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Cell-type and sex-specific rhythmic gene expression in the nucleus accumbens

Molecular Psychiatry (2024)Cite this article

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Abstract

Circadian rhythms are critical for human health and are highly conserved across species. Disruptions in these rhythms contribute to many diseases, including psychiatric disorders. Previous results suggest that circadian genes modulate behavior through specific cell types in the nucleus accumbens (NAc), particularly dopamine D1-expressing medium spiny neurons (MSNs). However, diurnal rhythms in transcript expression have not been investigated in NAc MSNs. In this study we identified and characterized rhythmic transcripts in D1- and D2-expressing neurons and compared rhythmicity results to homogenate as well as astrocyte samples taken from the NAc of male and female mice. We find that all cell types have transcripts with diurnal rhythms and that top rhythmic transcripts are largely core clock genes, which peak at approximately the same time of day in each cell type and sex. While clock-controlled rhythmic transcripts are enriched for protein regulation pathways across cell type, cell signaling and signal transduction related processes are most commonly enriched in MSNs. In contrast to core clock genes, these clock-controlled rhythmic transcripts tend to reach their peak in expression about 2-h later in females than males, suggesting diurnal rhythms in reward may be delayed in females. We also find sex differences in pathway enrichment for rhythmic transcripts peaking at different times of day. Protein folding and immune responses are enriched in transcripts that peak in the dark phase, while metabolic processes are primarily enriched in transcripts that peak in the light phase. Importantly, we also find that several classic markers used to categorize MSNs are rhythmic in the NAc. This is critical since the use of rhythmic markers could lead to over- or under-enrichment of targeted cell types depending on the time at which they are sampled. This study greatly expands our knowledge of how individual cell types contribute to rhythms in the NAc.

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Fig. 1: Rhythmicity in the NAc varies by cell type.
Fig. 2: Rhythmic transcripts vary across cell type and sex in the NAc.
Fig. 3: Rhythmic transcripts tend to peak later in females than males.
Fig. 4: Rhythmic transcripts peaking in the light phase contribute to largely distinct enriched pathways.
Fig. 5: Rhythmicity should be considered when cell-type-specific markers are selected.
Fig. 6: Model summarizing enriched rhythmic processes in MSNs across time of day and sex.

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Data availability

Sequencing data are available in the Gene Expression Omnibus (GEO) database. The code used for analysis is available at GitHub.

References

  1. Reppert SM, Weaver DR. Coordination of circadian timing in mammals. Nature. 2002;418:935–41.

    Article  CAS  PubMed  Google Scholar 

  2. Takahashi JS. Transcriptional architecture of the mammalian circadian clock. Nat Rev Genet. 2016;18:164–79.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Ko CH, Takahashi JS. Molecular components of the mammalian circadian clock. Hum Mol Genet. 2006;15:R271–7.

    Article  CAS  PubMed  Google Scholar 

  4. Easton A, Arbuzova J, Turek FW. The circadian Clock mutation increases exploratory activity and escape-seeking behavior. Genes Brain Behav. 2003;2:11–9.

    Article  CAS  PubMed  Google Scholar 

  5. Roybal K, Theobold D, Graham A, DiNieri JA, Russo SJ, Krishnan V, et al. Mania-like behavior induced by disruption of CLOCK. Proc Natl Acad Sci USA. 2007;104:6406–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Benedetti F, Serretti A, Colombo C, Barbini B, Lorenzi C, Campori E, et al. Influence of CLOCK gene polymorphism on circadian mood fluctuation and illness recurrence in bipolar depression. Am J Med Genet B Neuropsychiatr Genet. 2003;123B:23–6.

    Article  PubMed  Google Scholar 

  7. Benedetti F, Dallaspezia S, Colombo C, Pirovano A, Marino E, Smeraldi E. A length polymorphism in the circadian clock gene Per3 influences age at onset of bipolar disorder. Neurosci Lett. 2008;445:184–7.

