In Brief

Highlights

SUMMARY

INTRODUCTION
Acetylcholine was the first identified neurotransmitter (Dale, 1937 ), and the cholinergic system is one of the most extensively studied regulatory systems for mammalian sleep (Brown et al., 2012 ). The pioneering studies reported that pathological damages to the brain regions, which later appeared to be major cholinergic sources, resulted in sleep disorders (Economo, 1930; McGinty and Sterman, 1968; Nauta, 1946 ). The discovery of the regulatory site for rapid eye movement (REM) sleep in the brain- stem (Jouvet, 1962) was affirmed by the induction of REM-sleep- like state by cholinergic agonists injected into the site (Cordeau et al., 1963; George et al., 1964 ). Therefore, the long-standing model of the transition from non-rapid eye movement (NREM) sleep to REM sleep incorporated acetylcholine as a key factor (Hobson et al., 1975; McCarley, 2004). In addition, acetylcholine release was found to be abundant in the brainstem during REM sleep (Kodama et al., 1990) and in the cortex during REM sleep and wakefulness (Teles-Grilo Ruivo et al., 2017 ). Despite this ev- idence, it is unclear whether cholinergic regulation is essential, i.e., required, for REM sleep, because multilayer complexity from neural circuits to molecules may compensate for perturba- tion of the cholinergic system at any one level. For example, cholinergic neurons in the basal forebrain (BF) and regions of the brainstem, including the laterodorsal tegmentum (LDT) and the pedunculopontine tegmentum (PPT), are crucial for REM sleep ( McCarley, 2004 ), but lesioning each of those cholinergic sites results in relatively minor effects ( Brown et al., 2012 ), empha- sizing the need for further neuronal subtyping to untangle the spatially intermingled circuits (Chung et al., 2017; Hayashi et al., 2015; Weber and Dan, 2016; Xu et al., 2015 ). In addition, there are eleven mammalian neuronal-type nicotinic acetylcho- line receptors, and five muscarinic acetylcholine receptors (Gotti and Clementi, 2004; Wess, 2004), which results in considerable redundancy that hinders the identification of critical cholinergic receptors. Although in vivo pharmacological manipulations demonstrated that muscarinic acetylcholine receptors are important for the regulation of REM sleep ( Brown et al., 2012 ), genetic approaches to assess the contribution of muscarinic acetylcholine receptors have been limited (Goutagny et al., 2005 ), and it is unknown which muscarinic receptors are partic- ularly important and whether they are indispensable for the regu- lation of REM sleep. To investigate these complexities, we took comprehensive ge- netic approaches to evaluate the role of cholinergic molecular factors in mice. First, we established a neuronal subtype of cholinergic neurons by finding enriched expression of the neuro- trophic receptor tyrosine kinase 1 (Ntrk1) (also called TrkA) gene and its potential co-receptor nerve growth factor receptor (Ngfr) in the brain region encompassing the basal forebrain. Temporally controlled synaptic inhibition of TrkA-expressing (TrkA+) and Ngfr-expressing ( Ngfr+) neurons demonstrated that those neu- rons were crucial for sleep. Interestingly, the short-sleep pheno- type caused by inhibition of TrkA+ and Ngfr+ neurons was associated with consolidated wakefulness in the dark phase, rendering the daily sleep profile more biphasic rather than the polyphasic profile naturally seen in mice and rats. Next, we iden- tified the acetylcholine receptors whose inhibition recapitulates the characteristic short-sleep profile observed by inhibition of TrkA+ and Ngfr+ neurons. We knocked out most acetylcholine receptor genes identified in mice by a triple-target CRISPR method (Sunagawa et al., 2016 ) and found that loss of two Gq- type muscarinic acetylcholine receptors—Chrm1 and Chrm3— induced the characteristic short-sleep profile. Both single knock- outs of Chrm1 and Chrm3 reduced NREM sleep and reduced and fragmented REM sleep, respectively. Double-knockout of Chrm1 and Chrm3 diminished REM sleep to an almost undetect- able level. These findings suggested that muscarinic acetylcho- line receptors Chrm1 and Chrm3 are essential for sleep regula- tion, especially for REM sleep, and function in different ways.
RESULTS
Synaptic Inhibition of TrkA-Positive Neurons by Tetanus Toxin Induced a Characteristic Short-Sleep Phenotype with Consolidated Wake in the Dark Phase For subtyping neurons in the BF/preoptic area (POA) regions, which have been shown to be important for sleep regulation (Brown et al., 2012 ), we performed genome-wide mRNA expres- sion profiling of the BF and/or POA region along with data from 48 other brain regions in the BrainStars database ( Figures 1A and S1A: Kasukawa et al., 2011 ). We found 22 candidate marker genes that were significantly enriched in the sampled BF and/or POA region (Figure 1B). Among them, we focused on TrkA and Ngfr , because NGF was implicated in the regulation of sleep (Ramos et al., 2011 ) and the majority of TrkA+ neurons in the BF and/or POA region coexpress choline acetyltransferase (ChAT) (Sobreviela et al., 1994; Figures 1B–1F). To examine the function of TrkA+ neurons, we first established TrkA-tTA bacte- rial artificial chromosome (BAC)-Tg mice and confirmed that the TrkA-tTA-driven gene was expressed in the BF and/or POA region by crossing TrkA-tTA mice with two independent reporter strains—tetO-tdTomato and tetO-tauLacZ mice (Li et al., 2010; Reijmers et al., 2007; Figures 1G–1I and S1B). Then we crossed TrkA-tTA mice with tetO-EGFP/TeNT mice ( Wada et al., 2007 ; Yamamoto et al., 2003 ) and produced dou- ble-transgenic TrkA-TeNT mice. In TrkA-TeNT mice, tetanus toxin (TeNT) is expressed and inhibits synaptic vesicle release in TrkA+ neurons under the control of Tet-off system. Shortly after birth, we provided mice with food containing 40 ppm doxy- cycline (dox-food) via their parental mother. After weaning and maturation with dox-food, we released mice to food without doxycycline (normal-food) and maintained mice for four weeks to allow for TeNT expression and inhibit TrkA+ neurons (from week 1 to week 4 in Figure S3A). We monitored the daily sleep profile using the non-invasive respiration-based automated sleep phenotyping system—snappy sleep stager (SSS) (Suna- gawa et al., 2016 ) — and, at week 4 with normal-food, found a severe short-sleep phenotype of 593.0 ± 26.3 min (mean ± SEM; n = 6) of total sleep duration in a day, which was 173.0 min shorter than that of control littermates (n = 13; p < 0.001; Figures 2A–2C and S3A–S3D). Here, we used littermates as control that harbored only one or none of the two transgenes. Reduction of the sleep duration was mostly attributable to decreased Pws (the transition probability from wakefulness to sleep), especially at night, hence consolidated wakefulness in the dark phase, which resulted in a high-amplitude variation in sleep duration (Figures 2B and 2C). This high-amplitude varia- tion of TrkA-TeNT mice is apparent in the contrast between the light (resting) and the dark (active) phases in the time series of sleep duration represented by the heatmap (Figure 2A). In addition, there was a period of partially recovered sleep propen- sity at the late dark phase (Figure 2B). We confirmed that TeNT expression was induced in the BF and/or POA regions at week 2 and 3 by fluorescent in situ hybridization (FISH) analysis (Figures S4A and S4B). On and after week 5, we returned TrkA-TeNT mice to dox-food, and the characteristic short-sleep phenotype gradually weakened after one month and almost diminished three months later (week 16; Figures 2D–2F and S3A–S3D). We also confirmed that TeNT expression was not detected in the BF and/or POA regions at week 16 by FISH analysis (Figures S4A and S4B). These temporally controlled phenotypes were confirmed with different concentrations of doxycycline (Figures S3E-S3H). Electroencephalogram (EEG) and electromyogram (EMG) re- cordings of sleep phenotypes of TrkA-TeNT mice recapitulated the characteristic short-sleep profile ( Figure 2G), eliminating the possibility that TrkA-TeNT mice had an abnormality in the respiration system that might confound SSS recordings. Although the EEG power spectrum did not have a notable change (Figure S7D), sleep duration was 636.2 ± 29.8 min (mean ± SEM; n = 5), which was 134 min shorter than that of con- trol littermates (p < 0.01; n = 4). The reduction was mostly attrib- utable to a significant reduction of the duration of NREM sleep (Figure 2H). Although the duration of the REM sleep was not significantly changed over a day at 57.2 ± 3.2 min (mean ± SEM; n = 5) compared with that of the control littermates at 69.2 ± 5.9 min (mean ± SEM; n = 4; p > 0.1), focused in the dark phase, it was significantly reduced at 3.9 ± 1.0 min (mean ± SEM), which was 5.7 min shorter than that of the control littermates (p < 0.01; Figure 21). We also generated Ngfr-TeNT mice by crossing Ngfr-tTA mice (Figure S2D) with tetO-EGFP/TeNT mice. Both SSS analysis and EEG and EMG recordings revealed that they had the character- istic short-sleep profile with consolidated wake in the early dark phase (Figures 2J–2L, S2H, and S2I). Although the EEG power spectrum did not have a significant change (Figure S7E), the sleep duration measured by SSS was 620.9 ± 26.5 min (mean ± SEM; n = 7), which was 132 min shorter than that of control littermates (p < 0.01; n = 13; Figures 2J–2L). Furthermore, without temporal dox administration, the characteristic sleep phenotype was also observed in both TrkA-TeNT and Ngfr- TeNT mice (Figures S2A–S2C and S2E–S2G). In addition, inhibition of TrkA+ neurons in circadian-clock-defi- cient mice (Per1/2 double-knockout [DKO] mice; Bae et al., 2001) demonstrated that the function of TrkA+ neurons does not require a functional circadian clock (Figures S2J–S2O), excluding the possibility that TrkA+ neurons might have a role in the circadian process (process C) of the two-process model ( Borbély, 1982 ). Together, these results suggested that TrkA- and Ngfr-express- ing neurons regulate sleep in a way that promotes sleep.
