The fifth sentence of the subsection entitled 'General amphibian population model' under Methods should read: 'Using this scenario, we model per capita egg production as the mean clutch size (f) adjusted by the adult sex ratio (r; 0.5).' The online version of the original article can be found at http:// dx.

Olfactory receptor expression

Using a microarray, expression of 76% of predicted human olfactory receptor genes was detected in olfactory epithelia, and many were expressed in non-olfactory tissues.

In the setting of genome-wide association studies, we propose a method for assigning a measure of significance to pre-defined sets of markers in the genome. The sets can be genes, conserved regions, or groups of genes such as pathways. Using the proposed methods and algorithms, evidence for association between a particular functional unit and a disease status can be obtained not just by the presence of a strong signal from a SNP within it, but also by the combination of several simultaneous weaker signals that are not strongly correlated. This approach has several advantages. First, moderately strong signals from different SNPs are combined to obtain a much stronger signal for the set, therefore increasing power. Second, in combination with methods that provide information on untyped markers, it leads to results that can be readily combined across studies and platforms that might use different SNPs. Third, the results are easy to interpret, since they refer to functional sets of markers that are likely to behave as a unit in their phenotypic effect. Finally, the availability of gene-level p-values for association is the first step in developing methods that integrate information from pathways and networks with genome-wide association data, and these can lead to a better understanding of the complex traits genetic architecture. The power of the approach is investigated in simulated and real datasets. Novel Crohn's disease associations are found using the WTCCC data.

Olfactory receptor (OR) genes constitute the basis for the sense of smell. It has long been observed that a subset of mammalian OR genes are expressed in nonolfactory tissues, in addition to their expression in the olfactory epithelium. However, it is unknown whether OR genes have alternative functions in the nonolfactory tissues. Using a dedicated microarray, we surveyed OR gene expression in olfactory epithelium as well as a number of nonolfactory tissues, in human and chimpanzee. Our observations suggest that ectopically expressed OR orthologous genes are expressed in the same nonolfactory tissues in human and chimpanzee more often than expected by chance alone. Moreover, we found that the subset of orthologous OR genes with conserved ectopic expression evolve under stronger evolutionary constraint than OR genes expressed exclusively in the olfactory epithelium. Thus, although we cannot provide direct functional data, our observations are consistent with the notion that a subset of ectopically expressed OR genes have additional functions in nonolfactory tissues.

Inferring population genetic structure from large-scale genotyping of single-nucleotide polymorphisms or variants is an important technique for studying the history and distribution of extant human populations, but it is also a very important tool for adjusting tests of association. However, the structures inferred depend on the minor allele frequency of the variants; this is very important when considering the phenotypic association of rare variants.Using the Genetic Analysis Workshop 18 data set for 142 unrelated individuals, which includes genotypes for many rare variants, we study the following hypothesis: the difference in detected structure is the result of a "scale" effect; that is, rare variants are likely to be shared only locally (smaller scale), while common variants can be spread over longer distances. The result is similar to that of using kernel principal component analysis, as the bandwidth of the kernel is changed. We show how different structures become evident as we consider rare or common variants.