Article

Muscarinic Acetylcholine Receptors Chrm1 andChrm3 Are Essential for REM Sleep
Graphical Abstract

Authors
Yasutaka Niwa, Genki N. Kanda,
Rikuhiro G. Yamada, ..., Hiroshi Kiyonari,
Kenta Sumiyama, Hiroki R. Ueda

Correspondence
uedah-tky@umin.ac.jp

In Brief
The acetylcholine pathway has been
proposed to be important for
wakefulness and REM sleep, but genetic
evidence has been missing. Using aknockout of acetylcholine receptor
genes, Niwa et al. show that Chrm1 andChrm3 double knockout chronicallydiminishes REM sleep to an undetectablelevel and causes a severe short-sleep
phenotype.

Highlights
d

d

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Inhibition of TrkA+ cholinergic neurons causes a severe
short-sleep phenotype in mice
Knockout of the muscarinic acetylcholine receptors Chrm1
and Chrm3 reduces NREM sleep
Knockout of Chrm1 and Chrm3 reduces and fragments REM
sleep, respectively
Chrm1 and Chrm3 are essential for REM sleep

Niwa et al., 2018, Cell Reports 24, 2231–2247
August 28, 2018 ª 2018 The Authors.
https://doi.org/10.1016/j.celrep.2018.07.082

Cell Reports

ArticleMuscarinic Acetylcholine Receptors Chrm1
and Chrm3 Are Essential for REM Sleep
Yasutaka Niwa,1,2,14 Genki N. Kanda,1,3,4,14 Rikuhiro G. Yamada,1,14 Shoi Shi,1,5,6 Genshiro A. Sunagawa,1,4
Maki Ukai-Tadenuma,1,6 Hiroshi Fujishima,1 Naomi Matsumoto,7 Koh-hei Masumoto,8,9,10 Mamoru Nagano,8Takeya Kasukawa,11 James Galloway,12 Dimitri Perrin,1,12 Yasufumi Shigeyoshi,8 Hideki Ukai,1,6 Hiroshi Kiyonari,13Kenta Sumiyama,7 and Hiroki R. Ueda1,5,6,15,*
1Laboratory for Synthetic Biology, RIKEN Center for Biosystems Dynamics Research, 1-3 Yamadaoka, Suita, Osaka 565-0871, Japan
2International Institute for Integrative Sleep Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8575, Japan
3Graduate School of Frontier Biosciences, Osaka University, 1-3 Yamadaoka, Suita, Osaka 565-0871, Japan
4Laboratory for Retinal Regeneration, RIKEN Center for Biosystems Dynamics Research, 2-2-3 Minatojima Minamimachi, Chuo-ku, Kobe,
Hyogo 650-0047, Japan
5Department of Systems Pharmacology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033,
Japan
6International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study (UTIAS),The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
7Laboratory for Mouse Genetic Engineering, RIKEN Center for Biosystems Dynamics Research, 1-3 Yamadaoka, Suita, Osaka 565-0871,
Japan
8Department of Anatomy and Neurobiology, Kindai University Faculty of Medicine, 377-2 Ohno-Higashi, Osakasayama City, Osaka 589-8511,
Japan
9Center for Medical Science, International University of Health and Welfare, 2600-1 Kitakanemaru, Ohtawara, Tochigi 324-8501, Japan
10Division of Neuroanatomy, Department of Neuroscience, Yamaguchi University Graduate School of Medicine, 1-1-1 Mianmi-Kogushi, Ube,
Yamaguchi 755-8505, Japan
11Large Scale Data Managing Unit, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama,
Kanagawa 230-0045, Japan
12School of Electrical Engineering and Computer Science, Queensland University of Technology, GPO Box 2434, Brisbane, QLD 4001,
Australia
13Animal Resource Development Unit and Genetic Engineering Team, RIKEN Center for Biosystems Dynamics Research,
2-2-3 Minatojima Minami-machi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
14These authors contributed equally
15Lead Contact*Correspondence: uedah-tky@umin.ac.jp
https://doi.org/10.1016/j.celrep.2018.07.082

SUMMARY

INTRODUCTION

Sleep regulation involves interdependent signaling
among specialized neurons in distributed brain regions. Although acetylcholine promotes wakefulness
and rapid eye movement (REM) sleep, it is unclear
whether the cholinergic pathway is essential (i.e.,
absolutely required) for REM sleep because of redundancy from neural circuits to molecules. First, wedemonstrate that synaptic inhibition of TrkA+ cholinergic neurons causes a severe short-sleep phenotype and that sleep reduction is mostly attributable
to a shortened sleep duration in the dark phase. Subsequent comprehensive knockout of acetylcholine
receptor genes by the triple-target CRISPR method
reveals that a similar short-sleep phenotype appears
in the knockout of two Gq-type acetylcholine
receptors Chrm1 and Chrm3. Strikingly, Chrm1
and Chrm3 double knockout chronically diminishes
REM sleep to an almost undetectable level. These results suggest that muscarinic acetylcholine receptors, Chrm1 and Chrm3, are essential for REM sleep.

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 pathologicaldamages to the brain regions, which later appeared to be majorcholinergic sources, resulted in sleep disorders (Economo, 1930;
McGinty and Sterman, 1968; Nauta, 1946). The discovery of theregulatory site for rapid eye movement (REM) sleep in the brainstem (Jouvet, 1962) was affirmed by the induction of REM-sleeplike 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 evidence, 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 perturbation of the cholinergic system at any one level. For example,

Cell Reports 24, 2231–2247, August 28, 2018 ª 2018 The Authors. 2231
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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cholinergic neurons in the basal forebrain (BF) and regions of thebrainstem, including the laterodorsal tegmentum (LDT) and thepedunculopontine 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), emphasizing the need for further neuronal subtyping to untangle thespatially 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 acetylcholine 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 areimportant 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 particularly important and whether they are indispensable for the regulation of REM sleep.
To investigate these complexities, we took comprehensive genetic approaches to evaluate the role of cholinergic molecularfactors in mice. First, we established a neuronal subtype ofcholinergic neurons by finding enriched expression of the neurotrophic receptor tyrosine kinase 1 (Ntrk1) (also called TrkA) geneand 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+) andNgfr-expressing (Ngfr+) neurons demonstrated that those neurons were crucial for sleep. Interestingly, the short-sleep phenotype 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 thepolyphasic profile naturally seen in mice and rats. Next, we identified 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 Gqtype muscarinic acetylcholine receptors—Chrm1 and Chrm3—
induced the characteristic short-sleep profile. Both single knockouts 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 undetectable level. These findings suggested that muscarinic acetylcholine receptors Chrm1 and Chrm3 are essential for sleep regulation, 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 expression profiling of the BF and/or POA region along with data from48 other brain regions in the BrainStars database (Figures 1Aand 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 thefunction of TrkA+ neurons, we first established TrkA-tTA bacterial 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 double-transgenic TrkA-TeNT mice. In TrkA-TeNT mice, tetanus
toxin (TeNT) is expressed and inhibits synaptic vesicle releasein TrkA+ neurons under the control of Tet-off system. Shortly

Figure 1. The Tet-Driver Line for Subtyping the Cholinergic System Was Established based on Enriched Expression of TrkA and Ngfr Genes in
the BF and/or POA Region(A–D) Genome-wide mRNA expression profiles of BF and/or POA region analyzed along with data from 48 other brain regions, which we made public at the
database (http://poabf.brainstars.org/).
(A) The mRNA expression profiles in 49 distinct brain regions are represented in a heatmap. Genes whose expression was enriched in one of those regions wereselected from the genome-wide dataset. Each row corresponds to a gene and each column to a region designated at the top of the panel (see Figure S1 for theabbreviations).
(B) The expression profiles of candidate marker genes whose expression is most enriched in the BF and/or POA region.
(C and D) The mRNA expression profiles of Ntrk1(TrkA) (C) and Ngfr (D) across 49 brain regions. Blue bar represents the most enriched region, and green bars
represent the second most enriched regions.
(E and F) In situ hybridization of mRNA of Ntrk1(TrkA) (E) and Ngfr (F). The POA/BF region is magnified in the lower panels.
(G) A schematic representation of the modified BAC DNA where tTA and SV40 polyA signal were inserted just after the start codon of the TrkA gene. The genotypeof BAC transgenic mice was confirmed by PCR (inset).
(H) The expression of a reporter gene driven by TrkA-tTA in the POA/BF region confirmed by crossing TrkA-tTA mice with tetO-tauLacZ mice. LacZ signal stainedby X-gal was observed within the BF and/or POA region when both transgenes TrkA-tTA and tetO-tauLacZ were positive (bottom, dotted circle), but not observed
when the TrkA-tTA was absent (top).
(I) The expression of a reporter gene driven by TrkA-tTA in the BF and/or POA region of the brain. The masked tdTomato signal is shown in the reconstituted 3D
image for brains of tetO-tdTomato(+);TrkA-tTA() (left) and brains of tetO-tdTomato(+);TrkA-tTA(+) (right). Representative brains are shown. Gray dots represent
nuclear signal of RedDot2; green dots represent cells in the 99 detected regions.
The scale bars represent 2 mm.