Specific Rescue of ChAT-Positive Neurons in TrkA-TeNT
Mice Restored Sleep Duration
The majority of TrkA+ neurons in the BF and/or POA region are cholinergic (Sobreviela et al., 1994), but TrkA expression was also found in non-cholinergic neurons in other brain regions, including the interpeduncular nucleus (IPN) (Holtzman et al., 1995 ), which is implicated in the regulation of REM sleep ( Funato et al., 2010 ). To further characterize TrkA+ neurons that are responsible for the characteristic short-sleep phenotype of TrkA-TeNT mice, we designed a Tet effector tTR, which stands for tTA repressor. tTR inhibits tTA activity only when both are coexpressed in the same cells in a similar manner of Ga/80 and Gal4 in fruit fly genetics (Figure 3A: Lee and Luo, 1999). In cultured cell analysis, tTR effectively repressed tTA-induced tetO-luciferase activity in a dose-dependent manner (Figure 3B). For in vivo application of tTR, we first established embryonic stem cells (ESCs) from TrkA-TeNT mice. Then we generated two different tTR knockin strains, ChAT-tTR and VgluT1-tTR, with TrkA-TeNT ESCs and the TALEN-based gene-targeting strategy ( STAR Methods ; Ode et al., 2017b ; Ukai et al., 2017 ). In TrkA-TeNT;VGluT1-tTR mice, the characteristic short-sleep phenotype of TrkA-TeNT mice did not change (Figures 3C–3E). On the other hand, in TrkA-TeNT:ChAT-tTR mice, the short- sleep phenotype was mostly abolished (Figures 3C–3E). FISH analysis of those mice confirmed that TeNT expression was sup- pressed in TrkA-TeNT;ChAT-tTR mice, but not in TrkA-TeNT; VGluT1-tTR mice (Figure 3F). Furthermore, we generated VGluT1-tTR or ChAT-tTR single-knockin mice and confirmed that tTR and either VGIuT1 or ChAT was coexpressed by FISH (Figures S4C and S4D). These results suggested the TrkA+ cholinergic neurons are primarily responsible for the character- istic phenotype observed in TrkA-TeNT mice (Figures 2A–2C).
Comprehensive Analysis of Nicotinic Acetylcholine
Receptor KO Mice Showed Moderate Effects
After we discovered that TrkA+ cholinergic neurons have a crucial role in the regulation of sleep, we sought to elucidate the function of cholinergic receptors by comprehensively exam- ining the phenotypes of acetylcholine receptor knockout (KO) mice. There are two different families of acetylcholine receptors— nicotinic receptors and muscarinic receptors. Nicotinic acetyl- choline receptors (nAchR) consist of five types of subunits— alpha (α1–10), beta (β2–5), delta, epsilon, and gamma. These subunits can be divided into the muscle type and neuronal type. We focused on the mammalian neuronal type and targeted eleven genes—Chrna2, Chrna3, Chrna4, Chrna5, Chrna6, Chrna7, Chrna9, Chrna10, Chrnb2, Chrnb3, and Chrnb4 (Gotti and Clementi, 2004 ). To efficiently produce KO mice of each gene, we used a triple-target CRISPR method (STAR Methods). The genotype of KO mice was confirmed by gPCR (Figure S5: Table S2). KO of Chrna3 was lethal because mice died shortly af- ter birth (n = 26), which was consistent with the result of the con- ventional KO method (Xu et al., 1999). Among the KO mice, Chmb2 KO had a sleep profile resembling that of TrkA-TeNT mice (Figures 4A–4C and 2A–2C), but changes in sleep and wake parameters, including sleep duration, amplitude, and Pws, were not significant within the statistical power achieved by availability of the mutant mice. Changes in other KO mice were weaker than those of Chrnb2 KO, and none were significant (Figure 4C). Chrnb3 KO mice (n = 8), which were obtained in an additional batch of KO mice production at different research site, had significant changes in amplitude and Pws, but the change of sleep duration was moderate at 649.3 ± 13.5 min (mean ± SEM; n = 8), which was only 38.3 min shorter than that of wild-type (WT) mice (less than 0.76 SD; p < 0.05; n = 108; Figures 4D–4F). These results suggested that nicotinic acetylcholine receptors have relatively minor roles in the regula- tion of sleep. Comprehensive Analysis of Muscarinic Acetylcholine Receptor KO Mice Revealed that Chrm1 and Chrm3 Are Important for Sleep Regulation Therefore, we focused on muscarinic acetylcholine receptors (mAchRs), which are G-protein-coupled receptors comprising five members (Chrm1, Chrm2, Chrm3, Chrm4, and Chrm5; Wess, 2004 ), and comprehensively examined KO phenotypes with a triple-target CRISPR method (STAR Methods: Figure S6; Table S2 ). Interestingly, KO mice of two Gq-type muscarinic acetylcholine receptors, Chrm1 KO and Chrm3 KO, had the characteristic short-sleep profile with consolidated wake in the early dark phase, which resembled the sleep profile of TrkA- TeNT mice (Figures 5A–5C and 2A–2C). Sleep duration was decreased to 642.3 ± 25.5 min in Chrm1 KO mice (mean ± SEM; n = 8) and 607.0 ± 7.0 min in Chrm3 KO mice (mean ± SEM; n = 11), which was 82.4 min and 117.7 min shorter, respec- tively, (p < 0.01 and more than 1.85 SD for Chrm1 and p < 0.001 and more than 2.64 SD for Chrm3) compared to that of WT mice (n = 108). To preclude the possibility of off-target effects of the CRISPR guide RNAs used for producing Chrm1 KO and Chrm3 KO mice (set 1 in Figures 5A–5C and S6), we produced another group of KO mice using independent CRISPR quide RNAs (set 2; Fig- ure S6) and confirmed the observed characteristic short-sleep phenotypes (Figures 5D–5G). These results strongly suggested that the observed short-sleep phenotype of Chrm1 and Chrm3 KO mice cannot be attributed to the possible off-target effects of CRISPR but rather to the common genomic defects in the Chrm1 and Chrm3 genes, respectively. Importantly, the observed reduction of sleep duration in Chrm1 KO mice (set 2) and Chrm3 KO mice (set 2) was mostly attributable to the decreased Pws in the early dark phase (Figures 5F and 5G), which was also observed in Chrm1 KO mice (set 1) and Chrm3 KO mice (set 1; Figures 5B and 5C) as well as in TrkA-TeNT mice (Figures 2B and 2C).
Chrm3 KO Reduced the Duration of NREM Sleep and
Fragmented REM Sleep
To further ensure that the characteristic short-sleep pheno- type was not because of an artifact of sleep evaluation by the respiration-based SSS, we performed EEG and EMG recordings of Chrm1 and Chrm3 KO mice (set 1) used in the previous measurement (Figures 5A–5C) and confirmed the characteristic sleep profile with consolidated wake in the dark phase (Figures 6A, 6D, and 6G). Interestingly, EEG and EMG revealed that Chrm1 KO and Chrm3 KO mice had different sleep architectures (Figures 6B and 6E). Notably, the power spectrum of Chrm3 KO mice displayed increased power both in the delta (0.5–4 Hz) and theta (6–10 Hz) domains in sleep, implying that the synchrony of cortical neurons was increased at those frequency domains in Chrm3 KO mice (Fig- ures S7A and S7B). In Chrm3 KO mice, the duration of NREM sleep in a day was significantly reduced at 542.9 ± 16.5 min, which was 152.5 min shorter than that of WT mice (n = 6; p < 0.001), but the duration of REM sleep in a day did not significantly change at 73.7 ± 4.4 min compared with that of WT mice (p = 0.86; Figure 6E). The reduction of the duration of NREM sleep was attributable to decreased P WN (the transition probability from wakefulness to NREM sleep) and increased Pww (the transition probability from wakefulness to wakefulness or the probability of staying in wakefulness), especially in the dark phase (Figures 6F and 6G; Table S3 ). The duration of REM sleep did not significantly change ( Table S3 ). However, the transition probabilities be- tween REM sleep and NREM sleep ( P BN and P NB ) were mutu- ally increased (Figure 6F), especially in the light phase (Fig- ure 6G). The increased transition with the retained total duration of REM sleep indicated that REM sleep was frag- mented, and hence, PBB (the transition probability from REM sleep to REM sleep or the probability of staying in REM sleep) was decreased (Figure 6F), resulting in the reduced episode duration of REM sleep ( Table S3C ). Together, these observa- tions suggested that Chrm3 has a role in regulating the duration of NREM sleep in a day but also contributes to the consolida- tion of REM sleep.
Chrm1 KO Reduced the Duration of REM Sleep
In contrast to Chrm3 KO mice that retained the duration of REM sleep in a day, Chrm1 KO mice had a significantly decreased duration of REM sleep in a day at 47.4 ± 4.8 min, which was 33.6 min shorter than that of WT mice (n = 7; p < 0.001; Figures 6B and 6E; Table S3 ). The reduction in the duration of REM sleep was accounted for by an increased P RN (the transition probability from REM sleep to NREM sleep), implying weakened mainte- nance of REM sleep ( Figures 6C and 6G; Table S3 ). Although not as much as Chrm3 KO mice, Chrm1 KO mice also had a sig- nificant reduction in the duration of NREM sleep at 612.6 ± 23.6 min, which was 116.8 min shorter than that of WT mice (n = 7; p < 0.001). The reduction of the duration of NREM sleep was mostly attributable to reduced Pwn and increased Pww, especially in the dark phase ( Figures 6C and 6G; Table S3 ), which resulted in the characteristic short-sleep profile with consolidated wakefulness in the dark phase as was observed in Chrm3 KO mice (Figures 6A and 6G). These observations sug- gested that Chrm1 has a role in regulating the duration of REM sleep but also contributes to the duration of NREM sleep.
