Determining Scales and the Use of Transformations in Studies on Weight per Locule of Tomato Fruit

Powers, LeRoy

doi:10.2307/3001495

Cited by 42 publications

(12 citation statements)

References 2 publications

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“…Unfortunately, the same transformation exaggerates deviations in other families such that the cumulative chi square actually increases. This result is reminiscent of Powers' studies of tomato fruit characters, in which transformations useful in some crosses (yielding approximate additivity) were detrimental in others (Powers 1950(Powers , 1951.…”

Section: Discussionmentioning

confidence: 67%

Epistasis in Monkeyflowers

Kelly

2005

Genetics

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Epistasis contributes significantly to intrapopulation variation in floral morphology, development time, and male fitness components of Mimulus guttatus. This is demonstrated with a replicated line-cross experiment involving slightly over 7000 plants. The line-cross methodology is based on estimates for means. It thus has greater power than the variance partitioning approaches historically used to estimate epistasis within populations. The replication of the breeding design across many pairs of randomly extracted, inbred lines is necessary given the diversity of multilocus genotypes residing within an outbred deme. Male fitness is shown to exhibit synergistic epistasis, an accelerating decline in fitness with inbreeding. Synergism is a necessary, but not sufficient, condition for a mutational deterministic hypothesis for the evolutionary maintenance of sexual reproduction. Unlike male fitness measures, flower morphology and development time yield positive evidence of epistasis but not of synergism. The results for these traits suggest that epistatic effects are variable across genetic backgrounds or sets of interacting loci.

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Section: Discussionmentioning

confidence: 67%

Epistasis in Monkeyflowers

Kelly

2005

Genetics

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“…Powers, 1950;Gingerich, 2000). Most models in quantitative genetics rely on the assumption that effects tend to combine additively, and that both genetic and environmental effects are normally distributed.…”

Section: (I) Scalingmentioning

confidence: 99%

A modelling framework for the analysis of artificial-selection time series

2011

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Artificial-selection experiments constitute an important source of empirical information for breeders, geneticists and evolutionary biologists. Selected characters can generally be shifted far from their initial state, sometimes beyond what is usually considered as typical inter-specific divergence. A careful analysis of the data collected during such experiments may thus reveal the dynamical properties of the genetic architecture that underlies the trait under selection. Here, we propose a statistical framework describing the dynamics of selection-response time series. We highlight how both phenomenological models (which do not make assumptions on the nature of genetic phenomena) and mechanistic models (explaining the temporal trends in terms of e.g. mutations, epistasis or canalization) can be used to understand and interpret artificial-selection data. The practical use of the models and their implementation in a software package are demonstrated through the analysis of a selection experiment on the shape of the wing in Drosophila melanogaster.

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“…Barring this, one will probably have to exclude dominance variance, as in controlled experiments in mostly domesticated plants and animals, its quantity is quite small compared to additive genetic variance, particularly when a transformation is found that converts the phenotypic distribution to Gaussian (Powers 1950). However, theory predicts that dominance variance should be relatively large for fitness characters (Mousseau and Roff 1987), making its inference relevant for field studies of life history characters.…”

Section: The Precision Of Inference and Experimental Designmentioning

confidence: 99%

A Marker-Based Method for Inferences About Quantitative Inheritance in Natural Populations

1996

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Abstract.-A marker-based method for studying quantitative genetic characters in natural populations is presented and evaluated. The method involves regressing quantitative trait similarity on marker-estimated relatedness between individuals. A procedure is first given for estimating the narrow sense heritability and additive genetic correlations among traits, incorporating shared environments. Estimation of the actual variance of relatedness is required for heritability, but not for genetic correlations. The approach is then extended to include isolation by distance of environments, dominance, and shared levels of inbreeding. Investigations of statistical properties show that good estimates do not require great marker polymorphism, but rather require significant variation of actual relatedness; optimal allocation generally favors sampling many individuals at the expense of assaying fewer marker loci; when relatedness declines with physical distance, it is optimal to restrict comparisons to within a certain distance; the power to estimate shared environments and inbreeding effects is reasonable, but estimates of dominance variance may be difficult under certain patterns of relationship; and any linkage of markers to quantitative trait loci does not cause significant problems. This marker-based method makes possible studies with long-lived organisms or with organisms difficult to culture, and opens the possibility that quantitative trait expression in natural environments can be analyzed in an unmanipulative way.

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Determining Scales and the Use of Transformations in Studies on Weight per Locule of Tomato Fruit

Cited by 42 publications

References 2 publications

Epistasis in Monkeyflowers

Epistasis in Monkeyflowers

A modelling framework for the analysis of artificial-selection time series

A Marker-Based Method for Inferences About Quantitative Inheritance in Natural Populations

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