Building Bridges from Genome to Physiology Using Machine Learning and Drosophila Experimental Evolution.

Drosophila experimental evolution, with its well-defined selection protocols, has long supplied useful genetic material for the analysis of functional physiology. While there is a long tradition of interpreting the effects of large-effect mutants physiologically, identifying and interpreting gene-to-phenotype relationships has been challenging in the genomic era, with many labs not resolving how physiological traits are affected by multiple genes throughout the genome. Drosophila experimental evolution has demonstrated that multiple phenotypes change because of the evolution of many loci across the genome, creating the scientific challenge of sifting out differentiated but noncausal loci for individual characters. The fused lasso additive model method allows us to infer some of the differentiated loci that have relatively greater causal effects on the differentiation of specific phenotypes. The experimental material that we use in the present study comes from 50 populations that have been selected for different life histories and levels of stress resistance. Differentiation of cardiac robustness, starvation resistance, desiccation resistance, lipid content, glycogen content, water content, and body masses was assayed among 40-50 of these experimentally evolved populations. Through the fused lasso additive model, we combined physiological analyses from eight parameters with whole-body pooled-seq genomic data to identify potentially causally linked genomic regions. We have identified approximately 2,176 significantly differentiated 50-kb genomic windows among our 50 populations, with 142 of those identified genomic regions that are highly likely to have a causal effect connecting specific genome sites to specific physiological characters.

Genomics of Early Cardiac Dysfunction and Mortality in Obese Drosophila melanogaster.

In experimental evolution, we impose functional demands on laboratory populations of model organisms using selection. After enough generations of such selection, the resulting populations constitute excellent material for physiological research. An intense selection regime for increased starvation resistance was imposed on 10 large outbred Drosophila populations. We observed the selection responses of starvation and desiccation resistance, metabolic reserves, and heart robustness via electrical pacing. Furthermore, we sequenced the pooled genomes of these populations. As expected, significant increases in starvation resistance and lipid content were found in our 10 intensely selected SCO populations. The selection regime also improved desiccation resistance, water content, and glycogen content among these populations. Additionally, the average rate of cardiac arrests in our 10 obese SCO populations was double the rate of the 10 ancestral CO populations. Age-specific mortality rates were increased at early adult ages by selection. Genomic analysis revealed a large number of single nucleotide polymorphisms across the genome that changed in frequency as a result of selection. These genomic results were similar to those obtained in our laboratory from less direct selection procedures. The combination of extensive genomic and phenotypic differentiation between these 10 populations and their ancestors makes them a powerful system for the analysis of the physiological underpinnings of starvation resistance.

Starvation but not locomotion enhances heart robustness in Drosophila.

Insects and vertebrates have multiple major physiological systems, each species having a circulatory system, a metabolic system, and a respiratory system that enable locomotion and survival in stressful environments, among other functions. Broadening our understanding of the physiology of Drosophila melanogaster requires the parsing of interrelationships among such major component physiological systems. By combining electrical pacing and flight exhaustion assays with manipulative conditioning, we have started to unpack the interrelationships between cardiac function, locomotor performance, and other functional characters such as starvation and desiccation resistance. Manipulative sequences incorporating these four physiological characters were applied to five D. melanogaster lab populations that share a common origin from the wild and a common history of experimental evolution. While exposure to starvation or desiccation significantly reduced flight duration, exhaustion due to flight only affected subsequent desiccation resistance. A strong association was found between flight duration and desiccation resistance, providing additional support for the hypothesis that these traits depend on glycogen and water content. However, there was negligible impact on rate of cardiac arrests from exhaustion by flight or exposure to desiccant. Brief periods of starvation significantly lowered the rate of cardiac arrest. These results provide suggestive support for the adverse impact of lipids on Drosophila heart robustness, a parallel result to those of many comparable studies in human cardiology. Overall, this study underscores clear distinctions among the connections between specific physiological responses to stress and specific types of physiological performance.