Chrm1 and Chrm3 Are Essential for REM Sleep and
Important for NREM Sleep
Compared to TrkA-TeNT mice, changes in sleep phenotype, especially changes in amplitude and Pws, of Chrm1 KO mice and Chrm3 KO mice were moderate (Figures 5G and 2C; Table S3). To examine the combinatorial effect of Chrm1 and Chrm3 for sleep, we produced Chrm1 and Chrm3 double-KO mice (Chrm1/3 dKO mice) by triple-target CRISPR (set 1/set 1; Figure S6O) and measured phenotypes using SSS (Figures 6H-6J). Chrm1/3 double-KO mice had changes in sleep dura- tion, amplitude, and Pws to a degree comparable to that of TrkA-TeNT mice (Figures 61, 6J, 2B, and 2C; Table S3). In Chrm1/3 double-KO mice, sleep duration in a day was reduced to 591.1 ± 16.8 min (mean ± SEM; n = 5), which was 133.6 min shorter, amplitude was increased, and Pws was decreased compared to that of control mice (n = 108; p < 0.001 and more than 2.85 SD for the sleep duration; p < 0.001 for amplitude; p < 0.001 for Pws; Figures 6J and 2C; Table S3 ). Decreased Pws, especially in the dark phase, resulted in the characteristic short-sleep profile with consolidated wakefulness in the early dark phase ( Figure 61 ). In addition, both TrkA-TeNT mice and Chrm1/3 double-KO mice consistently exhibited the enhanced rebound sleep after sleep deprivation, which suggested that ho- meostatic sleep control remained functional in those mutant mice (Figures S7F–S7I). We observed the phenotypes of Chrm1/3 double-KO mice by EEG and EMG recordings, which confirmed the characteristic short-sleep phenotype with consolidated wakefulness in the dark phase (Figure 6K). Strikingly, dKO of Chrm1 and Chrm3 diminished REM sleep to an almost undetectable level (Figure 6L; Table S3 ). We did not find any overt abnormality resembling those found in REM behavior disorder (RBD) (Krenzer et al., 2011; Lu et al., 2006 ) by visual inspection of recorded video at timing of EEG theta-oscillation dominant period. We also checked transition periods from NREM sleep to wakefulness, which might contain REM sleep masked by RBD, and did not find any abnormality ( Krenzer et al., 2011 ; Lu et al., 2006 ). Although the interruption of REM sleep by abnormal behaviors could increase the transition probability from REM sleep to wakefulness ( P RW ) by conventional EEG analysis, P RW did not exhibit any marked increase either in Chrm1 and Chrm3 single- KO mice (Figures 6C and 6F), which supports the claim that RBD is not masking REM sleep in Chrm1/3 double-KO mice. Interestingly, the hypnograms showed that there is virtually no emergence of typical polygraphic manifestation of REM sleep, that is, a lasting low-delta power and low muscle tone in the Chrm1/3 double-KO mice (Figure 7C). In line with this observa- tion, the EEG power spectrum of Chrm1/3 double-KO mice dis- played reduced theta power in NREM sleep (Figure S7C). To further ensure loss of REM sleep, we produced another group of Chrm1/3 double-KO ESC mice by injecting CRISPR- edited ESCs into 8-cell stage embryos (Ode et al., 2017a; Ukai et al., 2017 ) and performed EEG and EMG recordings to evaluate the response of sleep deprivation in Chrm1/3 double-KO ESC mice. Chrm1/3 double-KO ESC mice were implanted with EEG and EMG probes, housed in a 12:12 hr light-dark cycle, and stim- ulated with the gentle touch of a brush to deprive sleep from zeit- geber time 6 (ZT6) to ZT12. REM sleep in Chrm1/3 double-KO ESC mice was virtually not detected both before and after sleep deprivation, despite a rebound in total sleep (14.3% increase; p < 0.01 from 276.7 ± 11.4 min in basal duration to 316.2 ± 11.0 min in rebound duration) and rebound REM sleep (154.4% increase; p < 0.001 from 16.5 ± 2.8 min to 37.4 ± 1.3 min) in the control WT mice or rebound total sleep in Chrm1/3 double-KO ESC mice (49.5% increase; p < 0.05 from 112.9 ± 16.1 min in basal duration to 168.8 ± 18.7 min in rebound duration; Figure 6M). These re- sults demonstrated that two Gq-type muscarinic acetylcholine receptors Chrm1 and Chrm3 are essential for REM sleep.
DISCUSSION
Since the pioneering works of defining REM sleep based on EEG and EMG (Aserinsky and Kleitman, 1953; Dement and Kleitman, 1957 ) and demonstrating that neural circuits in the brainstem are necessary and sufficient for REM sleep generation (Jouvet, 1962 ), our knowledge on the neural circuitry for regulating REM sleep has been steadily advancing (Hayashi et al., 2015; Weber and Dan, 2016 ). However, the essential molecular factors for defining and translating the output of the brainstem circuit to the collective activity of cortical neurons have been elusive. Mul- tiple lines of in vivo pharmacological evidence consistently indi- cated that muscarinic acetylcholine receptors are important for the regulation of REM sleep. Muscarinic receptor agonists and acetylcholinesterase inhibitors increase REM sleep and shorten REM latency (the delay of the onset of REM sleep to that of NREM sleep; Brown et al., 2012 ). Moreover, muscarinic receptor antagonists decrease REM sleep and lengthen REM latency ( Brown et al., 2012 ). Nonetheless, genetic approaches to assess the contribution of muscarinic acetylcholine receptors to REM sleep regulation have been limited (Goutagny et al., 2005 ), and it is unknown which muscarinic acetylcholine receptors are required for the regulation of REM sleep. In the present study, our comprehensive genetic assays of acetylcholine receptors re- vealed that two Gq-type muscarinic acetylcholine receptors Chrm1 and Chrm3 of the five muscarinic acetylcholine receptors from Chrm1 to Chrm5 are important for REM sleep. KO of other Gq-type receptor Chrm5 did not significantly change sleep phe- notypes, which may reflect the low abundance of Chrm5 in the brain. Chrm1 and Chrm3 are broadly expressed in different brain regions, including the cortex and the hippocampus, but Chrm5 is expressed in relatively limited regions, such as the substantia ni- gra and the ventral tegmental area (VTA), in the midbrain (Basile et al., 2002; Buckley et al., 1988; Yasuda et al., 1993 ). Chrm1/3 double-KO mice had an almost complete loss of REM sleep, which strongly suggested that Chrm1 and Chrm3 are essential for REM sleep. In addition, the Chrm1/3 double-KO mice exhibited the char- acteristic short-sleep profile with consolidated wakefulness in the early dark phase. This characteristic phenotype was also observed in Chrm1 and Chrm3 single-KO mice and in TrkA- TeNT mice. Reduction of sleep duration of all those mice was mostly attributable to the reduced duration of NREM sleep, indi- cating that cholinergic regulation is also important for NREM sleep. Impaired REM sleep might also reduce the duration of NREM sleep (Hayashi et al., 2015 ) because our observation indi- cated that the loss of either Chrm1 (Figures 6B, 6C, 7A, and 7D), Chrm3 (Figures 6E, 6F, 7B, and 7E), or both (Figures 6L, 7C, and 7F) resulted in reduced, fragmented, and diminished REM sleep, respectively. However, the question of how cholinergic path- ways regulate NREM sleep remains unresolved (Figure 7G). Recent optogenetic and pharmacogenetic studies suggested that cholinergic neurons promote wakefulness at the circuit level (Chen et al., 2016; Shi et al., 2015; Xu et al., 2015; Zant et al., 2016 ), whereas our results indicated that cholinergic regulation suppresses wakefulness at the systems level. This apparent inconsistency may be reconciled by hypothesizing muscarinic modulation of other neurotransmitter systems, such as glutama- tergic neurons ( Kamsler et al., 2010 ; Weng et al., 2014 ) and GABAergic neurons ( Xiao et al., 2009 ), or by hypothesizing the proximal projection of TrkA+ neurons to sleep-promoting neu- rons, such as POA GABAergic neurons, that inhibit wake-pro- moting neurons in the tuberomammillary histaminergic neurons (TMNs) (Chung et al., 2017 ). Indeed, a specific cholinergic re- ceptor could be sleep-promoting although overall effect of the cholinergic system is wake promoting, as reported for the redeye mutant in Drosophila , where REM sleep has so far not been iden- tified (Shi et al., 2014 ), implying the sleep-promoting cholinergic effect might be independent of REM sleep (Figure 7G). Our findings of the essential role of Chrm1 and Chrm3 genes in REM sleep will provide useful tools in future studies of REM sleep. In particular, the finding of unexpected viability despite the almost completely abolished REM sleep will allow us to rigor- ously verify whether REM sleep plays crucial roles in funda- mental functions of organism, such as learning and memory (Crick and Mitchison, 1983; Dement et al., 1967; Li et al., 2017 ), and open a way to study its underlying molecular and cellular mechanisms.
STAR★METHODS
Detailed methods are provided in the online version of this paper and include the following: ● KEY RESOURCES TABLE ● CONTACT FOR REAGENT AND RESOURCE SHARING ● EXPERIMENTAL MODEL AND SUBJECT DETAILS️Cultivation of mouse embryonic stem (ES) cells ○ Mice and sleep phenotyping Transfection and Luciferase Assay ● METHOD DETAILS゙Sampling of POA/BF regions ○ Microarray analysis ○ Generation of TrkA-tTA and Ngfr-tTA transgenic mouse lines ○ Construction of tTR ○ Generation of ChAT-tTR-nmNGx3 and VGluT1-tTR- nmNGx3 KI mice Triple-target CRISPR: gRNA synthesis ○ Triple-target CRISPR: Cas9 mRNA synthesis ○ Triple-target CRISPR: One-cell embryo microinjection ○ Triple-target CRISPR: Genotyping of KO mice and ESCs by quantitative PCR (qPCR) and sequencing Establishment of Chrm1/3 dKO ES cell ○ Sleep measurement with SSS ● Sleep measurement with EEG and EMG recordings️Visual inspection on behaviors ○ Sleep deprivation with SSS ○ Sleep deprivation with EEG and EMG recordings ○ X-gal staining and fluorescent imaging of Tet reporter mice️In situ hybridization ● QUANTIFICATION AND STATISTICAL ANALYSIS ● DATA AND SOFTWARE AVAILABILITY
SUPPLEMENTAL INFORMATION
Supplemental Information includes seven figures and three tables and can be found with this article online at https://doi.org/10.1016/j.celrep.2018.07.082 .
ACKNOWLEDGMENTS
We thank S. Nakanishi for tetO-EGFP/TeNT mice (obtained from RIKEN BRC no. RBRC02958); D.R. Weaver for Per1/2 DKO mice; T. Tsuji, K. Toyoshima, and K. Asakawa for FISH imaging; T. Mikami for SSS; R. Kageyama for BAC constructions; S. Yoshiura for critical comments; and I. Nikaido for administra- tion of the server of Brainstars. We also thank all the lab members at RIKEN Center for Development Biology (CDB), QBiC, Center for Biosystems Dy- namics Research (BDR), and the University of Tokyo; in particular, S. Fujino, Y. Fujiwara, K. Furuno, J. Hara, S. Hasegawa, T. Haze, N. Hori, A. Kishimoto, K. Kuwana, N. Koide, C. Kominami, M. Kunimi, K. Masawaki, E. Matsushita, A. Millius, A. Nishiyama, M. Nomura, Y. Sakakida, G. Sato, M. Shiokawa, E.A. Susaki, K. Tanaka, K. Tsujino, Y. Uranyu, M. Yamamoto, J. Yoshida-Garçon, H. Yukinaga, and Y. Wada for their kind help in preparing the materials and supporting experiments and the LARGE, RIKEN BDR for housing the mice. This work was supported by a grant from Japan Agency for Medical Research and Development (AMED)-Core Research for Evolution Science and Technol- ogy (CREST) (JP17gm0610006; AMED/Ministry of Education, Culture, Sports, Science and Technology [MEXT]; H.R.U.), CREST (Japan Science and Tech- nology Agency [JST]/MEXT; H.R.U.), Brain Mapping by Integrated Neurotech- nologies for Disease Studies (Brain/MINDS) (AMED/MEXT; H.R.U.), Basic Sci- ence and Platform Technology Program for Innovative Biological Medicine (AMED/MEXT; H.R.U.), a Grant-in-Aid for Scientific Research (S; Japan Soci- ety for the Promotion of Science [JSPS] KAKENHI grant number 25221004; H.R.U.), a Grant-in-Aid for Scientific Research (B; JSPS KAKENHI grant num- ber 15H04408; K.S.), a Grant-in-Aid for Scientific Research on Innovative Areas (JSPS KAKENHI grant number 23115006 to H.R.U.; 26113720 to K.S.), the strategic programs for R&D (President's Discretionary Fund) of RIKEN (to H.R.U.), an intramural Grant-in-Aid from the RIKEN Quantitative Biology Center (to H.R.U.), an incentive research fund from RIKEN (to Y.N.), a Grant-in-Aid for Challenging Exploratory Research (grant number 25560427; Y.N.), a Grant-in-Aid for JSPS Fellows (grant number 13J01565; G.N.K.), a Grant-in-Aid for Young Scientists (B; grant number 16K21619; G.N.K.), the RIKEN Special Postdoctoral Research Program (to Y.N. and G.N.K.), and an ECARD grant from Queensland University of Technol- ogy (to D.P.).
