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.

Identifying the genetic architecture of complex traits is important to many geneticists, including those interested in human disease, plant and animal breeding, and evolutionary genetics. Advances in sequencing technology and statistical methods for genome-wide association studies have allowed for the identification of more variants with smaller effect sizes, however, many of these identified polymorphisms fail to be replicated in subsequent studies. In addition to sampling variation, this failure to replicate reflects the complexities introduced by factors including environmental variation, genetic background, and differences in allele frequencies among populations. Using Drosophila melanogaster wing shape, we ask if we can replicate allelic effects of polymorphisms first identified in a genome-wide association studies in three genes: dachsous, extra-macrochaete, and neuralized, using artificial selection in the lab, and bulk segregant mapping in natural populations. We demonstrate that multivariate wing shape changes associated with these genes are aligned with major axes of phenotypic and genetic variation in natural populations. Following seven generations of artificial selection along the dachsous shape change vector, we observe genetic differentiation of variants in dachsous and genomic regions containing other genes in the hippo signaling pathway. This suggests a shared direction of effects within a developmental network. We also performed artificial selection with the extra-macrochaete shape change vector, which is not a part of the hippo signaling network, but showed a largely shared direction of effects. The response to selection along the emc vector was similar to that of dachsous, suggesting that the available genetic diversity of a population, summarized by the genetic (co)variance matrix (G), influenced alleles captured by selection. Despite the success with artificial selection, bulk segregant analysis using natural populations did not detect these same variants, likely due to the contribution of environmental variation and low minor allele frequencies, coupled with small effect sizes of the contributing variants.

The behavioral repertoire of Drosophila melanogaster in the presence of two predator species that differ in hunting mode.

The fruit fly, Drosophila melanogaster, has proven to be an excellent model organism for genetic, genomic and neurobiological studies. However, relatively little is known about the natural history of D. melanogaster. In particular, neither the natural predators faced by wild populations of D. melanogaster, nor the anti-predatory behaviors they may employ to escape and avoid their enemies have been documented. Here we observe and describe the influence of two predators that differ in their mode of hunting: zebra jumping spiders, Salticus scenicus (active hunters) and Chinese praying mantids, Tenodera sinensis (ambush predators) on the behavioral repertoire of Drosophila melanogaster. We documented three particularly interesting behaviors: abdominal lifting, stopping, and retreat-which were performed at higher frequency by D. melanogaster in the presence of predators. While mantids had only a modest influence on the locomotory activity of D. melanogaster, we observed a significant increase in the overall activity of D. melanogaster in the presence of jumping spiders. Finally, we observed considerable among-individual behavioral variation in response to both predators.

Electric fish genomics: Progress, prospects, and new tools for neuroethology.

Electric fish have served as a model system in biology since the 18th century, providing deep insight into the nature of bioelectrogenesis, the molecular structure of the synapse, and brain circuitry underlying complex behavior. Neuroethologists have collected extensive phenotypic data that span biological levels of analysis from molecules to ecosystems. This phenotypic data, together with genomic resources obtained over the past decades, have motivated new and exciting hypotheses that position the weakly electric fish model to address fundamental 21st century biological questions. This review article considers the molecular data collected for weakly electric fish over the past three decades, and the insights that data of this nature has motivated. For readers relatively new to molecular genetics techniques, we also provide a table of terminology aimed at clarifying the numerous acronyms and techniques that accompany this field. Next, we pose a research agenda for expanding genomic resources for electric fish research over the next 10years. We conclude by considering some of the exciting research prospects for neuroethology that electric fish genomics may offer over the coming decades, if the electric fish community is successful in these endeavors.

An image database of Drosophila melanogaster wings for phenomic and biometric analysis.

BACKGROUND: Extracting important descriptors and features from images of biological specimens is an ongoing challenge. Features are often defined using landmarks and semi-landmarks that are determined a priori based on criteria such as homology or some other measure of biological significance. An alternative, widely used strategy uses computational pattern recognition, in which features are acquired from the image de novo. Subsets of these features are then selected based on objective criteria. Computational pattern recognition has been extensively developed primarily for the classification of samples into groups, whereas landmark methods have been broadly applied to biological inference. RESULTS: To compare these approaches and to provide a general community resource, we have constructed an image database of Drosophila melanogaster wings - individually identifiable and organized by sex, genotype and replicate imaging system - for the development and testing of measurement and classification tools for biological images. We have used this database to evaluate the relative performance of current classification strategies. Several supervised parametric and nonparametric machine learning algorithms were used on principal components extracted from geometric morphometric shape data (landmarks and semi-landmarks). For comparison, we also classified phenotypes based on de novo features extracted from wing images using several computer vision and pattern recognition methods as implemented in the Bioimage Classification and Annotation Tool (BioCAT). CONCLUSIONS: Because we were able to thoroughly evaluate these strategies using the publicly available Drosophila wing database, we believe that this resource will facilitate the development and testing of new tools for the measurement and classification of complex biological phenotypes.

Transcriptome analysis indicates considerable divergence in alternative splicing between duplicated genes in Arabidopsis thaliana.

Gene and genome duplication events have created a large number of new genes in plants that can diverge by evolving new expression profiles and functions (neofunctionalization) or dividing extant ones (subfunctionalization). Alternative splicing (AS) generates multiple types of mRNA from a single type of pre-mRNA by differential intron splicing. It can result in new protein isoforms or downregulation of gene expression by transcript decay. Using RNA-seq, we investigated the degree to which alternative splicing patterns are conserved between duplicated genes in Arabidopsis thaliana. Our results revealed that 30% of AS events in α-whole-genome duplicates and 33% of AS events in tandem duplicates are qualitatively conserved within leaf tissue. Loss of ancestral splice forms, as well as asymmetric gain of new splice forms, may account for this divergence. Conserved events had different frequencies, as only 31% of shared AS events in α-whole-genome duplicates and 41% of shared AS events in tandem duplicates had similar frequencies in both paralogs, indicating considerable quantitative divergence. Analysis of published RNA-seq data from nonsense-mediated decay (NMD) mutants indicated that 85% of α-whole-genome duplicates and 89% of tandem duplicates have diverged in their AS-induced NMD. Our results indicate that alternative splicing shows a high degree of divergence between paralogs such that qualitatively conserved alternative splicing events tend to have quantitative divergence. Divergence in AS patterns between duplicates may be a mechanism of regulating expression level divergence.