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- Alvarez-Castro, Jose, et al.
(author)
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Modelling of genetic interactions improves prediction of hybrid patterns : a case study in domestic fowl
- 2012
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In: Genetical Research. - 0016-6723 .- 1469-5073. ; 94:5, s. 255-266
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Journal article (peer-reviewed)abstract
- Summary A major challenge in complex trait genetics is to unravel how multiple loci and environmental factors together cause phenotypic diversity. Both first (F1) and second (F2) generation hybrids often display phenotypes that deviate from what is expected under intermediate inheritance. We have here studied two chicken F2 populations generated by crossing divergent chicken lines to assess how epistatic loci, identified in earlier quantitative trait locus (QTL) studies, contribute to hybrid deviations from the mid-parent phenotype. Empirical evidence suggests that the average phenotypes of the intercross birds tend to be lower than the midpoint between the parental means in both crosses. Our results confirm that epistatic interactions, despite a relatively small contribution to the phenotypic variance, play an important role in the deviation of hybrid phenotypes from the mid-parent values (i.e. multi-locus hybrid genotypes lead to lower rather than higher body weights). To a lesser extent, dominance also appears to contribute to the mid-parent deviation, at least in one of the crosses. This observation coincides with the hypothesis that hybridization tends to break up co-adapted gene complexes, i.e. generate Bateson-Dobzhansky-Muller incompatibilities.
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- Felleki, Majbritt, et al.
(author)
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Estimation of breeding values for mean and dispersion, their variance and correlation using double hierarchical generalized linear models
- 2012
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In: Genetics Research. - : Cambridge University Press. - 0016-6723 .- 1469-5073. ; 94:6, s. 307-317
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Journal article (peer-reviewed)abstract
- The possibility of breeding for uniform individuals by selecting animals expressing a small response to environment has been studied extensively in animal breeding. Bayesian methods for fitting models with genetic components in the residual variance have been developed for this purpose, but have limitations due to the computational demands. We use the hierarchical (h)-likelihood from the theory of double hierarchical generalized linear models (DHGLM) to derive an estimation algorithm that is computationally feasible for large datasets. Random effects for both the mean and residual variance parts of the model are estimated together with their variance/covariance components. An important feature of the algorithm is that it can fit a correlation between the random effects for mean and variance. An h-likelihood estimator is implemented in the R software and an iterative reweighted least square (IRWLS) approximation of the h-likelihood is implemented using ASReml. The difference in variance component estimates between the two implementations is investigated, as well as the potential bias of the methods, using simulations. IRWLS gives the same results as h-likelihood in simple cases with no severe indication of bias. For more complex cases, only IRWLS could be used, and bias did appear. The IRWLS is applied on the pig litter size data previously analysed by Sorensen & Waagepetersen (2003) using Bayesian methodology. The estimates we obtained by using IRWLS are similar to theirs, with the estimated correlation between the random genetic effects being −0·52 for IRWLS and −0·62 in Sorensen & Waagepetersen (2003).
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- Jacobsson, Lina, et al.
(author)
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Many QTLs with minor additive effects are associated with a large difference in growth between two selection lines in chickens
- 2005
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In: Genetical Research. - 0016-6723 .- 1469-5073. ; 86:2, s. 115-125
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Journal article (peer-reviewed)abstract
- Two growth-selected lines in chickens have been developed from a single founder population bydivergent selection for body weight at 56 days of age. After more than 40 generations of selectionthey show a nine-fold difference in body weight at selection age and large differences in growth rate,appetite, fat deposition and metabolic characteristics. We have generated a large intercross betweenthese lines comprising more than 800 F2 birds. QTL mapping revealed 13 loci affecting growth.The most striking observation was that the allele in the high weight line in all cases was associatedwith enhanced growth, but each locus explained only a small proportion of the phenotypic varianceusing a standard QTL model (1.3–3.1%). This result is in sharp contrast to our previous studywhere we reported that the two-fold difference in adult body size between the red junglefowl andWhite Leghorn domestic chickens is explained by a small number of QTLs with large additiveeffects. Furthermore, no QTLs for anorexia or antibody response were detected despite largedifferences for these traits between the founder lines. The result is an excellent example where alarge phenotypic difference between populations occurs in the apparent absence of any single locuswith large phenotypic effects. The study underscores the need for powerful experimental designs ingenetic studies of multifactorial traits. No QTL at all would have reached genome-wide significanceusing a less powerful design (e.g. approx. 200 F2 individuals) regardless of the nine-fold phenotypicdifference between the founder lines for the selected trait.
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