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after birth, we provided mice with food containing 40 ppm doxycycline (dox-food) via their parental mother. After weaning andmaturation 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 (fromweek 1 to week 4 in Figure S3A). We monitored the daily sleep
profile using the non-invasive respiration-based automatedsleep phenotyping system—snappy sleep stager (SSS) (Sunagawa et al., 2016)—and, at week 4 with normal-food, found asevere 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 littermatesas control that harbored only one or none of the two transgenes.
Reduction of the sleep duration was mostly attributable todecreased PWS (the transition probability from wakefulness tosleep), especially at night, hence consolidated wakefulness inthe dark phase, which resulted in a high-amplitude variation insleep duration (Figures 2B and 2C). This high-amplitude variation of TrkA-TeNT mice is apparent in the contrast between
the light (resting) and the dark (active) phases in the time seriesof sleep duration represented by the heatmap (Figure 2A). In
addition, there was a period of partially recovered sleep propensity 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 diminishedthree 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 wereconfirmed with different concentrations of doxycycline (Figures
S3E–S3H).

Electroencephalogram (EEG) and electromyogram (EMG) recordings 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 notablechange (Figure S7D), sleep duration was 636.2 ± 29.8 min(mean ± SEM; n = 5), which was 134 min shorter than that of control littermates (p < 0.01; n = 4). The reduction was mostly attributable 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 thedark 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 2I).
We also generated Ngfr-TeNT mice by crossing Ngfr-tTA mice
(Figure S2D) with tetO-EGFP/TeNT mice. Both SSS analysis andEEG and EMG recordings revealed that they had the characteristic short-sleep profile with consolidated wake in the early darkphase (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 ofcontrol 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 NgfrTeNT mice (Figures S2A–S2C and S2E–S2G).
In addition, inhibition of TrkA+ neurons in circadian-clock-deficient mice (Per1/2 double-knockout [DKO] mice; Bae et al., 2001)
demonstrated that the function of TrkA+ neurons does not requirea functional circadian clock (Figures S2J–S2O), excluding thepossibility that TrkA+ neurons might have a role in the circadian
process (process C) of the two-process model (Borbély, 1982).

Figure 2. Inhibition of the TrkA- and Ngfr-Expressing Neurons Induced a Characteristic Short-Sleep Phenotype with Consolidated Wakefulness in the Dark Phase(A–C) Sleep phenotypes of TrkA-TeNT mice (n = 6) and control littermates with normal-food (n = 13) measured by the non-invasive respiration-based automatedsleep phenotyping system—snappy sleep stager (SSS).
(A) Heatmap representation of sleep duration (per hour) over 6 days.
(B) The profile of sleep duration and PWS (per hour) over 24 hr averaged over 6 days. The mean at each hour of the day is plotted for TrkA-TeNT mice (magenta line)
and for control mice (black line). Shaded area around the line represents SEM.
(C) Sleep and 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, and PWS and PSW are the respective transition probabilities from wakefulness to sleep and vice versa.
(D–F) Sleep phenotypes of the doxycycline (dox)-treated TrkA-TeNT mice (n = 6) and control littermates (n = 13) measured by SSS.
(D) Heatmap representation of sleep duration (per hour) over 6 days.
(E) The profile of sleep duration and PWS (per hour) over 24 hr averaged over 6 days. The mean at each hour of the day is plotted for TrkA-TeNT mice (magenta line)
and for control mice (black line). Shaded area represents SEM.
(F) Sleep and wake parameters are presented as in (C).
(G–I) Sleep phenotypes of TrkA-TeNT mice (n = 5) and control littermates (n = 4) measured by EEG and EMG recording.
(G) Heatmap representation of sleep duration (per hour) over 3 days.
(H) The duration of total sleep, NREM sleep, and REM sleep in a day.
(I) The duration of REM sleep in the light (left) or dark phase (right).
(J–L) Sleep phenotypes of Ngfr-TeNT mice (n = 7) and control littermates (n = 13) measured by SSS.
(J) Heatmap representation of sleep duration (per hour) over 6 days.
(K) The profile of sleep duration and PWS (per hour) over 24 hr averaged over 6 days. The mean at each hour of the day is plotted for Ngfr-TeNT mice (magenta line)
and control littermates (black line). Shaded area represents SEM.
(L) Sleep and wake parameters are presented as in (C).
Error bars represent SEM. *p < 0.05; **p < 0.01; ***p < 0.001.

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Together, these results suggested that TrkA- and Ngfr-expressing 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 arecholinergic (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 arecoexpressed in the same cells in a similar manner of Gal80 andGal4 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 embryonicstem 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-targetingstrategy (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 shortsleep phenotype was mostly abolished (Figures 3C–3E). FISH
analysis of those mice confirmed that TeNT expression was suppressed 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 confirmedthat tTR and either VGluT1 or ChAT was coexpressed by FISH
(Figures S4C and S4D). These results suggested the TrkA+
cholinergic neurons are primarily responsible for the characteristic 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 examining the phenotypes of acetylcholine receptor knockout (KO)mice.
There are two different families of acetylcholine receptors—
nicotinic receptors and muscarinic receptors. Nicotinic acetylcholine receptors (nAchR) consist of five types of subunits—alpha (a1–10), beta (b2–5), 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 eachgene, we used a triple-target CRISPR method (STAR Methods).
The genotype of KO mice was confirmed by qPCR (Figure S5;
Table S2). KO of Chrna3 was lethal because mice died shortly after birth (n = 26), which was consistent with the result of the conventional KO method (Xu et al., 1999). Among the KO mice,
Chrnb2 KO had a sleep profile resembling that of TrkA-TeNT
mice (Figures 4A–4C and 2A–2C), but changes in sleep andwake parameters, including sleep duration, amplitude, and
PWS, were not significant within the statistical power achievedby 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 researchsite, had significant changes in amplitude and PWS, but thechange of sleep duration was moderate at 649.3 ± 13.5 min(mean ± SEM; n = 8), which was only 38.3 min shorter thanthat 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 regulation 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

Figure 3. Rescue of Cholinergic Neurons in TrkA-TeNT Mice by the tTR System Mostly Abolished the Characteristic Short-Sleep Phenotype(A) Schematic representation of the dual conditional expression pattern achieved by Tet system and the tTA repressor tTR. In Tet system, the reporter or effector
expression is activated by tTA driven by promoter and/or enhancer of geneX (left) in the absence of dox. With tTR driven by promoter and/or enhancer of geneY as
an inhibitor, the reporter or effector expression is suppressed in cells expressing both geneX and geneY (right).
(B) Luciferase assay in cultured cells showing the effect of tTR on tTA-induced tetO-luciferase (FLuc) activity. The x axis indicates the amount of DNA (mg) for tTA
and tTR used in the experiment. Renilla luciferase (RLuc) was used as an internal control.
(C–E) Proof-of-concept experiments of tTR-rescue system in vivo. The sleep phenotypes of TrkA-TeNT mice (n = 25), TrkA-TeNT;ChAT-tTR mice (n = 16), TrkATeNT;VGluT1-tTR mice (n = 8), and control littermates (n = 53) were analyzed by SSS.
(C) Heatmap representation of sleep duration (per hour) over 6 days.
(D) The profile of sleep duration (per hour) over 24 hr averaged over 6 days. The mean sleep duration at each hour of the day is plotted for control littermates (blackline in each panel) and for mutants, i.e., TrkA-TeNT mice (magenta line), TrkA-TeNT;ChAT-tTR mice (green line), and TrkA-TeNT;VGluT1-tTR mice (blue line).
Shaded area represents SEM.
(E) Sleep and wake parameters. Sleep duration is the total sleep duration in a day, amplitude is related to the variation of the sleep duration (per hour) within thedaily sleep cycle, and PWS and PSW are the respective transition probabilities from wakefulness to sleep and vice versa. *p < 0.05; **p < 0.01; ***p < 0.001 by the
Steel test against TrkA-TeNT.
(F) Repressed expression of tetanus toxin (TeNT) by tTR. TrkA (fluorescein labeled, Flu; green) and TeNT expression were measured by fluorescent in situ
hybridization (FISH). TeNT expression was measured by an antisense RNA probe against Egfp fused to TeNT (digoxigenin labeled, Dig: red).
Error bars represent SEM.

