Noninvasive sleep monitoring in large-scale screening of knock-out mice reveals novel sleep-related genes (original) (raw)
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OF DISSERTATION IDENTIFICATION OF NOVEL SLEEP RELATED GENES FROM LARGE SCALE PHENOTYPING EXPERIMENTS IN MICE Humans spend a third of their lives sleeping but very little is known about the physiological and genetic mechanisms controlling sleep. Increased data from sleep phenotyping studies in mouse and other species, genetic crosses, and gene expression databases can all help improve our understanding of the process. Here, we present analysis of our own sleep data from the large-scale phenotyping program at The Jackson Laboratory (JAX), to identify the best gene candidates and phenotype predictors for influencing sleep traits. The original knockout mouse project (KOMP) was a worldwide collaborative effort to produce embryonic stem (ES) cell lines with one of mouse’s 21,000 protein coding genes knocked out. The objective of KOMP2 is to phenotype as many as of these lines as feasible, with each mouse studied over a ten-week period (www.mousephenotype.org). The phenotyping for sleep be...
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Sleep is a ubiquitous and complex behavior both in its manifestation and regulation. Despite its essential role in maintaining optimal performance, health, and well-being, the genetic mechanisms underlying sleep remain poorly understood. We here review the forward genetic approaches undertaken in the last 4 years to elucidate the genes and gene pathways affecting sleep and its regulation. Despite an increasing number of studies mining large databases, a coherent picture on ‘sleep’ genes has yet to emerge. We highlight the results achieved using unbiased genetic screens in human, mouse, and the fruit fly with emphasis on normal sleep and make reference to lessons learned from the circadian field.
Sleep
Significant differences in many aspects of sleep/wake activity among inbred strains of mice suggest genetic influences on the control of sleep. A number of genetic techniques, including transgenesis, random and targeted mutagenesis, and analysis of quantitative trait loci may be used to identify genetic loci. To take full advantage of these genetic approaches in mice, a comprehensive and robust description of behavioral states has been developed. An existing automated sleep scoring algorithm, designed for sleep analysis in rats, has been examined for acceptability in the analysis of baseline sleep structure and the response to sleep deprivation in mice. This algorithm was validated in three inbred strains (C57BL/6J, C3HeB/FeJ, 129X1/SvJ) and one hybrid line (C57BL/6J X C3HeB/FeJ). Overall accuracy rates for behavioral state detection (mean±SE) using this system in mice were: waking, 98. 8%±0.4; NREM sleep, 97.1%±0.5; and REM sleep, 89.7%±1.4. Characterization of sleep has been extended to include measurements of sleep consolidation and fragmentation, REM sleep latency, and delta density decline with sleep. An experimental protocol is suggested for acquiring baseline sleep data for genetic studies. This sleep recording protocol, scoring, and analysis system is designed to facilitate the understanding of genetic basis of sleep structure.
Identifying pathways modulating sleep duration: from genomics to transcriptomics
Scientific reports, 2017
Recognizing that insights into the modulation of sleep duration can emerge by exploring the functional relationships among genes, we used this strategy to explore the genome-wide association results for this trait. We detected two major signalling pathways (ion channels and the ERBB signalling family of tyrosine kinases) that could be replicated across independent GWA studies meta-analyses. To investigate the significance of these pathways for sleep modulation, we performed transcriptome analyses of short sleeping flies' heads (knockdown for the ABCC9 gene homolog; dSur). We found significant alterations in gene-expression in the short sleeping knockdowns versus controls flies, which correspond to pathways associated with sleep duration in our human studies. Most notably, the expression of Rho and EGFR (members of the ERBB signalling pathway) genes was down- and up-regulated, respectively, consistently with the established role of these genes for sleep consolidation in Drosophil...
