1. Cirelli, C. & Tononi, G. Changes in anti-phosphoserine and anti-phosphothreonine antibody binding during the sleep-waking cycle and after lesions of the locus coeruleus. Sleep Res. Online 1, 11–18 (1998).

2. Elliott, A. S., Huber, J. D., O’Callaghan, J. P., Rosen, C. L. & Miller, D. B. A review of sleep deprivation studies evaluating the brain transcriptome. Springerplus 3, 728 (2014).

3. Thompson, C. L. et al. Molecular and anatomical signatures of sleep deprivation in the mouse brain. Front. Neurosci. 4, 165 (2010).

4. Diering, G. H. et al. Homer1a drives homeostatic scaling-down of excitatory synapses during sleep. Science 355, 511–515 (2017).

5. Tononi, G. & Cirelli, C. Sleep and the price of plasticity: from synaptic and cellular homeostasis to memory consolidation and integration. Neuron 81, 12–34 (2014).

6. de Vivo, L. et al. Ultrastructural evidence for synaptic scaling across the wake/sleep cycle. Science 355, 507–510 (2017).

7. Vyazovskiy, V. V. & Harris, K. D. Sleep and the single neuron: the role of global slow oscillations in individual cell rest. Nat. Rev. Neurosci. 14, 443–451 (2013).

8. Borbely, A. A. A two process model of sleep regulation. Hum. Neurobiol. 1, 195–204 (1982).

9. Benington, J. H. Sleep homeostasis and the function of sleep. Sleep 23, 959–966 (2000).

10. Franken, P., Chollet, D. & Tafti, M. The homeostatic regulation of sleep need is under genetic control. J. Neurosci. 21, 2610–2621 (2001).

11. Vassalli, A. & Dijk, D. J. Sleep function: current questions and new approaches. Eur. J. Neurosci. 29, 1830–1841 (2009).

12. Funato, H. et al. Forward-genetics analysis of sleep in randomly mutagenized mice. Nature 539, 378–383 (2016).

13. Saper, C. B. & Fuller, P. M. Wake-sleep circuitry: an overview. Curr. Opin. Neurobiol. 44, 186–192 (2017).

14. Liu, S., Liu, Q., Tabuchi, M. & Wu, M. N. Sleep drive is encoded by neural plastic changes in a dedicated circuit. Cell 165, 1347–1360 (2016).

15. Lizcano, J. M. et al. LKB1 is a master kinase that activates 13 kinases of the AMPK subfamily, including MARK/PAR-1. EMBO J. 23, 833–843 (2004).

16. Erickson, B. K. et al. Evaluating multiplexed quantitative phosphopeptide analysis on a hybrid quadrupole mass filter/linear ion trap/orbitrap mass spectrometer. Anal. Chem. 87, 1241–1249 (2015).

17. McAlister, G. C. et al. MultiNotch MS3 enables accurate, sensitive, and multiplexed detection of differential expression across cancer cell line proteomes. Anal. Chem. 86, 7150–7158 (2014).

18. Weekes, M. P. et al. Quantitative temporal viromics: an approach to investigate host-pathogen interaction. Cell 157, 1460–1472 (2014).

19. Paulo, J. A. et al. Effects of MEK inhibitors GSK1120212 and PD0325901 in vivo using 10-plex quantitative proteomics and phosphoproteomics. Proteomics 15, 462–473 (2015).

20. Humphrey, S. J., James, D. E. & Mann, M. Protein phosphorylation: a major switch mechanism for metabolic regulation. Trends Endocrinol. Metab. 26, 676–687 (2015).

21. Greengard, P., Valtorta, F., Czernik, A. J. & Benfenati, F. Synaptic vesicle phosphoproteins and regulation of synaptic function. Science 259, 780–785 (1993).

22. Cesca, F., Baldelli, P., Valtorta, F. & Benfenati, F. The synapsins: key actors of synapse function and plasticity. Prog. Neurobiol. 91, 313–348 (2010).

23. Cantrell, A. R. et al. Molecular mechanism of convergent regulation of brain Na+ channels by protein kinase C and protein kinase A anchored to AKAP-15. Mol. Cell. Neurosci. 21, 63–80 (2002).

24. Tatsuki, F. et al. Involvement of Ca2+-dependent hyperpolarization in sleep duration in mammals. Neuron 90, 70–85 (2016).