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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 thecharacteristic short-sleep profile with consolidated wake in theearly dark phase, which resembled the sleep profile of TrkATeNT 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, respectively, (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 guide RNAs (set 2; Figure 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, theobserved reduction of sleep duration in Chrm1 KO mice (set 2)
and Chrm3 KO mice (set 2) was mostly attributable to thedecreased 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 andFragmented REM Sleep
To further ensure that the characteristic short-sleep phenotype 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) usedin the previous measurement (Figures 5A–5C) and confirmed
the characteristic sleep profile with consolidated wake inthe 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 wasincreased at those frequency domains in Chrm3 KO mice (Figures S7A and S7B).
In Chrm3 KO mice, the duration of NREM sleep in a day wassignificantly 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 durationof 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 attributableto decreased PWN (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 between REM sleep and NREM sleep (PRN and PNR) were mutually increased (Figure 6F), especially in the light phase (Figure 6G). The increased transition with the retained total
duration of REM sleep indicated that REM sleep was fragmented, and hence, PRR (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 episodeduration of REM sleep (Table S3C). Together, these observations suggested that Chrm3 has a role in regulating the durationof NREM sleep in a day but also contributes to the consolidation 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 PRN (the transition probability
from REM sleep to NREM sleep), implying weakened maintenance of REM sleep (Figures 6C and 6G; Table S3). Although
not as much as Chrm3 KO mice, Chrm1 KO mice also had a significant 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 withconsolidated wakefulness in the dark phase as was observed

Figure 4. Comprehensive Analysis of Sleep Phenotypes by Triple-Target CRISPR KO Revealed a Minor Effect from Nicotinic Receptors(A–C) Sleep phenotypes measured by SSS for the series of KO mice of nine nicotinic acetylcholine receptors: Chrna2 (n = 3); Chrna4 (n = 7); Chrna5 (n = 4); Chrna6(n = 7); Chrna7 (n = 6); Chrna9 (n = 4); Chrna10 (n = 12); Chrnb2 (n = 3); and Chrnb4 (n = 8).
(A) Heatmap representation of sleep duration (per hour) over 6 days.
(B) The profile of sleep duration (per hour) over 24 hr averaged over 6 days. The mean sleep duration at each hour of the day is plotted for KO mice (magenta line)
and for the C57BL/6N wild-type mice (gray line; n = 108; replotted from the previous report; Sunagawa et al., 2016). The shaded area represents SEM.
(C) Sleep and wake parameters. Sleep duration is the total sleep duration in a day, amplitude is related to the variation of the sleep duration (per hour) within thedaily sleep cycle, and PWS and PSW are the respective transition probabilities from wakefulness to sleep and vice versa. The black dashed line and the shaded area
represent the mean and 1 SD range of the wild-type control mice, respectively.
(D–F) Sleep phenotypes of Chrnb3 KO mice (n = 8) measured by SSS.
(D) Heatmap representation of sleep duration (per hour) over 6 days.
(E) The profile of sleep duration (per hour) over 24 hr averaged over 6 days. The mean sleep duration at each time of the day is plotted for Chrnb3 KO mice
(magenta line) and for C57BL/6N wild-type (gray line; n = 107). The shaded area represents SEM.
(F) The sleep and wake parameters are presented as in (C).
Error bars represent SEM. *p < 0.05; **p < 0.01; ***p < 0.001.

Cell Reports 24, 2231–2247, August 28, 2018 2239

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Figure 5. Comprehensive Analysis of Sleep Phenotypes by Triple-Target CRISPR KO Revealed Prominent Effects of Two Muscarinic
Acetylcholine Receptors Chrm1 and Chrm3(A–C) Sleep phenotypes measured by SSS for the series of KO mice of five muscarinic acetylcholine receptors: Chrm1 (set 1; n = 8); Chrm2 (n = 4); Chrm3 (set 1;
n = 11); Chrm4 (n = 8); and Chrm5 (n = 7).
(A) Heatmap representation of sleep duration (per hour) over 6 days. Set 1 indicates the guide (gRNAs) used for producing the mutant mice.

(legend continued on next page)2240 Cell Reports 24, 2231–2247, August 28, 2018

in Chrm3 KO mice (Figures 6A and 6G). These observations suggested 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 andImportant for NREM Sleep
Compared to TrkA-TeNT mice, changes in sleep phenotype,especially changes in amplitude and PWS, of Chrm1 KO miceand 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 duration, amplitude, and PWS to a degree comparable to that of
TrkA-TeNT mice (Figures 6I, 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 morethan 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 earlydark phase (Figure 6I). In addition, both TrkA-TeNT mice andChrm1/3 double-KO mice consistently exhibited the enhanced
rebound sleep after sleep deprivation, which suggested that homeostatic 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 thedark 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 towakefulness (PRW) by conventional EEG analysis, PRW did notexhibit 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 theChrm1/3 double-KO mice (Figure 7C). In line with this observation, the EEG power spectrum of Chrm1/3 double-KO mice displayed reduced theta power in NREM sleep (Figure S7C).
To further ensure loss of REM sleep, we produced anothergroup of Chrm1/3 double-KO ESC mice by injecting CRISPRedited 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 stimulated with the gentle touch of a brush to deprive sleep from zeitgeber 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 WTmice 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 results 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 arenecessary 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; Weberand Dan, 2016). However, the essential molecular factors fordefining and translating the output of the brainstem circuit to
the collective activity of cortical neurons have been elusive. Multiple lines of in vivo pharmacological evidence consistently indicated that muscarinic acetylcholine receptors are important for
the regulation of REM sleep. Muscarinic receptor agonists andacetylcholinesterase 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(B) The profile of sleep duration (per hour) over 24 hr averaged over 6 days. The mean sleep duration at each hour of the day is plotted for KO mice (magenta line)
and for the C57BL/6N wild-type mice (gray line; n = 108). The shaded area represents SEM.
(C) Sleep and wake parameters. Sleep duration is the total sleep duration in a day, amplitude is related to the variation of the sleep duration (per hour) within thedaily sleep cycle, and PWS and PSW are the respective transition probabilities from wakefulness to sleep and vice versa. The black dashed line and shaded area
represent the mean and 1 SD range of the wild-type control mice, respectively.
(D–G) Sleep phenotypes of another group of Chrm1 (n = 6) or Chrm3 (n = 7) KO mice produced by a different set of gRNAs (set 2).
(D) Heatmap representation of sleep duration (per hour) over 6 days.
(E) The profile of sleep duration (per hour) over 24 hr averaged over 6 days, as in (B).
(F) The profile of PWS (per hour) over 24 hr averaged over 6 days. The mean PWS at each hour of the day are plotted for KO (magenta line) and for C57BL/6N wildtype mice (gray; n = 108). The shaded area represents SEM.
(G) The sleep and wake parameters are presented as in (C).
Error bars represent SEM. *p < 0.05; **p < 0.01; ***p < 0.001.

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H

I

K

J

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M

(legend on next page)2242 Cell Reports 24, 2231–2247, August 28, 2018

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 revealed 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 otherGq-type receptor Chrm5 did not significantly change sleep phenotypes, which may reflect the low abundance of Chrm5 in thebrain. 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 nigra 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 characteristic short-sleep profile with consolidated wakefulness inthe early dark phase. This characteristic phenotype was also
observed in Chrm1 and Chrm3 single-KO mice and in TrkATeNT mice. Reduction of sleep duration of all those mice wasmostly attributable to the reduced duration of NREM sleep, indicating 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 indicated 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 pathways 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 glutamatergic neurons (Kamsler et al., 2010; Weng et al., 2014) and
GABAergic neurons (Xiao et al., 2009), or by hypothesizing theproximal projection of TrkA+ neurons to sleep-promoting neurons, such as POA GABAergic neurons, that inhibit wake-promoting neurons in the tuberomammillary histaminergic neurons(TMNs) (Chung et al., 2017). Indeed, a specific cholinergic receptor could be sleep-promoting although overall effect of thecholinergic system is wake promoting, as reported for the redeyemutant in Drosophila, where REM sleep has so far not been identified (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 rigorously verify whether REM sleep plays crucial roles in fundamental 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 andcellular mechanisms.
STAR+METHODS
Detailed methods are provided in the online version of this paper
and include the following:d KEY RESOURCES TABLE
d CONTACT FOR REAGENT AND RESOURCE SHARING
d EXPERIMENTAL MODEL AND SUBJECT DETAILS

