News Article | May 3, 2017
JUPITER, Fla.--(BUSINESS WIRE)--Dr. Mark Little, General Electric’s former chief technology officer and leader of GE Global Research, has joined the board of directors of Powerphase, maker of patented upgrades that improve the fuel efficiency and output of combustion turbines. Dr. Little accompanies Bob McGrath, former EVP Nextera Energy, as the second independent director appointed to the Powerphase board of Directors. During his tenure at GE, Dr. Little led one of the world’s largest and most diversified industrial research and technology organizations in the world that developed core technologies to help GE succeed in all of its core businesses, including energy, oil & gas and aviation. During his 37 year tenure at GE, he also served as Vice President of GE Energy power-generation, and several engineering and management positions in their turbine business, as well as in business development in their energy sector. Powerphase was started in 2012 by Bob Kraft who previously founded PSM, a combustion turbine parts manufacturer that was sold to Alstom in 2007 for $241 Million. “Dr. Little brings a tremendous global strategic market and technical background to Powerphase which will help us continue to expand our reach to customers around the world,” said Kraft. To that end, Powerphase recently announced the signing of an MoU to bring 2 GW of additional power to Indonesia. Powerphase has more than 100 patents pending globally around its dry-air injection technology for combustion turbines, called Turbophase®. “The Turbophase® dry air injection system offers customers a host of valuable benefits safely and quickly with just air,” said Dr. Little. “By generating hot-compressed air more efficiently than the turbine itself, the Turbophase system improves the efficiency of the combustion turbine. At the same time, Turbophase® offers tremendous power and generation flexibility at speeds that support grid efficiency improvements and renewable integration and can be offered at attractive terms to the customer.” Dr. Little continued, “I am excited to join the Powerphase board and bring my global experience to bear on this innovative company to help the Company accelerate globally with its heavily patent protected existing and new insurgent technology offerings.” Powerphase is a global leader in combustion turbine technologies with more than 100 patents pending globally. By focusing on combustion turbine air efficiency, Powerphase has been able to unlock previously untapped potential from combustion turbine power plants, cost-effectively improving output, fuel efficiency, flexibility and performance. Powerphase is based in the United States of America with global headquarters in Jupiter, Florida USA which is the sailfish capital of the world, and regional offices in Denver, Colorado, USA and Dubai, United Arab Emirates and Singapore.
News Article | May 15, 2017
CHARLESTON, S.C., May 15, 2017 /PRNewswire/ -- In January 2017, a joint announcement was made by Cindy Hollar, CEO of TE21 and Jamie Candee, CEO of Questar offering the CASE Benchmark Assessments on the Nextera Platform for the 2017-18 school year. After a year of joint planning, TE21 and Questar have decided to delay the partnership at this time due to multiple competing priorities and unforeseen events. We continue to believe that the experience of using CASE Benchmark Assessments on the Nextera Platform is in the best interest of students in Mississippi and hope to reinitiate our partnership in the future. Cindy Hollar, a Mississippi native and CEO of TE21 stated, "We felt offering benchmarks to the state of Mississippi in the Nextera Platform for their end-of-year testing would be ideal. However, after agreeing to delay the partnership with Questar, we are confident in our ability to serve our clients with our new proprietary platform, enCASE, as well as our proven and tested current partners MasteryConnect and I/O Education/EADMS."
News Article | May 17, 2017
Previously published KrasLSL-G12D (ref. 28), Trp53flox/flox (ref. 29), KrasFSF-G12D (ref. 30), Trp53frt/frt (ref. 31), Rosa26LSL-tdTomato (ref. 32), Apcflox/flox (ref. 33), Rosa26LSL-luciferase (ref. 34), Rosa26mTmG (ref. 35), Lgr5GFP-IRES-CreER/+ (ref. 36) and Lgr5CreER/+ (ref. 8) gene-targeted mice were used in the study. All mice were maintained in a mixed Sv129/C57BL/6 genetic background. Tumours were induced in KP mice with 2.5 × 107 plaque-forming units (PFU) of AdCMV-Cre (Iowa), 2 × 108 PFU of AdSPC-Cre23, 37, 1 × 108 PFU of AdCMV-FlpO (Iowa) or 15–50,000 transforming units of lentiviral Cre, as previously described38, 39, in mice that were between 8–12 weeks of age. Approximately equal numbers of male and female mice were included in all experimental groups in all mouse experiments. Mice bearing lung tumours were treated with 10 mg per kg per day of LGK974 (ref. 20) resuspended in 0.5% carboxymethylcellulose (Sigma-Aldrich) and 0.5% Tween 80 (Sigma-Aldrich) or vehicle (0.5% carboxymethylcellulose and 0.5% Tween 80 only). Weights of mice were followed weekly. The growth of autochthonous KrasG12D/+;Trp53Δ/Δ;Rosa26Luciferase/+ lung tumours was followed longitudinally by bioluminescence imaging, as previously described34. In brief, mice were anaesthetized by isoflurane inhalation, administered 100 mg kg−1 d-luciferin (Perkin Elmer) by intraperitoneal injection and imaged after 10 min, using the IVIS imaging system (Perkin Elmer). Such longitudinal imaging experiments were repeated three times and representative data from one such experiment is shown in Fig. 4a. Survival experiments were repeated three times and representative data from one such experiment is shown in Fig. 4b. For survival experiments, mice were randomized based on their tumour burden as assessed by μCT. Mice were assigned a tumour burden score ranging from 0 (no tumours) to 10 (lungs completely full of tumours), and experimental groups were formed such that each group had approximately equal average tumour burdens. Mice with tumour burden scores under 3 were excluded from the study. The health of the mice in all experiments was monitored daily by the investigators and/or veterinary staff at the Department of Comparative Medicine at Massachusetts Institute of Technology. Mice with a body condition score under 2 were humanely euthanized. Animal studies were approved by the Massachusetts Institute of Technology (MIT) Committee for Animal Care (institutional animal welfare assurance no. A-3125-01). The maximal tumour dimensions permitted by the MIT Committee for Animal Care were 2 cm across the largest tumour diameter and this limit was not reached in any of the experiments. Mice bearing KrasG12D/+;Trp53Δ/Δ;Rosa26tdTomato/+ (KPT) or KrasG12D/+;Trp53Δ/Δ;Rosa26tdTomato/+;Lgr5GFP-CreER/+(KPT;Lgr5GFP-CreER/+) LUAD tumours were euthanized 12–26 weeks after tumour induction and perfused with S-MEM (Gibco) through the right ventricle of the heart. Dissected lungs with tumours were dissociated in protease and DNase solution of the Lung Dissociation kit (Miltenyi Biotech) followed by mechanical dissociation using MACS C columns (Miltenyi Biotech) according to the manufacturer’s instructions. The dissociated cells were filtered using a 100-μm strainer and red blood cells were lysed using ACK (Thermo Scientific), followed by staining with APC-conjugated CD31 (Biolegend, 102510), CD45 (BD, 559864), CD11b (eBioscience, 17-0112-82) and TER119 (BD, 557909) antibodies and dead cells with DAPI (Sigma-Aldrich). The same approach using the Tumour Dissociation kit (Miltenyi Biotech) was used to isolate KPT;Lgr5GFP-CreER/+;Pdx1::Cre PDAC tumours cells when mice were 7 weeks of age. Fluorescence-activated cell sorting (FACS) of stained primary cells was performed using a FACSAria sorter (BD) by gating for tdTomato+/DAPI−/APC− cells (total cancer cell fraction) for KPT tumours. For KPT;Lgr5GFP-CreER/+ tumours, both tdTomato+/DAPI−/APC−/GFP+ (Lgr5+ cancer cell fraction) and tdTomato+/DAPI−/APC−/GFP− (Lgr5− cancer cell fraction) populations were sorted. Sorted cells were placed in 3D organotypic culture, transplanted intratracheally into NOD/SCID-γ (NSG) recipient mice, or subcutaneously into athymic nu/nu mice immediately after sorting (see below). For intratracheal transplantation, 8–10-weeks-old immunodeficient NSG mice were anaesthetized, intubated as previously described38, and allowed to inhale 15–50,000 sorted primary KP LUAD cancer cells resuspended in 30 μl of S-MEM (Gibco). For subcutaneous transplantation, 50–500,000 sorted primary KP LUAD cells, KP LUAD cell lines or single-cell clones derived from a KP;Lgr5GFP-CreER/+ LUAD cell line were resuspended in 50% Matrigel/50% S-MEM and injected subcutaneously into both flanks of athymic nu/nu mice in a volume of 100 μl. Mice with transplant tumours were injected intraperitoneally with 1 mg of 5-ethynyl-2-deoxyuridine (EdU, Setareh Biotech) 4 h before euthanasia to label proliferating cells. EdU was detected in cryosections using the Click-iT EdU Alexa Fluor 488 Imaging kit (Thermo Scientific) according to the manufacturer’s protocol. Lgr5+ cells in close proximity to porcupine were detected by GFP and porcupine immunofluorescence. All GFP+ cells were analysed as being immediately adjacent to at least one porcupine+ cell, as double-positive for both GFP and porcupine, or as neither of the above (Fig. 3a). All transplantation experiments were reproduced three times. 