    Article  CAS  PubMed  Google Scholar 

  8. Johansson C, Willeit M, Smedh C, Ekholm J, Paunio T, Kieseppä T, et al. Circadian clock-related polymorphisms in seasonal affective disorder and their relevance to diurnal preference. Neuropsychopharmacology. 2003;28:734–9.

    Article  CAS  PubMed  Google Scholar 

  9. Lavebratt C, Sjöholm LK, Soronen P, Paunio T, Vawter MP, Bunney WE, et al. CRY2 is associated with depression. PLoS ONE. 2010;5:e9407.

  10. Mansour HA, Talkowski ME, Wood J, Chowdari KV, McClain L, Prasad K, et al. Association study of 21 circadian genes with bipolar I disorder, schizoaffective disorder, and schizophrenia. Bipolar Disord. 2009;11:701–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Bi J, Gelernter J, Sun J, Kranzler HR. Comparing the utility of homogeneous subtypes of cocaine use and related behaviors with DSM-IV cocaine dependence as traits for genetic association analysis. Am J Med Genet Part B Neuropsychiatr Genet. 2014;165:148–56.

    Article  CAS  Google Scholar 

  12. Baranger DAA, Ifrah C, Prather AA, Carey CE, Corral-Frías NS, Drabant Conley E, et al. PER1 rs3027172 genotype interacts with early life stress to predict problematic alcohol use, but not reward-related ventral striatum activity. Front Psychol. 2016;7:464.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Blomeyer D, Buchmann AF, Lascorz J, Zimmermann US, Esser G, Desrivieres S, et al. Association of PER2 genotype and stressful life events with alcohol drinking in young adults. PLoS ONE. 2013;8:e59136.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Forbes EE, Dahl RE, Almeida JRC, Ferrell RE, Nimgaonkar VL, Mansour H, et al. PER2 rs2304672 polymorphism moderates circadian-relevant reward circuitry activity in adolescents. Biol Psychiatry. 2012;71:451–7.

    Article  CAS  PubMed  Google Scholar 

  15. Gamsby JJ, Templeton EL, Bonvini LA, Wang W, Loros JJ, Dunlap JC, et al. The circadian Per1 and Per2 genes influence alcohol intake, reinforcement, and blood alcohol levels. Behav Brain Res. 2013;249:15–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Ozburn AR, Larson EB, Self DW, McClung CA. Cocaine self-administration behaviors in ClockΔ19 mice. Psychopharmacology 2012;223:169–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Ozburn AR, Falcon E, Mukherjee S, Gillman A, Arey R, Spencer S, et al. The Role of Clock in Ethanol-Related Behaviors. Neuropsychopharmacology. 2013;38:2393–400.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Dong L, Bilbao A, Laucht M, Henriksson R, Yakovleva T, Ridinger M, et al. Effects of the circadian rhythm gene period 1 (Per1) on psychosocial stress-induced alcohol drinking. Am J Psychiatry. 2011;168:1090–8.

    Article  PubMed  Google Scholar 

  19. Wise RA, Rompre PP. Brain dopamine and reward. Annu Rev Psychol. 1989;40:191–225.

    Article  CAS  PubMed  Google Scholar 

  20. DePoy LM, McClung CA, Logan RW. Neural mechanisms of circadian regulation of natural and drug reward. Neural Plast. 2017;2017:1–14.

    Article  Google Scholar 

  21. Parekh PK, Becker-Krail D, Sundaravelu P, Ishigaki S, Okado H, Sobue G, et al. Altered GluA1 (Gria1) function and accumbal synaptic plasticity in the ClockΔ19 model of bipolar mania. Biol Psychiatry. 2018;84:817–26.

    Article  CAS  PubMed  Google Scholar 

  22. DePoy LM, Becker-Krail DD, Zong W, Petersen K, Shah NM, Brandon JH, et al. Circadian-dependent and sex-dependent increases in intravenous cocaine self-administration in Npas2 mutant mice. J Neurosci. 2021;41:1046.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Parekh PK, Logan RW, Ketchesin KD, Becker-Krail D, Shelton MA, Hildebrand MA, et al. Cell-type specific regulation of nucleus accumbens synaptic plasticity and cocaine reward sensitivity by the circadian protein, NPAS2. J Neurosci. 2019;39:4657–67.