Figure 6. Chrm1 and Chrm3 Have Differential Roles for NREM and REM Sleep and Are Essential for REM Sleep(A–F) Sleep phenotype of Chrm1 or Chrm3 KO mice measured by EEG and EMG recordings.
(A) Heatmap representation of sleep duration (per hour) over 3 days for Chrm1 KO (set 1; n = 7) and control (C57BL/6N) mice (n = 7).
(B) The durations of total sleep, NREM sleep, and REM sleep.
(C) The changes in transition probability among wakefulness, NREM sleep, and REM sleep are presented for Chrm1 KO mice. The green bold and magenta dottedlines represent a significant increase and decrease, respectively, compared to that of control mice.
(D) Heatmap representation of sleep duration (per hour) over 3 days for Chrm3 KO (set 1; n = 6) and control (C57BL/6N) mice (n = 8).
(E) The durations of total sleep, NREM sleep, and REM sleep.
(F) The changes in transition probability among wakefulness, NREM sleep, and REM sleep are presented for Chrm3 KO mice as in (C).
(G) The changes in transition probabilities among wakefulness, NREM sleep, and REM sleep in the light phase (ZT0–12) and dark phase (ZT12–24) for Chrm1 or
Chrm3 KO mice used in (A) and (D).
(H–J) Sleep phenotype of Chrm1 and Chrm3 double-KO mice (Chrm1/3 double-KO mice; set 1/set 1; n = 5) measured by SSS.
(H) Heatmap representation of sleep duration (per hour) over 6 days.
(I) The profile of sleep duration and PWS (per hour) over 24 hr averaged over 6 days. The mean at each hour of the day for the KO mice (magenta line) and for
C57BL/6N wild-type mice (gray line; n = 108) is shown. The shaded area represents SEM.
(J) The sleep and wake parameters. Sleep duration is the total sleep duration in a day, amplitude is related to the variation of the sleep duration (per hour) within thedaily sleep cycle, and PWS and PSW are the respective transition probabilities from wakefulness to sleep and vice versa. The black dashed line and the shaded area
represent the mean and 1 SD range of the control, respectively.
(K and L) Sleep phenotypes of Chrm1/3 double-KO mice (n = 5) and control mice (n = 11) measured by EEG and EMG recordings.
(K) Heatmap representation of sleep duration (per hour) over 6 days for Chrm1/3 DKO and control (C57BL/6N) mice.
(L) The durations of total sleep, NREM sleep, and REM sleep.
(M) The sleep duration of total sleep, NREM sleep, and REM sleep measured by EEG and EMG recordings in the 12 hr before and after sleep deprivation (SD).
‘‘After SD’’ and ‘‘before SD,’’ respectively, correspond to the sleep duration of ZT12–24 subsequent to SD and the sleep duration of ZT12–24 in the day before theday of SD. SD was applied for Chrm1/3 double-KO ESC mice (n = 7) and control (C57BL/6N) mice (n = 8) for 6 hr from ZT6 to ZT12.
Error bars represent SEM. *p < 0.05; **p < 0.01; ***p < 0.001.

Cell Reports 24, 2231–2247, August 28, 2018 2243

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G

Figure 7. Detailed EEG and EMG Analysis of Chrm1/3 Mutants and a Schematic Representation of Ach-Chrm1/3 Regulation of Sleep(A–C) Hypnogram, delta power (normalized mV2), ratio of theta/delta power, and total power of EMG wave. Two individual mice from each of Chrm1 KO (A), Chrm3
KO (B), Chrm1/Chrm3 CRISPR DKO (C), and their control mice group were presented over ZT6–12 of the first day of EEG and EMG recording. Colored triangles
indicate the arbitrary chosen position of epochs shown in (D)–(F). Red for wake, blue for REM, and green for NREM are shown.
(D–F) Representative EEG and EMG plot of two individual mice from Chrm1 KO (D), Chrm3 KO (E), Chrm1/Chrm3 CRISPR DKO (F), and their control group. The
horizontal axis represents a time of three epochs (24 s). The annotated stage (wake, NREM, or REM) is displayed for each epoch. The vertical axis represents
recorded signal (in range from 0.2 to 0.2 mV) of EEG (blue) and EMG (red).
(G) A hypothetical molecular and cellular scheme for REM sleep and NREM sleep regulation. The solid line represents interaction confirmed in this study. The
dashed line in a faint color means a potential interaction to be investigated in a future study. Other cells represent cholinergic sources other than TrkA/ChATpositive cells focused in this study, such as the laterodorsal tegmentum (LDT) and the pedunculopontine tegmentum (PPT) in the brainstem.

2244 Cell Reports 24, 2231–2247, August 28, 2018

B Cultivation of mouse embryonic stem (ES) cells
B Mice and sleep phenotyping
B Transfection and Luciferase Assayd METHOD DETAILSB Sampling of POA/BF regions
B Microarray analysis

Quantitative Biology Center (to H.R.U.), an incentive research fund fromRIKEN (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 (toY.N. and G.N.K.), and an ECARD grant from Queensland University of Technology (to D.P.).

B Generationof TrkA-tTA and Ngfr-tTA transgenic
mouse lines
B Construction of tTR
B Generation of ChAT-tTR-nmNGx3 and VGluT1-tTRnmNGx3 KI mice
B Triple-target CRISPR: gRNA synthesis
B Triple-target CRISPR: Cas9 mRNA synthesis
B Triple-target CRISPR: One-cell embryo microinjection
B Triple-target CRISPR: Genotyping of KO mice and
ESCs by quantitative PCR (qPCR) and sequencing
B Establishment of Chrm1/3 dKO ES cell
B Sleep measurement with SSS
B Sleep measurement with EEG and EMG recordings
B Visual inspection on behaviors
B Sleep deprivation with SSS
B Sleep deprivation with EEG and EMG recordings
B X-gal staining and fluorescent imaging of Tet reportermice
B In situ hybridizationd QUANTIFICATION AND STATISTICAL ANALYSIS
d DATA AND SOFTWARE AVAILABILITY
SUPPLEMENTAL INFORMATION
Supplemental Information includes seven figures and three tables and can befound 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 administration of the server of Brainstars. We also thank all the lab members at RIKEN
Center for Development Biology (CDB), QBiC, Center for Biosystems Dynamics 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 andsupporting experiments and the LARGE, RIKEN BDR for housing the mice.
This work was supported by a grant from Japan Agency for Medical Researchand Development (AMED)-Core Research for Evolution Science and Technology (CREST) (JP17gm0610006; AMED/Ministry of Education, Culture, Sports,
Science and Technology [MEXT]; H.R.U.), CREST (Japan Science and Technology Agency [JST]/MEXT; H.R.U.), Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS) (AMED/MEXT; H.R.U.), Basic Science and Platform Technology Program for Innovative Biological Medicine(AMED/MEXT; H.R.U.), a Grant-in-Aid for Scientific Research (S; Japan Society for the Promotion of Science [JSPS] KAKENHI grant number 25221004;
H.R.U.), a Grant-in-Aid for Scientific Research (B; JSPS KAKENHI grant number 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 RIKENAUTHOR 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 analysis. 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 themanuscript. All authors discussed the results and commented on the manuscript text.
DECLARATION OF INTERESTS
The authors declare no competing interests.
Received: March 14, 2018
Revised: June 3, 2018
Accepted: July 25, 2018
Published: August 28, 2018
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STAR+METHODSKEY RESOURCES TABLEREAGENT or RESOURCESOURCEIDENTIFIER

anti-Dig-Fab-AP

Merck

Cat# 11093274910; RRID: AB_2734716

Anti-Fluorescein-HRP

PerkinElmer

Cat# NEF710001EA

Anti-Digoxigenin-POD, Fab fragments from sheep

Roche

Cat# 11207733910; RRID: AB_514500

This paper

GEO: GSE107500

ATCC

CRL-3216

Antibodies

Deposited Data
Expression profile of adult mouse BF and/or POA regions
Experimental Models: Cell Lines
Human: HEK293T
Experimental Models: Organisms/Strains
Mouse:Tg(tetO-tdTomato,-Syp/EGFP*)1.1Luo/Jz

The Jackson Laboratory

JAX: 012345

Mouse:B6;DBA-Tg(Fos-tTA,Fos-EGFP*)1Mmay
Tg(tetO-lacZ,tTA*)1Mmay/J

The Jackson Laboratory

JAX:008344

Mouse:C57BL/6J-Tg(tetO-EGFP/TeNT)1Nak

RIKEN BRC

RBRC02958

Mouse: TrkA-tTA

This paper

N/A

Mouse: Ngfr-tTA

This paper

N/A

Mouse: ChAT-tTR-nmNGx3

This paper

N/A

Mouse: VGluT1-tTR-nmNGx3

This paper

N/A

Oligonucleotides for FISH, see Table S1

This paper

N/A

Oligonucleotides for triple-target CRISPR, see Table S2This paper

N/A

Oligonucleotides for plasmid DNA construction, see STAR methods

This paper

N/A

pEF-BOS

Mizushima and Nagata, 1990

N/A

pRL-SV40

Promega

N/A

Oligonucleotides

Recombinant DNA

CONTACT FOR REAGENT AND RESOURCE SHARING
Further information and requests for reagents should be directed to Lead Contact Hiroki R. Ueda (uedah-tky@umin.ac.jp).
EXPERIMENTAL MODEL AND SUBJECT DETAILS
Cultivation of mouse embryonic stem (ES) cells
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 PURECoatTM amine dishes (Beckton-Dickinson, NJ, U.S.A.) were exposed to medium containing LIF plus 6-bromoindirubin-30-oxime (BIO) (Sato et al., 2009) for more than 5 hours at 37 C with 5% CO2. 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% CO2.
Mice and sleep phenotyping
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 wascontrolled under 12 h light and 12 h dark cycle. Production and sleep phenotyping of Chrna2, Chrna4, Chrna5, Chrna6, Chrna7,
Chrna9, Chrna10, Chrnb2, and Chrnb4 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 phenotypingof 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.

