Estimation of variance components based on diallel model

Venkateswarlu, K.; Ponnuswamy, K.; Srinivasan, M. R.

doi:10.1016/s0025-5564(98)10007-x

Cited by 2 publications

(2 citation statements)

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“…Mixed model approaches, such as REML, MINQUE, GLS, and OLS, can provide a powerful tool for circumventing those difficult problems. To our knowledge, however, no one has introduced these methods into such a statistical analysis although Venkateswarlu et al (1998) proposed variance components methods for a classic diallel model. The employment of mixed model approaches endows our investigation with great flexibility and versatility in experimental designs and statistical analyses.…”

Section: Discussionmentioning

confidence: 99%

“…Genetic parameters are frequently estimated from the relatives, mostly derived from particular mating systems (relating to the mating design) and grown under given environmental conditions (referring to the environmental design), e.g., firstdegree parameters (Anderson and Kempthorne 1954;Griffing 1956;Hayman 1958a;Eberhart and Gardner 1966;Gardner and Eberhart 1966;Mather and Jinks 1971;Cockerham 1980), second-degree parameters (Comstock and Robinson 1948;Griffing 1956;Hayman 1960a;Cockerham 1980), and so forth. Out of these mating designs, diallel analysis can provide much useful genetic information on polygenes contributing to the trait differences among parents, and thus diallel cross designs have been widely employed in genetic and breeding experiments for exploring the mechanism of inheritance concerning the polygenic variation displayed in parents or in the reference population from which parents are sampled (Yates 1947;Hayman 1954Hayman , 1958bHayman , 1960bGriffing 1956;Kempthorne 1956;Eberhart and Gardner 1966;Gardner and Eberhart 1966;Topham 1966;Cockerham and Weir 1977;Falconer 1981;Venkateswarlu et al 1998).…”

Section: Introductionmentioning

confidence: 99%

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Estimating effects of a single gene and polygenes on quantitative traits from a diallel design

Lou

Yang

2006

Genetica

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A genetic model is developed with additive and dominance effects of a single gene and polygenes as well as general and specific reciprocal effects for the progeny from a diallel mating design. The methods of ANOVA, minimum norm quadratic unbiased estimation (MINQUE), restricted maximum likelihood estimation (REML), and maximum likelihood estimation (ML) are suggested for estimating variance components, and the methods of generalized least squares (GLS) and ordinary least squares (OLS) for fixed effects, while best linear unbiased prediction, linear unbiased prediction (LUP), and adjusted unbiased prediction are suggested for analyzing random effects. Monte Carlo simulations were conducted to evaluate the unbiasedness and efficiency of statistical methods involving two diallel designs with commonly used sample sizes, 6 and 8 parents, with no and missing crosses, respectively. Simulation results show that GLS and OLS are almost equally efficient for estimation of fixed effects, while MINQUE (1) and REML are better estimators of the variance components and LUP is most practical method for prediction of random effects. Data from a Drosophila melanogaster experiment (Gilbert 1985a, Theor appl Genet 69:625-629) were used as a working example to demonstrate the statistical analysis. The new methodology is also applicable to screening candidate gene(s) and to other mating designs with multiple parents, such as nested (NC Design I) and factorial (NC Design II) designs. Moreover, this methodology can serve as a guide to develop new methods for detecting indiscernible major genes and mapping quantitative trait loci based on mixture distribution theory. The computer program for the methods suggested in this article is freely available from the authors.

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Section: Discussionmentioning

confidence: 99%