DOI: 10.5061/dryad.nzs7h4545
title: Polycomb regulates sleep homeostasis in a specific group of cells in Drosophila brain

description: Sleep is regulated by the circadian rhythm and homeostasis. Previous
 studies have shown that epigenetic factors play a crucial role in
 controlling sleep homeostasis. However, a global view of the epigenetic
 target genes involved in sleep homeostasis is still lacking. In
 this study, we have discovered that Polycomb (Pc)
 regulates sleep
 in EB1-Gal4 and R69F08-Gal4 co-expressing cells, which are important for controlling sleep homeostasis. Using Targeted DAM-ID (TaDa) and RNAseq, we have identified Pc targets in EB1-Gal4 and R69F08-Gal4 expressing cells and analyzed Pc targets that are crucial for the control of sleep homeostasis. Furthermore, identifying common targets in EB1-Gal4 and R69F08-Gal4 marked cells provides a global view of the cluster-specific target genes of Pc, which potentially play a crucial role in controlling sleep homeostasis. The clustering of these target gene profiles reveals their enrichment distributions. Further experiments demonstrated that Pc stabilized the expression levels of their targets under conditions of sleep deprivation. This study sheds light on the role of Pc in sleep homeostasis control and identifies its target genes in a cell-specific manner. It also lays the foundation for further studies on the mechanisms of epigenetic regulation of sleep homeostasis
description: <strong>Fly strains and rearing</strong>
 All fly stocks were reared on standard corn meal/agar fly food at
 25°C, humidity of 60% and light dark cycle of 12:12 LD (12 hours of light
 followed by 12 hours of darkness). The following fly lines were used in
 this study: <em>w1118 <em>(BDSC:
 5905),</em> EB1-Gal4 <em>(BDSC: 44409),
 R69F08-Gal4</em> (BDSC: 39499), UAS-RedStinger</em> (BDSC:
 8547) are from the Bloomington stock
 center (BDSC). <em>UAS-PcRNAi</em>-1 (THU1990), <em>UAS-PcRNAi</em>-2 (THU1306), <em>UAS-GABA-B-R1RNAi</em>-1 <em>(THU2990), UAS-GABA-B-R1RNAi-2 (THO1472.N), UAS-GrdRNAi (THU5922), UAS-SecClRNAi (THU2480), UAS-CG12344RNAi (THU2249), UAS-nAChRalpha3RNAi (THU2756), UAS-HdcRNAi (THU2140), UAS-HisCl1RNAi (THU2851), UAS-Daao1RNAi (THO4274.N), UAS-Daao2RNAi (THO4297.N) are from the TsingHua Fly Center (THFC). UAS-stop&gt;kir2.1; LexAop-Flp</em>, <em>UAS-stop&gt;TNT; 8×LexAop-Flp</em>, LexAop-Flp; UAS-stop&gt;shits, <em>8×LexAop-Flp; UAS-stop&gt;TrpA1</em>, <em>LexAop-kir2.1</em>, <em>UAS-StingerGFP, lexAop-tomato::nls</em>, <em>13×LexAop-FLP; UAS-FRT&gt;stop&gt;FRT-myrGFP</em>, <em>tub-Gal80ts</em>, <em>UAS-inactive-TNT</em>, <em>UAS-Strong-TNT</em>, <em>UAS-kir2.1</em> and <em>UAS-dTrpA1</em> are gifts from Dr. Yi Rao’s lab (Peking University, Beijing, China). <em>R69F08-lexA</em> was generated based on <em>R69F08-Gal4</em> in this study by using the Site-specific recombination [28]. All behavior tests were performed in isogenous backgrounds. <strong>Activity measurement, sleep deprivation and sleep analysis</strong> Sleep measurement was conducted using the <em>Drosophila</em> Activity Monitor (DAM) system (Trikinetics, MA, US). The methodology for sleep measurement was consistent with previous studies conducted in our laboratory [19, 45, 46]. Briefly, flies were subjected to a 12-hour light/dark (LD) cycle at a temperature of 25°C, unless otherwise stated. Male flies aged between 4-7 days were placed in 65 mm × 5 mm tubes containing fly food and allowed to acclimate for 24-36 hours prior to sleep recording. Subsequently, sleep behavior was recorded continuously for 3 days under LD conditions without any disruptions. For the experiments with* tub-Gal80ts* (Fig. 1A-D; Fig. S1 and Fig. 5), to prevent <em>Pc</em> downregulation during development, flies were raised at 18°C in LD cycle. For sleep behavior with <em>UAS-PcRNAi</em>-1 and <em>UAS-PcRNAi</em>-2, the newly eclosed male flies were transferred to 29°C to allow Gal4 activity. Sleep behavior was recorded 3 days at 29°C in LD condition. The DAM system records each time a fly breaks an infrared beam that bisects the center of each glass tube, and activity counts are collected in a 1 min bin. Sleep was defined as resting for more than 5 minutes [47, 48]. Sleep curve and total sleep were analyzed using Pysolo software  For sleep deprivation experiments, sleep deprivation was carried out using the DAMs monitors as described previously [45]. For sleep deprivation experiments involving *tub-Gal80ts *(Fig. 1E-P; Fig. 5C-I), conditions for the induction of Gal4 activity were performed as described above, sleep measurement was performed at 29°C until the end of the experiment. For sleep deprivation experiments at 25°C (Fig. 3D-I; Fig. 8; Fig. 14A-B), sleep measurement was performed at 25°C until the end of the experiment. Baseline sleep was measured for 2 days prior to sleep deprivation. Sleep deprivation was achieved by loading flies in DAMs monitors into the shaker (Oscillation mixer, #QB-600, Kylin-Bell lab instruments) fitted with a custom base. Flies were vortexed from ZT12 (Zeitgeber time 12: beginning of the dark phase) to ZT24 (Zeitgeber time 24: beginning of the light phase) at the lower intensity setting for 3sec/min. Zeitgeber time is used to indicate the phase of the circadian rhythm in relation to a specific Zeitgeber. ZT12 is the time when the dark phase begins (or dusk). ZT0 (ZT24) corresponds to the time when the light/dark cycle begins (often