Biometrical Genetics

1992 ◽  
pp. 55-70 ◽  
Author(s):  
Michael C. Neale ◽  
Lon R. Cardon
Keyword(s):  
Biometrical Genetics

The genetic framework of plant breeding

1981 ◽  
Vol 292 (1062) ◽  
pp. 407-419 ◽  
Keyword(s):  
Plant Breeding ◽  
Recombinant Inbred ◽  
Recombinant Inbred Lines ◽  
Inbred Lines ◽  
Single Seed Descent ◽  
Crop Species ◽  
Biometrical Genetics ◽  
Mendelian Genetics ◽  
Linkage Disequilibria ◽  
Random Samples

The phenotypic variation that the breeder must manipulate to produce improved genotypes typically contains contributions from both heritable and non-heritable sources as well as from interactions between them. The totality of this variation can be understood only in terms of a methodology such as that of biometrical genetics - an extension of classical Mendelian genetics that retains all of its analytical, interpretative and predictive powers but only in respect of the net or summed effects of all contributing gene loci. In biometrical genetics the statistics that describe the phenotypic distributions are themselves completely described by heritable components based on the known types of gene action and interaction in combination with nonheritable components defined by the statistical properties of the experimental design. Biometrical genetics provides a framework for investigating the genetical basis and justification for current plant breeding strategies that are typified by the production of F 1 hybrids at one extreme and recombinant inbred lines at the other. From the early generations of a cross it can extract estimates of the heritable components of the phenotypic distributions that provide all the information required to interpret the cause of F 1 heterosis and predict the properties of any generation that can subsequently be derived from the cross. Applications to crosses in experimental and crop species show that true overdominance is not a cause of F 1 heterosis, although spurious overdominance arising from linkage disequilibria and non-allelic interactions can be. Predictions of the phenotypic distributions and ranges of recombinant inbred lines that should be extractable from these crosses are confirmed by observations made on random samples of inbred families produced from them by single seed descent. Within these samples, recombinant inbred lines superior to existing inbred lines and their F 1 hybrids are observed with the predicted frequencies.

scholarly journals Biometrical genetics

Heredity ◽  
1972 ◽  
Vol 29 (1) ◽  
pp. 101-102
Author(s):  
Kenneth Mather ◽  
J L Jinks
Keyword(s):  
Biometrical Genetics

A Century of Biometrical Genetics

Biometrics ◽  
2000 ◽  
Vol 56 (3) ◽  
pp. 659-666 ◽  
Author(s):  
Robert C. Elston ◽  
Elizabeth A. Thompson
Keyword(s):  
Biometrical Genetics

Discriminant Analysis in Biometrical Genetics

Nature ◽  
1961 ◽  
Vol 191 (4796) ◽  
pp. 1420-1420
Author(s):  
S. K. JAIN
Keyword(s):  
Discriminant Analysis ◽  
Biometrical Genetics

Biometrical Genetics.

Biometrics ◽  
1972 ◽  
Vol 28 (2) ◽  
pp. 638 ◽  
Author(s):  
K. Mather ◽  
J. L. Jinks
Keyword(s):  
Biometrical Genetics

scholarly journals The biometrical genetics of competitive parameters in Drosophila melanogaster

Heredity ◽  
1990 ◽  
Vol 64 (2) ◽  
pp. 223-231 ◽  
Author(s):  
Mortaza Hemmat ◽  
Paul Eggleston
Keyword(s):  
Drosophila Melanogaster ◽  
Biometrical Genetics

scholarly journals THE GENETICS OF COPPER TOLERANCE IN THE YELLOW MONKEY FLOWER, MIMULUS GUTTATUS. I. CROSSES TO NONTOLERANTS

Genetics ◽  
1979 ◽  
Vol 91 (3) ◽  
pp. 553-563
Author(s):  
Mark R Macnair
Keyword(s):  
Threshold Model ◽  
Copper Tolerance ◽  
Additive Effects ◽  
Mimulus Guttatus ◽  
Biometrical Genetics ◽  
First Order ◽  
Monkey Flower

ABSTRACT The biometrical genetics of copper tolerance has been investigated in two Californian populations of Mimulus guttatus by crosses to a nontolerant British population. A simple biometrical model involving only additive and dominance effects is not sufficient. When the first order interactions are included, the model is shown to fit the data. Interactions between the dominance effects of different loci, and between dominance and additive effects, are the most important. These interactions can be explained either by a threshold model, or by postulating dominance modification.

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