150–1,000 primary mouse KP LUAD cells, cells from established KP LUAD cell lines, or primary mouse PDAC cells were mixed in 50% Matrigel (BD) and 50% advanced DMEM/F12 (Gibco) and plated on 10 μl of Matrigel. The gel was allowed to solidify at 37 C, followed by addition of advanced DMEM/F12 (Thermo Scientific) supplemented with gentamicin (Thermo Scientific), penicillin–streptomycin (VWR), 10 mm HEPES (Thermo Scientific) and 2% heat-inactivated fetal bovine serum. For Wnt pathway manipulation, cultures were incubated with 1 μg ml−1 recombinant mouse (rm)R-spondin 1 (Sino Biological), 100 ng ml−1 rmWnt3a (R&D Sytstems), 500 ng ml−1 or 1 μg ml−1 rmDKK1 (R&D Systems) or 100 nM LGK974 (Medchem Express) for 6–14 days. Medium was changed every two days. At the end of the experiment, proliferating cells were labelled with 10 μM EdU for 4 h, followed by paraformaldehyde fixation and fluorescent labelling of proliferating cells using the Click-iT EdU Alexa Fluor 488 Imaging kit (Thermo Scientific), according to the manufacturer’s protocol, in whole-mount preparations of tumour spheroids. Proliferating spheroids were quantified using a Nikon Eclipse 80i microscope: a spheroid was classified as a cluster of at least 10 cells, and a proliferating spheroid contained at least one EdU positive nucleus (proliferating cells were not observed in clusters of cells smaller than 10 cells). At least four replicate wells per condition were quantified in each experiment. Images were acquired using a Nikon A1R confocal microscope. Stimulation and inhibitor experiments were reproduced at least 10 times for each experimental condition. Multiple cell lines were established from the mouse LUAD and PDAC KP GEMMs over the course of the study. The cell lines have not been authenticated. The cell lines were routinely tested for mycoplasma and found to be negative. At the time of conducting the experiments, no cell lines used were found to be listed in the ICLAC database of misidentified cell lines. Tissues or tumour organoids were fixed in 10% formalin overnight and embedded in paraffin. Immunohistochemistry (IHC) was performed on a Thermo Autostainer 360 with or without haematoxylin counterstaining using antibodies against β-catenin (BD, 610153), Ki67 (Vector Labs, VP-RM04), glutamine synthetase (BD, 610517), or porcupine (Abcam, ab105543). Lungs from at least three tumour-bearing mice were analysed for each antibody. Livers and small intestines collected from three normal, healthy mice were used for β-catenin, glutamine synthetase and porcupine IHC. 65 human LUAD tumours samples in two separate tissue microarrays were analysed by IHC for β-catenin and porcupine. 5 human colorectal adenocarcinoma samples were stained with porcupine antibodies. All human tissue material was obtained commercially from Janssen Pharmaceuticals. Mice were anaesthetized and perfused through the right cardiac ventricle with 1% paraformaldehyde. Lungs with tumours were dissected, immersed in 4% PFA overnight and frozen in OCT medium (Sakura Finetek). 7 μm sections were stained with antibodies to EpCAM (eBioscience, 17-5791-82), β-catenin (BD, 610153), GFP (Cell Signaling Technologies, 2956S; or Aves Labs, GFP-1020), CD11b (eBioscience, 17-0112-82) or porcupine (Abcam, ab105543). Lungs from at least three tumour-bearing mice were analysed for each antibody. Digitally scanned images of Ki67-stained slides were created with the Aperio ScanScope AT2 at 20× magnification. Aperio’s WebScope software was used to assess Ki67+ density per tumour area. A built-in IHC nuclear image analysis algorithm was used to classify cells on the basis of the intensity of the nuclear Ki67 stain. Nuclei were classified from 0 to 3+; only nuclei with moderate nuclear staining (2+) or intense nuclear staining (3+) were considered Ki67+. Tumour regions were outlined on WebScope before running the IHC nuclear image analysis algorithm such that the number of 2+ and 3+ cells was normalized to tumour area. Total RNA was isolated from tumours or cells using the RNeasy plus kit (Qiagen) according to the manufacturer’s instructions. cDNA was synthesized from 1 μg of RNA using the SuperScript VILO cDNA synthesis kit (Thermo Scientific). qPCR was performed in triplicates with 2 μl of diluted cDNA (1:10) using PerfeCTa SYBR Green FastMix (Thermo Scientific) on a Bio-Rad iCycler RT–PCR detection system. Expression was normalized to Actb or Gapdh. All oligonucleotides used in this study are listed in Supplementary Table 4. All qPCR experiments were reproduced using at least three biological replicates. Alternatively, a Mouse WNT Signalling Pathway RT2 Profiler PCR Array (Qiagen) was used according to the manufacturer’s instructions. Raw expression values were thresholded to remove genes that were not detected or had low expression (maximum C value set to 33; 0 values set to 33). Array position to gene-name mapping details were retrieved from the manufacturer’s website (www.pcrdataanalysis.sabiosciences.com). Expression values for all genes per array were normalized to the expression of the housekeeping gene Gusb. Three replicates of stroma samples and three replicates of tumour samples were compared to calculate log fold change and differential expression significance values (two-sided t-test). shRNAs were cloned into lentiviral pLKO.1 vectors (Addgene, 10878) or into pTRIPZ (Dharmacon) vectors and lentivirus was produced as previously described40. KP mouse LUAD cell lines were infected with the lentiviral vectors, followed by puromycin selection and, in the case of cells infected with the TRIPZ virus, incubation in 1 μg ml−1 doxycycline for four days and RNA extraction for testing target knockdown (Extended Data Fig. 2a and not shown). For combined Lgr4 and Lgr5 silencing experiments, cell lines expressing pLKO.1 driving Lgr4 or Lgr5 shRNAs were generated by puromycin selection, followed by infection with TRIPZ vectors driving miR30-based Lgr4 or Lgr5 shRNAs and turboRFP under the control of a TET-responsive promoter. Cells were incubated in 1 μg ml−1 doxycycline for two days and red fluorescent cells were sorted to generate pure cell lines expressing combinations of Lgr4 and Lgr5 shRNAs. All shRNA experiments were reproduced using at least three independent cell lines. 10,000 of KP LUAD cells were plated in 100 μl of medium containing 10% FBS per well of a white-walled 96-well plate (Perkin Elmer). After 24 h, mouse KP LUAD cells were transfected using Attractene transfection reagent (Qiagen) according to the manufacturer’s instructions with 150 ng of the TOPFLASH Firefly (M50) reporter41 (Addgene, 12456) and 20 ng of pRL-SV40P Renilla (Addgene, 27163) constructs. In initial experiments, the Wnt-insensitive FOPFLASH (negative control) Firefly (M51) reporter41 (Addgene, 12457) was used to rule out signal background (not shown). Cells were stimulated for 16 h with recombinant Rspo1 (1 μg ml−1, Sino Biological), recombinant Wnt3a (100 ng ml−1, R&D Systems) or their combination (RW) in advanced DMEM/F12 (Gibco), with supplements listed above. After stimulation, Firefly and Renilla signals were detected using Dual-Glo luciferase detection reagents (Promega) according to the manufacturer’s instructions. A Tecan Infiniti 200 Pro plate reader and automated injector system was used to detect luminescence. To control for transfection efficiency, Firefly luciferase levels were normalized to Renilla luciferase levels to generate a measurement of relative luciferase units. Experimental data are presented as mean ± s.d. from three independent wells. All TOPFLASH experiments were reproduced using at least three independent cell lines. Catalytically dead Cas9 (dCas9)-based systems have recently emerged as powerful tools for transcriptionally activating endogenous genes42. Notably, these systems allow for overexpression of genes in their endogenous genomic context. To overexpress Rspo2, Rspo3 or Lgr5 in KrasG12D/+;Trp53Δ/Δ LUAD cell lines, we used the SAM system, which is a three-component system based on: (1) the fusion of dCas9 to the transcriptional activator VP64 (a tandem repeat of four DALDDFDLDML sequences from Herpes simplex viral protein 16, VP16); (2) a modified gRNA scaffold containing two MS2 RNA aptamers; and (3) the MS2–p65–HSF1 tripartite synthetic transcriptional activator21. In this system, sgRNA-dependent recruitment of dCas9–VP64 and MS2–P65–HSF1 to the endogenous Rspo2, Rspo3 or Lgr5 loci results in potent transcriptional activation (Extended Data Fig. 1i–l). Non-clonal KrasG12D/+;Trp53Δ/Δ;Rosa26tdTomato/+ or KrasG12D/+;Trp53Δ/Δ;Lgr5GFP-CreER/+ LUAD cells stably expressing dCas9–VP64–blast (Addgene, 61425) and MS2–P65–HSF1–hygro (Addgene, 61426) were generated using sequential lentiviral transduction and selection with blasticidin and hygromycin, respectively. To overexpress Rspo2 or Rspo3 we designed four independent sgRNA sequences targeting the Rspo2 or Rspo3 transcription start site; sgRNAs targeting the upstream region of the Lgr5 gene were provided by L. Gilbert, M. Horlbeck and J. Weissman43. The sgRNAs were cloned into a lentiviral vector (Lenti-sgRNA-MS2-zeocin; Addgene, 61427) followed by transduction and zeocin selection of the aforementioned cell lines to generate KrasG12D/+;Trp53Δ/Δ;Lgr5GFP-CreER/+ LUAD cell lines stably expressing all three components. These experiments were reproduced using three independent cell lines. The 7TCF::luciferase-PGK::Cre, 7TCF::GFP-PGK-Cre and U6::sgRNA-EFS::Cre (pUSEC) lentivirus vectors were generated by Gibson assembly44, 45. In brief, a 1.8-kb part corresponding to 7TCF::luciferase or a 1.2-kb part corresponding to 7TCF::GFP were amplified from 7TFP (Addgene, 24308, ref. 46) or 7TGP (Addgene, 24305, ref. 46) respectively, and fused with a 0.5-kb PGK promoter part, a 1.0-kb Cre cDNA part and the PmeI and BsrGI linearized LV1-5 (Addgene, 68411) part44. U6::sgRNA-EFS::Cre was generated by amplifying a 2.2-kb part corresponding to the U6-filler-chimeric gRNA backbone from pSECC (Addgene, 60820), and fused with a 0.25-kb EFS promoter part, a 1.0-kb Cre cDNA part and the PmeI and BsrGI linearized LV1-5 (Addgene, 68411) part44. Lentivirus was produced in 293FS* cells, as previously described38. Experiments using 7TCF::luciferase-PGK::Cre (Fig. 2a) were performed twice (n = 15 mice in total) and experiments using 7TCF::GFP-PGK-Cre (Fig. 2b) three times (n = 19 mice in total). For generation of lentiviruses containing sgRNAs, three sgRNAs per gene targeting Porcn, Lgr4 or Lgr5 were designed using CRISPR Design47, cloned into pSpCas9(BB)-2A-GFP (pX458, Addgene, 48138) as previously described48, transfected into KP cells49, and screened for efficiency by western blotting for porcupine protein or by massively parallel sequencing of the regions in Lgr4 or Lgr5 targeted by the respective sgRNAs (data not shown). The most efficient Porcn sgRNA was cloned into pSECC as previously described49. The most efficient Lgr4 and Lgr5 sgRNAs were cloned into the pUSEC vector together with a synthetic mouse/human U6 promoter (sU6), as previously described50, to generate U6::sgLgr4-sU6::Lgr5-EFS::Cre (pU2SEC). A KPT LUAD cell line was transduced with 7TCF::luciferase-PGK::Puro (7TFP) lentiviruses46, selected for puromycin resistance, and transplanted subcutaneously into flanks of immunodeficient athymic nu/nu mice. Three weeks after transplantation, tumour burden was measured by registering tdTomato fluorescence using an IVIS imaging system (Perkin Elmer), followed by administration of 100 mg kg−1 d-Luciferin (Perkin Elmer) and detection of the luciferase signal (7TCF promoter activity). The luciferase signal was normalized to the tdTomato signal (Wnt pathway