referred to as the “lights-on” time or dawn). The 24-hour cycle is divided into 24 Zeitgeber times, where ZT0 represents the start of the light phase, and ZT12 corresponds to the start of the dark phase. The day time increase of total sleep amount after sleep deprivation was calculated by subtracting the baseline daytime sleep amount of each repeat from the corresponding daytime sleep amount after the sleep deprivation. The night time decrease of total sleep amount after sleep deprivation was calculated by subtracting the baseline night time sleep amount of each repeat by the corresponding night time sleep amount after the sleep deprivation. The percentage of sleep recovery was calculated by (day time increase of total sleep amount) / (night time decrease of total sleep amount). Sleep recovery (min) was calculated by (daytime sleep amount after sleep deprivation - baseline daytime sleep amount before sleep deprivation). For experiments involving <em>LexAop-Flp; UAS-stop&gt;shits</em>, <em>8×LexAop-Flp; UAS-stop&gt;TrpA1</em> and <em>UAS-dTrpA1</em>, flies were raised at 21°C in LD 12:12 condition until 4-7 days old (Fig. 6C-L; Fig. 7). Male flies were monitored at 21°C for at least one day followed by shifting to 29°C for 12 hrs at night (ZT12-ZT24) to activate the cells. After the heat pulse, the incubator temperature dropped to 21°C and the recovery sleep was measured. For experiments involving <em>UAS-stop&gt;kir2.1; LexAop-Flp</em>, <em>UAS-stop&gt;TNT; 8×LexAop-Flp</em>, <em>LexAop-kir2.1</em>, <em>UAS-kir2.1</em>, <em>UAS-inactive-TNT</em> and <em>UAS-Strong-TNT</em>, flies were raised at 25°C in LD 12:12 condition until 4-7 days old, sleep measurement was performed at 25°C until the end of the experiment. Sleep propensity was measured by examining the percentage of flies keep asleep in five minutes after light on. Waking activity was measured by examining activity counts in 24 hrs after being fully aroused. All statistical tests were conducted using GraphPad prism. The statistical tests for each experiment are shown in the figures. The sleep parameters were tested by unpaired Student’s t-test and One-way ANOVA followed by Tukey post hoc test. n.s. indicates no significant difference, * indicates P &lt; 0.05, ** indicates P &lt; 0.01, and *** indicates P &lt; 0.001. The sample size for all behavioral tests was determined previously [47, 48]. Flies were randomly selected for behavioral tests upon eclosion. Steps for blinding of the investigators were taken to minimize the subjective bias when analyzing the data. All sleep tests were done in males. <strong>Immunostaining and imaging</strong> Imaging was performed as previously described [27] with minor modifications. Briefly, male fly brains were dissected in cold 0.03% PBST and fixed in 2% PFA for 55 min at RT. After brief washes in washing buffer (1×PBS with 1% Triton X-100), the brain samples were mounted on glass slides with Mounting medium containing anti-fading and DAPI (Solarbio, #S2110). For Fig. 4 and Fig. 3A-C, 10-day-old fly brains were incubated with antibodies. The concentration used were 1:1000 for rabbit anti-GFP (Thermo Fisher Scientific, #A11122), 1:200 for Mouse anti-Repo (Developmental Studies Hybridoma Bank, #8D12) and 1:200 for Rat anti-Elav (Developmental Studies Hybridoma Bank, #7E8A10). After brief washes in washing buffer, brains were incubated with secondary antibodies. The concentration used were 1:200 for Alexa 488 anti-rabbit (ABclonal, #AS011) and 1:200 for Alexa 568 anti-mouse (Thermo Fisher Scientific, #A1104) and Alexa FluorTM 647 anti-mouse (Thermo Fisher Scientific, #A21247). The imaging was performed on Leica SP8 confocal microscope. <strong>Quantitative real-time PCR</strong> The process for total RNA extraction from fly heads involved the use of 40 fly heads from 3-5-day-old flies for each sample. Total RNA was extracted using Trizol Reagent, and the samples were then subjected to reverse transcription and quantitative real-time PCR. Specifically, we employed the HiScript III All-in-one RT SuperMix Perfect (Perfect for qPCR) (Vazyme, #R333) for reverse transcription and the ChamQ SYBR qPCR Master Mix (High ROX Premixed) (Vazyme, #Q341) for real-time PCR. For qPCR quantification, <em>Rp49</em> was used as normalization control, the delta-delta CT method was used for quantification. The sequence of primers is shown in Table S4. The significance of differences between genotypes was tested by Student’s t-test (GraphPad Prism). All experiments were done with at least 3 biological repeats, and three technical repeats were done for each biological repeat. All quantitative RT-PCR were performed using Step One Real-Time PCR system (Applied Biosystems). <strong>TaDa sample preparation and data analysis</strong> Tada plasmids were obtained from Andrea H Brand’s laboratory [20]. <em>UAS-PcDam</em> was generated in our previous study [19]. The genotypes used for the final experiments were <em>tub-Gal80ts/+; UAS-Dam/EB1-Gal4</em>, <em>tub-Gal80ts/+; UAS-PcDam/EB1-Gal4</em>, <em>tub-Gal80ts/+; UAS-Dam/R69F08-Gal4</em>, and <em>tub-Gal80ts/+; UAS-PcDam/R69F08-Gal4</em>. The experimental protocol details were described by Marshall et al., 2016 [20] with some minor adjustments. Briefly, flies were raised at 21°C until eclosion. Subsequently, the newly eclosed flies underwent a 72-hour heat shock at 29°C. Fly head tissue was collected at ZT12, and genomic DNA was extracted from approximately 