  24. Lobo MK, Covington HE, Chaudhury D, Friedman AK, Sun H, Damez-Werno D, et al. Cell type-specific loss of BDNF signaling mimics optogenetic control of cocaine reward. Science. 2010;330:385–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Wen S, Ma D, Zhao M, Xie L, Wu Q, Gou L, et al. Spatiotemporal single-cell analysis of gene expression in the mouse suprachiasmatic nucleus. Nat Neurosci. 2020;23:456–67.

    Article  CAS  PubMed  Google Scholar 

  26. Brami-Cherrier K, Lewis RG, Cervantes M, Liu Y, Tognini P, Baldi P, et al. Cocaine-mediated circadian reprogramming in the striatum through dopamine D2R and PPARγ activation. Nat Commun. 2020;11:4448.

  27. Ketchesin KD, Zong W, Hildebrand MA, Seney ML, Cahill KM, Scott MR, et al. Diurnal rhythms across the human dorsal and ventral striatum. Proc Natl Acad Sci USA. 2021;118:2016150118.

    Article  Google Scholar 

  28. Becker-Krail DD, Ketchesin KD, Burns JN, Zong W, Hildebrand MA, DePoy LM, et al. Astrocyte molecular clock function in the nucleus accumbens is important for reward-related behavior. Biol Psychiatry. 2022;92:68–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Hatcher KM, Royston SE, Mahoney MM. Modulation of circadian rhythms through estrogen receptor signaling. Eur J Neurosci. 2018;51:217–28.

  30. Becker JB, Hu M. Sex differences in drug abuse. Front Neuroendocrinol. 2008;29:36–47.

    Article  CAS  PubMed  Google Scholar 

  31. Chandra R, Francis TC, Konkalmatt P, Amgalan A, Gancarz AM, Dietz DM, et al. Opposing Role for Egr3 in nucleus accumbens cell subtypes in cocaine action. J Neurosci. 2015;35:7927.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Cornelissen G. Cosinor-based rhythmometry. Theor Biol Med Model. 2014;11:16.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:1–21.

    Article  Google Scholar 

  34. Cahill KM, Huo Z, Tseng GC, Logan RW, Seney ML. Improved identification of concordant and discordant gene expression signatures using an updated rank-rank hypergeometric overlap approach. Sci Rep. 2018;8:1–11.

    Article  CAS  Google Scholar 

  35. Tran MN, Maynard KR, Spangler A, Huuki LA, Montgomery KD, Sadashivaiah V, et al. Single-nucleus transcriptome analysis reveals cell-type-specific molecular signatures across reward circuitry in the human brain. Neuron. 2021;109:3088–3103.e5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Kosten TA, Gawin FH, Kosten TR, Rounsaville BJ. Gender differences in cocaine use and treatment response. J Subst Abuse Treat. 1993;10:63–6.

    Article  CAS  PubMed  Google Scholar 

  37. Kennedy AP, Epstein DH, Phillips KA, Preston KL. Sex differences in cocaine/heroin users: drug-use triggers and craving in daily life. Drug Alcohol Depend. 2013;132:29–37.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Robbins SJ, Ehrman RN, Childress AR, O’Brien CP. Comparing levels of cocaine cue reactivity in male and female outpatients. Drug Alcohol Depend. 1999;53:223–30.

    Article  CAS  PubMed  Google Scholar 

  39. Mavroudis PD, DuBois DC, Almon RR, Jusko WJ. Modeling circadian variability of core-clock and clock-controlled genes in four tissues of the rat. PLoS ONE 2018;13:e0197534.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Ozburn AR, Falcon E, Twaddle A, Nugent AL, Gillman AG, Spencer SM, et al. Direct regulation of diurnal drd3 expression and cocaine reward by npas2. Biol Psychiatry. 2015;77:425–33.

