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Dissecting the genetic basis of variation in Drosophila sleep using a multiparental QTL mapping resource

Citation

Macdonald, Stuart; R. Smith, Brittny (2020), Dissecting the genetic basis of variation in Drosophila sleep using a multiparental QTL mapping resource, Dryad, Dataset, https://doi.org/10.5061/dryad.6wwpzgmv8

Abstract

There is considerable variation in sleep duration, timing and quality in human populations, and sleep dysregulation has been implicated as a risk factor for a range of health problems. Human sleep traits are known to be regulated by genetic factors, but also by an array of environmental and social factors. These uncontrolled, non-genetic effects complicate powerful identification of the loci contributing to sleep directly in humans. The model system, Drosophila melanogaster, exhibits a behavior that shows the hallmarks of mammalian sleep, and here we use a multitiered approach, encompassing high-resolution QTL mapping, expression QTL data, and functional validation with RNAi to investigate the genetic basis of sleep under highly controlled environmental conditions. We measured a battery of sleep phenotypes in >750 genotypes derived from a multiparental mapping panel and identified several, modest-effect QTL contributing to natural variation for sleep. Merging sleep QTL data with a large head transcriptome eQTL mapping dataset from the same population allowed us to refine the list of plausible candidate causative sleep loci. This set includes genes with previously characterized effects on sleep and circadian rhythms, in addition to novel candidates. Finally, we employed adult, nervous system-specific RNAi on the Dopa decarboxylase, dyschronic, and timeless genes, finding significant effects on sleep phenotypes for all three. The genes we resolve are strong candidates to harbor causative, regulatory variation contributing to sleep.

Methods

This is a complex collection of raw data files, processed data, and analytical scripts written in the R programming language.

Nearly all the raw data derives from outputs produced by the TriKinetics.com "Drosophila Activity Monitoring System". Much of the processed data is derived from these files (and also contained in the repository) via the included R files.

We also provide R code for re-analysis of data originally produced by King et al. (2014, PLoS Genetics, PMID: 24810915).

Where other data is used it is either provided, or it is described how it was extracted from online databases (e.g., FlyBase.org).

Usage Notes

Everything a user would need to recapitulate the analyses/results reported in the manuscript are contained in the files in this repository.

The README file provides detail on each of the separate packed directories (what files and sub-directories are present in each, what analyses are executed by the contained scripts, and so on). Unpacking each file will reveal R (www.r-project.org) scripts. In addition to providing code, they additionally contain information on how to run them on the data provided.

Funding

National Institutes of Health, Award: OD010974

National Institutes of Health, Award: OD010974

Foundation for the National Institutes of Health, Award: OD010974

Foundation for the National Institutes of Health, Award: GM103418