AUTHOR CONTRIBUTIONS
H.R.U., Y.N., G.N.K., and R.G.Y. designed the study. K.M., M.N., T.K., and Y.S. performed microarray. M.U.-T., H.F., and K.S. performed the triple-target CRISPR. Y.N., H.U., and H.K. established genetically modified mice. Y.N., G.N.K., R.G.Y., S.S., G.A.S., and N.M. performed the sleep phenotype anal- ysis. Y.N. and G.N.K. performed in situ hybridization. Y.N., G.N.K., J.G., and D.P. performed CUBIC analysis. R.G.Y., Y.N., G.N.K., and H.R.U. wrote the manuscript. All authors discussed the results and commented on the manu- script text.
DECLARATION OF INTERESTS
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Further information and requests for reagents should be directed to Lead Contact Hiroki R. Ueda (uedah-tky@umin.ac.jp). Cultivation of mouse ES cells was conducted with the same protocol described in the previous report (Ode et al., 2017b; Ukai et al., 2017). Before cultivation, the surface of PURECoat™ amine dishes (Beckton-Dickinson, NJ, U.S.A.) were exposed to medium con- taining LIF plus 6-bromoindirubin-30-oxime (BIO) (Sato et al., 2009) for more than 5 hours at 37°C with 5% CO 2 . ES cells were cultured with or without feeder cells in 3i medium (Clontech Laboratories, Inc. A Takara Bio Company, Japan) at 37°C with 5% CO 2 . All experimental procedures and housing conditions were approved by the Institutional Animal Care and Use Committee of RIKEN Kobe Branch, and all the animals were cared for and treated humanely in accordance with the Institutional Guidelines for Experiments using Animals. All mice were given food and water ad libitum and maintained at ambient temperature and humidity. The light was controlled under 12 h light and 12 h dark cycle. Production and sleep phenotyping of Chrna2, Chrna4, Chrna5, Chrna6, Chrna7, Chma9, Chma10, Chmb2, and Chmb4 KO mice were performed in RIKEN CDB at Kobe using the sleep phenotype of C57BL/6N mice (n = 108) published in our previous paper for data on control mice (Sunagawa et al., 2016). Creation and sleep phenotyping of Chrnb3, Chrm1, Chem2, Chrm3, Chrm4, and Chrm5 KO mice were performed in RIKEN QBiC at Osaka using C57BL/6N mice (n = 107) for control data. 293T cells (American Type Culture Collection, ATCC) were maintained in DMEM (Thermo Fisher Scientific, MA, U.S.A.) supplemented with 10% FBS (Merck, Germany) and antibiotics (100 U/mL penicillin and 100 μg/mL streptomycin; Thermo Fisher Scientific, MA, U.S.A.) at 37°C with 5% CO 2 . One day prior to transfection, cells were plated onto 35 mm dishes at a density of 4 × 10° cells per well. The following day, 293T cells were co-transfected using FuGene6 (Roche, Switzerland) with 0.2 μg of a luciferase reporter plasmid (ptetO-Luc) and the indicated amount ( ιιθ ) of effector plasmids (pEF-tTA and pEF-tTR) (pEF-BOS vectors were previously developed (Mizushima and Nagata, 1990)) in Figure 3B (n = 3), according to the manufacturer's instructions, and cultured at 37°C. Empty vector was used to make up the total amount of DNA to 2 μg per well. Additionally, 40 ng of a pRL-SV40 plasmid (Renilla luciferase (RLuc) reporter vector; Promega, WI, U.S.A.) was added to each transfection as an internal control for transfection effi- ciency. Twenty-four hours after transfection, cells were harvested and assayed with a Dual-Luciferase Reporter Assay System (Promega, WI, U.S.A.). Luciferase (FLuc) activity was normalized by RLuc activity. Data are representative of two independent experiments. The samples of POA/BF regions were collected with the same protocol used in the previous report (Kasukawa et al., 2011). That is, 5-week BALB/c male mice were conditioned under a standard 12:12 light/dark cycle (LD) for 2 weeks, and samples were obtained under LD or constant darkness (DD) conditions every 4 h for 1 day starting at ZT0. At each time point, 0.5 mm-thick slices of mouse brain were cut on a Mouse Brain Matrix (Neuroscience Inc., Japan) and frozen. POA/BF regions in the brain slices were punched out bilaterally with a microdissecting needle (gauge 0.5 mm) under a stereomicroscope. We sampled 25 mice at each time point. The whole procedure was repeated twice (n = 2) to obtain experimental replicates. In obtaining an expression profile of POA/BF regions, we used the same experimental procedure as one used in the previous report (Kasukawa et al., 2011). Briefly, total RNA was extracted from the pooled POA/BF samples using Trizol reagent (Thermo Fisher Sci- entific, MA, U.S.A.). RNA samples were reverse transcribed, labeled, and hybridized to Affymetrix GeneChip Mouse Genome 430 2.0 according to the manufacturer's instruction (Affymetrix one-cycle method). The expression values were summarized together with the samples used in the previous report (Kasukawa et al., 2011) by the RMA method. CNS region-specific genes were identified with the method described in the previous report (GEO; GSE107500) (Kasukawa et al., 2011). BAC DNAs (R24-222B4 for TrkA-tTA and R24-309N6 for Ngfr-tTA) were obtained from BACPAC resources center at CHORI. BAC modification was performed by recombineering ( Warming et al., 2005 ). Briefly, tTA and SV40 polyA signal sequences were amplified from pTet-off (Clontech, CA, U.S.A.) and inserted into just after the start codon of TrkA or Ngfr genes by recombineering. Modified BAC DNAs were confirmed by electrophoresis and purified by NucleoBond Xtra midi (Macherey-Nagel, Germany). Purified transgene DNA was eluted with TE (10 mM Tris, 1 mM EDTA, pH 8.0) buffer, diluted with PBS(-) buffer to a final concentration of 5 ng/μL, and injected into pronuclei of C57BL/6N zygotes as reported previously (Abe et al., 2013). Transgenic lines termed TrkA-tTA (Acces- sion number CDB0522T: http://www2.clst.riken.jp/arg/TG%20mutant%20mice%20list.html) and Ngfr-tTA (Accession number CDB0523T: http://www2.clst.riken.jp/arg/TG%20mutant%20mice%20list.html) were selected for analysis based on PCR screening and fertility. Transgenic lines were successively backcrossed with C57BL/6N; mice were genotyped by PCR with the primers 5′-ggaaggcgagctggcattagggcctcaaaa-3′, 5′-cgacatccagacagtgactgcgcggctctg-3′, and 5′-tcttgccatgactcgccttccaggggcag-3′ for TrkA-tTA, and the primers 5′-gaggaggcgggctgctgcattgccttcac-3′, 5′-gactgctcccagtctcctacaccgcacccg-3′, and 5′-tcttgccat gactcgccttccaggggcag-3' for Ngfr-tTA , yielding 619 bp and 434 bp products ( TrkA-tTA ) and 585 bp and 426 bp products ( Ngfr- tTA), respectively. Our tTR system is similar to the tetracycline-controlled transcriptional silencer (tTS), which was originally developed to repress basal tetO promoter activity by blocking reverse tetracycline-controlled transactivator (rtTA) in the absence of doxycyline (dox) (Freundlieb et al., 1999). tTS doesn't bind to rtTA because it is not intended to interrupt rtTA's induction activity in the presence of dox. tTR was designed and generated by replacing the transcription activator domain of tTA with NLS and KRAB transcription suppressor domains (underlined in the following sequence) so that it could form a tTA-tTR heterodimer and effectively repress tTA activity. The amino acid sequence of tTR is as follows: MSRLDKSKVINSALELLNEVGIEGLTTRKLAQKLGVEQPTLYWHVKNKRALLDALAIEMLDRHHTHFCPLEGESWQDFLRNNAKSFRC ALLSHRDGAKVHLGTRPTEKQYETLENQLAFLCQQGFSLENALYALSAVGHFTLGCVLEDQEHQVAKEERETPTTDSMPPLLRQAIELFD HQGAEPAFLFGLELIICGLEKQLKCESGGPKKKRKLAVSVTFEDVAVLFTRDEWKKLDLSQRSLYREVMLENYSNLASMAGFLFTKPKVI SLLQQGEDPW. tTR fused with P2A at the N terminus, T2A at the C terminus, and BGH polyA were synthesized and cloned into the pENTR vector (ThermoFisher, USA) to make pENTR-2A-tTR. mNeonGreen (Allele Biotechnology, U.S.A.) with an NLS at the N terminus and two mNeonGreen were amplified and fused tandemly into nmNGx3. Then, nmNGx3 was cloned into the EcoRI site of the pENTR-2A- tTR vector by ligation. Destination vectors for targeting into the C terminus of the cholinergic marker gene choline acetyltransferase (ChAT) and the glutamatergic marker gene vesicular glutamate transporter 1 (VGluT1) were constructed as follows: Right-homology arms were amplified by PCR with the primers listed: forward primer for ChAT (5′-ggctcgatccctcgagttggggctca catgaagctgg-3'), reverse primer for ChAT (5'-cgggaattcgatgatatcgaatgcatcactgcttcaaacaactgtc-3'), forward primer for VGIuT1 (5′-ggctcgatccctcgaggcctgagcggcagtgtcgagg-3′), and reverse primer for VGluT1 (5′-cgggaattcgatgatatcgagcagaaactgaggtgca gac-3'). The PCR products were inserted into the Xhol and EcoRV digested back-bone vector pTVCI3 (Tainaka et al., 2014) using the In-Fusion HD Cloning Kit (Clontech Laboratories, Inc. A Takara Bio Company, Japan). Left-homology arms were amplified by PCR with primers as listed: forward primer for ChAT (5′-tagggataacagggtaatatagaggtgacagcaggattggaagtg-3′), reverse primer for ChAT (5'-gcggagaaagaggtaatgaaatgggcgtgggagtagtcaagattgcttgg-3'), forward primer for VGIuT1 (5'-tagggataacagggtaata tagccctcgctatgccagcatcttg-3′), and reverse primer for VGluT1 (5′-gcggagaaagaggtaatgaaatgggcgtagtcccggacaggggcg-3′). The products of first PCR for the left-homology arms were amplified with primers (5′-gcagttacgctagggataacagggtaatatag-3′ and 5′-gat catctatgtcgggtgcggagaagaggtaatgaaatgg-3′) and inserted into the I-Scel and PI-Scel digested pTVCI3-Rarm using the In-Fusion HD Cloning Kit. The puromycin resistance gene cassette (P(PGK)-Puro n-polyA) was inserted into I-Ceul and PI-Pspl digested pTVCI3-LRarm. Targeting, screening, and injection were performed according to the procedures described previously (Ode et al., 2017b; Ukai et al., 2017). The target sequences for Chrna2, Chrna4, Chrna5, Chrna6, Chrna7, Chrna9, Chrna10, Chrna10, Chrnb2, Chrnb3, Chrnb4 (Figures S5A–S5J), Chrm1 (set 1 and 2), Chrm2, Chrm3 (set 1 and 2), Chrm4, and Chrm5 (Figures S6A–S6E, S6K, and S6L) were designed using the on-line CRISPR guide RNA Design tool (Ma et al., 2013) or the mm10 CRISPR/Cas9 database (Sunagawa et al., 2016) (http:// crispr.riken.jp/). Possible off-target sequences within the mouse genome for each target sequence were checked using the CRISPR Design Tool (Ran et al., 2013) (http://tools.genome-engineering.org). Guide RNA (gRNA) synthesis was performed using the same protocol described in the previous report (Sunagawa et al., 2016). The gRNA templates were directly synthesized and fused to the T7 promoter by PCR. First, partial fragments of the gRNA templates including each target sequence were amplified from the pX330 plasmids (Addgene, #42230) (Cong et al., 2013; Ran et al., 2013) by PCR with the common reverse primer (5'-aaaagcaccgactcggtgcc-3'; Hokkaido System Science, Japan or Fasmac, Japan) (Wang et al., 2013) and forward primer-1 for each target sequence (Table S2A, Hokkaido System Science, or Fasmac). Subsequently, the T7 promoter-fused gRNA templates were amplified from the diluted PCR products by PCR with the common reverse primer and forward primer-2 for each target sequence ( Table S2A, Hokkaido System Science, or Fasmac). The T7 promoter-fused gRNA PCR fragments were used as a template for in vitro transcription using the MEGAshortscript T7 kit (Thermo Fisher Scientific, MA, U.S.A.). The gRNAs were purified using the MEGAclear kit (Thermo Fisher Scientific, MA, U.S.A.). Cas9 mRNAs were synthesized with the same protocol described in the previous report (Sunagawa et al., 2016). The p3s-Cas9HC plasmid (Cho et al., 2013) (Addgene, #43945), which includes a T7 promoter-fused Cas9 coding region, was digested with Xbal (Takara Bio Inc., Japan), and used as the template for in vitro transcription using the mMESSAGE mMACHINE T7 kit (Thermo Fisher Scientific, MA, U.S.A.). The Cas9 mRNA was purified using the MEGAclear kit (Thermo Fisher Scientific, MA, U.S.A.). One-cell embryo microinjection was conducted by the same protocol described in the previous report (Sunagawa et al., 2016). C57BL/6N females (4–6 weeks old, CLEA Japan Inc) were superovulated and mated with C57BL/6N males (CLEA Japan Inc., Japan). Fertilized eggs were collected from the ampulla of the oviduct of plugged C57BL/6N females by micro-dissection, and maintained in KSOM medium (Merck, Germany or ARK Resource, Japan) in a 5% CO 2 incubator at 37°C. Cas9 mRNA (100 ng/μL) and gRNAs (150 ng/ μ L in total) were co-injected into the cytoplasm of fertilized eggs in M2 medium (Merck Millipore or ARK Resource) at room temperature (23–25°C). Details of the cytoplasmic injection were reported previously (Sumiyama et al., 2010). After microinjec- tion, the embryos were cultured for 1 h in KSOM medium (Merck, Germany or ARK Resource, Japan) in a 5% CO 2 incubator at 37°C, and 25–35 embryos were then transferred to the oviducts of pseudopregnant female ICR mice. Triple-target CRISPR: Genotyping of KO mice and ESCs by quantitative PCR (qPCR) and sequencing Genotyping of KO mice was conducted with the same protocol described in the previous report (Sunagawa et al., 2016 ). Genomic DNA of wild-type and KO mice was prepared from their tails using the DNeasy Blood & Tissue Kit (QIAGEN, Germany), according to the manufacturer's instructions. qPCR for genotyping was performed using the ABI PRISM 7900/QuantStudio 7 Flex (Thermo Fisher Scientific, MA, U.S.A.) and the SYBR Premix Ex Taq GC (Takara Bio Inc., Japan). Primers for qPCR (Table S2B, Hokkaido System Science, or Fasmac) were annealed to the targeting sequences. The absolute target site abundance was calculated using a standard curve obtained from wild-type genomic DNA. The amount of Tbp (Tsujino et al., 2013) was quantified and used as an internal control. When we could not confirm KO genotype by qPCR, we performed sequencing or a second qPCR using alternative primers, which were independent of first qPCR. One-cell embryo, Cas9 mRNA, and gRNAs were prepared as described above. Cas9 mRNA (100 ng/μL) and gRNAs (150 ng/μL in total) were co-injected into the cytoplasm of 200 fertilized eggs in M2 medium (Merck Millipore, MA, U.S.A. or ARK Resource, Japan) at room temperature (23–25°C) as described above. After microinjection, the embryos were cultured for 2 days in KSOM medium (Merck Millipore, MA, U.S.A. or ARK Resource, Japan) in a 5% CO 2 incubator at 37°C. On the next day of injection, mitotic-inactivated MEFs were seeded into the wells of 1% gelatin-coated 4-well plates (1.5 × 10 5 cells/well) with mouse ES medium. The next day, ES medium was replaced with 3i medium, and the plates were incubated for at least 30 min at 37°C in 5% CO 2 before use. Two days after injection, 50 embryos that had developed to the 8-cell stage or later were transferred into 3i-culture medium on the feeder-coated dish. Embryos were incubated at 37°C in 5% CO 2 without replacing the medium for 10 days or more, until a lump-like ES colony (primary colony) appeared. On the day before proceeding to the next step, BIO medium-treated amine-coated wells (24-well plate), one well for each colony, were prepared. After incubation of the BIO-containing plates overnight at 37°C in 5% CO 2 , BIO-medium was replaced with 3i-culture medium, and then the plates were incubated at 37°C in 5% CO 2 . After confirming proliferation of the primary colony, culture medium was replaced with fresh 3i medium (pre-warmed to 37°C) and incubation continued for 3 h at 37°C in 5% CO 2. After washing the colony with PBS(-), trypsinized cells derived from each colony were harvested, and transferred into the BIO medium-treated amine-coated well containing 3i-culture medium. After cultivation for several days at 37°C in 5% CO 2 without replacing the medium, the colonies were cloned, expanded, stored, and used for genomic DNA extraction (Ode et al., 2017b; Ukai et al., 2017). The sex of the ES clones was determined by PCR on the Sry gene with the following primers: Sry-F, 5′-ccatgtcaagcgccccatga-3′; Sry-R, 5′-gtaaggcttttccacctgca-3′ (Hokkaido System Science, Japan or Fasmac, Japan). Genotyping by qPCR was performed as described above. The KO-ESC clones were injected in 8-cell-stage embryos and chimerism confirmed according to a previously re- ported protocol (Ode et al., 2017b; Ukai et al., 2017 ). SSS recording and analysis were carried out according to the protocol described previously (Sunagawa et al., 2016 ). One set of data recording in the SSS chamber was for one week. During the experiment, neither the chamber nor the rack was opened except for the sleep-deprivation experiment. The light condition of the SSS rack was set to the LD (12:12 light-dark) or the DD (constant dark) con- dition, and food and water were given ad libitum . For data analysis, six days from the second recording date were used. The control dataset of C57BL/6N wild-type mice were shared among different groups of mutant mice for analysis ( Table S3 ). Sleep parameters, such as sleep duration, amplitude, P ws, and P sw were defined previously (Sunagawa et al., 2016 ). For the pre- sent study, the definition of transition probabilities are as follows: The P ws and P sw represent different probabilities in regard to the direction of wake/sleep transition. For example, when a mouse shows a long sleep phonotype, its Pws (transition probability from wake to sleep) tends to be large while the Psw (transition probability from wake to sleep) tends to be small. More precisely, Pws is defined as Pws = Nws/(Nws+Nww) where Nws and Nww are the numbers of transition in the direction from wake to sleep and wake to wake (i.e., stay in wake), respectively, in the observed period. On the other hand, Psw is defined as Nsw/(Nsw+Nss) where Nsw and Nss are the numbers of transition in the direction from sleep to wake and sleep to sleep (i.e., stay in sleep), respectively, in the observed period. Similarly, P ww and P ss can also be defined. According to these definitions, it can be noticed that P sw + P ss = 1 and Pws + Pww = 1. Therefore, Psw and Pws reflect, in addition to the aforementioned wake/sleep propensities, the stabilities of sleep (Pss) and wake (Pww), respectively (Sunagawa et al., 2016). Telemetry EEG and EMG recording devices (DSI, MN, U.S.A.) were implanted into mice more than 10 days before recording. Further information on implantation of telemetry devices been described previously (Sunagawa et al., 2013). For the sleep staging, we used the FASTER method to automatically annotate EEG and EMG data (Sunagawa et al., 2013), and then the result of the FASTER anno- tation was corrected by visual inspection. In the automated staging of the FASTER method, EEG and EMG data were divided into 8 s segments (epochs), and each epoch was detrended by subtracting a linear trend, which was estimated by the least-squares linear regression. The power spectrum of the epoch was obtained by FFT with the Hann window. Both data arrays of the power spectrum of EEG and EMG from the same epoch were concatenated into a single array, and then the concatenated array of spectrum data was subjected to principal component analysis. The top four principal components were used for the subsequent clustering which was performed by the pdfCluster library ( Azzalini and Menardi, 2014; Azzalini and Torelli, 2007 ). To reduce computational load for clustering, the epochs of a whole time series were divided into subsets of epochs so that each subset was comprised of 5400 epochs, and within each subset, clusters were produced. The produced clusters were annotated by the following rules: First, the median log- arithm of EMG power of each cluster was computed