Library

X
feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Electronic Resource
    Electronic Resource
    Estimating major gene effects with partial information using Gibbs sampling (1996)
    Springer
    Theoretical and applied genetics 93 (1996), S. 1090-1097 
    Details
    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
    URL: http://dx.doi.org/10.1007/s001220050340
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
  • 2
    Electronic Resource
    Electronic Resource
    Estimating major gene effects with partial information using Gibbs sampling (1996)
    Springer
    Theoretical and applied genetics 93 (1996), S. 1090-1097 
    Details
    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
    URL: http://dx.doi.org/10.1007/BF00230130
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
  • 3
    Electronic Resource
    Electronic Resource
    Prediction of rates of inbreeding in populations undergoing index selection (1994)
    Springer
    Theoretical and applied genetics 87 (1994), S. 878-892 
    Details
    ISSN: 1432-2242
    Keywords: Inbreeding rate ; Effective population size ; Index selection
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract For populations undergoing mass selection, previous studies have shown that the rate of inbreeding is directly related to the mean and variance of long-term contributions from ancestors to descendants, and thus prediction of the rate of inbreeding can be achieved via the prediction of long-term contributions. In this paper, it is shown that the same relationship between the rate of inbreeding and long-term contributions is found when selection is based on an index of individual and sib records (index selection) and where sib records may be influenced by a common environment. In these situations, rates of inbreeding may be considerably higher than under mass selection. An expression for the rate of inbreeding is derived for populations undergoing index selection based on variances of (one-generation) family size and incorporating the concept of long-term selective advantage. When the mating structure is hierarchical, and when half-sib records are included in the index, the correlation between parental breeding values and the index values of their offspring is higher for male parents than female parents. This introduces an important asymmetry between the contributions of male and female ancestors to the evolution of inbreeding which is not present when selection is based on individual and/or full-sib records alone. The prediction equation for index selection accounts for this asymmetry. The prediction is compared to rates of inbreeding calculated from simulation. The prediction is good when family size is small relative to the number selected. The reasons for overprediction in other situations are discussed.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00221142
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
  • 4
    Electronic Resource
    Electronic Resource
    Effective sizes of livestock populations to prevent a decline in fitness (1994)
    Springer
    Theoretical and applied genetics 89 (1994), S. 1019-1026 
    Details
    ISSN: 1432-2242
    Keywords: Critical effective population size Inbreeding depression ; Natural selection ; Fitness Conservational biology
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract In livestock populations, fitness may decrease due to inbreeding depression or as a negatively correlated response to artificial selection. On the other hand, fitness may increase due to natural selection. In the absence of a correlated response due to artificial selection, the critical population size at which the increase due to natural selection and the decrease due to inbreeding depression balance each other is approximately D/2σwa 2, where D=the inbreeding depression of fitness with complete inbreeding, and σwa 2=the additive genetic variance of fitness. This simple expression agrees well with results from transmission probability matrix methods. If fitness declines as a correlated negative response to artificial selection, then a large increase in the critical effective population size is needed. However, if the negative response is larger than the response to natural selection, a reduction in fitness cannot be prevented. From these results it is concluded that a negative correlation between artificial and natural selection should be avoided. Effective sizes to prevent a decline in fitness are usually larger than those which maximize genetic gain of overall efficiency, i.e., the former is a more stringent restriction on effective size. In the examples presented, effective sizes ranged from 31 to 250 animals per generation.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00224533
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
  • 5
    Electronic Resource
    Electronic Resource
    Methods for predicting rates of inbreeding in selected populations (1990)
    Springer
    Theoretical and applied genetics 80 (1990), S. 503-512 
    Details
    ISSN: 1432-2242
    Keywords: Inbreeding ; Effective size ; Selection
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Summary In selected populations, families superior for the selected trait are likely to contribute more offspring to the next generation than inferior families and, as a consequence, the rate of inbreeding is likely to be higher in selected populations than in randomly mated populations of the same structure. Methods to predict rates of inbreeding in selected populations are discussed. The method of Burrows based on probabilities of coselection is reappraised in conjunction with the transition matrix method of Woolliams. The method of Latter based on variances and covariances of family size is also examined. These methods are one-generation approaches in the sense that they only account for selective advantage over a single generation, from parents to offspring. Two-generation methods are developed that account for selective advantage over two generations, from grandparent to grandoffspring as well as from parent to offspring. Predictions are compared to results from simulation. The best one-generation method was found to underpredict rates of inbreeding by 10–25%, and the two-generation methods were found to underpredict rates of inbreeding by 9–18%.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00226752
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
  • 6
    Electronic Resource
    Electronic Resource
    Predicting age-age genetic correlations in tree-breeding programs: a case study of Pinus taeda L. (2000)
    Springer
    Theoretical and applied genetics 100 (2000), S. 199-206 
    Details
    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
    URL: http://dx.doi.org/10.1007/s001220050027
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...