25. Campbell, I. G. & Feinberg, I. NREM delta stimulation following MK-801 is a response of sleep systems. J. Neurophysiol. 76, 3714–3720 (1996).

26. Campbell, I. G. & Feinberg, I. Noncompetitive NMDA channel blockade during waking intensely stimulates NREM delta. J. Pharmacol. Exp. Ther. 276, 737–742 (1996).

27. Schaffer, B. E. et al. Identification of AMPK phosphorylation sites reveals a network of proteins involved in cell invasion and facilitates large-scale substrate prediction. Cell Metab. 22, 907–921 (2015).

28. Clark, K. et al. Phosphorylation of CRTC3 by the salt-inducible kinases controls the interconversion of classically activated and regulatory macrophages. Proc. Natl Acad. Sci. USA 109, 16986–16991 (2012).

29. Eng, J. K., McCormack, A. L. & Yates, J. R. An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J. Am. Soc. Mass Spectrom. 5, 976–989 (1994).

30. Peng, J., Elias, J. E., Thoreen, C. C., Licklider, L. J. & Gygi, S. P. Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC–MS/MS) for large-scale protein analysis: the yeast proteome. J. Proteome Res. 2, 43–50 (2003).

31. Elias, J. E. & Gygi, S. P. Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry. Nat. Methods 4, 207–214 (2007).

32. Kall, L., Canterbury, J. D., Weston, J., Noble, W. S. & MacCoss, M. J. Semi-supervised learning for peptide identification from shotgun proteomics datasets. Nat. Methods 4, 923–925 (2007).

33. Taus, T. et al. Universal and confident phosphorylation site localization using phosphoRS. J. Proteome Res. 10, 5354–5362 (2011).

34. Wang, X. et al. JUMP: a tag-based database search tool for peptide identification with high sensitivity and accuracy. Mol. Cell. Proteomics 13, 3663–3673 (2014).

35. Li, Y. et al. JUMPg: an integrative proteogenomics pipeline identifying unannotated proteins in human brain and cancer cells. J. Proteome Res. 15, 2309–2320 (2016).

36. Benjamini, Y., Krieger, A. M. & Yekutieli, D. Adaptive linear step-up procedures that control the false discovery rate. Biometrika 93, 491–507 (2006).

37. Wu, R. et al. Correct interpretation of comprehensive phosphorylation dynamics requires normalization by protein expression changes. Mol. Cell. Proteomics 10, M111 009654 (2011).

38. Ashburner, M. et al. Gene ontology: tool for the unification of biology. Nat. Genet. 25, 25–29 (2000).

39. The Gene Ontology Consortium. C. Expansion of the Gene Ontology knowledgebase and resources. Nucleic Acids Res. 45, D331–D338 (2017).

40. Mi, H. et al. PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements. Nucleic Acids Res. 45, D183–D189 (2017).

41. Beacham, D., Ahn, M., Catterall, W. A. & Scheuer, T. Sites and molecular mechanisms of modulation of Na(v)1.2 channels by Fyn tyrosine kinase. J. Neurosci. 27, 11543–11551 (2007).

42. James, T. F. et al. The Nav1.2 channel is regulated by GSK3. Biochim. Biophys. Acta 1850, 832–844 (2015).

43. Siwek, M. E. et al. The CaV2.3 R-type voltage-gated Ca2+ channel in mouse sleep architecture. Sleep 37, 881–892 (2014).

44. Parker, M. J. et al. De novo, heterozygous, loss-of-function mutations in SYNGAP1 cause a syndromic form of intellectual disability. Am. J. Med. Genet. A. 167A, 2231–2237 (2015).

45. Carlisle, H. J. et al. Deletion of densin-180 results in abnormal behaviors associated with mental illness and reduces mGluR5 and DISC1 in the postsynaptic density fraction. J. Neurosci. 31, 16194–16207 (2011).

46. Soorya, L. et al. Prospective investigation of autism and genotype–phenotype correlations in 22q13 deletion syndrome and SHANK3 deficiency. Mol. Autism 4, 18 (2013).

47. Ahnaou, A., Raeymaekers, L., Steckler, T. & Drinkenbrug, W. H. Relevance of the metabotropic glutamate receptor (mGluR5) in the regulation of NREM–REM sleep cycle and homeostasis: evidence from mGluR5−/−mice. Behav. Brain Res. 282, 218–226 (2015).

