Automated Phenotyping Indicates Pupal Size in Drosophila Is a Highly Heritable Trait with an Apparent Polygenic Basis

Effect of D. melanogaster larval density on pupal size

Many genetic pathways and environmental factors have been shown to affect Drosophila melanogaster adult body size. Larval density often varies considerably between vials, even when the same number of females of the same genotype are allowed to lay eggs in the vials for the same amount of time. To more accurately quantify the effects that larval population density has on pupal size, we established cultures of 1, 2, 10, 25, 50, 75 or 100 first instar larvae into vials and measured pupal length. We collected Oregon-R eggs on apple juice plates in six different cages and generated replicate cultures. We found that pupal size decreases as larval density in the culture increases by 25 individuals. The difference between male and female length remained relatively constant at each density (0.2 mm), but overall size decreased. The mean size differences between vials with 1 larvae and 100 larvae is 0.1(+/-0.02) mm in females and 0.11(+/-0.02) mm in males. These results suggest that fecundity and sex ratio could complicate results in Drosophila size studies.

Fitness effects of CRISPR endonucleases in Drosophila melanogaster populations

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 provides a highly efficient and flexible genome editing technology with numerous potential applications ranging from gene therapy to population control. Some proposed applications involve the integration of CRISPR/Cas9 endonucleases into an organism's genome, which raises questions about potentially harmful effects to the transgenic individuals. One example for which this is particularly relevant are CRISPR-based gene drives conceived for the genetic alteration of entire populations. The performance of such drives can strongly depend on fitness costs experienced by drive carriers, yet relatively little is known about the magnitude and causes of these costs. Here, we assess the fitness effects of genomic CRISPR/Cas9 expression in Drosophila melanogaster cage populations by tracking allele frequencies of four different transgenic constructs that allow us to disentangle 'direct' fitness costs due to the integration, expression, and target-site activity of Cas9, from fitness costs due to potential off-target cleavage. Using a maximum likelihood framework, we find that a model with no direct fitness costs but moderate costs due to off-target effects fits our cage data best. Consistent with this, we do not observe fitness costs for a construct with Cas9HF1, a high-fidelity version of Cas9. We further demonstrate that using Cas9HF1 instead of standard Cas9 in a homing drive achieves similar drive conversion efficiency. These results suggest that gene drives should be designed with high-fidelity endonucleases and may have implications for other applications that involve genomic integration of CRISPR endonucleases.

Testing Implications of the Omnigenic Model for the Genetic Analysis of Loci Identified through Genome-wide Association

Organismal phenotypes usually have a quantitative distribution, and their genetic architecture can be studied by genome-wide association (GWA) mapping approaches. In most of such studies, it has become clear that many genes of moderate or small effects contribute to the phenotype.^1-4 Hence, the attention has turned toward the loci falling below the GWA cut-off, which may contribute to the phenotype through modifier interactions with a set of core genes, as proposed in the omnigenic model.⁵ One can thus predict that both moderate effect GWA-derived candidate genes and randomly chosen genes should have a similar likelihood to affect a given phenotype when they are analyzed via gene disruption assays. We have tested this hypothesis by using an automated phenotyping system for Drosophila pupal phenotypes.^6,7 We first identified candidate genes for pupal length in a GWA based on the Drosophila Genetic Reference Panel (DGRP)^8,9 and showed that most of these candidate genes are indeed involved in the phenotype. We then randomly chose genes below a GWA significance threshold and found that three-quarters of them had also an effect on the trait with comparable effect sizes as the GWA candidate genes. We further tested the effects of these knockout lines on an independent behavioral pupal trait (pupation site choice) and found that a similar fraction had a significant effect as well. Our data thus confirm the implication that a large number of genes can influence independent quantitative traits.

Identification of a genetic network for an ecologically relevant behavioural phenotype in Drosophila melanogaster

Pupation site choice of Drosophila third-instar larvae is critical for the survival of individuals, as pupae are exposed to various biotic and abiotic dangers while immobilized during the 3-4 days of metamorphosis. This singular behavioural choice is sensitive to both environmental and genetic factors. Here, we developed a high-throughput phenotyping approach to assay the variation in pupation height in Drosophila melanogaster, while controlling for possibly confounding factors. We find substantial variation of mean pupation height among sampled natural stocks and we show that the Drosophila Genetic Reference Panel (DGRP) reflects this variation. Using the DGRP stocks for genome-wide association (GWA) mapping, 16 loci involved in determining pupation height could be resolved. The candidate genes in these loci are enriched for high expression in the larval central nervous system. A genetic network could be constructed from the candidate loci, which places scribble (scrib) at the centre, plus other genes known to be involved in nervous system development, such as Epidermal growth factor receptor (Egfr) and p53. Using gene disruption lines, we could functionally validate several of the initially identified loci, as well as additional loci predicted from network analysis. Our study shows that the combination of high-throughput phenotyping with a genetic analysis of variation captured from the wild can be used to approach the genetic dissection of an environmentally relevant behavioural phenotype.

An integrative genomic analysis of the Longshanks selection experiment for longer limbs in mice

Evolutionary studies are often limited by missing data that are critical to understanding the history of selection. Selection experiments, which reproduce rapid evolution under controlled conditions, are excellent tools to study how genomes evolve under selection. Here we present a genomic dissection of the Longshanks selection experiment, in which mice were selectively bred over 20 generations for longer tibiae relative to body mass, resulting in 13% longer tibiae in two replicates. We synthesized evolutionary theory, genome sequences and molecular genetics to understand the selection response and found that it involved both polygenic adaptation and discrete loci of major effect, with the strongest loci tending to be selected in parallel between replicates. We show that selection may favor de-repression of bone growth through inactivating two limb enhancers of an inhibitor, Nkx3-2. Our integrative genomic analyses thus show that it is possible to connect individual base-pair changes to the overall selection response.

RNA Interference (RNAi) Screening in Drosophila

In the last decade, RNA interference (RNAi), a cellular mechanism that uses RNA-guided degradation of messenger RNA transcripts, has had an important impact on identifying and characterizing gene function. First discovered in Caenorhabditis elegans, RNAi can be used to silence the expression of genes through introduction of exogenous double-stranded RNA into cells. In Drosophila, RNAi has been applied in cultured cells or in vivo to perturb the function of single genes or to systematically probe gene function on a genome-wide scale. In this review, we will describe the use of RNAi to study gene function in Drosophila with a particular focus on high-throughput screening methods applied in cultured cells. We will discuss available reagent libraries and cell lines, methodological approaches for cell-based assays, and computational methods for the analysis of high-throughput screens. Furthermore, we will review the generation and use of genome-scale RNAi libraries for tissue-specific knockdown analysis in vivo and discuss the differences and similarities with the use of genome-engineering methods such as CRISPR/Cas9 for functional analysis.