100 fly heads. The TaDa experiments were then conducted as per the description provided by Marshall et al., 2016 [20]. The TaDa samples were utilized for TaDa-seq, which was carried out by Novogene in Beijing, China. Tada data analysis: The damidseq_pipeline was used to analyze Tada data [20, 49]. Transcriptome sequencing data was compared with <em>Drosophila</em> genome annotation release 6.37 using Bwa software, genome sequence was divided into 395891 intervals of different lengths according to methylated GATC sites by the damidseq_pipeline. Additionally, Log2 ratio files were generated by comparing Dam-Pc over Dam-only samples and subjected to median normalization for further analysis. In this study, we used the coverage ratio of genes as the threshold (coverage ratio≥0.182 for <em>DamPc/EB1-Gal4</em> and coverage ratio ≥ 1.028 for <em>DamPc/R69F08-Gal4</em>) to screen out meaningful regions. To ensure the accuracy of our results, macs2 software was also used to predict the enrichment of transcripts on the genome besides using Damidseq_pipeline software. After macs2 software screening (macs2 threshold is 0.2), there are 32817 peaks in the <em>R69F08-Gal4/PcDam</em> samples and 77481 peaks in the <em>EB1-Gal4/PcDam</em> samples. Further, analysis revealed that 7781 peaks and 13128 peaks fell within the gene region, respectively. In our study, we intersect Damidseq_pipeline and macs2 results, we found that 6089 Pc binding target genes exist in the <em>R69F08-Gal4</em> cells and 9252 target genes exist in the <em>EB1-Gal4</em> cells. Pc binding genes and down-regulated <em>Pc</em> genes in the <em>R69F08-Gal4</em> cells and <em>EB1-Gal4</em> cells were used for volcano plots, dot plots, KEGG enrichment, and Gene Ontology (GO) enrichment analysis. Tada data peaks were annotated to genomic features and the nearest genes of TSS using R package Chipseeker (v1.31.3.900) [50]. Volcano plots were plotted by R-package ggplot2 (v3.2.1) [51].  KEGG enrichment, GO enrichment and dot plots were performed by using the R package clusterProfiler (v4.3.3) [52] and org.Dm.eg.db (v3.7.0) dictionary. The simplify output from compareCluster by removing redundancy (cutoff=0.7, by=”p. adjust”) of enriched GO terms. Venn diagrams were generated by R package VennDiagram (v1.7.1) [53]. <strong>RNA-seq sample preparation and data analysis</strong> For the RNA-seq analysis in this study, <em>Drosophila</em> heads of specific genotypes at ZT12 were utilized. The RNA-seq experiments were conducted by Biomics Company in Beijing, China, following standard protocols. To perform differential expression analysis, the EBSeq method [54] was employed. This approach allows for the identification of genes that exhibit significant differences in expression between control and treatment conditions. Specifically, genes with a mean fold change greater than 1.2 were considered as significantly changed and selected for further analysis. Each sample used in the analysis consisted of 50 fly heads.  Genotypes for RNA-seq: <em>tub-Gal80ts/+; EB1-Gal4/+</em> <em>tub-Gal80ts/+; UAS-PcRNAi/EB1-Gal4</em> <em>tub-Gal80ts/+; R69F08-Gal4/+</em> <em>tub-Gal80ts/+; UAS-PcRNAi/R69F08-Gal4</em>
description: # Polycomb regulates sleep homeostasis in a specific group of cells in
 Drosophila brain Dataset DOI:
 [10.5061/dryad.nzs7h4545](10.5061/dryad.nzs7h4545) ## Description of the
 data and file structure This dataset was generated to test whether
 Polycomb (Pc) regulates sleep amount and sleep homeostasis in *Drosophila*
 and to identify the cell types and downstream genes involved. We combined
 cell-type–specific genetics (EB1-Gal4, R69F08-Gal4, Repo-Gal4; UAS-Pc
 RNAi; Kir2.1/TNT; dTrpA1; LexA/LexAop intersections) with behavioral
 recording under LD cycles. Sleep was measured as 24-h profiles, total
 sleep, and recovery after 12-h night sleep deprivation. Brain expression
 patterns and co-localization were assessed by immunostaining. Pc targets
 were mapped by TaDa (Targeted DamID) in the above populations and by
 RNA-seq after Pc perturbation, followed by GO/KEGG enrichment. The files
 provide the raw/processed data underlying the main and supplementary
 figures/tables. ### Files and variables #### Source_data_for_fig._1.xlsx
 Fig. 1 Polycomb (Pc) is required for sleep and homeostasis regulation in
 cells expressing EB1-Gal4 and R69F08-Gal4. To systematically elucidate the
 role of the epigenetic factor *Pc* in sleep regulation, we performed a
 cell-specific knockdown screen. We employed two Gal4 drivers to
 specifically induce the knockdown of *Pc*. Specifically,
 *EB1-Gal4*-induced Pc knockdown led to a reduction in both total daytime
 (ZT0-ZT12, Unit: minutes) and nighttime sleep (ZT12-ZT24, Unit: minutes)
 (Fig. 1A-B). Similarly, *R69F08-Gal4*-induced *Pc* knockdown also resulted
 in decreased total daytime (ZT0-ZT12) and nighttime sleep
 (ZT12-ZT24) (Fig. 1C-D). To understand the role of *Pc* in sleep
 homeostasis, we employed *EB1-Gal4* and *R69F08-Gal4* to drive *Pc* RNAi
 expression in sleep deprivation experiments. Normally, sleep deprivation
 was achieved by mechanical shaking of the flies, which would lead to a
 recovery of sleep amount during the daytime after deprivation. Our results
 indicated that *Pc* knockdown induced by *EB1-Gal4* (Fig. 1M-N) and
 *R69F08-Gal4* (Fig. 1O-P) led to significant changes in sleep recovery
 after 12 hours of sleep deprivation when compared with the controls group.