and clusters that have higher median logarithm of EMG power than the 0.5 quar- tiles of that of all data points were annotated as 'Wake'. Within the remaining non-wake clusters, median logarithm of EEG delta power (0.5–4 Hz) was calculated, and if it was greater than 0.1 quartile of EEG delta power among all non-wake data points, it was annotated as 'NREM sleep' and the rest of the clusters were annotated as 'REM sleep'. In manual scoring, each epoch was staged by visual inspection as NREM, REM, and Wake by the following criteria: An epoch was staged as NREM sleep when it was characterized by high-amplitude EEG waves with low-frequency (0.5–4 Hz by visual inspection) dominance and very low amplitude of EMG signal. The stage of REM sleep was assigned when an epoch was characterized by low- amplitude EEG wave with a relatively high-frequency fluctuation (6–10 Hz by visual inspection) and very low EMG power. The stage of Wake was assigned when an epoch was characterized by high amplitude EMG signal. Transition probabilities among wakefulness, NREM sleep, and REM sleep (Figures 6C, 6F, and 6G) were calculated in a similar way to Psw described in the above section (Sleep measurement with SSS). For example, the transition probability from NREM sleep to wakefulness is defined as P nw = N nw/(N nw + N n r + N nw) where N nn is defined as a number of transitions from state m to n (m,n = {wakefulness, NREM sleep, REM sleep}) in the observed period. Notably, in the EEG and EMG recordings, there are theoretically eight possible transitions, however, we did not take into account the transition from wakefulness to REM sleep because the transition usually does not occur in mice. The power spectrum density for Figures 7 and S7 was calculated for each epoch by fast Fourier transformation (FFT) with Welch's averaging method (Hayes, 1996). Briefly, each 8 s segment (800 data points as the sampling frequency was at 100 Hz) was further divided into eight overlapping sequences. The length of overlap was 50% of each sequence. Hamming window was applied onto the sequences prior to the FFT and the obtained spectrum was averaged over the eight sequences. The dirty segments were excluded from the subsequent processes (Sunagawa et al., 2013). The power spectrum of each behavioral state was calculated by averaging the power spectral densities of segments within each state over the first three days of the observation period. Two mutant mice and two control mice used in Figure 6M were randomly selected and subjected to video recordings in parallel with EEG and EMG recordings. EEG power spectrum was produced in the FASTER method (Sunagawa et al., 2013). The EEG theta-oscil- lation dominant periods were extracted by calculating the ratio of EEG-theta power (6-10 Hz) to delta power (0.5-4 Hz) for each epoch (EEG data with time length of 8 s). Mean and SD of the theta/delta ratios were obtained for each 12-hour interval just before and just after the sleep-deprivation for individual mice. The timestamp of epoch was reported when its theta/delta ratio exceeded the threshold of mean + 5 SD, and the associated videos were visually inspected. The inspection covered the 30-hour period prior to and 12-hour period subsequent to the sleep-deprivation. The timestamps of transition from NREM sleep to wakefulness were ex- tracted according to annotated stages. Mice were sleep deprived for 1, 2, 4, and 6 h by automated shaker (NR-40, TAITEC, Japan) in a different breeding rack from the one used for SSS recordings. The shaking speed was at around 120–130 rpm, and shaking method was alternatively switched between reciprocal and rotary every two hours. Every duration of sleep deprivation (SD) ended at ZT12. After SD, mice were returned to the SSS rack and recorded for 2 days. Sleep deprivation with EEG and EMG recordings Mice were implanted with EEG and EMG probes and sleep deprived for 6 h (ZT6-12) by the gentle touch of a brush. X-gal staining of Tet reporter mice was performed as reported previously with minor modifications (Imayoshi et al., 2006). Briefly, fresh samples of adult mice brain were sliced into 400 μm sections, fixed in 2% formaldehyde and 0.2% glutaraldehyde in PBS so- lution for 1 h at 4°C, rinsed twice in 0.1 M phosphate buffer (PB) (pH 7.4), 2 mM MgCl 2 , 0.01% sodium deoxycholate, 0.02% NP-40, and stained at 37°C for 4 h in X-gal stain buffer (2 mg/mL X-gal, 2 mM MgCl 2 , 0.01% sodium deoxycholate, 0.02% NP-40, 5 mM K₃Fe(CN)₂, 5 mM K₄Fe(CN)₂ in 0.1 M PB). Stained samples were washed twice in PBS and post-fixed with 4% PFA in PBS for 2 h at room temperature (23–25°C). Fluorescent imaging of Tet reporter mice was performed as reported previously (Susaki et al., 2014). Each fixed brain was immersed in 10 g of CUBIC reagent-1 at 37°C with gentle shaking for 3 days, then the solution was exchanged, and the sample immersed in the same volume of fresh reagent-1 for an additional 3–4 days. The treated brain was washed with PBS several times at room temperature (23–25°C) with gentle shaking, immersed in 20% (w/v) sucrose in PBS, degassed, and immersed in reagent-2 (10 g per brain) for 3–7 days. After imaging, the sample was washed again with PBS, immersed in 20% (w/v) sucrose in PBS, and stored in O.C.T. compound at −80°C. Fluorescence images were acquired with an LSFM (Ultramicroscope, LaVision BioTec, Ger- many) as described in the previous report (Susaki et al., 2014). For each brain sample of CUBIC analysis, 3D NIfTI-1 files were generated from the Z stacks acquired in the dorsal-ventral (DV) and ventral-dorsal (VD) directions, merged, and registered as described previously (Susaki et al., 2014; Susaki et al., 2015). We normal- ized the tdTomato signals and used the NIFTI-1 images aligned to the Allen Brain Atlas (Lein et al., 2007) to extract only pixels located inside the brain. We calculated the median intensity of these pixels for each brain and normalized the data so that all brain samples had the same median intensity. Activated cells were detected in the image stack using Fiji software (Schindelin et al., 2012). For each horizontal slice of a given brain sample, we started by subtracting the background (rolling ball radius: 2 pixels). We then calculated a Gaussian blur (sigma: 2) and subtracted from the image in order to preserve only the signal of interest. We then successively ran the "setThreshold" (with parameters 800, 65536), ''Threshold,'' and ''Analyze Particles'' (with size = 2–25, circularity = 0.3–1.0) commands. The number of activated cells in a brain sample was calculated as the sum of the number of cells identified in each of its slices. When processing each slice, we also saved an image containing only the detected activated cells in order to reconstruct 3D images of cell activation throughout the brain. To analyze local patterns, we aligned these images to the brain atlas using the registration parameters calculated above. Analyzing aligned samples meant that we did not have access to single-cell resolution, and the Fiji-based cell detection method could not be applied. However, it was previously shown that the intensity of the extracted signal could be used to estimate the number of activated cells with R² ⇒0.95 (Tatsuki et al., 2016). We extracted the detected signal corresponding to this specific region in the Allen Brain Atlas. To filter out noise, we focused on regions with a non-zero signal in at least 3 of the 9 brains. For these regions, hierarchical clustering was performed in R (R Develop- ment Core Team, 2016). We identified a cluster of 99 regions (out of the 1203 regions defined on the reference atlas) with no (or close to no) signal in TrkA-tTA(-);tetO-tdTomato(+) brains, and reliable signal in TrkA-tTA(+);tetO-tdTomato(+) brains. For this cluster, we generated a whole-brain mask to extract and reconstruct a 3D image of the cell signal specific to these 99 regions. Probes against TrkA, Ngfr, and ChAT were amplified from mouse brain cDNA (C57BL6/N, male), and Egfp and mNeonGreen were amplified from plasmids by PCR. Probes against VGluT1 (kindly provided by Dr. Kazunari Miyamichi) were amplified from mouse brain cDNA (first strand cDNA mouse brain MD01, GenoStaff). All the probe fragments were cloned into pCR-Bluntll-TOPO vector (Thermo Fisher Scientific, MA, U.S.A.) for storage, and in vitro transcription (IVT) templates were generated by PCR using the cloned vector. All primers used for cloning and IVT reactions are listed in Table S1. Probe labeling and purification were conducted using the same protocol described in the previous paper (Tatsuki et al., 2016). Probes for ChAT-1 and ChAT-2 were mixed before hybridization. For fluorescence in situ hybridization (FISH), mice were sacrificed at ZT5, and the brain was used for the same procedures described previously ( Tatsuki et al., 2016 ). For NBT-BCIP staining, mice were sacrificed at ZT5, and the same procedures were performed until the blocking step of the FISH protocol. After blocking, the sections were incubated with the blocking buffer containing anti-Dig-Fab-AP (Merck, Germany; #11093274910, 1:1000) overnight at 4°C. The next day, the sections were washed three times in PBS containing 0.3% Triton X-100 (PBST) for 10 min each, then incubated in NTMT solution (50 mM MgCl₂, 100 mM NaCl, 100 mM Tris-HCl (pH 9.5), 1% Tween-20) for 5 min, and incubated in NTMT solution containing NBT/BCIP stock solution (Merck, Germany; 1:50) for 4–5 days at 4°C. The sections were incubated in TE buffer for 5 min and embedded with 80% glycerol. Images of in situ hybridization samples were acquired with a BX51 inverted confocal microscope (Olympus, Japan). A series of images covering