Adding further power to the Haseman and Elston method for detecting linkage in larger sibships: weighting sums and differences

Haseman and Elston (H-E) proposed a robust test to detect linkage between a quantitative trait and a genetic marker. In their method the squared sib-pair trait difference is regressed on the estimated proportion of alleles at a locus shared identical by descent by sib pairs. This method has recently been improved by changing the dependent variable from the squared difference to the mean-corrected product of the sib-pair trait values, a significantly positive regression indicating linkage. Because situations arise in which the original test is more powerful, a further improvement of the H-E method occurs when the dependent variable is changed to a weighted average of the squared sib-pair trait difference and the squared sib-pair mean-corrected trait sum. Here we propose an optimal method of performing this weighting for larger sibships, allowing for the correlation between pairs within a sibship. The optimal weights are inversely proportional to the residual variances obtained from the two different regressions based on the squared sib-pair trait differences and the squared sib-pair mean-corrected trait sums, respectively, allowing for correlations among sib pairs. The proposed method is compared with the existing extension of the H-E approach for larger sibships. Control of the type I error probabilities for sibships of any size can be improved by using a generalized estimating equation approach and the robust sandwich estimate of the variance, or a Monte-Carlo permutation test.     

Livestock grazing affects the egg size of an insectivorous passerine

Livestock grazing is a major driver of ecosystem change, and has been associated with significant declines in various bird species worldwide. In Britain, there is particular concern that severe grazing pressure is deleteriously affecting vegetation and birds in upland regions. However, the mechanism by which grazing affects birds is unclear. Here, we report for the first time, to our knowledge, that sheep grazing pressure affects the egg size of a common upland passerine: the meadow pipit Anthus pratensis. We manipulated sheep stocking densities in a replicated field experiment, and found that plots with the highest stocking density contained nests with the smallest eggs, and that plots with low stocking density contained nests with the largest eggs. However, eggs laid in ungrazed plots were also small, suggesting that either too many sheep or their removal from upland areas might have a detrimental effect on pipit egg size. We found no significant effect on fledging success but the reduced post-fledging survival of young from smaller eggs, as seen in other studies, could partly explain declines in upland birds.     

Inhibition of E6-induced degradation of its cellular substrates by novel blocking peptides

The E6 oncoprotein derived from the tumour-associated human papillomavirus (HPV) types induces the ubiquitin-mediated degradation of several cellular proteins by conjugating them with the cellular ubiquitin ligase E6-AP. This is a HECT domain-containing ligase that was originally identified through its involvement in the E6-mediated degradation of the cellular tumour suppressor protein p53. Here we have investigated, in more detail, the nature of the E6/E6-AP interaction using binding peptides isolated from an E6-specific library. The selected peptides were either predicted or shown to have an alpha-helical core resembling the E6-binding motif on E6-AP, as well as amino acid alterations that increased their affinity for E6. These peptides were potent inhibitors of the E6/E6-AP interaction. Further analysis of the effects of these peptides on the ability of E6 to direct the proteolytic degradation of its various substrates, including p53, Dlg and the MAGI family of proteins, as well as using E6-AP immunodepletion, revealed striking differences in the mechanism by which E6 targets its cellular substrates for degradation. These results suggest that the site on E6 bound by E6-AP is also most likely occupied by other, as yet unidentified, ubiquitin ligases.     

Ascertainment Adjustment: Where Does It Take Us?

It is commonly assumed that the parameter estimates of a statistical genetics model that has been adjusted for ascertainment will estimate parameters in the general population from which the ascertained subpopulation was originally drawn. We show that this is true only in certain restricted circumstances. More generally, ascertainment-adjusted parameter estimates reflect parameters in the ascertained subpopulation. In many situations, this shift in perspective is immaterial: the parameters of interest are the same in the ascertained sample and in the population from which it was drawn, and it is therefore irrelevant to which population inferences are presumed to apply. In other circumstances, however, this is not so. This has important implications, particularly for studies investigating the etiology of complex diseases.     

A tournament of linkage tests in complex inheritance

The performance of some weakly parametric linkage tests in common use was compared on 200 replicates of oligogenic inheritance from Genetic Analysis Workshop 10. Each random sample for the quantitative trait was dichotomized at different thresholds and also selected through 2 affected sibs, generating 8 combinations of sample and variable. The variance component program SOLAR performed best with a continuous trait, even in selected samples, when the population mean was used. The sib-pair program SIBPAL2 was best in most other cases when the phenotype product, population mean, and empirical estimates of pair correlations were used. The BETA program that introduced phenotype products was slightly more powerful than maximum likelihood scores under the null hypothesis and approached but did not exceed SIBPAL2 under its optimal conditions. Type I errors generally exceeded expectations from a chi(2) test, but were conservative with respect to bounds on lods. All methods can be improved by use of the population mean, empirical correlations, logistic representation for affection status, and correct lods for samples that favour the null hypothesis. It remains uncertain whether all information can be extracted by weakly parametric methods and whether correction for ascertainment bias demands a strongly parametric model. Performance on a standard set of simulated data is indispensable for recognising optimal methods.     

Adaptive two-stage analysis of genetic association in case-control designs

We study a two-stage analysis of genetic association for case-control studies. In the first stage, we compare Hardy-Weinberg disequilibrium coefficients between cases and controls and, in the second stage, we apply the Cochran- Armitage trend test. The two analyses are statistically independent when Hardy-Weinberg equilibrium holds in the population, so all the samples are used in both stages. The significance level in the first stage is adaptively determined based on its conditional power. Given the level in the first stage, the level for the second stage analysis is determined with the overall Type I error being asymptotically controlled. For finite sample sizes, a parametric bootstrap method is used to control the overall Type I error rate. This two-stage analysis is often more powerful than the Cochran-Armitage trend test alone for a large association study. The new approach is applied to SNPs from a real study.