activity/total tumour burden). Quantification of Wnt pathway activity was performed every 24 h for a week in mice treated with 10 mg per kg per day of LGK974 or vehicle. The maximal tumour dimensions permitted by the MIT IACUC were 2 cm across the largest tumour diameter and this limit was not reached in these experiments. This experiment was performed twice. Single-molecule in situ hybridization was performed on formalin-fixed paraffin-embedded tissues using the Advanced Cell Diagnostics RNAscope 2.5 HD Detection kit (322360). Catalogue numbers of the probes are 400331 (Axin2), 318321 (Lgr4), 312171 (Lgr5) and 404971 (Porcn), 401991 (Rspo1), 316791 (Wnt5a), 401121 (Wnt7a) and 401131 (Wnt7b). Lungs from three tumour-bearing mice were analysed. We generated KrasFSF-G12D/+;Trp53frt/frt;Lgr5CreER/+;Rosa26mTmG/+ mice and induced lung tumours by intratracheal administration of AdCMV-FlpO. Lung tumours were collected, enzymatically dissociated and passaged in vitro for 8–10 passages to eradicate stromal cells from the cultures. Such early-passage cell lines were transplanted subcutaneously into flanks of NSG mice. When mice developed palpable tumours, they were administered a single tamoxifen pulse (20 mg kg−1) or corn-oil vehicle control. Tumours were collected at 2 days or 14 days after tamoxifen administration and prepared for cryosectioning. Three sections 500 μm apart were prepared from each tumour and imaged under a fluorescence microscope. The number of GFP+ cells per section was quantified in nine tumours per time point. An eXplore CT 120 microcomputed tomography (μCT) system (Northridge Tri-Modality Imaging Inc.) was used for in vivo imaging. Mice were imaged under anaesthesia (induced at 3% isoflurane in oxygen, maintained at between 2–2.5% during imaging) in groups of 4 in a custom mouse holder. Scanner settings were as follows: 720 views, 360° rotation, 70 kVp, 50 mA, 32 ms integration time with 2 × 2 detector pixel binning (isotropic nominal resolution of 50 μm). Data were reconstructed using the Parallax Innovations GPU accelerated reconstruction engine for the eXplore CT120. Tissue density values (in Hounsfield Units (HU)) for normal, air-filled lung parenchyma were determined by eye using MicroView software (Parallax Innovations). For the scanning conditions in this study a range of −550 to −300 HU was determined to represent the range of normal lung parenchyma values. A custom analysis script was created using MATLAB (MathWorks) to identify a region of interest (ROI) including the soft tissue of the mouse thorax. Within this region the volume of tissue within the ‘healthy’ density range was measured. Within this same volume minimum intensity projections (MinP) were created, both to confirm the accuracy of the ROI and to qualitatively assess lung pathology. For data visualization, the change in healthy lung volume was inverted to represent the change in tumour volume (Extended Data Fig. 10b). One experiment involving 9 mice treated with LGK974 and 11 mice treated with vehicle control was carried out to track changes in tumour volume (Extended Data Fig. 10b). RNA-seq gene expression profiles of primary tumours and relevant clinical data of 488 patients with lung adenocarcinoma were obtained from The Cancer Genome Atlas (TCGA LUAD; http://cancergenome.nih.gov/). The previously published Wnt signalling geneset22 (24 genes upregulated after stimulation with recombinant human WNT3A) was obtained from the Molecular Signatures Database (MSigDB)51 and used to score individual patient expression profiles using ssGSEA52, 53. Patients were stratified according to their correlation score, into top (n = 115) and bottom (n = 114) 20th percentile sets. Kaplan–Meier survival analysis was conducted between these sets of patients and the log-rank test was used to assess significance. Subsequently, the Kaplan–Meier survival analysis methodology was extended to assess significant survival differences across 35 TCGA cancer types using a similar strategy. Additionally, the Cox proportional hazards regression model was used to analyse the prognostic value of the published geneset22 across all patients within the TCGA LUAD cohort, in the context of additional clinical covariates. All univariate and multivariable analyses were conducted within a five-year survival timeframe. The following patient and tumour-stage clinical characteristics were used: signature (signature from ref. 22 strong versus weak correlation); gender (male or female); age (years, continuous); smoking history (reformed >15 years versus non-smoker, reformed <15 years versus non-smoker, current smoker versus non-smoker); mutational load (derived as the number of non-silent mutations per 30 Mb of coding sequence, continuous); Union for International Cancer Control (UICC) TNM Stage specification (stage III/IV versus I/II); UICC T score specification (T2 versus T1, T3/T4 versus T1); UICC N score specification (N1/N2 versus N0). Hazard ratio proportionality assumptions for the Cox regression model were validated by testing for all interactions simultaneously (P = 0.703). Interaction between the signature of ref. 22 and TNM stage, T score and N score (significant covariates in the model) were tested using a likelihood ratio test to contrast a model consisting of both covariates with another model consisting of both covariates plus an interaction term. No statistically significant difference was found between the two models (TNM, P = 0.8751; T score, P = 0.8204; N score: P = 0.8625; likelihood ratio test). To test for statistically significant differences between the previously published22 signature correlation scores across TCGA LUAD grade levels (T scores), the Kurskal–Wallis test was used to assess overall significance and the Mann–Whitney–Wilcoxon test was used to assess pairwise differences. All statistical analyses were conducted in R (http://www.R-project.org) and all survival analyses and were conducted using the survival package in R. Finally, we analysed the expression of Wnt pathway genes present in the Mouse WNT Signalling Pathway RT2. Profiler PCR Array (Qiagen) in the human TCGA LUAD data (Supplementary Table 3). Expression levels between 57 LUAD tumour samples and corresponding matched normal samples were analysed using empirical cumulative distribution function plots. Significance of different expression levels was assessed using the Kolmogorov–Smirnov test. For a more comprehensive analysis covering human orthologues of all WNT pathway genes tested on the mouse qPCR array, pairwise differential expression analysis (tumour versus normal, n = 57 each) was performed using EBSeq version 1.4.0 (ref. 54). CRISPR-Cas9-induced mutations were detected as before59. Briefly, genomic regions containing the sgPorcn, sgLgr4 or sgLgr5 target sequences were amplified using Herculase II Fusion DNA polymerase and gel purified (primer sequences are shown in Supplementary Table 4). Sequencing libraries were prepared from 50 ng of PCR product using the Nextera DNA Sample Preparation kit (Illumina) according to the manufacturer’s instructions and sequenced on Illumina MiSeq sequencers to generate 150-bp, paired-end reads. CRISPR-Cas9-mutated loci were computationally analysed as before59. Briefly, illumina MiSeq reads (150 bp paired-end) were trimmed to 120 bp after reviewing base quality profiles, in order to remove lower quality 3′ ends. Traces of Nextera adapters were clipped using the FASTX toolkit (Hannon Laboratory, CSHL) and pairs with each read greater than 15 bp in length were retained. Additionally, read pairs where either read had 50% or more bases below a base quality threshold of Q30 (Sanger) were removed from subsequent analyses. The reference sequence of the target locus was supplemented with 10 bp genomic flanks and was indexed using an enhanced suffix array55. Read ends were anchored in the reference sequence using 10 bp terminal segments for a suffix array index lookup to search for exact matches. A sliding window of unit step size and a maximal soft-clip limit of 10 bp were used to search for possible anchors at either end of each read. For each read, optimal Smith–Waterman dynamic programming alignment56 was performed between the reduced state space of the read sequence and the corresponding reference sequence spanning the maximally distanced anchor locations. Scoring parameters were selected to allow sensitive detection of short and long insertions and deletions while allowing for up to four mismatches and the highest scoring alignment was selected. Read pairs with both reads aligned in the proper orientation were processed to summarize the number of wild-type reads and the location and size of each insertion and deletion event. Overlapping reads within pairs were both required to support the event if they overlapped across the event location. Additionally, mutation events and wild-type reads were summarized within the extents of the sgRNA sequence and PAM site by considering read alignments that had a minimum of 20 bp overlap with this region. Mutation calls were translated to genomic coordinates and subsequently annotated using Annovar57. The alignment and post-processing code was implemented in C++ along with library functions from SeqAn58 and SSW59 and utility functions in Perl and R (http://www.R-project.org). Mutation calls were subjected to manual review using the Integrated Genomics Viewer (IGV)60. Statistical analysis was carried out as indicated in the Figure legends, Extended Data Figure legends and in the Methods for each experiment. The data were found to meet the assumptions of the statistical tests. Variation was estimated for each group of data, the variance was found to be similar between the groups that were compared. No animals were excluded from any of the studies. The investigator was blinded with respect to group assignment for the quantification of 3D spheroids, proliferating (Ki67+) cells and for the analysis of healthy lung volume by μCT. Power calculations were performed to estimate the sample size for experiments involving LGK974 treatment. In brief, to detect a difference of 30% in average survival between the two groups (effect size = 1.2 s.d. of survival based on Cohen’s d (ref. 61) using untreated sample baseline survival from ref. 39) with 90% power, a minimum of five mice per group needed to be used. Massively parallel sequencing data are available in the NCBI/SRA data repository under accession number PRJNA379539. Source code and all other data are available from the authors upon reasonable request.