all areas of a section were acquired and stitched with the pairwise stitching plugin of ImageJ (Preibisch et al., 2009). Statistical analyses were performed by Microsoft Excel for Mac version 15.40, R version 3.1.0., Wolfram Mathematica version 9.0.1.0, 11.2.0.0. For paired samples, the normality was tested by Shapiro test at a significance level of 0.05. When normality was not rejected in both groups, the homogeneity of variance was tested by F-test at a significance level of 0.05. When the null hypothesis of normal distri- bution with equal variance for the two groups was not rejected, a Student's paired t test was used, otherwise a two-sample Wilcoxon t test was applied. For unpaired two samples, the means of two sets of data were evaluated. The normality was tested by the Shapiro test at a sig- nificance level of 0.05. When the normality was not rejected in both groups, the homogeneity of variance was tested by F-test at a significance level of 0.05. When the null hypothesis of normal distribution with equal variance for the two groups was not rejected, a Student's t test was used. When the normality was not rejected but the null hypothesis of equal variance was rejected, a Welch's t test was used. Otherwise, a two-sample Wilcoxon test was applied. For comparing more than two samples (i.e., CRISPR mutant mice) against identical one sample (i.e., C57BL/6N control mice), data means were evaluated. The normality was tested by the Kolmogorov-Smirnov test at a significance level of 0.05. When the normality was not rejected in all groups, the homogeneity of variance was tested by Bartlett's test at a significance level of 0.05. When the null hypothesis of normal distribution with equal variance was not rejected for all groups, Dunnett's test was used, otherwise the Steel test was applied. In this study, p < 0.05 was considered significant (*p < 0.05, **p < 0.01, ***p < 0.001, and n.s. for not significant). Genome-wide mRNA expression profiles of BF/POA region analyzed along with data from 48 other brain regions which we made public at the database ( http://poabf.brainstars.org/ ). Cell Reports, Volume 24 Supplemental Information Muscarinic Acetylcholine Receptors Chrm1 and Chrm3 Are Essential for REM Sleep Yasutaka Niwa, Genki N. Kanda, Rikuhiro G. Yamada, Shoi Shi, Genshiro A. Sunagawa,   Maki   Ukai-Tadenuma,   Hiroshi   Fujishima,   Naomi   Matsumoto,   Koh-hei
Masumoto,     Mamoru    Nagano,    Takeya    Kasukawa,    James    Galloway,    Dimit Perrin, Yasufumi Shigeyoshi, Hideki Ukai, Hiroshi Kiyonari, Kenta Sumiyama, and Hiroki R. Ueda 0 +3 S.D. B Figure S1. Identification of marker genes in the BF/POA region and establishment of TrkA-fTA mice. Related to Figure 1 A, The mRNA expression profiles in 49 distinct brain regions are represented in a heatmap. Genes whose expression was decreased in one of those regions were selected from the genome-wide dataset. Each row corresponds to a gene, and each column to a region designated at the top of the panel. CH, cerebrum. TH, thalamus. HY, hypothalamus. MB, midbrain. P, pons. CB, cerebellum. SC, spinal cord. BF/POA, basal forebrain/preoptic area. LS, lateral septal nucleus. RS, retrosplenial cortex. Cx motor, cerebral cortex motor. Cx cingulate, cerebral cortex cingulate. OB anterior, olfactory bulb anterior. OB posterior, olfactory bulb posterior. Pir, piriform cortex. Tu, olfactory tubercle. ventral S, ventral subiculum. CA1, CA1 (hippocampus). CA2/CA3, CA2/CA3 (hippocampus). DG, dentate gyrus (hippocampus). A anterior, amygdala anterior. A posterior, amygdala posterior. GP, globus pallidus. CPu lateral, caudate putamen lateral. CPu medial, caudate putamen medial. MD, mediodorsal thalamic nucleus. VA/VL, ventral anterior thalamic nucleus/ventrolateral thalamic nucleus. VP/VPL, ventral posteromedial thalamic nucleus/ventral posterolateral thalamic nucleus. LG, lateral geniculate body. MG, medial geniculate nucleus. Hb, habenular nucleus. Pineal, corpus pineal. M, mammillary body. ME, median eminence. SCN, suprachiasmatic nucleus. MPA, medial preoptic area. SO, supraoptic nucleus. Pa, paraventricular hypothalamic nucleus. SPa ventral, subparaventricular zone ventral. SPa dorsal, subparaventricular zone dorsal. DM, dorsomedial hypothalamic nucleus. VMH, ventromedial hypothalamic nucleus. Arc, arcuate hypothalamic nucleus. LH, lateral hypothalamus. PAG, periaqueductal gray. SC, superior colliculus. IC, inferior colliculus. VTA, ventral tegmental area. SN, substantia nigra. Tg, dorsal tegmental nucleus. Pn, pontine nucleus. MVe, medial vestibular nucleus. Cb vermis, cerebellar cortex vermis. Cb lobe, cerebellar cortex lobe. Cb nucleus, cerebellar nucleus. B, The expression of a reporter gene driven by TrkA-tTA in the BF/POA region of the brain. Brains of mice harboring tetO- tdTomato transgene with and without TrkA- tTA transgene were imaged and analyzed as in Figure 11 . The tdTomato signal is shown in the reconstituted 3D image for brains of tetO-tdTomato(+);TrkA-tTA(-) (top row) and brains of tetO-tdTomato(+);TrkA-tTA(+) (lower two rows). All analyzed brains are presented except the representative ones shown in Figure 11. Gray dots represent nuclear signal of RedDot2; green dots represent cells in the 99 detected regions. Scale bar, 2 mm. Figure S2. Sleep phenotype of TrkA-TeNT mice in the no-dox condition and in the Per1, Per2 DKO background and that of Ngfr-TeNT mice. Related to Figure 2 A-C, Sleep phenotype of TrkA-TeNT mice (n = 5) and control littermates (n = 11) maintained in the no-dox condition measured by SSS. A, Heatmap representation of sleep duration (per hour) over 6 days. B, Sleep duration and Pws (per hour) over 24 h averaged over 6 days. The mean at each hour of the day is plotted for TrkA-TeNT mice (magenta line), and for control littermates (black line). Shaded area around line represents standard error of mean (SEM). C, Sleep/wake parameters. Sleep duration is the total sleep duration in a day, amplitude is related to the variation of sleep duration (per hour) within the daily sleep cycle, Pws and Psw are the respective transition probabilities from wakefulness to sleep and vice versa. D, Schematic representation of modified BAC where tTA and polyA signal were inserted just after the start codon of the Ngfr gene and PCR confirmation for genotypes of established BAC transgenic mice (inset). E-G, Sleep phenotype of Ngfr-TeNT mice (n = 6) and control littermates (n = 6) maintained in the no-dox condition measured by SSS. E, Heatmap representation of sleep duration (per hour) over 6 days. F, Sleep duration and Pws (per hour) over 24 h averaged over 6 days. The mean at each hour of the day is plotted for Ngfr-TeNT mice (magenta line) and for control mice (black line). Shaded area represents SEM. G, Sleep/wake parameters are presented as in (c). H, I, Sleep phenotype of Ngfr-TeNT mice (n = 3) and control littermates (n = 11) measured by EEG and EMG recordings. H, Heatmap representation of sleep duration (per hour) over 3 days. I, The duration of total sleep, NREM sleep, and REM sleep in a day. J-O, Sleep phenotype of TrkA-TeNT, Per1/2 double KO (DKO) mice (n = 9) and control Per1/2 DKO mice (n = 15) under LD (J-L) and DD (M-O) conditions measured by SSS. Mice were maintained with dox after birth and released from dox 4 weeks before SSS measurement. J, M, Heatmap representation of sleep duration (per hour) over 6 days. K, N, Sleep duration and Pws (per hour) over 24 h averaged over 6 days. The mean at each hour of the day is plotted for TrkA-TeNT, Per1/2 DKO mice (magenta line) and for control Per 1/2 DKO mice (black line). Shaded area represents SEM. L, O, Sleep/wake parameters. Sleep duration is the total sleep duration in a day, amplitude is related to the variation of sleep duration (per hour) within the daily sleep cycle, Pws and Psw are the respective transition probabilities from wakefulness to sleep and vice versa. Error bars, SEM. *P < 0.05, **P < 0.01, ***P < 0.001. A Dox 40 ppm -
Dox 40 ppm week 5 week 6 week 7 week 16** *week 4 is shown in Figures 2A-C E
Figure S3. Sleep phenotype of TrkA-TeNT mice in the 40 ppm and 5 ppm dox-on and dox-off conditions. Related to Figure 2 A, Experimental protocol of 40 ppm doxycycline (dox) treatment of TrkA-TeNT mice and control littermates (also shown in Figure S4A). The data of week 4 and week 16 are shown in Figure 2A-C and D-F, respectively. B-D, Sleep phenotype of TrkA-TeNT mice (n = 6) and control littermates (n = 13) with 40 ppm dox-food measured by SSS. B, Heatmap representation of sleep duration (per hour) over 6 days. C, Sleep duration (per hour) over 24 h averaged over 6 days. The mean sleep duration at each hour of the day is plotted for TrkA-TeNT mice (magenta line) and for control mice (black line). Shaded area represents SEM. D, Sleep/wake parameters. Sleep duration is the total sleep duration in a day, amplitude is related to the variation of sleep duration (per hour) within the daily sleep cycle, Pws and Psw are the respective transition probabilities from wakefulness to sleep and vice versa. E, Experimental protocol of 5 ppm doxycycline (dox) treatment of TrkA-TeNT mice and control mice. F-H, Sleep phenotype of TrkA-TeNT mice (n = 8) and control littermates (n = 13) with 5 ppm dox- food measured by SSS. F, Heatmap representation of sleep duration (per hour) over 6 days. G, Sleep duration (per hour) over 24 h averaged over 6 days. The mean sleep duration at each hour of the day is plotted for TrkA- TeNT mice (magenta line) and for control mice (black line). Shaded area represents SEM. H, Sleep/wake parameters are presented as in (D). Error bars, SEM. * P < 0.05, ** P < 0.01, *** P < 0.001. week 16