 These findings indicate that *Pc* is essential for the regulation of sleep
 homeostasis in *EB1-Gal4* and *R69F08-Gal4* expressing cells. Data
 information: (A-B) The sleep phenotypes of *EB1-Gal4* driven
 *Pc* knockdown. (C-D) The sleep phenotypes of *R69F08-Gal4* driven
 *Pc* knockdown. (M-N, O-P) For sleep deprivation
 experiments involving *tub-Gal80^ts^*, conditions for the induction of
 Gal4 activity were performed, sleep measurement was performed at 29°C
 until the end of the experiment. Sleep deprivation was achieved by loading
 flies in DAMs monitors into the shaker fitted with a custom base. Flies
 were vortexed from ZT12 (Zeitgeber time 12: beginning of the dark phase)
 to ZT24 (Zeitgeber time 24: beginning of the light phase) at the
 lower intensity setting for 3 sec/min. Zeitgeber time is used to indicate
 the phase of the circadian rhythm in relation to a specific Zeitgeber. The
 24-hour cycle is divided into 24 Zeitgeber times, where ZT0 represents the
 start of the light phase, and ZT12 corresponds to the start of the dark
 phase. The day time increase of total sleep amount (min) after sleep
 deprivation was calculated by subtracting the baseline daytime sleep
 amount of each repeat from the corresponding daytime sleep amount after
 the sleep deprivation. The night time decrease of total sleep amount (min)
 after sleep deprivation was calculated by subtracting the baseline night
 time sleep amount of each repeat by the corresponding night time sleep
 amount after the sleep deprivation. (M, O) Sleep Recovery (%)
 during ZT0-ZT12 was calculated by (day time increase of total sleep
 amount) / (night time decrease of total sleep amount). (N, P) Sleep
 Recovery (min) during ZT0-ZT12 was calculated by (daytime sleep amount
 after sleep deprivation - baseline daytime sleep amount before sleep
 deprivation). ZT0-ZT12 and ZT12-ZT24 (ZT denotes Zeitgeber time) indicate
 light and dark periods under LD (Light/Dark), respectively. Total sleep
 time (minutes) across circadian phases. Values indicate the total minutes
 of sleep recorded during the 12-hour light (ZT0-ZT12) and 12-hour dark
 (ZT12-ZT24) periods. ### Source_data_for_fig._3.xlsx Fig. 3 Sleep profiles
 after inhibiting R69F08-lexA and R69F08-Gal4 expressing cells. To
 investigate the function of the EB1+/R69F08+ cells, we generated
 *R69F08-lexA*. Inhibition of *R69F08-lexA* expressing cells resulted in
 the same sleep phenotypes as inhibition of *R69F08-Gal4* expressing cells
 (Fig. 3D-E). Moreover, sleep recovery following deprivation was abolished
 after inhibiting *R69F08-lexA* (Fig. 3G) or *R69F08-Gal4* (Fig.
 3I) expressing cells. In conclusion, the *R69F08-lexA* represents
 *R69F08-Gal4* expressing cells in both expression pattern and function.
 Data information: Sleep phenotypes (total sleep - day time during ZT0-ZT12
 and total sleep - nighttime during ZT12-ZT24) caused by inhibiting the
 *R69F08-LexA* expressing cells (D). Sleep phenotypes (total sleep -
 daytime during ZT0-ZT12 and total sleep - nighttime during ZT12-ZT24)
 caused by inhibiting the *R69F08-Gal4* expressing cells (E). For sleep
 deprivation experiments at 25°C, sleep measurement was performed at 25°C
 until the end of the experiment. Baseline sleep was measured for 2 days
 prior to sleep deprivation. Sleep deprivation was achieved by loading
 flies in DAMs monitors into the shaker fitted with a custom base. Flies
 were vortexed from ZT12 (Zeitgeber time 12: beginning of the dark phase)
 to ZT24 (Zeitgeber time 24: beginning of the light phase) at the
 lower intensity setting for 3 sec/min. Zeitgeber time is used to indicate
 the phase of the circadian rhythm in relation to a specific Zeitgeber. The
 24-hour cycle is divided into 24 Zeitgeber times, where ZT0 represents the
 start of the light phase, and ZT12 corresponds to the start of the dark
 phase. Sleep recovery after Sleep deprivation (min) (Fig. 3G & I) was
 calculated by (daytime sleep amount after sleep deprivation - baseline
 daytime sleep amount before sleep deprivation). ZT0-ZT12 and ZT12-ZT24 (ZT
 denotes Zeitgeber time) indicate light and dark periods under LD
 (Light/Dark), respectively. Total sleep time (minutes) across circadian
 phases. Values indicate the total minutes of sleep recorded during the
 12-hour light (ZT0-ZT12) and 12-hour dark (ZT12-ZT24) periods. ###
 Source_data_for_fig._5.xlsx Fig. 5 Pc is required for sleep and
 homeostasis regulation in Glia cells. Knocking down of Pc using
 *Repo-Gal4* partially recapitulated the phenotype driven by *EB1-Gal4* and
 *R69F08-Gal4*. While Repo-Gal4-driven *Pc* knockdown partially phenocopied
 the sleep defects observed in *EB1-Gal4*-/*R69F08-Gal4*-marked cells (Fig.