News Article | May 10, 2017
No statistical methods were used to predetermine sample size. All cells were tested for mycoplasma and included for analysis only upon testing negative. The identity of all cell lines was confirmed by whole-exome sequencing and SNP array analysis. The experiments were not randomized and the investigators were not blinded to allocation during experiments and outcome assessment. As a source of hES cells for this study, we focused on those that had been voluntarily listed by research institutions on the registry of hES cell lines maintained by the US National Institutes of Health (NIH) (http://grants.nih.gov/stem_cells/registry/current.htm). As of 8 July 2015, a total of 307 hES cell lines were listed on this registry. Of these, we requested viable frozen stocks of the 182 lines annotated to be available for distribution and to lack known karyotypic abnormalities or disease-causing mutations. During our effort to obtain these cell lines, we found that 45 were subject to overly restrictive material transfer agreements that precluded their use in our studies and 11 could not be readily obtained as frozen stocks owing to differences in human subjects research regulations between the US and the UK. Nine cell lines were unavailable upon request or were overly difficult to import, and three could not be cultured despite repeated attempts. Further details on the availability of cell lines can be found in Supplementary Table 1. The generation of hES cells used in this study was previously approved by the institutional review boards (IRBs) of all providing institutions. Use of the hES cells for sequencing at Harvard was further approved and determined not to constitute Human Subjects Research by the Committee on the Use of Human Subjects in Research at Harvard University. A protocol for the adaptation of hES cell lines from diverse culture conditions can be found at Protocol Exchange30. In brief, we considered that different laboratories employ different methods to culture hES cells, raising the question of how best to thaw and culture the cell lines we obtained from multiple sources. Traditionally, hES cells are maintained on gelatinized plates and co-cultured with replication-incompetent mouse embryonic fibroblast (MEF) feeder cells in tissue culture medium containing knockout serum replacement (KOSR). More recently, hES cells have been cultured on a substrate of cell-line-derived basal membrane proteins known by the trade names of Matrigel (BD Biosciences) or Geltrex (Life Technologies), in mTeSR1 (ref. 31), E8 (ref. 32) or similar in the absence of feeder cells. In previous work, we found that a medium containing an equal volume of KOSR-based hES cell medium (KSR) and mTeSR1 (STEMCELL Technologies) (KSR–mTeSR1) robustly supports the pluripotency of hES cells undergoing antibiotic selection during the course of gene-targeting experiments under feeder-free conditions33. To minimize stress to hES cells previously cultured and frozen under diverse conditions, cell lines were thawed in the presence of 10 μM Y-27632 (DNSK International) into two wells of a 6-well plate, one of which contained KSR–mTeSR1 on a substrate of Matrigel, and the other containing KOSR-based hES cell medium on a monolayer of irradiated MEFs. After 24 h, Y-27632 was removed and cells were fed daily with the aforementioned media in the absence of any antibiotics. All cultures were tested for the presence of mycoplasma and cultured in a humidified 37 °C tissue culture incubator in the presence of 5% CO and 20% O . Colonies of cells with hES cell morphology and with a diameter of approximately 400 μm were transferred into KSR–mTeSR1 medium containing 10 μM Y-27632 on a substrate of Matrigel by manual picking under a dissecting microscope. Cells with differentiated morphology were removed from plates by aspiration during feeding. Once cultures consisting of cells with homogeneous pluripotent stem cell morphology had been established, they were passaged by brief (2–10 min) incubation in 0.5 mM EDTA in PBS followed by gentle trituration in KSR–mTeSR1 medium containing 10 μM Y-27632 and re-plating. Once cultures had reached approximately 90% confluence in one well of a six-well plate, they were passaged with ETDA onto a Matrigel-coated 10 cm plate. Upon reaching approximately 90% confluence, cell lines were dissociated with EDTA as described above and banked for later use in cryoprotective medium containing 50% KSR–mTeSR1, 10 μM Y-27632, 10% DMSO, and 40% fetal bovine serum (HyClone). A subset of hES cell lines (Supplementary Table 1) were passaged enzymatically with TrypLE Express (Life Technologies), expanded onto two 15 cm plates, and frozen down in 25 cryovials. Cell pellets of approximately 1–5 million cells were generated from banked cryovials of research-grade hES cell lines, or were obtained directly from institutions providing GMP-grade hES cell lines. Cell pellets were digested overnight at 50 °C in 500 μl lysis buffer containing 100 μg ml−1 proteinase K (Roche), 10 mM Tris (pH 8.0), 200 mM NaCl, 5% w/v SDS, 10 mM EDTA, followed by phenol:chloroform precipitation, ethanol washes, and resuspension in 10 mM Tris buffer (pH 8.0). Genomic DNA was then transferred to the Genomics Platform at the Broad Institute of MIT and Harvard for Illumina Nextera library preparation, quality control, and sequencing on the Illumina HiSeq X10 platform. Sequencing reads (150 bp, paired-end) were aligned to the hg19 reference genome using the BWA alignment program. Genotypes from WES data for the cell lines were computed using best practices from GATK software34 compiled on 31 July 2015. Sequencing quality and coverage were analysed using Picard tool metrics. Cross sample contamination was estimated using VerifyBamID (v1.1.2)35, and none was detected. Data from each cell line were independently processed with the HaplotypeCaller walker and further aggregated with the CombineGVCFs and GenotypeGVCFs walkers to generate a combined variant call format (VCF) file. Genotyped sites were finally filtered using the ApplyRecalibration walker. To determine whether lines with or without acquired TP53 mutations showed other chromosomal aberrations or smaller regional changes in copy number, additional genotyping of the 140 hES cell lines was performed using a custom high density SNP array (‘Human Psych array’) that contains more than half a million SNPs across the genome. CNVs larger than 500 kb were identified using the PennCNV (v1.0.0)36 tool (http://penncnv.openbioinformatics.org). All CNVs were manually reviewed and are shown in Supplementary Table 6. To identify candidate mosaic variants, a table of heterozygous variants was generated from the VCF (Supplementary Table 2). To limit the frequency of false positive calls due to sequencing artefacts and PCR errors, variants were included if they had a variant read depth of at least 10, if they were either flagged as a ‘PASS’ site or were not reported in the Exome Aggregation Consortium (ExAC) database11, and if they were not located in regions of the genome with low sequence complexity, common large insertions and segmental duplications, as described by Genovese and colleagues5. Multiallelic sites were split, left-aligned, and normalized. The resulting list of 2.1 million ‘high-quality heterozygous variants’ was further refined to include sites that were covered by at least 60 unique reads and had a high confidence variant score (‘PASS’) as ascertained by GATK’s Variant Quality Score Recalibration software (840,222 variants). To exclude common inherited variants, we selected variants present in less than 0.01% of the (ExAC) control population and restricted our analysis to only singleton or doubleton variants (9,490 variants present in 1–2 of the 140 samples). Coverage was calculated by summing reference and alternate allele counts for each variant. Allelic fraction was calculated by dividing the alternate allele count by the total read coverage (both alleles) of the site. Although the allelic fraction of inherited heterozygous variants is expected to be 50%, reference capture bias (a tendency of hybrid selection to capture the reference allele more efficiently than alternative alleles) causes the actual expected allele fraction for SNPs and indels to be closer to 45% and 35%, respectively5. To account for these technical biases, we used a binomial test with a null model centred at 45% allelic fraction for inherited SNPs and 35% for inherited indels. Variants for which this binomial test was nominally significant (P < 0.01) were deemed to be candidate mosaic variants. The nominal P-value threshold of 0.01 was chosen as an inclusive threshold in order to screen sensitively for potentially mosaic variants, at the expense of also capturing false positives for which low allelic fractions represented statistical sampling fluctuations. For this reason, we considered it important to further evaluate putative mosaic variants by independent molecular methods that deeply sample alleles at the nominated sites (Fig. 3). A more stringent computational screen based on a P-value threshold of 1 × 10−7 identified three of the six TP53 variants, and TP53 was also the only gene with multiple putatively mosaic variants in this screen. We also identified all high quality heterozygous variants that passed the inclusive statistical threshold of (P < 0.01) in our binomial test and could potentially be mosaic (n = 36,396). These data are included in Supplementary Table 2. Variant