Increasing association mapping power and resolution in mouse genetic studies through the use of meta-analysis for structured populations

Genetic studies in mouse models have played an integral role in the discovery of the mechanisms underlying many human diseases. The primary mode of discovery has been the application of linkage analysis to mouse crosses. This approach results in high power to identify regions that affect traits, but in low resolution, making it difficult to identify the precise genomic location harboring the causal variant. Recently, a panel of mice referred to as the hybrid mouse diversity panel (HMDP) has been developed to overcome this problem. However, power in this panel is limited by the availability of inbred strains. Previous studies have suggested combining results across multiple panels as a means to increase power, but the methods employed may not be well suited to structured populations, such as the HMDP. In this article, we introduce a meta-analysis-based method that may be used to combine HMDP studies with F2 cross studies to gain power, while increasing resolution. Due to the drastically different genetic structure of F2s and the HMDP, the best way to combine two studies for a given SNP depends on the strain distribution pattern in each study. We show that combining results, while accounting for these patterns, leads to increased power and resolution. Using our method to map bone mineral density, we find that two previously implicated loci are replicated with increased significance and that the size of the associated is decreased. We also map HDL cholesterol and show a dramatic increase in the significance of a previously identified result.     

A Survey of Sample Size Formulas for Pairwise and Many‐one Multiple Comparisons in the Parametric,Nonparametric and Binomial Case

We present a survey of sample size formulas derived in other papers for pairwise comparisons of k treatments and for comparisons of k treatments with a control. We consider the calculation of sample sizes with preassigned per‐pair, any‐pair and all‐pairs power for tests that control either the comparisonwise or the experimentwise type I error rate. A comparison exhibits interesting similarities between the parametric, nonparametric and binomial case.     

Hemocyanin gene family evolution in spiders (Araneae), with implications for phylogenetic relationships and divergence times in the infraorder Mygalomorphae

Hemocyanins are multimeric copper-containing hemolymph proteins involved in oxygen binding and transport in all major arthropod lineages. Most arachnids have seven primary subunits (encoded by paralogous genes a–g), which combine to form a 24-mer (4 × 6) quaternary structure. Within some spider lineages, however, hemocyanin evolution has been a dynamic process with extensive paralog duplication and loss. We have obtained hemocyanin gene sequences from numerous representatives of the spider infraorders Mygalomorphae and Araneomorphae in order to infer the evolution of the hemocyanin gene family and estimate spider relationships using these conserved loci. Our hemocyanin gene tree is largely consistent with the previous hypotheses of paralog relationships based on immunological studies, but reveals some discrepancies in which paralog types have been lost or duplicated in specific spider lineages. Analyses of concatenated hemocyanin sequences resolved deep nodes in the spider phylogeny and recovered a number of clades that are supported by other molecular studies, particularly for mygalomorph taxa. The concatenated data set is also used to estimate dates of higher-level spider divergences and suggests that the diversification of extant mygalomorphs preceded that of extant araneomorphs. Spiders are diverse in behavior and respiratory morphology, and our results are beneficial for comparative analyses of spider respiration. Lastly, the conserved hemocyanin sequences allow for the inference of spider relationships and ancient divergence dates.