 5A-B & I), this pan-glial driver cannot isolate contributions from the
 specific EB1+/R69F08+ glial subpopulation. The partial overlap suggests
 that both neuron-glia interactions within EB1/R69F08 lineages and
 subtype-specific glial functions contribute to sleep regulation. Data
 information: (A-B) The sleep phenotypes (Total sleep during ZT0-ZT12 and
 Total sleep during ZT12-ZT24) of *Repo-Gal4* driven *Pc* knockdown. For
 sleep deprivation experiments involving *tub-Gal80^ts^*, conditions for
 the induction of Gal4 activity were performed, sleep measurement was
 performed at 29°C until the end of the experiment. Sleep deprivation was
 achieved by loading flies in DAMs monitors into the shaker fitted with a
 custom base. Flies were vortexed from ZT12 (Zeitgeber time 12: beginning
 of the dark phase) to ZT24 (Zeitgeber time 24: beginning of the light
 phase) at the lower intensity setting for 3 sec/min. Zeitgeber time is
 used to indicate the phase of the circadian rhythm in relation to a
 specific Zeitgeber. The 24-hour cycle is divided into 24 Zeitgeber times,
 where ZT0 represents the start of the light phase, and ZT12 corresponds to
 the start of the dark phase. Sleep recovery (min) during ZT0-ZT12 was
 calculated by (daytime sleep amount after sleep deprivation - baseline
 daytime sleep amount before sleep deprivation) (I). ZT0-ZT12 and ZT12-ZT24
 (ZT denotes Zeitgeber time) indicate light and dark periods under LD
 (Light/Dark), respectively. Total sleep time (minutes) across circadian
 phases. Values indicate the total minutes of sleep recorded during the
 12-hour light (ZT0-ZT12) and 12-hour dark (ZT12-ZT24) periods. ###
 Source_data_for_fig._6.xlsx Fig. 6 Sleep drive is modulated through
 EB1-Gal4- and R69F08-Gal4-expressing cells. In our investigation into the
 role of *EB1-Gal4* and *R69F08-Gal4* expressing cells in sleep regulation,
 we assessed their inhibitory phenotype using *UAS-TNT* and their activated
 phenotype using UAS-dTrpA. The inhibition of the activity of
 *EB1-Gal4* and *R69F08-Gal4* marked cells resulted in reduced overall
 sleep time (Fig. 6A-B). While, activation of *EB1-Gal4* and
 *R69F08-Gal4* expressing cells increased total sleep time (Fig. 6E).  
 Activation of cells expressing *R69F08-Gal4* alone is adequate to regulate
 sleep homeostasis. Consistent with the findings of Liu et al., 2016,
 inducing activation in *R69F08-Gal4* expressing cells resulted in a
 sustained increase in sleep pressure. This is evidenced by the rise in
 daytime sleep subsequent to the activation of these cells via
 temperature-induced dTrpA1, even when the flies had slept well the
 preceding night (Fig. 6F). Conversely, activating *EB1-Gal4* expressing
 cells had no such effect (Fig. 6F). Sleep propensity value, defined as the
 percentage of flies initiating sleep within five minutes after lights-off,
 serves as an indicator of relative sleep pressure. Results demonstrated
 that in contrast to the activation of *EB1-Gal4* marked cells, activating
 *R69F08-Gal4* marked cells heightened sleep pressure (Fig. 6G). We also
 observed that cells expressing *EB1-Gal4* and *R69F08-Gal4* under sleep
 deprivation exhibited increased sleep duration compared to the control
 group (Fig. 6J). The sleep propensity value, representing the percentage
 of flies falling asleep within five minutes after lights-off, indicated
 that under sleep deprivation, activation of *R69F08-Gal4* and
 *EB1-Gal4* expressing cells results in a sustained increase in sleep
 pressure (Fig. 6K). Activation of *R69F08-Gal4* or EB-Gal4 marked cells
 did not alter waking activity (Fig. 6L). Data information: Sleep
 phenotypes (Total sleep during ZT0-ZT12 and Total sleep during ZT12-ZT24)
 caused by inhibiting the *R69F08-Gal4* marked cells (A) and the
 *EB1-Gal4* marked cells (B). (E-G) Sleep phenotypes caused by activating
 the *R69F08-Gal4* and EB1-Gal4 marked cells. Protocol for sleep
 phenotypes: after being maintained at 21℃ for 1 day, flies were treated by
 heat pulse for 12 hr at night at 29℃ until the end of the night and then
 restored to 21℃ for 1 day. (E) Calculation of the sleep amount (Sleep
 amount during ZT12-ZT24) during dTrpA1 activation. (F) Calculation of the
 sleep amount (Sleep amount during ZT12-ZT24; daytime sleep at 21℃) after
 dTrpA1 activation. (G) Calculation of the sleep propensity in five minutes
 after light on. Sleep propensity value, defined as the percentage of flies
 initiating sleep within five minutes after lights-off, serves as an
 indicator of relative sleep pressure. (J-L) Sleep phenotypes caused by
 sleep deprivation and activating the *R69F08-Gal4* or EB1-Gal4 marked
 cells simultaneously. Protocol for sleep deprivation: after being
 maintained at 21℃ for 1 day, flies were simultaneously treated by
 mechanical perturbation and heat pulse for 12 hr at night at 29℃ until the
 end of the night and then continued to 21℃ for 1 day. (J) Calculation of
 the sleep amount 24 hours after sleep deprivation and dTrpA1
 activation. (K) Calculation of the sleep propensity in five minutes after
 light off. Sleep propensity value, defined as the percentage of flies
 initiating sleep within five minutes after lights-off, serves as an
 indicator of relative sleep pressure. (L) Calculation of the
 waking activity in 24 hours after being fully aroused. Waking activity was
 measured by examining activity counts in 24 hrs after being fully aroused.
