Study design.

Thirty-three BXD lines plus the 2 parental strains and their reciprocal F1 progeny were phenotyped. Mice were submitted to either one of 2 experiments. In Experiment 1 (left), EEG/EMG signals and LMA were recorded under standard 12:12 h light–dark conditions (white and black bars under top-left panel) for 2 baseline days (B1, B2), a 6 h SD (red bar) from ZT0–6 (ZT0 = light onset), followed by 2 recovery days (R1, R2). The deep sleep-wake phenome consists of 341 sleep-wake state-, LMA-, and EEG-related phenotypes quantified in each mouse, among which time spent in NREM sleep (gray area spans mean maximum and minimum NREM sleep time among BXD lines, respectively, for consecutive 90 min intervals). Mice in Experiment 2 (right) were used to collect cortex, liver, and blood samples at ZT6. Half of the mice were challenged with an SD as in Experiment 1, the other half were left undisturbed and served as controls (labeled Ctr). Cortex and liver samples were used to quantify gene expression by RNA-seq, blood samples for a targeted analysis of 124 metabolites by LC/MS, or with FIA/MS. For phQTLs, mQTLs, and eQTLs, a high-density genotype dataset (Genome; approximately 11,000 SNPs) was created, merging identified RNA-seq variants with a publicly available database (www.genenetwork.org). The entirety of the multilevel dataset was integrated in a systems genetics analysis to chart molecular pathways underlying the many facets of sleep and the EEG, using newly developed computational tools to interactively visualize the results and pathways, and to prioritize candidate genes. EEG/EMG, electroencephalography/electromyogram; eQTL, expression quantitative trait locus; FIA/MS, flow injection analysis/mass spectrometry; LC/MS, liquid chromatography/mass spectrometry; LMA, locomotor activity; mQTL, metabolic quantitative trait locus; NREM, non-REM; phQTL, phenotypic quantitative trait locus; RNA-seq, RNA sequencing; SD, sleep deprivation; ZT, zeitgeber time.