Selection and the direction of phenotypic evolution.

Predicting adaptive phenotypic evolution depends on invariable selection gradients and on the stability of the genetic covariances between the component traits of the multivariate phenotype. We describe the evolution of six traits of locomotion behavior and body size in the nematode for 50 generations of adaptation to a novel environment. We show that the direction of adaptive multivariate phenotypic evolution can be predicted from the ancestral selection differentials, particularly when the traits were measured in the new environment.

Phenotypic stasis with genetic divergence.

Whether or not genetic divergence in the short-term of tens to hundreds of generations is compatible with phenotypic stasis remains a relatively unexplored problem. We evolved predominantly outcrossing, genetically diverse populations of the nematode under a constant and homogeneous environment for 240 generations and followed individual locomotion behavior. Although founders of lab populations show highly diverse locomotion behavior, during lab evolution, the component traits of locomotion behavior - defined as the transition rates in activity and direction - did not show divergence from the ancestral population.

Variation in mutational (co)variances.

Because of pleiotropy, mutations affect the expression and inheritance of multiple traits and, together with selection, are expected to shape standing genetic covariances between traits and eventual phenotypic divergence between populations. It is therefore important to find if the M matrix, describing mutational variances of each trait and covariances between traits, varies between genotypes. We here estimate the M matrix for six locomotion behavior traits in lines of two genotypes of the nematode Caenorhabditis elegans that accumulated mutations in a nearly neutral manner for 250 generations.

The genetic architecture of temperature adaptation is shaped by population ancestry and not by selection regime.

Background: Understanding the genetic architecture of temperature adaptation is key for characterizing and predicting the effect of climate change on natural populations. One particularly promising approach is Evolve and Resequence, which combines advantages of experimental evolution such as time series, replicate populations, and controlled environmental conditions, with whole genome sequencing. Recent analysis of replicate populations from two different Drosophila simulans founder populations, which were adapting to the same novel hot environment, uncovered very different architectures-either many selection targets with large heterogeneity among replicates or fewer selection targets with a consistent response among replicates.

A morphological trait involved in reproductive isolation between Drosophila sister species is sensitive to temperature.

Male genitalia are usually extremely divergent between closely related species, but relatively constant within one species. Here we examine the effect of temperature on the shape of the ventral branches, a male genital structure involved in reproductive isolation, in the sister species and . We designed a semi-automatic measurement machine learning pipeline that can reliably identify curvatures and landmarks based on manually digitized contours of the ventral branches.

The Evolution of Phenotypic Plasticity in Response to Temperature Stress.

Phenotypic plasticity is the ability of a single genotype to produce different phenotypes in response to environmental variation. The importance of phenotypic plasticity in natural populations and its contribution to phenotypic evolution during rapid environmental change is widely debated. Here, we show that thermal plasticity of gene expression in natural populations is a key component of its adaptation: evolution to novel thermal environments increases ancestral plasticity rather than mean genetic expression.

Neuronal Function and Dopamine Signaling Evolve at High Temperature in Drosophila.

Neuronal activity is temperature sensitive and affects behavioral traits important for individual fitness, such as locomotion and courtship. Yet, we do not know enough about the evolutionary response of neuronal phenotypes in new temperature environments. Here, we use long-term experimental evolution of Drosophila simulans populations exposed to novel temperature regimes.

Genetic redundancy fuels polygenic adaptation in Drosophila.

The genetic architecture of adaptive traits is of key importance to predict evolutionary responses. Most adaptive traits are polygenic-i.e.

A 24 h Age Difference Causes Twice as Much Gene Expression Divergence as 100 Generations of Adaptation to a Novel Environment.

Gene expression profiling is one of the most reliable high-throughput phenotyping methods, allowing researchers to quantify the transcript abundance of expressed genes. Because many biotic and abiotic factors influence gene expression, it is recommended to control them as tightly as possible. Here, we show that a 24 h age difference of females that were subjected to RNA sequencing (RNA-Seq) five and six days after eclosure resulted in more than 2000 differentially expressed genes.

A simple genetic basis of adaptation to a novel thermal environment results in complex metabolic rewiring in Drosophila.

Background: Population genetic theory predicts that rapid adaptation is largely driven by complex traits encoded by many loci of small effect. Because large-effect loci are quickly fixed in natural populations, they should not contribute much to rapid adaptation.

Results: To investigate the genetic architecture of thermal adaptation - a highly complex trait - we performed experimental evolution on a natural Drosophila simulans population.

High-throughput fecundity measurements in Drosophila.

Fecundity is probably the most frequently studied fitness component in Drosophila. Nevertheless, currently used methods to measure fecundity are not well-suited for large-scale experiments, with many populations being assayed in parallel. Here we present a standardized pipeline to measure fecundity in many Drosophila population samples with substantially reduced hand on times.

An automated image analysis system to measure and count organisms in laboratory microcosms.

1. Because of recent technological improvements in the way computer and digital camera perform, the potential use of imaging for contributing to the study of communities, populations or individuals in laboratory microcosms has risen enormously. However its limited use is due to difficulties in the automation of image analysis.

Nutrient flows between ecosystems can destabilize simple food chains.

Dispersal of organisms has large effects on the dynamics and stability of populations and communities. However, current metacommunity theory largely ignores how the flows of limiting nutrients across ecosystems can influence communities. We studied a meta-ecosystem model where two autotroph-consumer communities are spatially coupled through the diffusion of the limiting nutrient.