annotation was performed using SnpEff with GRCh37.75 Ensembl gene models. Variants with moderate effect were classified as damaging by a consensus model based on seven in silico prediction algorithms37. We turned to the ExAC database11 that compiles the whole-exome sequences of over 60,000 individuals to assess the frequency at which the amino acid residues we observed to be mutated in some hES cells were affected in the general population. We then consulted the COSMIC12 (http://cancer.sanger.ac.uk/cosmic/gene/analysis?ln=TP53), ICGC13 (https://dcc.icgc.org/), and IARC P53 (ref. 14) (http://p53.iarc.fr/TP53SomaticMutations.aspx) databases and plotted the percentage of tumours carrying a mutation in each codon (Fig. 2d, Extended Data Fig. 2b). To visualize the spatial location of the amino acid residues affected by TP53 mutations observed in hES cells by WES on the P53 protein, we downloaded the 1.85 Angstrom X-ray diffraction-based structure file from the Research Collaboratory for Structural Bioinformatics Protein Data Bank (file 2AHI) and built the model protein/DNA system (chain IDs D, G, and H) to visualize the secondary structure of a P53 monomer complexed to DNA as a ribbon diagram. DNA was illustrated as a space-filling model. Water molecules were discarded when building the wild-type model and minimized in two steps using the AMBER 16 package38. Affected residues were indicated as space-filling model superimposed on the ribbon diagram of P53 and highlighted in blue (wild-type) or red (mutated) without consideration of how the mutations might affect the secondary or tertiary structure of the protein. We assayed the allelic fraction of the four distinct TP53 mutations identified by WES (Supplementary Table 3) in the 140 hES cell lines by droplet digital PCR (ddPCR). Each ddPCR analysis incorporated a custom TaqMan assay (IDT). Assays were designed with Primer3Plus and consisted of a primer pair and a 5′ fluorescently labelled probe (HEX or FAM) with 3′ quencher (Iowa Black with Zen) for either the control (reference) or mutant (alternative) base for each identified P53 variant (Supplementary Table 4). Genomic DNA from each hES cell line was analysed by ddPCR according to the manufacturer’s protocol (BioRad). The frequency of each allele for a given sample was estimated first by Poisson correction of the endpoint fluorescence reads21. These corrected counts were then converted to fractional abundance estimates of the mutant allele and multiplied by two to determine the fraction of cells carrying the variant allele. To assess how the allelic fraction of TP53 mutations might change over time in culture, hES cell lines CHB11 (passage 22 or 25), WA26 (passage 13 or 15), and ESI035 (passage 36 in two separate experiments) were serially passaged in mTeSR1 media (STEMCELL Technologies) at a density of approximately 30,000 cells cm−2 in the presence of 10 μM Y-27632 on the day of passaging. Cells were fed daily with mTeSR1 and passaged with Accutase (Innovative Cell Technologies Inc.) at approximately 90% confluence. To monitor changes in allelic fractions, genomic DNA from cells at the indicated passages were analysed by ddPCR. To calculate the relative expansion rate of mutant relative to wild-type cells, we applied the following formula: where R is defined as the ratio of (variant positive cells)/(variant negative cells) after some number of starting passages and R and R represent the aforementioned ratios measured on the same sample at T and T > T passages respectively. From this equation, the estimation of variant positive cells after T passages from starting ratio R can be defined as R egT. Note that this equation estimates the relative growth rate of cells carrying the variant allele with a round of passaging as unit of time, with both relative survival and growth being incorporated. These data are included in Supplementary Table 5. For the subsequent calculation of the earliest passage at which these mutations might have become detectable, the detection thresholds (R ) for WES and ddPCR was assumed to be 0.1 (10 / 100 reads) and 0.001 (1 per 1,000 droplets), respectively. In order to identify TP53 mutations in hPS cells, we analysed 256 publicly available high-throughput RNA sequencing samples of hPS cells from the SRA database39 (http://www.ncbi.nlm.nih.gov/sra). Data accession numbers for SRA (and GEO, where applicable) are provided in Supplementary Table 7. 5 of these 256 samples were not considered further as they were from single cells rather than cell lines. Following sequence alignment to the hg19 human reference genome with Tophat2 (ref. 40), single nucleotides divergent from the reference genome were identified using GATK HaplotypeCaller34. As sufficient sequencing depth is required to deduce sequence mutation, a threshold of 25 reads per nucleotide was set. Under this criterion, 43 samples (40 hES cell lines and 3 hiPS cell lines) had a missense mutation in TP53. 10 of the 40 hES cell samples (WA09) carried two separate mutations (Supplementary Table 7). Upon the identification of cell lines carrying mutant reads, RNA sequencing data from studies containing differentiated samples were included for analysis. In order to evaluate TP53 alleles, we assessed the level of polymorphism by calculating the ratio between the minor and major alleles across chromosome 17. So as to minimize sequencing noise and errors, we included SNPs covered by more than 10 reads and that are located in the dbSNP build 142 database41. The resulted wig files were then plotted using Integrative Genomics Viewer (IGV)42 (Extended Data Fig. 4). In order to quantify the difference in polymorphism between samples, we converted the wig files to BigWig using UCSC Genome Browser utilities43 and summed the allelic ratios between the distal part of the short arm of chromosome 17 (17p), the proximal side of this arm and the long arm of chromosome 17 (17q). The allelic ratio sum was then divided by the region’s length (bp), which resulted in the proportion of SNPs, followed by one-sided Z-score test for two population proportion to compare between the chromosome 17 areas within each sample. Whereas most samples with mutations in TP53 showed a comparable, non-significant rate of polymorphic sites along the chromosome, WIBR3 samples with H193R mutations and WA09 samples with both P151S and R248Q mutations had a significantly different proportion (P < 0.001) of polymorphic sites, in the distal part of the short arm of the chromosome (first 16 × 106 base pairs), including the TP53 site. Unlike the three mutant WIBR3 samples, the wild-type WIBR3 sample had a normal distribution of polymorphic sites with no significant difference between the short and long arms. Sequence data from cell lines listed on the NIH hES cell registry have been deposited in the NCBI database of Genotypes and Phenotypes (dbGaP) under accession number phys001343.v1.p1 (at https://www.ncbi.nlm.nih.gov/gap/?term=phys001343.v1.p1). Sequence data from the remaining cell lines reported in our study have been deposited at the European Genome-phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGAS00001002400 (at https://www.ebi.ac.uk/ega/search/site/EGAS00001002400).
News Article | May 24, 2017
GAD2-IRES-Cre, VGLUT2-IRES-Cre, VGAT-IRES-Cre, GAD1-eGFP, CCK-IRES-Cre, CRH-IRES-Cre, TAC1-IRES-Cre, and HDC-IRES-Cre mice (Jackson stock numbers 010802, 016963, 016962, 007677, 012706, 012704, 021877, and 021198, respectively) were obtained from Jackson Laboratory19, 32, 33 and VGLUT2-eGFP mice were from MMRRC (MMRRC 011835-UCD). PDYN-IRES-Cre mice were obtained from Bradford Lowell34. GAL-Cre mice were obtained from GENSAT (stock number KI87). Mice were housed in 12 h light–dark cycle (lights on 7:00 and off at 19:00) with free access to food and water. Experiments were performed in adult male or female mice (6–12 weeks old). All procedures were approved by Institutional Animal Care and Use Committees of the University of California, Berkeley, University of California, San Francisco, Allen Institute for Brain Science, and Stanford University and were done in accordance with federal regulations and guidelines on animal experimentation. Note that, in different experiments, GAD1, GAD2, and VGAT were used to identify GABAergic neurons. To examine the relationship between GAD1, GAD2, and VGAT in the POA, we quantified the overlap between GAD1 and VGAT on the basis of the double in situ hybridization data from the Allen Mouse Brain Atlas (http://connectivity.brain-map.org/transgenic/experiment/100142488) and found that 95% (327 out of 345) of VGAT-positive neurons also contained GAD1. Comparison between GAD1 and GAD2 expression in the POA (http://connectivity.brain-map.org/transgenic/experiment/100142491) showed that 99% (246 out of 248) of GAD1 neurons also contained GAD2. Together, these data indicate a very high degree of overlap between GAD1, GAD2, and VGAT in the POA. AAV -EF1α-DIO-ChR2–eYFP and AAV -hSyn-FLEX-hM4D(Gi)–mCherry were obtained from the University of North Carolina vector core. The final titre was estimated to be ~1012 genome copies per millilitre. AAV -EF1α-DIO-ChR2–eYFP, AAV -EF1α-DIO–eYFP, AAV -EF1α-DIO-iC++–eYFP, and AAV -EF1α-DIO-iC++–eYFP were obtained from Stanford University virus core. Lentivirus rEIAV-DIO-TLoop-ChR2–eYFP, rEIAV-DIO-TLoop-iC++–eYFP, and rEIAV-DIO-TLoop-nls–eYFP were obtained from Salk virus core and Allen Institute for Brain Science13. Rabies-tracing reagents (AAV-CAG-FLExloxP-TVA–mCherry, AAV-CAG-FLExloxP-RG (RG, rabies glycoprotein) and EnvA-pseudotyped, rabies-glycoprotein-deleted, and GFP-expressing rabies viral particles (RVdG)), cTRIO reagents (CAV-FLExloxP-Flp, AAV-FLExFRT-TVA–mCherry, AAV-FLExFRT-RG, and EnvA-pseudotyped, rabies-glycoprotein-deleted, and GFP-expressing rabies viral particles (RVdG)) and axon arborization analysis reagents (CAV-FLExloxP-Flp and AAV-hSyn1-FLExFRT–mGFP–2A-synaptophysin–mRuby) were obtained from Stanford University15. HSV-LoxSTOPLox-FlagHA-L10a was obtained from the University of California, San Francisco. Mice of a specific genotype were randomly assigned to experimental and control groups. Experimental and control animals were subjected to exactly the same surgical and behavioural manipulations. Data from animals used in experiments were excluded on the basis of histological criteria that included injection sites, virus expression, and optical fibre placement. Only animals with injection sites and optic fibre placement in the region of interest were included. To implant EEG and EMG recording electrodes, adult mice (6–12 weeks old) were anaesthetized with 1.5–2% isoflurane and placed on a stereotaxic frame. Two stainless steel screws were inserted into the skull 1.5 mm from midline and 1.5 mm anterior to the bregma, and two others were inserted 3 mm from midline and 3.5 mm posterior to the bregma. Two EMG electrodes were inserted into the neck musculature. Insulated leads from the EEG and EMG electrodes were soldered to a 2 × 3-pin header, which was secured to the skull using dental cement. For optogenetic activation/inhibition experiments, a craniotomy was made on top of the target region for optogenetic manipulation in the same surgery as for EEG and EMG implant, and 0.1–0.5 μl virus was injected into the target region using Nanoject II (Drummond Scientific) via a micropipette. We then implanted optic fibres bilaterally into the target region. Dental cement was applied to cover the exposed skull completely and to secure the implants for EEG and EMG recordings to the screws. After surgery, mice were allowed to recover for at least 2–3 weeks before experiments. For anti-histamine experiments (Extended Data Fig. 4), triprolidine (Tocris) was administered intraperitoneally at 20 mg per kg (body weight) and brain states were recorded for 3 h. For retrograde tracing in Extended Data Fig. 1a, 0.2–0.3 μl red or green RetroBeads (Lumafluor) was injected into each target region. For optrode recording experiments, the optrode assembly was inserted into the POA at a depth of 4.9 mm. Screws were attached to the skull for EEG recordings, and an EMG electrode was inserted into the neck musculature. The optrode assembly, screws, and EEG/EMG electrodes were secured to the skull using dental cement. These procedures are related to the results in Fig. 3 and Extended Data Fig. 6. For rabies tracing, AAV-CAG-FLExloxP-TVA–mCherry and AAV-CAG-FLExloxP-RG were injected into the TMN of HDC-Cre mice. Two to three weeks later, EnvA-pseudotyped, glycoprotein-deleted, and GFP-expressing rabies viral particles (RVdG) were injected into the TMN, and mice were euthanized 1 week later. These procedures are related to the results in Extended Data Fig. 2. For cTRIO experiments, a retrograde virus CAV-FLExloxP-Flp (5.0 × 1012 genome copies per millilitre) was injected into either the TMN or the PFC of GAD2-Cre mice to express Flp recombinase specifically in GABAPOA→TMN or GABAPOA→PFC neurons, and AAV-FLExFRT-TVA–mCherry (2.6 × 1012 genome copies per millilitre) and AAV-FLExFRT-RG (1.3 × 1012 genome copies per millilitre) were injected into the POA to express TVA (the receptor for the EnvA envelope glycoprotein)–mCherry and rabies glycoprotein in the Flp-expressing neurons. Two to three weeks later, EnvA-pseudotyped, glycoprotein-deleted, and GFP-expressing rabies viral particles (RVdG) (5.0 × 108 colony forming units per millilitre) were injected into the POA, and mice were euthanized 1 week later for histology. These procedures are related to the results in Extended Data Fig. 7. For axon arborization experiments, CAV-FLExloxP-Flp was injected into TMN, and AAV-hSyn1-FLExFRT–mGFP–2A-synaptophysin–mRuby was injected into the POA of GAD2-Cre mice. Mice were euthanized 4–7 weeks later for histology. These procedures are related to the results in Extended Data Fig. 7. For pharmacogenetic experiments, AAV -hSyn-FLEX-hM4D(Gi)–mCherry was injected bilaterally into the POA. These procedures are related to the results in Extended Data Fig. 10. For TRAP experiments, we injected Cre-inducible HSV expressing the large ribosomal subunit protein Rpl10a fused with Flag/haemagglutinin tag (HSV-LoxSTOPLox-FlagHA-L10a) into the TMN of VGAT-Cre mice. After 30–45 days of expression, the POA was dissected, and ribosome immunoprecipitation was performed to pull down the messenger RNAs (mRNAs) attached to Rpl10a. These procedures are related to the results in Fig. 4 and Extended Data Fig. 8. For single-cell RNA-seq experiments, rEIAV-DIO-TLoop-nls–eYFP was injected into the TMN of GAD2-Cre and VGAT-Cre mice. Four weeks later, we dissociated eYFP-labelled POA neurons for single-cell RNA-seq. These procedures are related to the results in Fig. 4 and Extended Data Fig. 8. For immunohistochemistry-detecting peptides, mice received a single intraventricular injection of colchicine (12 μg) 1–2 days before killing. These procedures are related to the results in Fig. 4. The stereotaxic coordinates were as follows. TMN: anteroposterior (AP) −2.45 mm, mediolateral (ML) 1 mm, dorsoventral (DV) 5–5.2 mm from the cortical surface; POA: AP 0 mm, ML 0.7 mm, DV 5.2 mm; PFC: AP +2.0 mm, ML 0.4 mm, DV 2 mm; vlPAG: AP −4.7 mm, ML 0.7 mm, DV 2.3 mm; dorsomedial hypothalamus: AP −1.8 mm, ML 0.4 mm, DV 5.2 mm; habenula: AP −1.8 mm, ML 0.5 mm, DV 2.2 mm. Sleep deprivation started at the beginning of the light period (7:00) and lasted till 13:00. Mice were kept awake by a combination of cage tapping, introduction of foreign objects such as paper towels, cage rotation, and fur stroking with a paintbrush35, gentle handling procedures that have been used extensively to induce sleep deprivation36. EEG and EMG were not recorded during sleep deprivation and recovery. After 6 h of deprivation, sleep-deprived mice were allowed rebound sleep for 4 h before being euthanized by cervical dislocation and decapitation. c-Fos immunohistochemistry was performed as described below. These procedures are related to the results in Extended Data Figs 1 and 2. Behavioural experiments were performed in home cages placed in sound-attenuating boxes. Sleep recordings were performed between 12:00 and 19:00 (light on at 7:00 and off at 19:00). EEG and EMG electrodes were connected to flexible recording cables via a mini-connector. EEG and EMG signals were recorded and amplified using AM Systems, digitally filtered (0.1–1,000 Hz and 10–1,000 Hz for EEG and EMG recordings respectively), and digitized at 600 Hz using LabView. Spectral analysis was performed using fast Fourier transform, and brain states were classified into NREM, REM, and wake states (wake: desynchronized EEG and high EMG activity; NREM: synchronized EEG with high-amplitude, low-frequency (0.5–4 Hz) activity and low EMG activity; REM: high power at theta frequencies (6–9 Hz) and low EMG activity). Brain states were classified into NREM sleep, REM sleep, and wakefulness using custom-written MATLAB software, and the classification was performed without any information about the identity of the animal or laser stimulation timing as previously described25. Each optic fibre (200 μm diameter; ThorLabs) was attached through an FC/PC adaptor to a 473-nm blue laser diode (Shanghai laser), and light pulses were generated using a Master 8 (A.M.P.I.). All photostimulation/inhibition experiments were conducted bilaterally and fibre optic cables were connected at least 2 h before the experiments for habituation. For photostimulation/inhibition experiments in ChR2-, iC++-, or eYFP-expressing mice, light pulses (10 ms per pulse, 10 Hz, 4–8 mW) or step pulses (60 s) were triggered using Master 8 that provided simultaneous input into two blue lasers. In each optogenetic manipulation experiment, inter-stimulation interval for optogenetic manipulation was chosen randomly from a uniform distribution between 15 and 25 min. Custom-made optrodes37 consisted of an optic fibre (200 μm in diameter) glued together with six pairs of stereotrodes. Two FeNiCr wires (Stablohm 675, California Fine Wire) were twisted together and electroplated to an impedance of ~ 600 kΩ using a custom-built plating device. The optrode was attached to a driver to allow vertical movement of the optrode assembly. The optrode was slowly lowered to search for light-responsive neurons. Wires to record cortical EEG and EMG from neck musculatures were also attached for simultaneous recordings. A TDT RZ5 amplifier was used for all the recordings, signals were filtered (0.3–8 kHz) and digitized at 25 kHz. At the end of the experiment, an electrolytic lesion was made by passing a current (100 μA, 10 s) through one or two electrodes to identify the end of the recording tract. Spikes were sorted offline on the basis of the waveform energy and the first three principal components of the spike waveform on each stereotrode channel. For single unit isolation, all channels were separated into groups and spike waveforms were identified either manually using Klusters (http://neurosuite.sourceforge.net/) or automatically