e1 Cell Reports 24, 2231–2247.e1–e7, August 28, 2018

Transfection and Luciferase Assay
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 mg/mL streptomycin; Thermo Fisher Scientific, MA,
U.S.A.) at 37 C with 5% CO2. One day prior to transfection, cells were plated onto 35 mm dishes at a density of 4 3 105 cells per
well. The following day, 293T cells were co-transfected using FuGene6 (Roche, Switzerland) with 0.2 mg of a luciferase reporter
plasmid (ptetO-Luc) and the indicated amount (mg) 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 mg per well. Additionally, 40 ng of a pRL-SV40 plasmid (Renillaluciferase (RLuc) reporter vector; Promega, WI, U.S.A.) was added to each transfection as an internal control for transfection efficiency. 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.
METHOD DETAILSSampling of POA/BF regions
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 mousebrain 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.
Microarray analysis
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 Scientific, 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 withthe 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).
Generation of TrkA-tTA and Ngfr-tTA transgenic mouse lines
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/mL,
and injected into pronuclei of C57BL/6N zygotes as reported previously (Abe et al., 2013). Transgenic lines termed TrkA-tTA (Accession 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
50 -ggaaggcgagctggcattagggcctcaaaa-30 , 50 -cgacatccagacagtgactgcgcggctctg-30 , and 50 -tcttgccatgactcgccttccagggggcag-30 for
TrkA-tTA, and the primers 50 -gaggaggcggggctgctgcattgccttcac-30 , 50 -gactgctcccagtctcctacaccgcacccg-30 , and 50 -tcttgccat
gactcgccttccagggggcag-30 for Ngfr-tTA, yielding 619 bp and 434 bp products (TrkA-tTA) and 585 bp and 426 bp products (NgfrtTA), respectively.
Construction of tTR
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 acidsequence of tTR is as follows:
MSRLDKSKVINSALELLNEVGIEGLTTRKLAQKLGVEQPTLYWHVKNKRALLDALAIEMLDRHHTHFCPLEGESWQDFLRNNAKSFRC
ALLSHRDGAKVHLGTRPTEKQYETLENQLAFLCQQGFSLENALYALSAVGHFTLGCVLEDQEHQVAKEERETPTTDSMPPLLRQAIELFDHQGAEPAFLFGLELIICGLEKQLKCESGGPKKKRKLAVSVTFEDVAVLFTRDEWKKLDLSQRSLYREVMLENYSNLASMAGFLFTKPKVISLLQQGEDPW*Cell Reports 24, 2231–2247.e1–e7, August 28, 2018 e2

Generation of ChAT-tTR-nmNGx3 and VGluT1-tTR-nmNGx3 KI micetTR 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-2AtTR 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 (50 -ggctcgatccctcgagttgggggctca
catgaagctgg-30 ), reverse primer for ChAT (50 -cgggaattcgatgatatcgaatgcatcactgcttcaaacaactgtc-3 0 ), forward primer for VGluT1(50 -ggctcgatccctcgaggcctgagcggcagtgtcgagg-30 ), and reverse primer for VGluT1 (50 -cgggaattcgatgatatcgagcagagaaactgaggtgca
gac-30 ). The PCR products were inserted into the XhoI 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 (50 -tagggataacagggtaatatagaggtgacagcaggattggaagtg-30 ), reverse primer
for ChAT (50 -gcggagaaagaggtaatgaaatgggcgtgggagtagtcaagattgcttgg-3 0 ), forward primer for VGluT1 (50 -tagggataacagggtaatatagccctcgctatgccagcatcttg-30 ), and reverse primer for VGluT1 (50 -gcggagaaagaggtaatgaaatgggcgtagtcccggacagggggcg-3 0 ). The
products of first PCR for the left-homology arms were amplified with primers (50 -gcagttacgctagggataacagggtaatatag-30 and 50 -gat
catctatgtcgggtgcggagaaagaggtaatgaaatgg-30 ) and inserted into the I-SceI and PI-SceI digested pTVCI3-Rarm using the In-Fusion
HD Cloning Kit. The puromycin resistance gene cassette (P(PGK)-PuroR-polyA) was inserted into I-CeuI and PI-PspI digested
pTVCI3-LRarm.
Targeting, screening, and injection were performed according to the procedures described previously (Ode et al., 2017b; Ukai
et al., 2017).
Triple-target CRISPR: gRNA synthesis
The target sequences for Chrna2, Chrna4, Chrna5, Chrna6, Chrna7, Chrna9, 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 theon-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 (50 -aaaagcaccgactcggtgcc-30 ; 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 andforward 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.).
Triple-target CRISPR: Cas9 mRNA synthesis
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 XbaI
(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.).
Triple-target CRISPR: One-cell embryo microinjection
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% CO2 incubator at 37 C. Cas9 mRNA (100 ng/mL) and gRNAs(150 ng/mL in total) were co-injected into the cytoplasm of fertilized eggs in M2 medium (Merck Millipore or ARK Resource) atroom temperature (23–25 C). Details of the cytoplasmic injection were reported previously (Sumiyama et al., 2010). After microinjection, the embryos were cultured for 1 h in KSOM medium (Merck, Germany or ARK Resource, Japan) in a 5% CO2 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

e3 Cell Reports 24, 2231–2247.e1–e7, August 28, 2018

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, whichwere independent of first qPCR.
Establishment of Chrm1/3 dKO ES cell
One-cell embryo, Cas9 mRNA, and gRNAs were prepared as described above. Cas9 mRNA (100 ng/mL) and gRNAs (150 ng/mL 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% CO2 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 3 105
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% CO2 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 thefeeder-coated dish. Embryos were incubated at 37 C in 5% CO2 without replacing the medium for 10 days or more, until a lump-likeES 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% CO2, BIO-medium was replaced with 3i-culture
medium, and then the plates were incubated at 37 C in 5% CO2.
After confirming proliferation of the primary colony, culture medium was replaced with fresh 3i medium (pre-warmed to 37 C) andincubation continued for 3 h at 37 C in 5% CO2. 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% CO2 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, 50 -ccatgtcaagcgccccatga-30 ;Sry-R, 50 -gtaaggcttttccacctgca-30 (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 reported protocol (Ode et al., 2017b; Ukai et al., 2017).
Sleep measurement with SSS
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) condition, 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, PWS, and PSW were defined previously (Sunagawa et al., 2016). For the present study, the definition of transition probabilities are as follows: The PWS and PSW represent different probabilities in regard to thedirection of wake/sleep transition. For example, when a mouse shows a long sleep phonotype, its PWS (transition probability fromwake 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 andwake 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 theobserved period. Similarly, PWW and PSS can also be defined. According to these definitions, it can be noticed that PSW + PSS = 1 andPWS + 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).
Sleep measurement with EEG and EMG recordings
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 annotation 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

Cell Reports 24, 2231–2247.e1–e7, August 28, 2018 e4

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 logarithm of EMG power of each cluster was computed and clusters that have higher median logarithm of EMG power than the 0.5 quartiles 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 wasstaged 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 lowamplitude 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 towakefulness is defined as PNW = NNW/(NNW + NNR + NNN) where Nmn is defined as a number of transitions from state m to n (m,n 4{wakefulness, NREM sleep, REM sleep}) in the observed period. Notably, in the EEG and EMG recordings, there are theoreticallyeight 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 thesequences 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.
Visual inspection on behaviors
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-oscillation 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 justafter the sleep-deprivation for individual mice. The timestamp of epoch was reported when its theta/delta ratio exceeded thethreshold of mean + 5 SD, and the associated videos were visually inspected. The inspection covered the 30-hour period prior toand 12-hour period subsequent to the sleep-deprivation. The timestamps of transition from NREM sleep to wakefulness were extracted according to annotated stages.
Sleep deprivation with SSS
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 oneused 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 and fluorescent imaging of Tet reporter mice
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 mm sections, fixed in 2% formaldehyde and 0.2% glutaraldehyde in PBS solution for 1 h at 4 C, rinsed twice in 0.1 M phosphate buffer (PB) (pH 7.4), 2 mM MgCl2, 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 MgCl2, 0.01% sodium deoxycholate, 0.02% NP-40, 5 mM
K3Fe(CN)6, 5 mM K4Fe(CN)6 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, andstored in O.C.T. compound at 80 C. Fluorescence images were acquired with an LSFM (Ultramicroscope, LaVision BioTec, Germany) as described in the previous report (Susaki et al., 2014).

e5 Cell Reports 24, 2231–2247.e1–e7, August 28, 2018

For each brain sample of CUBIC analysis, 3D NIfTI-1 files were generated from the Z stacks acquired in the dorsal-ventral (DV) andventral-dorsal (VD) directions, merged, and registered as described previously (Susaki et al., 2014; Susaki et al., 2015). We normalized the tdTomato signals and used the NIfTI-1 images aligned to the Allen Brain Atlas (Lein et al., 2007) to extract only pixels locatedinside 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’’ (withparameters 800, 65536), ‘‘Threshold,’’ and ‘‘Analyze Particles’’ (with size = 2–25, circularity = 0.3–1.0) commands. The number ofactivated 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 imagesof cell activation throughout the brain.
To analyze local patterns, we aligned these images to the brain atlas using the registration parameters calculated above. Analyzingaligned samples meant that we did not have access to single-cell resolution, and the Fiji-based cell detection method could not beapplied. However, it was previously shown that the intensity of the extracted signal could be used to estimate the number of activatedcells with R2 z0.95 (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 onregions with a non-zero signal in at least 3 of the 9 brains. For these regions, hierarchical clustering was performed in R (R Development 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.
In situ hybridization
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 mousebrain cDNA (first strand cDNA mouse brain MD01, GenoStaff). All the probe fragments were cloned into pCR-BluntII-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 thesame 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 ofimages covering all areas of a section were acquired and stitched with the pairwise stitching plugin of ImageJ (Preibisch et al., 2009).
QUANTIFICATION AND STATISTICAL ANALYSIS
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 bothgroups, 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 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 significance level of 0.05. When the normality was not rejected in both groups, the homogeneity of variance was tested by F-test at asignificance level of 0.05. When the null hypothesis of normal distribution with equal variance for the two groups was not rejected, aStudent’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), datameans 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