Figure S4. Characterization of TrkA-TeNT , ChAT-tTR-mNG KI and VGluT1-tTR-mNG KI mice by FISH analysis. Related to Figure 2 and 3 A, Experimental protocol of doxycycline (dox) treatment on TrkA-TeNT mice and control littermates. Mice were maintained with dox shortly after birth. After weaning and maturation, mice were released to food without doxycycline (normal-food) and maintained for four weeks (from week 1 to week 4). On and after week 5, mice were returned to dox-food. B, TeNT expression in the BF of TrkA-TeNT mice and control littermates measured by fluorescent in situ hybridization (FISH) analysis with a fluorescein labeled Trka antisense RNA probe ( Trka- Flu; green) and digoxigenin labeled Egfp RNA probe ( Egfp-Dig; red) in the dox-off (week 1, week 2, week 3) and dox-on (week 16) condition. Two representative samples are shown. C, Colocalization of Chat mRNA expression (fluorescein labeled, Flu; green) and tTR mRNA expression (digoxigenin labeled, Dig; red) detected by antisense RNA probe for mNeonGreen ( mNG ) in the BF, CPu, and LDT of ChAT-tTR-mNG KI mice. D, Colocalization of Vglut1 mRNA expression (fluorescein labeled, Flu; green) and tTR mRNA expression (digoxigenin labeled, Dig; red) detected by an antisense RNA probe for mNG in the Ctx/OB and HIP of VGluT1-tTR-mNG KI mice. Neither VGluT1 nor tTR expression were observed in the BF. BF, basal forebrain. CPu, caudate putamen. LDT, laterodorsal tegmentum. Ctx/OB, cerebral cortex/olfactory bulb. HIP, hippocampus. chr14 (+) 66,145,000
gatgtogtcatogtocgctt (-) gaaagtcacgtcgatgctgc (-) ggttcoggtggogttgataa (+) -2 Chrna2 target sequence-3 Chrna2 target sequence Chrna2 target sequence C | chr9 (+) 54,990,000 55,000,000 Chma5 Chma5 ggcaaagacagtcaccataa (-) gtagcgaatgcaatcgagcg (-) Chrna5 target sequence-1 Chma5 target sequence-2 gaaacatccgatcgagaact (-) Chma5 target sequence-3 chr7 (-) 63,200,000 63,150,000 Chma7 u gaactccttgcaggaatccc (-) ggtcaagaactacaacccgc (-) ggccatagtagtgtccta (+) Chrna7 target sequence-1 Chrna7 target sequence-2 Chma7 target sequence-3 G | chr7 (-) 102,115,000 102,113,000 Art1 Chma10 gactctaaatgtgaccctgg (+) ggacagacgcctacctacat (+) gcacttggttccgttcatcc (-) Chma10 target sequence-1 Chrna10 target sequence-2 Chrna10 target sequence-3 chr8 (+) 27,380,000 27,390,000
Chmb3
Chmb3 ggacagaocaaaattacga (+) ggagagtaagggaacogtga (+) ggttcogctggatttcacaa (-) Chrnb3 target sequence-2 Chmb3 target sequence-3 Chrnb3 target sequence-1 K Chrna5 (1st qPCR) 120
l-type = 100 M gaatgtctcogatccogtca (+) gggcaacctcctgatgtaga (-) iaatcgaccttctcatcat (+ Chrna6 target sequence-1 Chrna6 target sequence-2 Chrna6 target sequence-3 u chr5 (+) 65,970,000 65,975,000 Chrna9 gagatgacgttcttcacggc (-) gggatogagaccagtatgac (+) ggagccagaacaaatcacga (+) Chrna9 target sequence-1 Chrna9 target sequence-2 Chma9 target sequence-3 H | chr3 (-) 89,760,000 89,755,000 Adar Chrnb2 ggcacactattcttccgcga (+) gogataatcttcccactcct (-) cacctagtg (+ Chrnb2 target sequence-1 Chrnb2 target sequence-2 Chmb2 target sequence-3 550,040,000 550,030,000
Chrnb4 J chr9 (-) ggggtaaagtcatccatga (-) ggactggaaattcgtcgcaa (+) tgaacggtggtgcacattg (-) Chrnb4 target sequence-1 Chrnb4 target sequence-2 Chmb4 target sequence-3 d-type = 100 Chma7 (1st qPCR) Chma6 (1st qPCR) gcacacgcocatcatagaac (+) gatgtggtccttgtccgctt (-) ggcatgactacaaactgcgc (-) Chrna4 target sequence-1 Chma4 target sequence-3 Chrna4 target sequence-2 D   chr8 (-) 27,410,000
5 6 Chma9 (1st qPCR) ome DNA/T -type = 100 100 120 ome DNA/ d-type = 100 60 40 20 0 WT 2 3 4 5 6 8 9 10 11 12 Chrnb4 (1st qPCR) 120 100 80 60 40 20 0 WT 1 2 3 5 8 7 B  chr2 (-) 181,035,000 181,030,000 Chma4 d-type = 100 me DNA/ ome DNA/ 80 40 WT 80 Chrnb3 (1st qPCR) enome DNA/Tb
ild-type = 100% 40 20 0 8 120 100 type = 100 3 4 5 Chrna10 (1st qPCR) 60 N 100 80 60 120 6 wild-type = 100 iome DNA/ 4 A-J, Target sequences of the gRNAs for knockout of the nicotinic acetylcholine receptor family. Chrna2 (A), Chrna4 (B), Chrna5 (C), Chrna6 (D), Chrna7 (E), Chrna9 (F), Chrna10 (G), Chrnb2 (H), Chrnb3 (I), and Chrnb4 (J); each gene had three target sequences. The mouse genomic sequence data were obtained from GRCm38/mm10 via the UCSC Genome Browser (http://genome.ucsc.edu/) (Rhead et al., 2010). The colored letters (blue, orange, and green) show the 20-base target sequences. The target sequences were designed on the sense (+) or antisense (-) strand of the genomic DNA. K-T, The genotype of nicotinic acetylcholine receptor family KO mice. Chrna2 (K), Chrna4 (L), Chrna5 (M), Chrna6 (N), Chrna7 (O), Chrna9 (P), Chrna10 (Q), Chrnb2 (R), Chrnb3 (S), and Chrnb4 (T); each gene had three targets for quantitative PCR (qPCR) genotyping. The amount of intact DNA for each target sequence was measured by qPCR. The genomic DNA was purified from tail of each mouse. The amount of measured DNA of KO mice for each target sequence is expressed as the percentage of that of wild-type mouse. Number and WT below the bar plot denote the ID of KO mouse and the wild-type mouse, respectively. KO mice, which were confirmed by the relative DNA amount of less than 0.5% by at least one of three targets, are labelled in magenta otherwise in black. TATA-binding protein ( Tbp ) was used as internal control. Color of bars correspond to that of gRNA sequences.
gcattcatogggatcaccac (+) Chrm1 target sequence-1 gtgggcctcttgactgtatt (-) gcaaaggccaaaacccga (+) Chrm1 target sequence-2 Chrm1 target sequence-3 C
gacaaggatgttgccgatga (-) Chrm3 target sequence-1 gcacgaaacggtcatctagg (+) gctgcatacccaaacctat (+) Chrm3 target sequence-2 Chrm3 target sequence-3 E 112,480,500 chr2 (-)
gaccaagacattgcogacaa (-) Chrm5 target sequence-1 gtagatocggcagtagagta (+) gacaaacaatggctgtcgta (+) Chrm5 target sequence-2 Chrm5 target sequence-3 G K
cagtcccaacatcacogtct (-) attcatgaca Chrm1 target sequence-4 Chrm1 target sequence-5 gagaaggggccattagcat (+) Chrm1 target sequence-6 M nome DNA/T d-type = 100 Chrm1 (set 2, 1st qPCR)
cgcttaactgggtaggttag (-) Chrm2 target sequence-1 gggactgaaaactgcgttca (+ gttggctttcatcatcacgt (+) Chrm2 target sequence-2 Chrm2 target sequence-3 D
gactgtgggtaacatcc (+) ctgocatcttagtagtgcgg (-) gtaaccaggtgcgcaagaag (+) Chrm4 target sequence-2 Chrm4 target sequence-1 Chrm4 target sequence-3 F 6 8 6
ctacatcattatgaaccgct (+) aaacgagccggtgtgatgat (+) gtccttcaaagaagccacgc (+) Chrm3 target sequence-4 Chrm3 target sequence-5 Chrm3 target sequence-6 N ■  Chrm1 - Target - 1 ■ Chrm1 - Target - 2 Chrm1 - Target - 3 ■  Chrm3 - Target - 1 ■  Chrm3 - Target - 2 ■  Chrm3 - Target - 3 B A l Chrm1/Chrm3 o H A-E, K, L, Target sequences of the gRNAs for knockout of the muscarinic acetylcholine receptor family. Chrm1 (set 1, A), Chrm2 (B), Chrm3 (set 1, C), Chrm4 (D), Chrm5 (E), Chrm1 (set 2, K), and Chrm3 (set 2, L); each gene had three target sequences. The mouse genomic sequence data were obtained from GRCm38/mm10 via the UCSC Genome Browser ( http://genome.ucsc.edu/ ) (Rhead et al., 2010). The colored letters (blue, orange, and green) show the 20-base target sequences. The target sequences were designed on the sense (+) or antisense (-) strand of the genomic DNA. F-J, M-O, The genotype of muscarinic acetylcholine receptor family KO mice. Chrm1 (set 1, F), Chrm2 (G), Chrm3 (set 1, H), Chrm4 (I), Chrm5 (J), Chrm1 (set 2, M), Chrm3 (set 2, N), and Chrm1/3 (O); each gene had three targets for quantitative PCR (qPCR) genotyping. The amount of intact DNA for each target sequence was measured by qPCR. The genomic DNA was purified from tail of each mouse. The amount of measured DNA of KO mice for each target sequence is expressed as the percentage of that of wild- type mouse. Number and WT below the bar plot denote the ID of KO mouse and the wild-type mouse, respectively. KO mice, which were confirmed by the relative DNA amount of less than 0.5% by at least one of three targets, are labelled in magenta otherwise in black. TATA-binding protein ( Tbp ) was used as internal control. Color of bars correspond to that of gRNA sequences. Ngfr-TeNT Figure S7. FFT power spectrum on EEG/EMG recording and the response of TrkA-TeNT and Chrm1/3- DKO mice to sleep-deprivation. Related to Figure 2, 6 and 7 A-E, FFT frequency spectrum of Chrm1 KO (A), Chrm3 KO (B), Chrm1/Chrm3 DKO (C), TrkA-TeNT (D), and Ngfr-TeNT (E) mice. The mean power density at each frequency is plotted for mutant mice (magenta line) and for control mice (black line). All the time series of EEG data were normalized so that the standard deviation of the first 24 hours becomes 1 before calculating the power spectrum. Shaded area represents SEM. Statistical results are shown in inset. F-I , The duration of sleep measured by SSS before and after sleep-deprivation (SD). SD was applied for durations of 1, 2, 4, and 6 h by automated shaker. SD of each duration ended at ZT12. F, G, The phenotypes of sleep-deprived TrkA-TeNT mice (n = 6) and control littermates (n = 12). H, I, The phenotypes of sleep-deprived Chrm1/3 double KO (DKO) mice (n = 5) and control C57BL/6N mice, used in Figure 6H-J. F, H, Heatmap representation of sleep duration (per hour) measured by SSS over 6 days. G, I, Fold change of sleep duration induced by SD. Each sleep duration of "After SD" and "Basal" respectively corresponds to the sleep duration of ZT12–24 subsequent to SD and the averaged sleep duration of ZT12-24 in three days before the day of SD. Error bars, SEM. * P < 0.05, ** P < 0.01, *** P < 0.001.
Table S1. Primers for RNA probes of in situ hybridization in this study. Related to Figure 1 and 3 Anti-sense RNA probes for TrkA , Ngfr , Egfp , mNeonGreen , ChAT , and VGluT1 were produced by in vitro transcription with T3-probe PCR fragments. ChAT probes were used as mixes of ChAT-1 and 2. T3 promoter sequence is underlined.