Publications

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]

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 (in prep)

Adam N. Spierer, Denise Yoon, Lei Zhu, and David M. Rand
In prep as a Methods paper for Journal of Experimental Biology

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 w[1118] nuclear background.