Proteome-wide association studies identify biochemical modules associated with a wing-size phenotype in Drosophila melanogaster.

The manner by which genetic diversity within a population generates individual phenotypes is a fundamental question of biology. To advance the understanding of the genotype-phenotype relationships towards the level of biochemical processes, we perform a proteome-wide association study (PWAS) of a complex quantitative phenotype. We quantify the variation of wing imaginal disc proteomes in Drosophila genetic reference panel (DGRP) lines using SWATH mass spectrometry. In spite of the very large genetic variation (1/36 bp) between the lines, proteome variability is surprisingly small, indicating strong molecular resilience of protein expression patterns. Proteins associated with adult wing size form tight co-variation clusters that are enriched in fundamental biochemical processes. Wing size correlates with some basic metabolic functions, positively with glucose metabolism but negatively with mitochondrial respiration and not with ribosome biogenesis. Our study highlights the power of PWAS to filter functional variants from the large genetic variability in natural populations.

Genome-Wide Analysis Reveals Novel Regulators of Growth in Drosophila melanogaster.

Organismal size depends on the interplay between genetic and environmental factors. Genome-wide association (GWA) analyses in humans have implied many genes in the control of height but suffer from the inability to control the environment. Genetic analyses in Drosophila have identified conserved signaling pathways controlling size; however, how these pathways control phenotypic diversity is unclear. We performed GWA of size traits using the Drosophila Genetic Reference Panel of inbred, sequenced lines. We find that the top associated variants differ between traits and sexes; do not map to canonical growth pathway genes, but can be linked to these by epistasis analysis; and are enriched for genes and putative enhancers. Performing GWA on well-studied developmental traits under controlled conditions expands our understanding of developmental processes underlying phenotypic diversity.

The FlyCatwalk: a high-throughput feature-based sorting system for artificial selection in Drosophila.

Experimental evolution is a powerful tool for investigating complex traits. Artificial selection can be applied for a specific trait and the resulting phenotypically divergent populations pool-sequenced to identify alleles that occur at substantially different frequencies in the extreme populations. To maximize the proportion of loci that are causal to the phenotype among all enriched loci, population size and number of replicates need to be high. These requirements have, in fact, limited evolution studies in higher organisms, where the time investment required for phenotyping is often prohibitive for large-scale studies. Animal size is a highly multigenic trait that remains poorly understood, and an experimental evolution approach may thus aid in gaining new insights into the genetic basis of this trait. To this end, we developed the FlyCatwalk, a fully automated, high-throughput system to sort live fruit flies (Drosophila melanogaster) based on morphometric traits. With the FlyCatwalk, we can detect gender and quantify body and wing morphology parameters at a four-old higher throughput compared with manual processing. The phenotyping results acquired using the FlyCatwalk correlate well with those obtained using the standard manual procedure. We demonstrate that an automated, high-throughput, feature-based sorting system is able to avoid previous limitations in population size and replicate numbers. Our approach can likewise be applied for a variety of traits and experimental settings that require high-throughput phenotyping.