 ZT0-ZT12 and ZT12-ZT24 (ZT denotes Zeitgeber time) indicate light and dark
 periods under LD (Light/Dark), respectively. Total sleep time (minutes)
 across circadian phases. Values indicate the total minutes of sleep
 recorded during the 12-hour light (ZT0-ZT12) and 12-hour dark (ZT12-ZT24)
 periods. ### Source_data_for_fig._7.xlsx Fig. 7 EB1-Gal4 and R69F08-Gal4
 co-expressing cells played important roles in sleep homeostasis
 regulation. Inhibiting EB1+/R69F08+ cells using Kir2.1, TNT or shibire
 resulted in reduced daytime sleep (Fig. 7A-B & D), while activating
 them via *UAS-TrpA1* increased sleep amount (Fig. 7F). In summary,
 modulating the activity of cells expressing *EB1-Gal4* and *R69F08-Gal4*,
 as well as their overlapping populations, elicits distinct sleep-related
 phenotypes. Additionally, there are no significant alterations in sleep
 propensity value (Fig. 7G). To investigate the inhibition and activation
 effects of these cell clusters under conditions of sleep deprivation, we
 assessed the parameters of sleep homeostasis following interventions
 targeting cell inhibition and activation associated with sleep
 deprivation. Inhibiting *EB1-Gal4* and *R69F08-Gal4* expressing cells led
 to disrupted sleep recovery following mechanical sleep deprivation.
 Inhibition of EB1+/R69F08+ cells by overexpressing kir2.1 or shibire
 significantly reduced sleep recovery and sleep propensity (Fig. 7I-J &
 7L-M). Activating EB1+/R69F08+ cells by overexpressing TrpA1 resulted in
 significantly increased sleep recovery and sleep propensity (Fig. 7O-P).
 These results suggest that activation of *R69F08-Gal4* or
 *EB1-Gal4* marked cells increases sleep pressure. Additionally, these
 findings imply that *EB1-Gal4* and *R69F08-Gal4* marked cells, along with
 EB1+/R69F08+ cells, are necessary for maintaining normal homeostasis. Data
 information: (A-B) Sleep phenotypes caused by inhibiting the
 *EB1-Gal4* and *R69F08-lexA* co-expressing cells. (D) Sleep profile for
 inhibition of the *EB1-Gal4* and* R69F08-lexA* co-expressing cells at
 29℃. Total sleep during the 24-hr inhibition. (F-G) Sleep profile during
 nighttime activation of *EB1-Gal4* and *R69F08-LexA* co-expressing neurons
 at 29℃. (F) Calculation of the sleep amount during TrpA1 activation. (G)
 Calculation of the sleep propensity in five minutes after light on. Sleep
 propensity value, defined as the percentage of flies initiating sleep
 within five minutes after lights-off, serves as an indicator of relative
 sleep pressure. (I-J) Sleep phenotypes caused by mechanical perturbation
 for 12 hr at night until the end of the night. (I) Calculation of Sleep
 recovery  during ZT0-ZT12 after sleep deprivation. (J) Calculation of the
 sleep propensity in five minutes after light off. Sleep propensity value,
 defined as the percentage of flies initiating sleep within five minutes
 after lights-off, serves as an indicator of relative sleep
 pressure. (L-M) Protocol for sleep deprivation: after being maintained at
 21℃ for 1 day, flies were simultaneously treated by mechanical
 perturbation and heat pulse for 12 hr at night at 29℃ until the end of the
 night and then continued to 29℃ for 1 day. (L) Calculation of Sleep
 recovery during ZT0-ZT12 after sleep deprivation. (M) Calculation of the
 sleep propensity in five minutes after light off. (O-P) Protocol for sleep
 deprivation: after being maintained at 21℃ for 1 day, flies were
 simultaneously treated by mechanical perturbation and heat pulse for 12 hr
 at night at 29℃ until the end of the night and then continued to 29℃ for 1
 day. (O) Calculation of the sleep amount sleep amount during ZT0-ZT24
 after dTrpA1 activation. (P) Calculation of the sleep propensity in five
 minutes after light off. ZT0-ZT12 and ZT12-ZT24 (ZT denotes Zeitgeber
 time) indicate light and dark periods under LD (Light/Dark),
 respectively. Total sleep time (minutes) across circadian phases. Values
 indicate the total minutes of sleep recorded during the 12-hour light
 (ZT0-ZT12) and 12-hour dark (ZT12-ZT24) periods. ###
 Source_data_for_fig._8.xlsx Fig. 8 EB1-Gal4 and R69F08-Gal4 expressing
 cells played an important role in sleep homeostasis regulation. To
 investigate the inhibition effects of these cell clusters under conditions
 of sleep deprivation, we assessed the parameters of sleep homeostasis
 following interventions targeting cell inhibition associated with sleep
 deprivation. Inhibiting *EB1-Gal4* expressing cells led to disrupted sleep
 recovery following mechanical sleep deprivation (Fig. 8C-D). Data
 information: (C-D) Sleep recovery during the 12hr following sleep
 deprivation for *EB1-Gal4&gt;UAS-inactive-TNT* and
 *EB1-Gal4&gt;UAS-strong-TNT*. (C) Sleep recovery quantified as a
 percentage (%). Sleep recovery (%) was calculated by (day time increase of
 total sleep amount) / (night time decrease of total sleep amount).
