Drosophila model systems for genetic sleep research

The successful sequencing of the human genome in 2000, along with sequencing the genomes of several genetic model organisms, have ushered in a new era of sleep research in which the power of genetic and genomic strategies can be brought to bear on previously intractable problems pertaining to sleep mechanism and function. Indeed, genetic studies in humans (Chapter 14), mice (Chapter 15), zebra fish (Chapter 6), Drosophila melanogaster (Chapter 5), and Caenorhabditis elegans (Chapter 6) have been successful in advancing our understanding of basic sleep mechanisms (see [1]). Although it is still common for laboratories to focus their research on a preferred model organism, it is becoming increasingly clear that progress can be enhanced when labs cross-validate their findings between more than one species [2–6]. This is particularly true for human studies in which establishing causation is non-trivial. For example, He and colleagues in 2009 identified a point mutation in human DEC2 that was associated with a short-sleeping phenotype and demonstrated causation using transgenic mice and flies [4]. Similarly, in 2013, Allebrandt et al. identified a variant of the ABCC9 gene in a human genome-wide association study (GWAS) and then, using Drosophila genetics, demonstrated a functional role for ABCC9 gene in regulating sleep time [6]. Likewise, Freeman and colleagues used Drosophila genetics to show that a gene identified in human GWAS studies for restless legs syndrome (RLS), BTB9, recapitulates key aspects of RLS in flies [5]. With this in mind, the following chapter will review the use of genetics in Drosophila to advance sleep research. Our goal is to highlight the sophisticated genetic toolbox that allows studies to be conducted quickly and at little cost. Together, these data demonstrate that the fly is well suited for not only revealing basic sleep mechanisms in its own right, but can also be directly incorporated into human studies to provide additional insight into causative mechanisms.