Literature DB >> 24430832

Simulation of quantitative characters from qualitatively acting genes : II. Orthogonal subdivision of hereditary variance in two-locus genetic systems.

S Jana1.   

Abstract

The phenotypes associated with the nine genotypes in a quantitative genetic system consisting of two loci, each having two alleles can be described in terms of nine parameters, giving a system of nine linear equations. Populations with desired magnitudes and known nature of intra- and interlocus interactions are obtained by the use of this linear combination model. The total sums of squares for genotypes in these populations are partitioned into orthogonal components denoting additive and dominance effects of the two loci and the four types of nonallelic interactions between them. In most cases, the relative magnitudes of dominance and epistatic variances are found to be considerably smaller than the actual proportions of these genetic effects. Duplicate interaction produces larger epistatic variance than complementary type of gene interaction. At the higher levels of epistasis, dominant epistasis yields much larger epistatic variance than recessive epistasis. No epistatic variance is produced in the absence of epistatic effects. But, appreciable contributions of additive and dominance gene actions to the total genotypic variability are obtained even in the complete absence of these effects, if additive × dominance and dominance × dominance epistatic effects, respectively, are present. It is concluded that in elucidating the nature of gene action in simplified genetic systems, the estimates of first degree parameters obtained from the linear combination model are more useful than the orthogonal components of genotypic sum of squares.

Year:  1972        PMID: 24430832     DOI: 10.1007/BF00583413

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  7 in total

1.  An Extension of the Concept of Partitioning Hereditary Variance for Analysis of Covariances among Relatives When Epistasis Is Present.

Authors:  C C Cockerham
Journal:  Genetics       Date:  1954-11       Impact factor: 4.562

2.  Nonallelic Gene Interactions in the Inheritance of Quantitative Characters in Barley.

Authors:  A C Fasoulas; R W Allard
Journal:  Genetics       Date:  1962-07       Impact factor: 4.562

3.  Simulation of quantitative characters from qualitatively acting genes : I. Nonallelic gene interactions involving two or three loci.

Authors:  S Jana
Journal:  Theor Appl Genet       Date:  1971-01       Impact factor: 5.699

4.  Biometrical analysis with two or three gene loci.

Authors:  S Jana
Journal:  Can J Genet Cytol       Date:  1972-03

5.  Complementary and duplicate gene interactions in biometrical genetics.

Authors:  K Mather
Journal:  Heredity (Edinb)       Date:  1967-02       Impact factor: 3.821

6.  Biometrical genetics with one or two loci. I. The choice of a specific genetic model.

Authors:  J Stewart
Journal:  Heredity (Edinb)       Date:  1969-05       Impact factor: 3.821

7.  The Inheritance of Gossypol Level in Gossypium I. Additive, Dominance, Epistatic, and Maternal Effects Associated with Seed Gossypol in Two Varieties of GOSSYPIUM HIRSUTUM L.

Authors:  J A Lee; C C Cockerham; F H Smith
Journal:  Genetics       Date:  1968-06       Impact factor: 4.562

  7 in total
  5 in total

Review 1.  Integrating physical and genetic maps: from genomes to interaction networks.

Authors:  Andreas Beyer; Sourav Bandyopadhyay; Trey Ideker
Journal:  Nat Rev Genet       Date:  2007-09       Impact factor: 53.242

2.  Epistatic contributions to quantitative traits in Tribolium castaneum : I. Traits not closely related to fitness.

Authors:  R E Goodwill; R D Walker
Journal:  Theor Appl Genet       Date:  1978-07       Impact factor: 5.699

3.  Investigations on inheritance of quantitative characters in animals by gene markers I. Methods.

Authors:  H Geldermann
Journal:  Theor Appl Genet       Date:  1975-01       Impact factor: 5.699

4.  Current applications of models of genetic effects with interactions across the genome.

Authors:  José M Alvarez-Castro
Journal:  Curr Genomics       Date:  2012-04       Impact factor: 2.236

5.  Maximal extraction of biological information from genetic interaction data.

Authors:  Gregory W Carter; David J Galas; Timothy Galitski
Journal:  PLoS Comput Biol       Date:  2009-04-03       Impact factor: 4.475

  5 in total

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