Cell Reports 24, 2231–2247.e1–e7, August 28, 2018 e6

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).
DATA AND SOFTWARE AVAILABILITY
Genome-wide mRNA expression profiles of BF/POA region analyzed along with data from 48 other brain regions which we madepublic at the database (http://poabf.brainstars.org/).

e7 Cell Reports 24, 2231–2247.e1–e7, August 28, 2018

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, Dimitri
Perrin, Yasufumi Shigeyoshi, Hideki Ukai, Hiroshi Kiyonari, Kenta Sumiyama, and Hiroki
R. UedaTrkA-tTA (+)
tetO-tdTomato (+)

TrkA-tTA (-)
tetO-tdTomato (+)

Genes
BF/POALSRS
Cx motor
Cx cingulate
OB anterior
OB posterior
PirTuventral S
CA1
CA2/CA3
DG
A anterior
A posteriorGP
CPu lateral
CPu medial
MD
VA/VL
VPM/VPL
LG
MG
Hb
M
ME
SCN
MPA
SO
Pa
SPa ventral
SPa dorsal
DM
VMH
Arc
LH
PAG
SC
IC
VTA
SN
Tg
Pn
MVe
Cb vermis
Cb lobeCb nucleus
spinal cord anterior
spinal cord posterior

A
CH
TH

Normalized gene expression : -3

HY

0

B

Niwa et al. Figure S1MB+3 S.D.

P
CB SC

Figure S1. Identification of marker genes in the BF/POA region and establishment of TrkA-tTA 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, lateralgeniculate body. MG, medial geniculate nucleus. Hb, habenular nucleus. Pineal, corpus pineal. M, mammillarybody. 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 TrkAtTA transgene were imaged and analyzed as in Figure 1I. 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 1I. Gray dots
represent nuclear signal of RedDot2; green dots represent cells in the 99 detected regions. Scale bar, 2 mm.

1

2

C

3 4 5
Time (day)

67

1

2

3 4 5
Time (day)

6

7

0

60

0.2
PWS

B

60

Sleep duration (min)Mouse

TrkA-TeNT (n = 5)

Mouse

Control (n = 11)

Sleep duration (min)

A

30

0.1

0

0
0

6

12
18
Time (h)

24

0

6

12
18
Time (h)24Control

400 500 600 700 800 900
Sleep duration (min)0.2

0.4 0.6 0.8
Amplitude

D

1.0

0.02

E

Control (n = 6)Marker

Tg

- +

pA

3 4 5
Time (day)

6

1

7

60

30

6

12
18
Time (h)

24

2

3 4 5
Time (day)

6

1

7

2

3 4 5
Time (day)

6

7

0

0.04
Pws

0

6

12
18
Time (h)

24

n.s.

800
600
400
200
Ctrl NgfrTeNT

0.06

0.02

0.06

n.s.

600
400
200
0

0.04
Psw

*

800

Ctrl NgfrTeNT

100
80
60
40
20
0

Ctrl NgfrTeNT

K
60

0

0.2

60
PWS

Mouse

(n = 9)

Mouse
1

0.02

*

0

7

n.s.

1000

Per1/2-DKO, TrkA-TeNT(n = 15)

L

0

6

0
0

1.0

Sleep duration (min)Per1/2-DKO

Sleep duration (min)1 2 3 4
Time (day)60

Sleep duration (min)J

0.4 0.6 0.8
Amplitude

I
Sleep duration (min)Ngfr-TeNT(n = 3, EEG/EMG)

Mouse

Control(n = 11, EEG/EMG)

0.2

3 4 5
Time (day)0.1

0NREM duration (min)400 500 600 700 800 900
Sleep duration (min)

2

60

0.2

**

**

1 2 3 4
Time (day)

0.06

Mouse
2

Control
Ngfr-TeNT

H

0.04
Psw

Ngfr-TeNT (n = 6)

PWS

F

ATG

Sleep duration (min)

Ngfr

G

0.02

95,575,000
1

tTA

0.06

REM duration (min)95,585,000

Mouse chr11:

0.04
Pws

Mouse

BAC
R24-309N6

n.s.

**

Sleep duration (min)****TrkA-TeNT

30

0.1
0

0
0

6

12
18
Time (h)

0

24

6

12
18
Time (h)24Per1/2-DKO

0.4 0.6 0.8
Amplitude(n = 9)
Mouse

2

3 4 5
Time (day)

6

7

1

2

3 4 5
Time (day)

6

7

***
0.02

1.0

0.04
Pws

***

0.06

0.02

0.04
Psw

0.06

12
18
Time (h)

24

N
60

0

60

0.2
PWS

Per1/2-DKO, TrkA-TeNT(n = 15)

Sleep duration (min)Per1/2-DKO

Mouse
1

O

0.2

Sleep duration (min)400 500 600 700 800 900
Sleep duration (min)

M

**

**

Per1/2-DKO,
TrkA-TeNT

30

0.1

0

0
0

6

12
18
Time (h)2406Per1/2-DKO
n.s.

**

Per1/2-DKO,
TrkA-TeNT
400 500 600 700 800 900
Sleep duration (min)0.2

0.4 0.6 0.8
Amplitude

1.0

Niwa et al. Figure S2

***
0.02

0.04
Pws

0.06

**
0.02

0.04
Psw

0.06

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 ofmodified 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) andcontrol Per1/2 DKO mice (n = 15) under LD (J-L) and DD (M-O) conditions measured by SSS. Mice weremaintained 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 haveraged over 6 days. The mean at each hour of the day is plotted for TrkA-TeNT, Per1/2 DKO mice (magentaline) and for control Per1/2 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 (perhour) within the daily sleep cycle, PWS and PSW are the respective transition probabilities from wakefulness tosleep and vice versa. Error bars, SEM. *P < 0.05, **P < 0.01, ***P < 0.001.

A

Dox 40 ppm

Dox 0 ppm
week 1week 2Dox 40 ppm

week 3week 4*week 5week 6week 7week 16****week 4 is shown in Figures 2A-C**week 16 is shown in Figures 2D-F

B
Control

Mouse

TrkA-TeNT

Mouse

week 1

1
Sleep duration (min)

C

2

Sleep
duration (min)Amplitude

1

2

3

4

5

7

6

1

12
18
Time (h)24Control

0

6

12

18

24

n.s.

TrkA-TeNT
400 500 600 700 800 900
Control

0.4

0.6

0.8

400 500 600 700 800 900

1.0Control

0.04

0.2

0.4

0.6

0.02

Control

0.8

Control

Mouse

TrkA-TeNT

Mouse
1

2

0.06

2

3

4

5

7

1

24

0

6

0.04

0.02

6

12

18

2

3

4

week 7

5

7

1

24

0

6

0.2

0.4

0.6

0.02

0.04

0.8

1.0

0.2

0.4

0.6

0.02

0.04

0.8

2

3

4

5

7

6

0.02

1

24

0

2

3

4

week 2

7

1

24

0

6

2

week 3

3

18

24

***
400 500 600 700 800 900

0.4

0.6

0.02

0.04

0.8

1.0

***
0.2

0.4

0.6

0.02

0.04

0.8

1.0

*

***
0.06

0.06
n.s.

**

0.06

0.02

0.04

0.06

0.02

0.04

0.06

Dox 5 ppm
week 5week 3

5

0.2

0.06

0.04

12

***

n.s.

0.06

6

***

*

0.06

0.04

18

400 500 600 700 800 900

1.0

n.s.
0.02

12

***

*

0.06

6

***
400 500 600 700 800 900

**

0.06

0.04

0

Dox 0 ppm

7

6

24

***

week 23 4 5Time (day)

18

n.s.

week 1

Sleep duration (min)1

400 500 600 700 800 900

1.0

n.s.
0.04

12

n.s.

0.06

TrkA-TeNT

6

***

n.s.

TrkA-TeNT

F

4

week 6week 7week 5

5

7

1

24

0

6

2

3

4

week 6

5

7

1

24

0

6

2

3

4

week 7

5

7

1

24

0

6

2

3

4

5

7

6

60

30

0
0

Sleep
Amplitude duration (min)

7

6

n.s.

n.s.

TrkA-TeNT

0week 16

12
18Time (h)Control

6

12

18

n.s.