 (D) Sleep recovery measured in absolute minutes (min). Sleep recovery
 (min) was calculated by (daytime sleep amount after sleep deprivation -
 baseline daytime sleep amount before sleep deprivation). ZT0-ZT12 (ZT
 denotes Zeitgeber time) indicate light period.   ###
 Source_data_for_Fig._9.xlsx Fig. 9 Analysis of the Pc target gene profiles
 identified by RNAseq and TaDa. We identified Pc binding profiles in the
 *EB1-Gal4* and *R69F08-Gal4* expressing cells by using the Tada assay.
 TaDa is based on DamID, a technology designed to detect genome-wide
 binding sites of proteins in vivo. When coupled with the Gal4 system in
 *Drosophila*, TaDa achieves both temporal and spatial resolution. KEGG
 enrichment analysis revealed that this group of genes was enriched in
 multiple pathways (Fig. 9F). To identify Pc-regulated targets in cells
 expressing *EB1-Gal4* and *R69F08-Gal4*, we conducted RNA sequencing on
 head tissues with specific *Pc* knockdown mediated by *EB1-Gal4* and
 *R69F08-Gal4*. KEGG enrichment analysis unveiled that this gene set is
 enriched in multiple pathways (Fig. 9G). In summary, our multi-omics
 approach defines Pc’s genomic targets in sleep-regulatory cells,
 implicating transcriptional and signaling networks in sleep homeostasis.
 Data information: (F-G) The genes of Pc identified by RNAseq and TaDa were
 assigned to functional classes on the basis of the KEGG
 annotation. (F) KEGG enrichment analysis of the chimeras-defined targets
 of Pc identified by TaDa in the *EB1-Gal4* or *R69F08-Gal4* marked
 cells. (G) KEGG enrichment analysis of the regulated targets of Pc
 identified by RNAseq in the *EB1-Gal4* or *R69F08-Gal4* marked cells. ###
 Source_data_for_fig._10.xlsx Fig. 10 GO enrichment analysis of the Pc
 target gene profiles identified by RNAseq and TaDa. To characterize the
 features of Pc's direct targets in the
 *EB1-Gal4* and *R69F08-Gal4* marked cells, we conducted combined TaDa and
 RNA-seq analyses.The Pc targets* *identified were assigned to functional
 classes on the basis of the GO annotation (Fig. 10A-D). GO Enrichment
 analysis of the Pc targets identified by TaDa in the EB1-Gal4* and
 *R69F08-Gal4* marked cells respectively (Fig. 10A). GO Enrichment analysis
 of the Pc targets *identified by RNAseq in EB1-Gal4* and
 *R69F08-Gal4* marked cells respectively (Fig. 10B). GO Enrichment analysis
 of functional direct targets (Pc *targets* identified by RNAseq and TaDa)
 in the R69F08-Gal4 or *EB1-Gal4* marked cells (Fig. 10C). TaDa is based on
 DAM-ID, a technology designed to detect genome-wide binding sites of
 proteins in vivo. We identified Pc binding profiles using the Tada assay.
 GO Enrichment analysis of the gene profiles found in TaDa data, but not in
 RNA seq data in R69F08-Gal4 or *EB1-Gal4* marked cells (Fig. 10D). Data
 information: (A-D) GO enrichment is measured by p.adjust and GeneRatio in
 this pathway. p.adjust value is the p value corrected by multiple
 hypothesis test, the range of q value is [0,1], the closer it is to zero,
 the more significant the enrichment is. GeneRatio refers to the ratio of
 the number of binding genes or differentially expressed genes in different
 pathways to all annotated total genes. ### Source_data_for_Fig._11.xlsx
 Fig. 11 Functional classifications of Pc target genes enriched in the
 EB1-Gal4 and R69F08-Gal4 marked cells. The targets of Pc identified by
 RNAseq and TaDa are shown by Venn diagrams (Fig. 11A). The distribution of
 common targets of Pc found in both RNAseq and TaDa (TaDa is based on
 DAM-ID, a technology designed to detect genome-wide binding sites of
 proteins in vivo. We identified Pc binding profiles using the Tada assay)
 are shown by Volcano plot (Fig. 11B-C). Panel B and Panel C indicated the
 distribution of Pc targets in *R69F08-Gal4* marked cells (Fig. 11B) and
 *EB1-Gal4* marked cells (Fig. 11C). KEGG Enrichment analysis of functional
 direct targets (Pc *targets*  identified by both RNAseq and TaDa) in the
 R69F08-Gal4 or *EB1-Gal4* marked cells (Fig. 11D). KEGG Enrichment
 analysis of the gene profiles found in TaDa data, but not in RNA seq data
 in the R69F08-Gal4 or *EB1-Gal4* marked cells (Fig. 11E). Data
 information: Log2FC represents the logarithm of the difference multiple of
 the expression level of a gene in two samples. FDR (False Discovery Rate)
 is a statistically adjusted value following multiple testing corrections.
