Naturally segregating genetic variants contribute to thermal tolerance in a Drosophila melanogaster model system.

Thermal tolerance is a fundamental physiological complex trait for survival in many species. For example, everyday tasks such as foraging, finding a mate, and avoiding predation are highly dependent on how well an organism can tolerate extreme temperatures. Understanding the general architecture of the natural variants within the genes that control this trait is of high importance if we want to better comprehend thermal physiology. Here, we take a multipronged approach to further dissect the genetic architecture that controls thermal tolerance in natural populations using the Drosophila Synthetic Population Resource as a model system. First, we used quantitative genetics and Quantitative Trait Loci mapping to identify major effect regions within the genome that influences thermal tolerance, then integrated RNA-sequencing to identify differences in gene expression, and lastly, we used the RNAi system to (1) alter tissue-specific gene expression and (2) functionally validate our findings. This powerful integration of approaches not only allows for the identification of the genetic basis of thermal tolerance but also the physiology of thermal tolerance in a natural population, which ultimately elucidates thermal tolerance through a fitness-associated lens.

Naturally segregating genetic variants contribute to thermal tolerance in a D. melanogaster model system.

Thermal tolerance is a fundamental physiological complex trait for survival in many species. For example, everyday tasks such as foraging, finding a mate, and avoiding predation, are highly dependent on how well an organism can tolerate extreme temperatures. Understanding the general architecture of the natural variants of the genes that control this trait is of high importance if we want to better comprehend how this trait evolves in natural populations. Here, we take a multipronged approach to further dissect the genetic architecture that controls thermal tolerance in natural populations using the Drosophila Synthetic Population Resource (DSPR) as a model system. First, we used quantitative genetics and Quantitative Trait Loci (QTL) mapping to identify major effect regions within the genome that influences thermal tolerance, then integrated RNA-sequencing to identify differences in gene expression, and lastly, we used the RNAi system to 1) alter tissue-specific gene expression and 2) functionally validate our findings. This powerful integration of approaches not only allows for the identification of the genetic basis of thermal tolerance but also the physiology of thermal tolerance in a natural population, which ultimately elucidates thermal tolerance through a fitness-associated lens.

Learning to collaborate: bringing together behavior and quantitative genomics.

The genetic basis of complex trait like learning and memory have been well studied over the decades. Through those groundbreaking findings, we now have a better understanding about some of the genes and pathways that are involved in learning and/or memory. However, few of these findings identified the naturally segregating variants that are influencing learning and/or memory within populations. In this special issue honoring the legacy of Troy Zars, we review some of the traditional approaches that have been used to elucidate the genetic basis of learning and/or memory, specifically in fruit flies. We highlight some of his contributions to the field, and specifically describe his vision to bring together behavior and quantitative genomics with the aim of expanding our knowledge of the genetic basis of both learning and memory. Finally, we present some of our recent work in this area using a multiparental population (MPP) as a case study and describe the potential of this approach to advance our understanding of neurogenetics.

Multiple genetic loci affect place learning and memory performance in Drosophila melanogaster.

Learning and memory are critical functions for all animals, giving individuals the ability to respond to changes in their environment. Within populations, individuals vary, however the mechanisms underlying this variation in performance are largely unknown. Thus, it remains to be determined what genetic factors cause an individual to have high learning ability and what factors determine how well an individual will remember what they have learned. To genetically dissect learning and memory performance, we used the Drosophila synthetic population resource (DSPR), a multiparent mapping resource in the model system Drosophila melanogaster, consisting of a large set of recombinant inbred lines (RILs) that naturally vary in these and other traits. Fruit flies can be trained in a "heat box" to learn to remain on one side of a chamber (place learning) and can remember this (place memory) over short timescales. Using this paradigm, we measured place learning and memory for ~49 000 individual flies from over 700 DSPR RILs. We identified 16 different loci across the genome that significantly affect place learning and/or memory performance, with 5 of these loci affecting both traits. To identify transcriptomic differences associated with performance, we performed RNA-Seq on pooled samples of seven high performing and seven low performing RILs for both learning and memory and identified hundreds of genes with differences in expression in the two sets. Integrating our transcriptomic results with the mapping results allowed us to identify nine promising candidate genes, advancing our understanding of the genetic basis underlying natural variation in learning and memory performance.

Rescue of a Mouse Model of Spinal Muscular Atrophy With Respiratory Distress Type 1 by AAV9-IGHMBP2 Is Dose Dependent.

Spinal muscular atrophy with respiratory distress type 1 (SMARD1) is an autosomal recessive disease occurring during childhood. The gene responsible for disease development is a ubiquitously expressed protein, IGHMBP2. Mutations in IGHMBP2 result in the loss of α-motor neurons leading to muscle atrophy in the distal limbs accompanied by respiratory complications. Although genetically and clinically distinct, proximal SMA is also caused by the loss of a ubiquitously expressed gene (SMN). Significant preclinical success has been achieved in proximal SMA using viral-based gene replacement strategies. We leveraged the technologies employed in SMA to demonstrate gene replacement efficacy in an SMARD1 animal model. Intracerebroventricular (ICV) injection of single-stranded AAV9 expressing the full-length cDNA of IGHMBP2 in a low dose led to a significant level of rescue in treated SMARD1 animals. Consistent with drastically increased survival, weight gain, and strength, the rescued animals demonstrated a significant improvement in muscle, NMJ, motor neurons, and axonal pathology. In addition, increased levels of IGHMBP2 in lumbar motor neurons verified the efficacy of the virus to transduce the target tissues. Our results indicate that AAV9-based gene replacement is a viable strategy for SMARD1, although dosing effects and potential negative impacts of high dose and ICV injection should be thoroughly investigated.