Identification of polymorphic variants impacting sleep in Drosophila

National Heart, Lung, And Blood Institute

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Abstract

Aim 1. Sleep is thought to be regulated by two processes: a homeostatic process, and a circadian process. Under this aim we attempt to relate gene expression to sleep need in the fruit fly, Drosophila melanogaster. RNA was extracted from single long- and short-sleeping flies of the Sleep Inbred Panel in 3-hour intervals over a 48-hour time period. The samples reflect a normal 12:12-hr light:dark cycle, and include male and female samples. In addition, some of the flies were sleep deprived during the night. We prepared 384 samples total. We will identify genes that are cycling under normal conditions and in response to sleep deprivation in the long and short sleepers, with the goal of contrasting the two. Aim 2. Sleep latency is the amount of time that it takes to fall asleep at the beginning of the night. It is one indicator of sleep need. Sleep latency varies among and within species and is heritable, but little is known about the underlying genetic network influencing this trait. Using data previously collected on a wild-derived panel of flies, we calculated sleep latency and estimated its heritability. We performed a genome-wide association study on these data, identifying 520 polymorphisms in 248 genes contributing to variation in this complex trait. Additional testing of mutations in candidate genes and genetic rescue implicated Piezo and Proc-R in sleep latency. We published these results, "Genome-wide association in Drosophila identifies a role for Piezo and Proc-R in sleep latency." Aim 3. According to the two-process model, the timing of sleep is governed by the circadian clock. We have assessed circadian timing phenotypes in the Drosophila Genetic Reference Panel and performed genome-wide association to identify genes influencing sleep timing. Verification studies are ongoing. Aim 4. Recent work by another research group suggested that sleep states could be discerned from fly sleep and activity count data using a Hidden Markov Model. We have applied this model to fly sleep and activity data from the DGRP and from the Sleep Inbred Panel. We used the HMM to estimate the time spent in each sleep state. We found that the time spent in each sleep state was heritable. Furthermore, we conducted arousal threshold studies to demonstrate that the model's prediction of deeper states of sleep had correspondingly high arousal thresholds in the flies. We developed software to implement the HMM to Trikinetics data. We are currently writing up this work for publication. Aim 5. Work from human epidemiological studies suggests that fragmented sleep is associated with an increased risk of disease, such as Alzheimer's Disease and cardiovascular disease. Using our previous strategy of artificial selection, we have begun to breed flies for greater fragmentation and consolidation, respectively. We are currently in the third generation of the selective breeding experiment. We will map changes in the DNA polymorphisms to these phenotypes. Aim 6. Much work has been devoted to studying sleep under normal endogenous conditions. Less is known about the underlying genetic networks influencing the response to sleep deprivation. We are currently depriving DGRP3 flies of sleep and measuring their response. As the DGRP3 panel has been sequenced, we plan to conduct a GWAS of the response to sleep deprivation.