48. Hagebeuk, E. E., van den Bossche, R. A. & de Weerd, A. W. Respiratory and sleep disorders in female children with atypical Rett syndrome caused by mutations in the CDKL5 gene. Dev. Med. Child Neurol. 55, 480–484 (2012).

49. Lonart, G., Tang, X., Simsek-Duran, F., Machida, M. & Sanford, L. D. The role of active zone protein Rab3 interacting molecule 1 alpha in the regulation of norepinephrine release, response to novelty, and sleep. Neuroscience 154, 821–831 (2008).

50. Iqbal, Z. et al. Homozygous and heterozygous disruptions of ANK3: at the crossroads of neurodevelopmental and psychiatric disorders. Hum. Mol. Genet. 22, 1960–1970 (2013).

51. von Stulpnagel, C. et al. SYNGAP1 mutation in focal and generalized epilepsy: a literature overview and a case report with special aspects of the EEG. Neuropediatrics 46, 287–291 (2015).

52. Mangatt, M. et al. Prevalence and onset of comorbidities in the CDKL5 disorder differ from Rett syndrome. Orphanet J. Rare Dis. 11, 39 (2016).

53. Fehr, S. et al. The CDKL5 disorder is an independent clinical entity associated with early-onset encephalopathy. Eur. J. Hum. Genet. 21, 266–273 (2013).

54. Jiang, P. et al. A systems approach identifies networks and genes linking sleep and stress: implications for neuropsychiatric disorders. Cell Reports 11, 835–848 (2015).

55. Welch, J. M. et al. Cortico-striatal synaptic defects and OCD-like behaviours in Sapap3-mutant mice. Nature 448, 894–900 (2007).

56. Bayes, A. et al. Comparative study of human and mouse postsynaptic proteomes finds high compositional conservation and abundance differences for key synaptic proteins. PLoS ONE 7, e46683 (2012).

57. Li, J. et al. Long-term potentiation modulates synaptic phosphorylation networks and reshapes the structure of the postsynaptic interactome. Sci. Signal. 9, rs8 (2016).

58. Uezu, A. et al. Identification of an elaborate complex mediating postsynaptic inhibition. Science 353, 1123–1129 (2016).

59. Gonzalez-Lozano, M. A. et al. Dynamics of the mouse brain cortical synaptic proteome during postnatal brain development. Sci. Rep. 6, 35456 (2016).

60. Weingarten, J. et al. The proteome of the presynaptic active zone from mouse brain. Mol. Cell. Neurosci. 59, 106–118 (2014).

61. Boyken, J. et al. Molecular profiling of synaptic vesicle docking sites reveals novel proteins but few differences between glutamatergic and GABAergic synapses. Neuron 78, 285–297 (2013).

62. Abul-Husn, N. S. et al. Systems approach to explore components and interactions in the presynapse. Proteomics 9, 3303–3315 (2009).

63. Biesemann, C. et al. Proteomic screening of glutamatergic mouse brain synaptosomes isolated by fluorescence activated sorting. EMBO J. 33, 157–170 (2014).

64. Distler, U. et al. In-depth protein profiling of the postsynaptic density from mouse hippocampus using data-independent acquisition proteomics. Proteomics 14, 2607–2613 (2014).

65. Loh, K. H. et al. Proteomic analysis of unbounded cellular compartments: synaptic clefts. Cell 166, 1295-1307 (2016).

66. Nakamura, Y. et al. Proteomic characterization of inhibitory synapses using a novel pHluorin-tagged γ-aminobutyric acid receptor, type A (GABA A ), α2 subunit knock-in mouse. J. Biol. Chem. 291, 12394–12407 (2016).

67. de Hoon, M. J., Imoto, S., Nolan, J. & Miyano, S. Open source clustering software. Bioinformatics 20, 1453–1454 (2004).

68. Lee, E. E. et al. A protein kinase C phosphorylation motif in GLUT1 affects glucose transport and is mutated in GLUT1 deficiency syndrome. Mol. Cell 58, 845–853 (2015).

69. Kinoshita, E., Kinoshita-Kikuta, E., Takiyama, K. & Koike, T. Phosphate-binding tag, a new tool to visualize phosphorylated proteins. Mol. Cell. Proteomics 5, 749–757 (2006).

70. Vizcaino, J. A. et al. ProteomeXchange provides globally coordinated proteomics data submission and dissemination. Nat. Biotechnol. 32, 223–226 (2014).