Threshold trait architecture of Hsp90-buffered variation

Charles C Carey , Kristen F Gorman , Becky Howsmon , Charles Kooperberg , Aaron K Aragaki , Suzannah Rutherford
doi: http://dx.doi.org/10.1101/016980

Common genetic variants buffered by Hsp90 are candidates for human diseases of signaling such as cancer. Like cancer, morphological abnormalities buffered by Hsp90 are discrete threshold traits with a continuous underlying basis of liability determining their probability of occurrence. QTL and deletion maps for one of the most frequent Hsp90-dependent abnormalities in Drosophila, deformed eye (dfe), were replicated across three genetically related artificial selection lines using strategies dependent on proximity to the dfe threshold and the direction of genetic and environmental effects. Up to 17 dfe loci (QTL) linked by 7 interactions were detected based on the ability of small recombinant regions of an unaffected and completely homozygous control genotype to dominantly suppress or enhance dfe penetrance at its threshold in groups of isogenic recombinant flies, and over 20 deletions increased dfe penetrance from a low expected value in one or more line, identifying a complex network of genes responsible for the dfe phenotype. Replicated comparisons of these whole-genome mapping approaches identified several QTL regions narrowly defined by deletions and 4 candidate genes, with additional uncorrelated QTL and deletions highlighting differences between the approaches and the need for caution in attributing the effect of deletions directly to QTL genes.

The origins of a novel butterfly wing patterning gene from within a family of conserved cell cycle regulators

Nicola Nadeau , Carolina Pardo-Diaz , Annabel Whibley , Megan Ann Supple , Richard Wallbank , Grace C. Wu , Luana Maroja , Laura Ferguson , Heather Hines , Camilo Salazar , Richard ffrench-Constant , Mathieu Joron , William Owen McMillan , Chris Jiggins
doi: http://dx.doi.org/10.1101/016006

A major challenge in evolutionary biology is to understand the origins of novel structures. The wing patterns of butterflies and moths are derived phenotypes unique to the Lepidoptera. Here we identify a gene that we name poikilomousa (poik), which regulates colour pattern switches in the mimetic Heliconius butterflies. Strong associations between phenotypic variation and DNA sequence variation are seen in three different Heliconius species, in addition to associations between gene expression and colour pattern. Colour pattern variants are also associated with differences in splicing of poik transcripts. poik is a member of the conserved fizzy family of cell cycle regulators. It belongs to a faster evolving subfamily, the closest functionally characterised orthologue being the cortex gene in Drosophila, a female germ-line specific protein involved in meiosis. poik appears to have adopted a novel function in the Lepidoptera and become a major target for natural selection acting on colour and pattern variation in this group.

Dimensionality and the statistical power of multivariate genome-wide association studies

Eladio J. Marquez , David Houle
doi: http://dx.doi.org/10.1101/016592

Mutations virtually always have pleiotropic effects, yet most genome-wide association studies (GWAS) analyze effects one trait at a time. In order to investigate the performance of a multivariate approach to GWAS, we simulated scenarios where variation in a d-dimensional phenotype space was caused by a known subset of SNPs. Multivariate analyses of variance were then carried out on k traits, where k could be less than, greater than or equal to d. Our results show that power is maximized and false discovery rate (FDR) minimized when the number of traits analyzed, k, matches the true dimensionality of the phenotype being analyzed, d. When true dimensionality is high, the power of a single univariate analysis can be an order of magnitude less than the k=d case, even when the single trait with the largest genetic variance is chosen for analysis. When traits are added to a study in order of their independent genetic variation, the gains in power from increasing k up to d are much larger than the loss in power when k exceeds d. Simulations that explicitly model linkage disequilibrium (LD) indicate that when SNPs in disequilibrium are subjected to multivariate analysis, the magnitude of the apparent effect induced onto null SNPs by SNPs carrying a true effect weakens as k approaches d, such that the rank of P-values among a set of correlated SNPs becomes an increasingly reliable predictor of true positives. Multivariate GWAS outperform univariate ones under a wide range of conditions, and should become the standard in studies of the inheritance of complex phenotypes.