effect ranged from 12 to 58%. Estimates using GS generally had small detectable biases when the polygenic heritability used in the analysis was inflated or estimated simultaneously. However, the benefit of using information from individuals with unknown genotypes was still maintained when comparing the mean square error of the estimates using either GS or MM when genotypes are only known for a subset of the population. When the population has been under selection, the use of Gibbs sampling to incorporate information of individuals without genotypes reduced substantially the bias and mean square error found for MM analysis on partial data. Nevertheless, there was some bias detected using Gibbs sampling. The gene frequency of the major gene in the base population was also well estimated despite its change over generations due to selection.
    Type of Medium: Electronic Resource
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Theoretical and applied genetics 93 (1996), S. 1090-1097 
    ISSN: 1432-2242
    Keywords: Estimation ; Gibbs-sampling ; Major-gene ; Selection ; Dominance
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract A method for estimating major gene effects using Gibbs sampling to infer genotype of individuals with unknown values, was compared with a standard mixed-model analysis. The purpose of this study was to evaluate the effect of including information of individuals with unknown genotypes on the estimates and their error variances (Ve) of the single-gene effects. When genotypes were known for all the individuals, results using the Gibbs method (GS) were similar to those obtained with the mixed model (MM). In the absence of selection, when information from individuals with unknown genotypes was included, GS yielded unbiased estimates of the major gene effects while reducing the Ve associated with them. This reduction in Ve depended on the gene frequency and mode of action of the major locus. For the additive effect, the reduction in Ve ranged from 29 to 69% of the total reduction which would have been obtained if all individuals had had a known genotype. Similarly the reduction in Ve found for the dominance effect ranged from 12 to 58%. Estimates using GS generally had small detectable biases when the polygenic heritability used in the analysis was inflated or estimated simultaneously. However, the benefit of using information from individuals with unknown genotypes was still maintained when comparing the mean square error of the estimates using either GS or MM when genotypes are only known for a subset of the population. When the population has been under selection, the use of Gibbs sampling to incorporate information of individuals without genotypes reduced substantially the bias and mean square error found for MM analysis on partial data. Nevertheless, there was some bias detected using Gibbs sampling. The gene frequency of the major gene in the base population was also well estimated despite its change over generations due to selection.
    Type of Medium: Electronic Resource
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
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