using the software klustakwik (http://klustakwik.sourceforge.net/). The quality of each unit was assessed by the presence of a refractory period and quantified using isolation distance and L . Units with an isolation distance <20 and L >0.1 were discarded38. To identify ChR2-tagged neurons, laser pulse trains (10 and/or 20 Hz) were delivered intermittently every minute. A unit was identified as ChR2-expressing if spikes were evoked by laser pulses with short first-spike latency (<6 ms for all units in our sample) and the waveforms of the laser-evoked and spontaneous spikes were highly similar (correlation coefficient >0.9). Mean latency of all identified units was 3.05 ms. Mean correlation coefficient of all identified units was 0.99. To calculate the average firing rate of each unit in each brain state, spikes during the laser pulse trains were excluded. These procedures are related to the results in Fig. 3 and Extended Data Fig. 6. Mice were deeply anaesthetized and transcardially perfused using PBS buffer followed by 4% paraformaldehyde in PBS. Brains were post-fixed in fixative and stored in 30% sucrose in PBS overnight for cryoprotection. Brains were embedded and mounted with Tissue-Tek OCT compound (Sakura Finetek) and 20 μm sections were cut using a cryostat (Leica). Brain slices were washed using PBS, permeabilized using PBST (0.3% Triton X-100 in PBS) for 30 min and then incubated with blocking solution (5% normal goat serum or normal donkey serum in PBST) for 1 h followed by primary antibody incubation overnight at 4 °C using the following antibodies: anti–GFP antibody (A-11122 or A-11120, Life technologies, 1:1,000); anti-cFos antibody (sc-52-G and sc-52, Santa Cruz Biotech, 1:1,000); anti-CCK-8 antibody (20078, Immunostar, 1:500); anti-CRH antibody (sc-1759, Santa Cruz Biotech, 1:500); anti-haemagglutinin antibody (C29F4, Cell Signaling tech, 1:1,000); and anti-HDC antibody (16045, Progen, 1:1,000). The next day, slices were washed with PBS and incubated with appropriate secondary antibodies for 2 h (1:500, all from Invitrogen): A-11008, Alexa Fluor 488 goat anti-rabbit IgG; A-21206, Alexa Fluor 488 donkey anti-rabbit IgG; A-11055, Alexa Fluor 488 donkey anti-goat IgG; A-21202, Alexa Fluor 488 donkey anti-mouse IgG; A-11012, Alexa Fluor 594 goat anti-rabbit IgG; A-21207, Alexa Fluor 594 donkey anti-rabbit IgG; A-11058, Alexa Fluor 594 donkey anti-goat IgG; A-21245, Alexa Fluor 647 goat anti-rabbit IgG. The slices were washed with PBS followed by counterstaining with DAPI or Hoechst and coverslipped. Fluorescence images were taken using a confocal microscope (LSM 710 AxioObserver Inverted 34-Channel Confocal, Zeiss) or Nanozoomer (Hamamatsu). FISH was performed with two methods. First, FISH for CCK, CRH, TAC1, and GAD1 was done using RNAscope assays according to the manufacturer’s instructions (Advanced Cell Diagnostics). Second, to make TAC1, GAD1, and GAD2 FISH probes, DNA fragments containing the coding or untranslated sequences were amplified using PCR from mouse whole brain complementary DNA (cDNA) (Zyagen). A T7 RNA polymerase recognition site was added to the 3′ end of the PCR product. The PCR product was purified using a PCR purification kit (Qiagen). One microgram of DNA was used for in vitro transcription by using digoxigenin (DIG) RNA labelling mix (Roche) and T7 RNA polymerase. After DNase I treatment for 30 min at 37 °C, the RNA probe was purified using probeQuant G-50 Columns (GE Healthcare). Sections (20 μm) were pre-treated with proteinase K (0.1 μg ml−1), acetylated, dehydrated through ethanol (50, 70, 95, and 100%), and air dried. Pre-treated sections were then incubated for 16–20 h at 60 °C, in a hybridization buffer containing sense or anti-sense riboprobes. After the sections were hybridized, they were treated with RNase A (20 μg ml−1) for 30 min at 37 °C and then washed four times in decreasing salinity (from 2× to 0.1× standard saline citrate buffer) and a 30 min wash at 68 °C. Sections were incubated with 3% hydrogen peroxide in PBS for 1 h and washed using PBS. After incubation in the blocking buffer for 1 h (TNB buffer, Perkin Elmer), sections were incubated with anti-DIG-POD antibody (1:500, Roche) in TNB buffer for 2 h. TSA-plus-Fluorescein reagent was used to visualize the signal. For GAD-FISH, anti-DIG-AP antibody (1:500, Roche) and Fast Red TR/Naphthol AS-MX (F4523, Sigma-Aldrich) were used to visualize the signal. After washing the sections in PBS, they were incubated with blocking buffer for 2 h followed by incubation with anti–GFP antibody overnight, and finally incubated with a secondary antibody as described above. To examine the overlap between each peptide marker and GAD, we used CCK-, CRH-, TAC1-, and PDYN-Cre mice injected with AAV-EF1α-DIO-ChR2–eYFP or AAV-EF1α-DIO–eYFP. These procedures are related to the results in Extended Data Figs 2 and 8. For analysis of rabies-tracing data, consecutive 60 μm coronal sections were collected and stained using Hoechst. Slides were scanned using Nanozoomer (Hamamatsu). GFP+ input neurons were counted from the forebrain to the posterior brainstem except sections adjacent to the injection sites (1 mm from the injection site), and grouped into ten regions based on Allen Mouse Brain Atlas (http://mouse.brain-map.org/static/atlas) using anatomical landmarks in the sections visualized by Hoechst staining and autofluorescence. We normalized the number of neurons in each region by the total number of input neurons in the entire brain. These procedures are related to the results in Extended Data Fig. 7. Consecutive 60 μm coronal sections were collected and stained using Hoechst. Slides were scanned using a Nanozoomer (Hamamatsu). All images were acquired using identical settings and were analysed using ImageJ as previously described15. Images were background subtracted (rolling ball radius of 50 pixels), thresholded, and pixels above this threshold were interpreted as positive signals. The mGFP- or eYFP-labelled axon arborization signal was measured for each region and averaged across the five sections. These procedures are related to the results in Extended Data Fig. 7. We adapted a previously described procedure to perform TRAP experiment39. Mice were euthanized at 12:00 to 14:00 and the POA was rapidly dissected on ice with a dissection buffer (1× HBSS, 2.5 mM HEPES (pH 7.4), 4 mM NaHCO , 35 mM glucose, 100 μg ml−1 cycloheximide). Brains from six mice were then pooled, homogenized in the homogenization buffer (10 mM HEPES (pH 7.4), 150 mM KCl, 5 mM MgCl , 100 nM calyculin A, 2 mM DTT, 100 U ml−1 RNasin, 100 μg ml−1 cycloheximide and protease). Homogenates were transferred to a microcentrifuge tube and clarified at 2,000g for 10 min at 4 °C. The supernatant was transferred to a new tube, and 70 μl of 10% NP40 and 70 μl of 1,2-diheptanoyl-sn-glycero-3-phosphocholine (DHPC, 300 mM) per millilitre of supernatant were added. This solution was mixed and then clarified at 17,000g for 10 min at 4 °C. The resulting high-speed supernatant was transferred to a new tube. This supernatant served as the input. A small amount (25 μl) was added to a new tube containing 350 μl of buffer RLT for future input RNA purification. Immunoprecipitation was performed with an anti-Flag antibody loaded beads. The beads were washed four times using 0.15 M KCl Wash buffer (10 mM HEPES (pH 7.4), 350 mM KCl, 5 mM MgCl , 2 mM DTT, 1% NP40, 100 U ml−1 RNasin, and 100 μg ml−1 cycloheximide). After the final wash, the RNA was eluted by addition of buffer RLT (350 μl) to the beads on ice, the beads removed by a magnet, and the RNA purified using the RNeasy Micro Kit (Qiagen) and analysed using an Agilent 2100 Bioanalyzer. cDNA libraries for RNA-seq were prepared with Ovation RNA-Seq System V2 and Ovation Ultralow Library Systems (NuGen), and analysed on an Illumina HiSeq 2500. Gene classification shown in Supplementary Table 1 was performed using PANTHER (http://pantherdb.org/)40. These procedures are related to the results in Fig. 4 and Extended Data Fig. 8. We adapted a previously described procedure to isolate fluorescently labelled neurons from the mouse brain41, 42, 43. Individual adult male mice (postnatal day 56 ± 3) were anaesthetized in an isoflurane chamber, decapitated, and the brain was immediately removed and submerged in fresh ice-cold artificial cerebrospinal fluid (ACSF) containing 126 mM NaCl, 20 mM NaHCO , 20 mM dextrose, 3 mM KCl, 1.25 mM NaH PO , 2 mM CaCl , 2 mM MgCl , 50 μM DL-AP5 sodium salt, 20 μM DNQX, and 0.1 μM tetrodotoxin, bubbled with a carbogen gas (95% O and 5% CO ). The brain was sectioned on a vibratome (Leica VT1000S) on ice, and each slice (300–400 μm) was immediately transferred to an ACSF bath at room temperature. After the brain slicing was complete (not more than 15 min), individual slices of interest were transferred to a small Petri dish containing bubbled ACSF at room temperature. The POA was microdissected under a fluorescence dissecting microscope, and the slices before and after dissection were imaged to examine the location of the microdissected tissue and confirm its location. The dissected tissue pieces were transferred to a microcentrifuge tube and treated with 1 mg ml−1 pronase (Sigma, P6911-1G) in carbogen-bubbled ACSF for 70 min at room temperature without mixing in a closed tube. After incubation, with the tissue pieces sitting at the bottom of the tube, the pronase solution was pipetted out of the tube and exchanged with cold ACSF containing 1% fetal bovine