Mito-nuclear Interactions Modify Drosophila Exercise Performance
Alyson Sujkowski, Adam N Spierer, Thiviya Rajagopalan, Brian Bazzell, Maryam Safdar, Dinko Imsirovic, Robert Arking, David M Rand, Robert Wessells
Mitochondrion 2019 Jul;47:188-205. [link]
Abstract: Endurance exercise has received increasing attention as a broadly preventative measure against age-related disease and dysfunction. Improvement of mitochondrial quality by enhancement of mitochondrial turnover is thought to be among the important molecular mechanisms underpinning the benefits of exercise. Interactions between the mitochondrial and nuclear genomes are important components of the genetic basis for variation in longevity, fitness and the incidence of disease. Here, we examine the effects of replacing the mitochondrial genome (mtDNA) of several Drosophila strains with mtDNA from other strains, or from closely related species, on exercise performance. We find that mitochondria from flies selected for longevity increase the performance of flies from a parental strain. We also find evidence that mitochondria from other strains or species alter exercise performance, with examples of both beneficial and deleterious effects. These findings suggest that both the mitochondrial and nuclear genomes, as well as interactions between the two, contribute significantly to exercise capacity.
Natural variation in the regulation of neurodevelopmental genes modifies flight performance in Drosophila (in review)
Adam N. Spierer, Jim A. Mossman, Samuel Pattillo Smith, Lorin Crawford, Sohini Ramachandran, David M. Rand
BioRxiv 2020, May 27. [preprint link] (submitted to PLoS Genetics)
Author summary: Insect flight is a widely recognizable phenotype of winged insects, hence the name: flies. While fruit flies, or Drosophila melanogaster, are a genetically tractable model, flight performance is a highly integrative phenotype, making it challenging to comprehensively identify the genetic modifiers that contribute to its genetic architecture. Accordingly, we screened 197 Drosophila Genetic Reference Panel lines for their ability to react and respond to an abrupt drop. Using several computational tools, we successfully identified several additive, marginal, and epistatic variants, as well as whole genes and altered sub-networks of gene-gene and protein-protein interaction networks, demonstrating the benefits of using multiple methodologies to elucidate the genetic architecture of complex traits more generally. Many of these significant genes and variants mapped to regions of the genome that affect development of sensory and motor neurons, wing and muscle development, and regulation of transcription factors. We also introduce PEGASUS_flies, a Drosophila-adapted version of the PEGASUS platform first used in human studies, to infer gene-level significance of association based on the distribution of individual variant P-values. Our results contribute to the debate over the relative importance of individual, additive factors and epistatic, or higher order, interactions, in the mapping of genotype to phenotype.
FreeClimber: Automated High Throughput Quantification of Climbing Performance in Drosophila, with Examples from Mitonuclear Genotypes
Adam N. Spierer, Denise Yoon, Lei Zhu, and David M. Rand
Journal of Experimental Biology. Accepted November 5, 2020 [link]
Abstract: Negative geotaxis (climbing) performance is a useful metric for quantifying the health and vigor of Drosophila across experimental treatments and conditions. Manual methods to compute climbing performance are slow and tedious, while available computation methods have inflexible hardware or software requirements. We present an alternative with our open-source program: FreeClimber. This Python-based method performs a rapid background subtraction step to allow for rapid spot detection on a heterogeneous background. FreeClimber quantifies the most linear portion of a velocity curve for each specified vial, via local linear regression. Output files report results as precalculated slopes, or as individual spot locations for further processing and predictive linking (tracking). We demonstrate FreeClimber’s utility in a longitudinal study for endurance exercise performance using six distinct mitochondrial haplotypes paired with a common Drosophila nuclear background.
The Genetic Architecture of Robustness for Flight Performance in Drosophila
Abstract: A central challenge of quantitative genetics is partitioning phenotypic variation into genetic and non-genetic components. These non-genetic components are usually interpreted as environmental effects; however, variation between genetically identical individuals in a common environment can still exhibit phenotypic variation. A trait’s resistance to variation is called robustness, though the genetics underlying it are poorly understood. Accordingly, we performed an association study on a previously studied, whole organism trait: flight performance. Using 197 of the Drosophila Genetic Reference Panel (DGRP) lines, we surveyed variation at the level of single nucleotide polymorphisms and whole genes using additive, marginal, and epistatic analyses that associated with robustness for flight performance. Many genes had developmental and neurodevelopmental annotations, and many more were identified from associations that differed between sexes. Additionally, many genes were pleiotropic, with several annotated for fitness-associated traits (e.g. gametogenesis and courtship). Our results corroborate a previous study for genetic modifiers of micro-environmental variation, and have sizable overlap with studies for modifiers of wing morphology and courtship behavior. These results point to an important and shared role for genetic modifiers of robustness of flight performance affecting development, neurodevelopment, and behavior.