TrkA-TeNT
400 500 600 700 800 900
Control

0.4

0.6

0.8

400 500 600 700 800 900

1.0Control

0.02

0.04

0.2

0.06

Control

0.4

0.6

0.8

0.02

0.04

0.06

18

0.04

0.2

0.06

0.4

0.6

0.8

0.04

0.06

18

0.04

0.2

0.06

0.4

0.6

0.8

0.04

0.06

18

0.04

0.2

0.06

0.4

0.6

0.8

Niwa et al. Figure S3

0.04

0.06

18

24

n.s.
400 500 600 700 800 900

1.0

n.s.
0.2

0.4

0.6

0.8

1.0
n.s.

**
0.02

0.04

0.06

n.s.
0.02

12

*

*
0.02

6

n.s.
400 500 600 700 800 900

1.0

*
0.02

12

**

***
0.02

6

*
400 500 600 700 800 900

1.0

**
0.02

12

***

***
0.02

6

***
400 500 600 700 800 900

1.0

n.s.

TrkA-TeNT

12

**

n.s.

TrkA-TeNT

6

*

n.s.

TrkA-TeNT
0.2

Pws

5

week 60
6

Dox 5 ppm

Psw

4

0

E

H

3

30

0.02

G

2

30

0.02
Psw

7

6

week 5

60

0.2
Pws

3 4 5
Time (day)week 360

0D

week 2

0.02

0.04

0.06
n.s.

*
0.02

0.04

0.06

0.02

0.04

0.06

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-foodmeasured by SSS. B, Heatmap representation of sleep duration (per hour) over 6 days. C, Sleep duration (perhour) 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 (perhour) within the daily sleep cycle, PWS and PSW are the respective transition probabilities from wakefulness tosleep and vice versa. E, Experimental protocol of 5 ppm doxycycline (dox) treatment of TrkA-TeNT mice andcontrol mice. F-H, Sleep phenotype of TrkA-TeNT mice (n = 8) and control littermates (n = 13) with 5 ppm doxfood 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 TrkATeNT mice (magenta line) and for control mice (black line). Shaded area represents SEM. H, Sleep/wakeparameters are presented as in (D). Error bars, SEM. *P < 0.05, **P < 0.01, ***P < 0.001.

A

Dox 40 ppm

Dox 0 ppm
week 1B

week 2week 3Dox 40 ppm
week 4week 5week 16

Control

TrkA-TeNT
Egfp-Dig

Chat-Flu

mNeonGreen-Dig

Trka-Flu

Egfp-Digweek 16

week 3week 2week 1

Trka-FluD

Ctx/OB

BF

Vglut1-Flu

HIP

LDT

CPu

BF

C

Niwa et al. Figure S4

mNeonGreen-Dig

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 weremaintained 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 (TrkaFlu; 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) detectedby 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.

A chr14 (+)

66,145,000

B chr2 (-)

66,150,000

181,035,000

181,030,000

Chrna2Chrna4gatgtggtcatcgtgcgctt (-)
gaaagtcacgtcgatgctgc (-)
ggttccggtggcgttgataa (+)
Chrna2 target sequence-1 Chrna2 target sequence-2 Chrna2 target sequence-3

gatgtggtccttgtccgctt (-)
ggcatgactacaaactgcgc (-) gcacacgcccatcatagaac (+)
Chrna4 target sequence-1 Chrna4 target sequence-2 Chrna4 target sequence-3

C chr9 (+)

54,990,000

D chr8 (-)

55,000,000

27,410,000

27,405,500

Chrna5Chrna5Chrna5Chrna6

gaatgtctccgatcccgtca (+)
gaaatcgaccttctcatcat (+)
gggcaacctcctgatgtaga (-)
Chrna6 target sequence-1 Chrna6 target sequence-2 Chrna6 target sequence-3

ggcaaagacagtcaccataa (-) gtagcgaatgcaatcgagcg (-) gaaacatccgatcgagaact (-)
Chrna5 target sequence-1 Chrna5 target sequence-2 Chrna5 target sequence-3

E chr7 (-) 63,200,000

65,970,000

65,975,000

Chrna7Chrna9ggtcaagaactacaacccgc (-) gaactccttgcaggaatccc (-)
ggccatagtagagtgtccta (+)
Chrna7 target sequence-1 Chrna7 target sequence-2 Chrna7 target sequence-3

gggatcgagaccagtatgac (+) gagatgacgttcttcacggc (-) ggagccagaacaaatcacga (+)
Chrna9 target sequence-1 Chrna9 target sequence-2 Chrna9 target sequence-3

G chr7 (-)

102,115,000

H chr3 (-)

102,113,000

89,760,000

89,755,000

Art1
Chrna10Adar
Chrnb2

gactctaaatgtgaccctgg (+)
gcacttggttccgttcatcc (-)
ggacagacgcctacctacat (+)
Chrna10 target sequence-1 Chrna10 target sequence-2 Chrna10 target sequence-3

gcgataatcttcccactcct (-)
ggacgacttcacacctagtg (+) ggcacactattcttccgcga (+)
Chrnb2 target sequence-1 Chrnb2 target sequence-2 Chrnb2 target sequence-3

I chr8 (+)

27,380,000

J chr9 (-)

27,390,000

550,040,000

550,030,000

Chrnb3
Chrnb3
Chrnb3

Chrnb4
Chrnb4

ggacagaccaaaaattacga (+) ggttccgctggatttcacaa (-) ggagagtaagggaaccgtga (+)
Chrnb3 target sequence-1 Chrnb3 target sequence-2 Chrnb3 target sequence-3

gggggtaaagtcatccatga (-)
gtgaacggtggtgcacattg (-) ggactggaaattcgtcgcaa (+)
Chrnb4 target sequence-1 Chrnb4 target sequence-2 Chrnb4 target sequence-3

L

2

3

Q

2

3

120
100
80
60
40
20
0

WT 1

2

3

4

5

4

120
100
80
60
40
20
0

WT

1

2

3

4

5

6

Genome DNA/Tbp(wild-type = 100%)

6

2

3

4

5

6

7

4

5

120
100
80
60
40
20
0

7

6

7

WT

7

8

9

8

Niwa et al. Figure S5

1

3

4

7

Chrna7 (1st qPCR)

WT 1

R

2

3

4

5

6

Chrnb2 (1st qPCR)

10 11 12

120
100
80
60
40
20
0

WT 1

2

3

7

8

Chrnb4 (1st qPCR)
Genome DNA/Tbp(wild-type = 100%)

WT 1

3

O

T

Chrnb3 (1st qPCR)
120
100
80
60
40
20
0

2

Chrna10 (1st qPCR)
Genome DNA/Tbp(wild-type = 100%)

Genome DNA/Tbp(wild-type = 100%)

S

WT 1

1

Chrna6 (1st qPCR)

4Chrna9 (1st qPCR)
120
100
80
60
40
20
0

WT

Genome DNA/Tbp(wild-type = 100%)

Genome DNA/Tbp(wild-type = 100%)

P

WT 1

120
100
80
60
40
20
0

Genome DNA/Tbp(wild-type = 100%)

N

Chrna5 (1st qPCR)
120
100
80
60
40
20
0

(2nd qPCR)

Chrna4 (1st qPCR)
Genome DNA/Tbp(wild-type = 100%)

Chrna2 (1st qPCR)
120
100
80
60
40
20
0
WT 1 2 3

Genome DNA/Tbp(wild-type = 100%)

Genome DNA/Tbp(wild-type = 100%)K

M

F chr5 (+)

63,150,000

120
100
80
60
40
20
0

WT 1

2

3

4

5

6

Figure S5. Confirmation of knockout of nicotinic acetylcholine receptors. Related to Figure 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), andChrnb4 (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 thesense (+) 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 thepercentage of that of wild-type mouse. Number and WT below the bar plot denote the ID of KO mouse and thewild-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.