serum. The tissue pieces were dissociated into single cells by gentle trituration through Pasteur pipettes with polished tips of 600, 300, and 150 μm diameter. Single cells were isolated by fluorescence-activated cell sorting into individual wells of 96-well plates or 8-well PCR strips containing 2.275 μl of Dilution Buffer (SMARTer Ultra Low RNA Kit for Illumina Sequencing, Clontech 634936), 0.125 μl RNase inhibitor (SMARTer kit), and 0.1 μl of 1:1,000,000 diluted RNA spike-in RNAs (ERCC RNA Spike-In Mix 1, Life Technologies 4456740). Sorting was performed on a BD FACSAriaII SORP using a 130 μm nozzle, a sheath pressure of 10 p.s.i., and in the single-cell sorting mode. To exclude dead cells, DAPI (DAPI*2HCl, Life Technologies D1306) was added to the single-cell suspension to the final concentration of 2 ng ml−1. Sorted cells were frozen immediately on dry ice and stored at −80 °C. We used the SMARTer kit described above to reverse transcribe single-cell RNA and amplify the cDNA for 19 PCR cycles. To stabilize the RNA after quickly thawing the cells on ice, we immediately added to each sample an additional 0.125 μl of RNase inhibitor mixed with SMART CDS Primer II A. All steps downstream were performed according to the manufacturer’s instructions. cDNA concentration was quantified using Agilent Bioanalyzer High Sensitivity DNA chips. For most samples, 1 ng of amplified cDNA was used as input to make sequencing libraries with a Nextera XT DNA kit (Illumina FC-131-1096). Individual libraries were quantified using Agilent Bioanalyzer DNA 7500 chips. To assess sample quality and adjust the concentrations of libraries for multiplexing on HiSeq, all libraries were sequenced first on Illumina MiSeq to obtain approximately 100,000 reads per library, and then on Illumina HiSeq 2000 or 2500 to generate 100 base pair reads. These procedures are related to the results in Fig. 4 and Extended Data Fig. 8. Since both TRAP and single-cell RNA-seq have technical limitations and are prone to false-positive and false-negative errors, we used the following strategy for identifying markers for POA sleep neurons. (1) To eliminate false-positive errors, the candidate markers with existing Cre lines were tested in optogenetic experiments, and cell types that did not promote sleep were eliminated (for example, GAL, which was found to be enriched in the TRAP experiment). (2) To reduce false-negative errors, we included markers identified by either method in our candidate list, rather than only those identified by both methods. This should have enhanced our chance of finding a useful marker, even if it were missed by one of the methods because of false-negative errors. Of course, this strategy could increase the probability for false-positive errors in our candidate list, but these errors were eliminated by the functional test in (1). To inhibit CCK, CRH, or TAC1 neurons, we injected CNO dissolved in 0.1 ml vehicle solution (PBS with 0.5% dimethyl sulfoxide (DMSO)) into CCK-, CRH- or TAC1-Cre mice expressing hM4Di in the POA, 20 min before the recording session. CNO was administered intraperitoneally at 2.5 mg per kg (body weight). Vehicle solution was injected for the control experiment. These procedures are related to the results in Extended Data Fig. 10. Slice recordings were made at postnatal days 42–50. AAV -EF1α-DIO-ChR2–eYFP (500 nl) was injected into the POA of GAD2-Cre mice, and recording was made 2–3 weeks after injection. Slice preparation was according to procedures described previously44. A mouse was deeply anaesthetized with 5% isoflurane. After decapitation, the brain was dissected rapidly and placed in ice-cold oxygenated HEPES-buffered ACSF (in mM: NaCl 92, KCl 2.5, NaH PO 1.2, NaHCO 30, HEPES 20, glucose 25, sodium ascorbate 5, thiourea 2, sodium pyruvate 3, MgSO ·7H O 10, CaCl ·2H O 0.5, and NAC 12, at pH 7.4, adjusted with 10 M NaOH), and coronal sections of the TMN were made with a vibratome (Leica). Slices (300 μm thick) were recovered in oxygenated NMDG–HEPES solution (in mM: NMDG 93, KCl 2.5, NaH PO 1.2, NaHCO 30, HEPES 20, glucose 25, sodium ascorbate 5, thiourea 2, sodium pyruvate 3, MgSO ·7H O 10, CaCl ·2H O 0.5, and NAC 12, at pH 7.4, adjusted with HCl) at 32 °C for 10 min and then maintained in an incubation chamber with oxygenated standard ACSF (in mM: NaCl 125, KCl 3, CaCl 2, MgSO 2, NaH PO 1.25, sodium ascorbate 1.3, sodium pyruvate 0.6, NaHCO 26, glucose 10, and NAC 10, at pH 7.4, adjusted by 10 M NaOH) at 25 °C for 1–4 h before recording. All chemicals were from Sigma. Whole-cell recordings were made at 30 °C in oxygenated solution (in mM: NaCl 125, KCl 4, CaCl 2, MgSO 1, NaH PO 1.25, sodium ascorbate 1.3, sodium pyruvate 0.6, NaHCO 26, and glucose 10, at pH 7.4). Inhibitory postsynaptic currents were recorded using a caesium-based internal solution (in mM: CsMeSO 125, CsCl 2, HEPES 10, EGTA 0.5, MgATP 4, Na GTP 0.3, sodium phosphocreatine 10, TEACl 5, QX-314 3.5, at pH 7.3, adjusted with CsOH, 290–300 mOsm) and isolated by clamping the membrane potential of the recorded neuron at the reversal potential of the excitatory synaptic currents. The resistance of the patch pipette was 3–5 MΩ. The cells were excluded if the series resistance exceeded 40 MΩ or varied by more than 20% during the recording period. To activate ChR2, we used a mercury arc lamp (Olympus) coupled to the epifluorescence light path and bandpass filtered at 450–490 nm (Semrock), gated by an electromagnetic shutter (Uniblitz). A blue light pulse (5 ms) was delivered through a 40 × 0.8 numerical aperture water immersion lens (Olympus) at a power of 1–2 mW. Data were recorded with a Multiclamp 700B amplifier (Axon instruments) filtered at 2 kHz and digitized with a Digidata 1440A (Axon instruments) at 4 kHz. Recordings were analysed using Clampfit (Axon instruments). These procedures are related to the results in Extended Data Fig. 2. At the end of each recording, cytoplasm was aspirated into the patch pipette, expelled into a PCR tube as described previously45. The single-cell reverse-transcription PCR (RT–PCR) protocol was designed to detect the presence of mRNAs coding for GAPDH, GAD1, VGLUT2, and HDC. First, reverse transcription and the first round of PCR amplification were performed with gene-specific multiplex primer using the SuperScript III One-Step RT–PCR kit (12574-018, Invitrogen) according to the manufacturer’s protocol. Second, nested PCR was performed using GoTaq Green Master Mix (M7121, Promega) with nested primers for each gene. Amplification products were visualized via electrophoresis using 2% agarose gel. Primers (5′>3′) for single-cell RT–PCR were as follows. GAPDH (sense/anti-sense): multiplex, ACTCCACTCACGGCAAATTC/CACATTGGGGGTAG GAACAC; nested, AGCTTGTCATCAACGGGAAG/GTCATGAGCCCTTC CACAAT; Final product 331 base pairs (bp). GAD1 (sense/anti-sense): multiplex, CACAGGTCACCCTCGATTTT/TCTATGCCGCTGAGTTTGTG; nested, TAGCTGGTGAATGGCTGACA/CTTGTAACGAGCAGCCATGA; final product 200 bp. VGLUT2 (sense/anti-sense): multiplex, GCCGCTACATCATAGCCATC/GCTCTCTCCAATGCTCTCCTC; nested, ACATGGTCAACAACAGCACTATC/ATAAGACACCAGAAGCCAGAACA; final product 506 bp. HDC (sense/anti-sense): multiplex, GGAGCCCTGTGAATACCGTG/TCCACTGAAGAGTGAGCCTGA; nested, CGTGAATACTACCGAGCTAGAGG/ACTCGTTCAATGTCCCCAAAG; final product 182 bp. These procedures are related to the results in Extended Data Fig. 2. Statistical analysis was performed using MATLAB, GraphPad Prism, or Python. The selection of statistical tests was based on reported previous studies. All statistical tests were two-sided. The 95% confidence intervals for brain state probabilities were calculated using a bootstrap procedure: for an experimental group of n mice, with mouse i comprising m trials, we repeatedly resampled the data by randomly drawing for each mouse m trials (random sampling with replacement). For each of the 10,000 iterations, we recalculated the mean probabilities for each brain state across the n mice. The lower and upper confidence intervals were then extracted from the distribution of the resampled mean values. To test whether a given brain state was significantly modulated by laser stimulation, we calculated for each bootstrap iteration the difference between the mean probabilities during laser stimulation and the preceding period of identical duration. The investigators were not blinded to allocation during experiments and outcome assessment. To determine the sample size for optogenetic and pharmacogenetic experiments, we first performed pilot experiments with two or three mice. Given the strength of the effect and the variance across this group, we then predicted the number of animals required to reach sufficient statistical power. To determine the sample size (number of units) for optrode recordings, we first recorded from two animals. Given the success rate of finding identified units and the homogeneity of units in the initial data set, we set a target sample size. For rabies-mediated retrograde tracing, histology, and slice recording experiments, the selection of the sample size was based on numbers reported in previous studies. For gene profiling experiments, sample size was not calculated a priori, and the selection of the sample size was based on previous studies. Otherwise, no statistical methods were used to predetermine sample size. The single-cell RNA-seq data have been deposited in the Gene Expression Omnibus under accession number GSE79108. All other data are available from the corresponding author upon reasonable request.