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Sleep science is entering a new era, thanks to new data-driven analysis approaches that, combined with mouse gene-editing technologies, show a promise in functional genomics and translational research. However, the investigation of sleep is time consuming and not suitable for large-scale phenotypic datasets, mainly due to the need for subjective manual annotations of electrophysiological states. Moreover, the heterogeneous nature of sleep, with all its physiological aspects, is not fully accounted for by the current system of sleep stage classification. In this study, we present a new data-driven analysis approach offering a plethora of novel features for the characterization of sleep. This novel approach allowed for identifying several substages of sleep that were hidden to standard analysis. For each of these substages, we report an independent set of homeostatic responses following sleep deprivation. By using our new substages classification, we have identified novel differences ...
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Sleep, 2000
Significant differences in many aspects of sleep/wake activity among inbred strains of mice suggest genetic influences on the control of sleep. A number of genetic techniques, including transgenesis, random and targeted mutagenesis, and analysis of quantitative trait loci may be used to identify genetic loci. To take full advantage of these genetic approaches in mice, a comprehensive and robust description of behavioral states has been developed. An existing automated sleep scoring algorithm, designed for sleep analysis in rats, has been examined for acceptability in the analysis of baseline sleep structure and the response to sleep deprivation in mice. This algorithm was validated in three inbred strains (C57BL/6J, C3HeB/FeJ, 129X1/SvJ) and one hybrid line (C57BL/6J X C3HeB/FeJ). Overall accuracy rates for behavioral state detection (mean±SE) using this system in mice were: waking, 98.8%±0.4; NREM sleep, 97.1%±0.5; and REM sleep, 89.7%±1.4. Characterization of sleep has been extended to include measurements of sleep consolidation and fragmentation, REM sleep latency, and delta density decline with sleep. An experimental protocol is suggested for acquiring baseline sleep data for genetic studies. This sleep recording protocol, scoring, and analysis system is designed to facilitate the understanding of genetic basis of sleep structure.
Forward-genetics analysis of sleep in randomly mutagenized mice
Nature, 2016
Sleep is conserved from invertebrates to vertebrates, and is tightly regulated in a homeostatic manner. The molecular and cellular mechanisms that determine the amount of rapid eye movement sleep (REMS) and non-REMS (NREMS) remain unknown. Here we identify two dominant mutations that affect sleep and wakefulness by using an electroencephalogram/electromyogram-based screen of randomly mutagenized mice. A splicing mutation in the Sik3 protein kinase gene causes a profound decrease in total wake time, owing to an increase in inherent sleep need. Sleep deprivation affects phosphorylation of regulatory sites on the kinase, suggesting a role for SIK3 in the homeostatic regulation of sleep amount. Sik3 orthologues also regulate sleep in fruitflies and roundworms. A missense, gain-of-function mutation in the sodium leak channel NALCN reduces the total amount and episode duration of REMS, apparently by increasing the excitability of REMS-inhibiting neurons. Our results substantiate the use o...
Identification of causal genes, networks, and transcriptional regulators of REM sleep and wake
2011
STUDY OBJECTIVE Sleep-wake traits are well-known to be under substantial genetic control, but the specific genes and gene networks underlying primary sleep-wake traits have largely eluded identification using conventional approaches, especially in mammals. Thus, the aim of this study was to use systems genetics and statistical approaches to uncover the genetic networks underlying 2 primary sleep traits in the mouse: 24-h duration of REM sleep and wake. DESIGN Genome-wide RNA expression data from 3 tissues (anterior cortex, hypothalamus, thalamus/midbrain) were used in conjunction with high-density genotyping to identify candidate causal genes and networks mediating the effects of 2 QTL regulating the 24-h duration of REM sleep and one regulating the 24-h duration of wake. SETTING Basic sleep research laboratory. PATIENTS OR PARTICIPANTS Male [C57BL/6J × (BALB/cByJ × C57BL/6J*) F1] N(2) mice (n = 283). INTERVENTIONS None. MEASUREMENTS AND RESULTS The genetic variation of a mouse N2 m...