Analysis of genetic changes in radiated and non-radiated bulk oat (Avena sativa L.) populations

Summary In both radiated and non-radiated oat populations inbreeding coefficients increased more slowly than was expected on the assumption of full selfing and equal selective values for homozygotes and heterozygotes. Assuming 1% outcrossing for oats and a selective value of 1.0 for the mean, the heterozygotes for two loci governing crown rust reaction have an advantage of 50% over the homozygotes. This study supports previous observations that the heterozygote often has a decided advantage in predominantly self-pollinated crops.     

ABC as a flexible framework to estimate demography over space and time: some cons,many pros

The analysis of genetic variation to estimate demographic and historical parameters and to quantitatively compare alternative scenarios recently gained a powerful and flexible approach: the Approximate Bayesian Computation (ABC). The likelihood functions does not need to be theoretically specified, but posterior distributions can be approximated by simulation even assuming very complex population models including both natural and human‐induced processes. Prior information can be easily incorporated and the quality of the results can be analysed with rather limited additional effort. ABC is not a statistical analysis per se, but rather a statistical framework and any specific application is a sort of hybrid between a simulation and a data‐analysis study. Complete software packages performing the necessary steps under a set of models and for specific genetic markers are already available, but the flexibility of the method is better exploited combining different programs. Many questions relevant in ecology can be addressed using ABC, but adequate amount of time should be dedicated to decide among alternative options and to evaluate the results. In this paper we will describe and critically comment on the different steps of an ABC analysis, analyse some of the published applications of ABC and provide user guidelines.     

Actuarial senescence in laboratory and field populations of Lepidoptera

1. Recent observations of actuarial senescence – an increase in mortality rate with age – have challenged the assertion that the brevity of adult insect life spans precludes ageing. 2. Here the rate of senescence in 22 species of Lepidoptera was quantified by fitting demographic models to adult survivorship data drawn from a range of field and laboratory studies. 3. Senescence was evident in all 22 species investigated, with a model of age‐related mortality consistently fitting the survivorship curves significantly better than an alternative model which assumes constant mortality. 4. The rates of senescence varied significantly among species. The rates of senescence also differed significantly between sexes for all species tested, but not in a consistent way.     

A variable selection index for the compensation of correlated genetic change

Summary A selection index for two traits has been constructed which allows partial restriction for one of the traits. The index is used in a situation where correlated response to selection in one sex is compenstated for by selection for other traits in the opposite sex. A numerical example is given.     

Describing Ordinal Odds Ratios for Stratified r × c Tables

For an r × ctable with ordinal responses, odds ratios are commonly used to describe the relationship between the row and column variables. This article shows two types of ordinal odds ratios where local‐global odds ratios are used to compare several groups on a c‐category ordinal response and a global odds ratio is used to measure the global association between a pair of ordinal responses. When there is a stratification factor, we consider Mantel‐Haenszel (MH) type estimators of these odds ratios to summarize the association from several strata. Like the ordinary MH estimator of the common odds ratio for several 2 × 2 contingency tables, the estimators are used when the association is not expected to vary drastically among the strata. Also, the estimators are consistent under the ordinary asymptotic framework in which the number of strata is fixed and also under sparse asymptotics in which the number of strata grows with the sample size. Compared to the maximum likelihood estimators, simulations find that the MH type estimators perform better especially when each stratum has few observations. This article provides variances and covariances formulae for the local‐global odds ratios estimators and applies the bootstrap method to obtain a standard error for the global odds ratio estimator. At the end, we discuss possible ways of testing the homogeneity assumption.     

Experimental study of the influence of errors of genetic correlation estimates on unrestricted,optimum, and desired gains selection indices

Summary Effects of errors in estimates of the genetic correlation on the accuracy of unrestricted, optimum, and desired gains selection indices were examined experimentally in Tribolium castaneum. Three lines were selected for three generations for pupal weight at 21 days and adult weight at 31 days, using unrestricted (I9), optimum (O9), and desired gains (G9) index selection methods. The genetic correlation between pupal and adult weights in the base population was 0.95. The optimum index was designed to set the response of pupal weight by a fixed amount, while in the desired gains index the responses of pupal and adult weights were specified as being equal to 31. Three other indices were constructed using a deliberately incorrect genetic correlation (0.25), i.e., unrestricted (I2), optimum (O2), and desired gains (G2). Responses observed in unrestricted index lines (I9 versus I2) and optimum index lines (O9 versus O2) did not differ significantly, even though lines I9 and I2 differed in a practical sense. Responses in desired gains index lines (G9 versus G2) differed significantly. Responses obtained for aggregate genotype (pupal weight + adult weight) and for the component traits were greater in line I9 than those obtained in line I2. Responses obtained in the O9 and O2 lines for pupal and adult weights were similar, while those obtained in the G9 and G2 lines were similar for pupal weight but not (P<0.05) for adult weight. Therefore, underestimation of the genetic correlation seems to affect the efficiency of a desired gains index more than that of unrestricted or optimum indices.     

Bias of maximum likelihood estimator of intraclass correlation

Summary A bias correction was derived for the maximum likelihood estimator (MLE) of the intraclass correlation. The bias consisted of two parts: a correction from MLE to the analysis of variance estimator (ANOVA) and the bias of ANOVA. The total possible bias was always negative and depended upon both the degree of correlation and the design size and balance. The first part of the bias was an exact algebraic expression from MLE to ANOVA, and the corrected estimator by this part was ANOVA. It was also shown that the first correction term was equivalent to Fisher's reciprocal bias correction on hisZ scores. The total possible bias of MLE was large for small and moderate samples. Relative biases were larger for small parametric values and vice versa. To ensure a relative bias less than 10% assuming an intraclass correlation of 0.025, which is not unusual in most of the animal genetic studies, the total number of observations (N) should be not less than 500. From a design point of view, minimum bias occurred atn = 2, the minimum family size possible, underN fixed.