A

B

chr19 (+)

8,670,000

chr6 (+)

8,680,000

36,450,000

36,500,000

Chrm1
Chrm1
gcattcatcgggatcaccac (+)
Chrm1 target sequence-1

Chrm2

cgcttaactgggtaggttag (-)
Chrm2 target sequence-1

gtgggcctcttgactgtatt (-) gcaaaggccaaaaaccccga (+)
Chrm1 target sequence-2 Chrm1 target sequence-3

C

gggactgaaaactgcgttca (+)
Chrm2 target sequence-2

gttggctttcatcatcacgt (+)
Chrm2 target sequence-3

D

chr13 (-)

10,200,000

10,000,000

chr2 (+)

91,925,000

91,927,500

Chrm3
Chrm3
gacaaggatgttgccgatga (-)
Chrm3 target sequence-1

gcacgaaacggtcatctagg (+)
Chrm3 target sequence-2

Chrm4
Chrm4

gctgcatacccaaaacctat (+)
Chrm3 target sequence-3

gactgtggtgggtaacatcc (+)
Chrm4 target sequence-1

E

ctgccatcttagtagtgcgg (-) gtaaccaggtgcgcaagaag (+)
Chrm4 target sequence-2 Chrm4 target sequence-3

F
112,480,500

Genome DNA/Tbp(wild-type = 100%)chr2 (-)

112,479,500
Chrm5

Genome DNA/Tbp(wild-type = 100%)

G
120
100
80
60
40
20
0

Chrm2 (1st qPCR)

WT 1

2

3

gacaaacaatggctgtcgta (+)
Chrm5 target sequence-3

H(2nd qPCR)

4

WT 4

Chrm4 (1st qPCR)

120
100
80
60
40
20
0

WT 1

2

3

4

5

6

WT 1

8

WT 2

3

5

K

2

2

3

4

6

3

5

J

(2nd qPCR)

7

WT 1

4

5

6

7

8

9

10 11

Chrm3 (set 1, 1st qPCR)

Genome DNA/Tbp(wild-type = 100%)

Genome DNA/Tbp(wild-type = 100%)

I
120
100
80
60
40
20
0

gtagatccggcagtagagta (+)
Chrm5 target sequence-2

Genome DNA/Tbp(wild-type = 100%)

gaccaagacattgccgacaa (-)
Chrm5 target sequence-1

Chrm1 (set 1, 1st qPCR)
120
100
80
60
40
20
0

7

120
100
80
60
40
20
0

6

7

8

Chrm5 (1st qPCR)

WT 1

2

3

4

5

6

7

L

chr19 (+)

8,670,000

8,680,000

chr13 (-)

10,200,000

10,000,000

Chrm1
Chrm1
cagtcccaacatcaccgtct (-)
Chrm1 target sequence-4

M

attcatgacagaggcgttgc (+)
Chrm1 target sequence-5

ctacatcattatgaaccgct (+)
Chrm3 target sequence-4

WT 1

2

O

3

4

5

6

WT 5

Genome DNA/Tbp(wild-type = 100%)

Chrm1/Chrm3
120
100
80
60
40
20
0

Chrm1 - Target - 1
Chrm1 - Target - 2
Chrm1 - Target - 3
Chrm3 - Target - 1
Chrm3 - Target - 2
Chrm3 - Target - 3
WT

1

2

3

4

aaacgagccggtgtgatgat (+)
Chrm3 target sequence-5

N(2nd qPCR)

Genome DNA/Tbp(wild-type = 100%)

Genome DNA/Tbp(wild-type = 100%)

Chrm1 (set 2, 1st qPCR)
120
100
80
60
40
20
0

gagaagggggccattagcat (+)
Chrm1 target sequence-6

Chrm3
Chrm3

5

Niwa et al. Figure S6

gtccttcaaagaagccacgc (+)
Chrm3 target sequence-6

Chrm3 (set 2, 1st qPCR)
120
100
80
60
40
20
0

WT 1

2

3

4

5

6

(2nd qPCR)

7

WT 4

Figure S6. Confirmation of knockout of muscarinic acetylcholine receptors. Related to Figure 5, 6 and 7
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); eachgene 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, andgreen) 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), andChrm1/3 (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 wildtype 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 ofthree 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.

0.3

Delta: Ctrl < Mut, n.s. (p = 0.09)
Theta: Ctrl < Mut, * (p = 0.02)

0.2

0.2

0.1

0.1

0.1

0.1

0.1

0

0

0

0

0.3

10
20
30
Frequency (Hz)Delta: Ctrl < Mut, n.s. (p = 0.25)
Theta: Ctrl < Mut, n.s. (p = 0.26)

0

0.3

0

10
20
30
Frequency (Hz)Delta: Ctrl < Mut, ** (p = 0.007)
Theta: Ctrl < Mut, *** (p < 0.001)

10
20
30
Frequency (Hz)

0
0

0.3

0.3

Delta: Ctrl < Mut, * (p = 0.04)
Theta: Ctrl < Mut, n.s. (p = 0.14)

0.2

0.2

0.2

0.2

0.1

0.1

0.1

0.1

0
0

0.3

0
0

10
20
30
Frequency (Hz)0.3

Delta: Ctrl < Mut, n.s. (p = 0.80)
Theta: Ctrl < Mut, n.s. (p = 0.33)

10
20
30
Frequency (Hz)Delta: Ctrl < Mut, * (p = 0.01)
Theta: Ctrl < Mut, ** (p = 0.009)

0
0

0.3

Delta: Ctrl > Mut, n.s. (p = 0.70)
Theta: Ctrl > Mut, ** (p = 0.007)

0.3

10
20
30
Frequency (Hz)Delta: Ctrl > Mut, n.s. (p = 0.73)
Theta: Ctrl > Mut, n.s. (p = 0.08)

0.3

0.2

0.2

0.2

0.2

0.1

0.1

0.1

0.1

0.1
10
20
30
Frequency (Hz)***(n = 12)Control

2 h SD

4 h SD(ZT 8-12)

6 h SD(ZT 6-12)(n = 5)(n = 12)(ZT 10-12)

**

4.0
3.0
2.0
1.0
0

1h

2h

I

4h

6h

*
5.0
4.0
3.0
2.0
1.0
0

1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7Time (day)Time (day)Time (day)Time (day)SD :Niwa et al. Figure S7

*

5.0

SD :

Fold change (After SD/Basal)

1 h SD1020
30Frequency (Hz)G

(ZT 6-12)

1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7Time (day)Time (day)Time (day)Time (day)(ZT 11-12)

0

Control

6 h SD

00

Fold change (After SD/Basal)(ZT 8-12)102030Frequency (Hz)TrkA-TeNT

4 h SD00

1 hr

Control

2 h SD(ZT 10-12)

10
20
30
Frequency (Hz)

10
20
30
Frequency (Hz)Delta: Ctrl < Mut, n.s. (p = 0.98)
Theta: Ctrl > Mut, n.s. (p = 0.08)

Chrm1/3-DKO

0
0

TrkA-TeNT

102030Frequency (Hz)Chrm1/3-DKO

00

Delta: Ctrl < Mut, n.s. (p = 0.80)
Theta: Ctrl < Mut, n.s. (p = 0.16)

0

0.2
0

10
20
30
Frequency (Hz)

0
0

10
20
30
Frequency (Hz)(n = 6)

TrkA-TeNT

0.3

0.1

1 h SD

Chrm1/3-DKO Control

0

10
20
30
Frequency (Hz)0.2
0Delta: Ctrl < Mut, n.s. (p = 0.26)
Theta: Ctrl < Mut, n.s. (p = 0.59)

TrkA-TeNT0(ZT 11-12)

H

0.3

0.2

2 hrs

4 hrs

Chrm1/3-DKO

Delta: Ctrl > Mut, n.s. (p = 0.47)
Theta: Ctrl < Mut, n.s. (p = 0.40)

0.2

Control

0.3

0.2

Control

Delta: Ctrl > Mut, n.s. (p = 0.85)
Theta: Ctrl < Mut, ** (p = 0.003)

Ngfr-TeNT

TrkA-TeNT

0.3

TrkA-TeNT

Chrm1/3-DKO

Delta: Ctrl > Mut, n.s. (p = 0.84)
Theta: Ctrl < Mut, ** (p = 0.006)

Chrm1/Chrm3-DKO

Control

0.3

Chrm3-KO

E

ControlPower density(normalized mV2/Hz)

Chrm1-KO

D

ControlPower density(normalized mV2/Hz)

Wake
REM
NREM

F

C

Control

B
Power density(normalized mV2/Hz)

A

6 hrs

Figure S7. FFT power spectrum on EEG/EMG recording and the response of TrkA-TeNT and Chrm1/3DKO 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), andNgfr-TeNT (E) mice. The mean power density at each frequency is plotted for mutant mice (magenta line) andfor 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. Statisticalresults 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 inthree days before the day of SD. Error bars, SEM. *P < 0.05, **P < 0.01, ***P < 0.001.

SUPPLEMENTAL*TABLES*
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 vitrotranscription with T3-probe PCR fragments. ChAT probes were used as mixes of ChAT-1 and 2. T3 promoter
sequence is underlined.
Gene

PrimerSequence

Forward5'-cctactgagggcaaaggctccggact-3'

Reverse5'-aattaaccctcactaaaggggtagacatcaggagggcaggcg-3'

Forward5'-tacgttctctgacgtggtaagc-3'

Reverse5'-aattaaccctcactaaagggagtctatatgctccggctggta-3'

Forward5'-cccatcctggtcgagctggacg-3'

Reverse5'-aattaaccctcactaaagggcacgaactccagcaggaccatg-3'

Forward5'-taacatggcctctctcccagcg-3'

Reverse5'-aattaaccctcactaaagggcacatcggtaaaggccttttgc-3'

Chat

Forward5'-ccccccaaagatgcctgtacaagc-3'(Probe #1)

Reverse5'-aattaaccctcactaaagggcctggaccatccaggcataccag-3'

Chat

Forward5'-ggtggaggctgcagcttgaatgga-3'(Probe #2)

Reverse5'-aattaaccctcactaaagggcaggctccatacccattgggtacc-3'

Vglut1

Forward5'-ctggcagtgacgaaagtgaa-3'(Slc17a7)

Reverse5'-aattaaccctcactaaagggacacaacaaatggccactga-3'

Trka

Ngfr

Egfp

mNeonGreen*