 It indicates the expected proportion of false positives (false
 discoveries) among all genes identified as differentially expressed. A
 smaller FDR value suggests higher reliability of the result. The use of
 -log10(FDR) is intended to represent small, significant FDR values,
 thereby more intuitively showing the significance level of gene
 differential expression: the higher the Log2FC value, the more significant
 the gene's differential expression. This study used significance
 threshold is FDR &lt; 0.05 (B-C). KEGG enrichment is measured by p.adjust
 and GeneRatio in this pathway. p.adjust value is the p value corrected by
 multiple hypothesis test, the range of q value is [0,1], the closer it is
 to zero, the more significant the enrichment is. GeneRatio refers to the
 ratio of the number of binding genes or differentially expressed genes in
 different pathways to all annotated total genes (D-E). ###
 Source_data_for_fig._12.xlsx Fig. 12 Enrichment analysis of Pc target
 genes in glial and neurons. Enrichment analysis of Pc targets expressed in
 either glia or neurons revealed their distribution among different
 pathways (Fig. 12C-E). These findings position Pc as a pan-cellular
 epigenetic regulator, with targets spanning neural and glial functions in
 sleep circuitry. KEGG Enrichment analysis of Pc targets exhibiting
 expression in glia cells (Pc *targets* identified by both RNAseq or
 TaDa) (Fig. 12C). KEGG Enrichment analysis of Pc targets exhibiting
 expression in neurons (Fig. 12D). KEGG Enrichment analysis of Pc targets
 exhibiting expression in both glia and neurons (Fig. 12E). Data
 information: (C-E) KEGG enrichment is measured by p.adjust and GeneRatio
 in this pathway. p.adjust value is the p value corrected by multiple
 hypothesis test, the range of q value is [0,1], the closer it is to zero,
 the more significant the enrichment is. GeneRatio refers to the ratio of
 the number of binding genes or differentially expressed genes in different
 pathways to all annotated total genes. ### Source_data_for_fig._13.xlsx
 Fig. 13 Heightened sensitivity of Pc target gene expression to sleep
 deprivation upon Pc knockdown. Quantitative RT-PCR analysis of Pc targets
 in control and treatment groups. Replicate # indicates biological
 replicates, with each replicate comprising &gt; 25 individual fly
 heads. Sleep dep indicates Sleep deprivation (Fig. 13A’-H’). ###
 Source_data_for_fig._14.xlsx Fig. 14 Pc target genes that are involved in
 neurotransmission are required for sleep homeostasis regulation in
 EB1-Gal4 and R69F08-Gal4 expressing cells. Sleep Recovery at ZT0-ZT12
 (%) phenotypes after sleep deprivation when the genes involved in
 neurotransmission are knocked down using *EB1-Gal4* and
 *R69F08-Gal4* respectively (Fig. 14A). Sleep recovery at ZT0-ZT12 (min)
 phenotypes after sleep deprivation when the genes involved in
 neurotransmission are knocked down using *EB1-Gal4* and
 *R69F08-Gal4* respectively (Fig. 14B). Sleep amount (ZT0-ZT24) when the
 genes involved in neurotransmission are knocked down using *EB1-Gal4* and
 *R69F08-Gal4* respectively (Fig. 14C). ZT0-ZT12 and ZT12-ZT24 (ZT denotes
 Zeitgeber time) indicate light and dark periods under LD (Light/Dark),
 respectively. Data information: For sleep deprivation experiments at 25°C,
 sleep measurement was performed at 25°C until the end of the experiment.
 Baseline sleep was measured for 2 days prior to sleep deprivation. Sleep
 deprivation was achieved by loading flies in DAMs monitors into the shaker
 fitted with a custom base. Flies were vortexed from ZT12 (Zeitgeber time
 12: beginning of the dark phase) to ZT24 (Zeitgeber time 24: beginning of
 the light phase) at the lower intensity setting for 3 sec/min. Zeitgeber
 time is used to indicate the phase of the circadian rhythm in relation to
 a specific Zeitgeber. The 24-hour cycle is divided into 24 Zeitgeber
 times, where ZT0 represents the start of the light phase, and ZT12
 corresponds to the start of the dark phase. The day time increase of total
 sleep amount (min) after sleep deprivation was calculated by subtracting
 the baseline daytime sleep amount of each repeat from the corresponding
 daytime sleep amount after the sleep deprivation. The night time decrease
 of total sleep amount (min) after sleep deprivation was calculated by
 subtracting the baseline night time sleep amount of each repeat by the
 corresponding night time sleep amount after the sleep deprivation. Sleep
 recovery (%) was calculated by (day time increase of total sleep amount) /
 (night time decrease of total sleep amount) (A). Sleep recovery (min) was
 calculated by (daytime sleep amount after sleep deprivation - baseline
 daytime sleep amount before sleep deprivation) (B).  ###
 Source_data_for_fig._15.xlsx Fig. 15 Gene intersection size of the Pc
 targets identified by TaDa and ChIP. Gene intersection size of Pc targets
 identified by RNAseq and TaDa (TaDa is based on DAM-ID, a technology
 designed to detect genome-wide binding sites of proteins in vivo. We
 identified Pc binding profiles using the Tada assay) in *EB1-Gal4* and
 *R69F08-Gal4* marked cells comparing with ChIPseq data, which was reported
 in the Schwartz et al., 2006. ChIP (Chromatin Immunoprecipitation) is an
 experimental method used to study protein-DNA interactions.  ###
 Source_data_for_fig._S1.xlsx Fig. S1 Effect of Pc knockdown on the
 survival of EB1-Gal4 and R69F08-Gal4 expressing cells.
 *EB1-Gal4* expressing cells after induce the Pc RNAi in the same condition
 with control group in 3-5-day-old flies. Cells expressing RFP denote red
 fluorescent protein. The calculation of *EB1-Gal4* expressing cells number
 (The number of EB neurons) (Fig. S1G). *R69F08-Gal4* expressing cells
 after induce the Pc RNAi in the same condition with control group by
 imaging. Cells expressing RFP denote red fluorescent protein. The
 calculation of *R69F08-Gal4* expressing cells number (The number of EB
 neurons) (Fig. S1K). Figures are stored in Zenodo at
 [https://doi.org/10.5281/zenodo.17038126](https://doi.org/10.5281/zenodo.17038126) ## Code/software No original code was produced; the software used is described in the Methods section above. ## Access information Other publicly accessible locations of the data: * No Data was derived from the following sources: * No