David Houle

Behavior evolves as a correlated response to selection on cuticle color in Drosophila melanogaster and D. simulans

This study shows that artificial selection on cuticle color in Drosophila species leads to correlated changes in aggression and basal activity, but not in other behaviors.

Appendometer: A system for simultaneous, high-throughput morphometry of Drosophila legs and wings

The paper introduces a high-throughput system for simultaneous morphometry of Drosophila legs and wings, showing similar evolutionary rates for wings and legs but higher allometric change in wings.

Complexities of recapitulating polygenic effects in natural populations: replication of genetic effects on wing shape in artificially selected and wild caught populations of Drosophila melanogaster.

The paper investigates the replication of genetic effects on wing shape in Drosophila melanogaster using artificial selection and bulk segregant analysis, finding shared genetic responses but limited replication in natural populations.

The power of a multivariate approach to genome-wide association studies: an example with Drosophila melanogaster wing shape

This paper demonstrates that multivariate genome-wide association analysis of multiple traits improves power and informativeness compared to univariate analyses, using Drosophila wing shape as an example.

Quantitative morphological variation in the developing Drosophila wing

The paper quantifies morphological variation in Drosophila wing development across stages and links early morphology to adult traits.

Linkage Disequilibrium and Inversion-Typing of the Drosophila melanogaster Genome Reference Panel

The paper calculates linkage disequilibrium across the Drosophila melanogaster genome and identifies highly correlated SNPs for association studies, revealing patterns related to inversion polymorphisms and genotype-karyotype discrepancies.

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

This study shows that multivariate GWAS have higher power and lower FDR than univariate analyses when the number of traits matches the true phenotype dimensionality.