    Article  CAS  PubMed  Google Scholar 

  41. Ferris MJ, España RA, Locke JL, Konstantopoulos JK, Rose JH, Chen R, et al. Dopamine transporters govern diurnal variation in extracellular dopamine tone. Proc Natl Acad Sci USA. 2014;111:E2751-9.

  42. Castañeda TR, De Prado BM, Prieto D, Mora F. Circadian rhythms of dopamine, glutamate and GABA in the striatum and nucleus accumbens of the awake rat: modulation by light. J Pineal Res. 2004;36:177–85.

    Article  PubMed  Google Scholar 

  43. Stowe TA, Pitts EG, Leach AC, Iacino MC, Niere F, Graul B, et al. Diurnal rhythms in cholinergic modulation of rapid dopamine signals and associative learning in the striatum. Cell Rep. 2022;39:110633.

  44. Bolaños JP. Bioenergetics and redox adaptations of astrocytes to neuronal activity. J Neurochem. 2016;139:115.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Gonçalves CA, Rodrigues L, Bobermin LD, Zanotto C, Vizuete A, Quincozes-Santos A, et al. Glycolysis-derived compounds from astrocytes that modulate synaptic communication. Front Neurosci. 2018;12:1035.

  46. Malarkey EB, Parpura V. Mechanisms of glutamate release from astrocytes. Neurochem Int. 2008;52:142–54.

    Article  CAS  PubMed  Google Scholar 

  47. Brancaccio M, Patton AP, Chesham JE, Maywood ES, Hastings MH. Astrocytes control circadian timekeeping in the suprachiasmatic nucleus via glutamatergic signaling. Neuron. 2017;93:1420–1435.e5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Chen R, Blosser TR, Djekidel MN, Hao J, Bhattacherjee A, Chen W, et al. Decoding molecular and cellular heterogeneity of mouse nucleus accumbens. Nat Neurosci. 2021;24:1757–71.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We would like to thank Mariah Hildebrand and Ioannis Migias for animal care and genotyping. We thank Dr. Mary Kay Lobo for providing the Ribotag transgenic mice, as well as for technical assistance with co-immunoprecipitations. This project used the University of Pittsburgh Health Sciences Sequencing Core at UPMC Children’s Hospital of Pittsburgh (RNA sequencing) and the University of Pittsburgh Center for Research Computing, RRID:SCR_022735, through the resources provided. Specifically, this work used the HTC cluster, which is supported by NIH award number S10OD028483. This work was funded by the National Institutes of Health: DA039865, DA046346, MH111601, MH106460 (PI: Colleen McClung, PhD), DA046117, DA055064, L60DA054665 (PI: LMD) and MH128763 (PI: KDK) as well as the Brain and Behavior Research Foundation (29386, LMD and 30823 (P&S Fund), Ketchesin).

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Authors and Affiliations

  1. Department of Psychiatry, Translational Neuroscience Program, University of Pittsburgh School of Medicine, 15219, Pittsburgh, PA, USA

    Lauren M. DePoy, Kaitlyn A. Petersen, Kyle D. Ketchesin, Ross C. Matthaei, Megan S. Perez, Darius Becker-Krail, Madeline R. Scott & Colleen A. McClung

  2. Center for Neuroscience, University of Pittsburgh, 15261, Pittsburgh, PA, USA

    Lauren M. DePoy, Kaitlyn A. Petersen, Kyle D. Ketchesin, Darius Becker-Krail, Madeline R. Scott & Colleen A. McClung

  3. Department of Biostatistics, University of Pittsburgh, 15261, Pittsburgh, PA, USA

    Wei Zong, RuoFei Yin & George C. Tseng

  4. Department of Human Genetics, School of Public Health, University of Pittsburgh, 15261, Pittsburgh, PA, USA

    Megan S. Perez

  5. David O. Robbins Neuroscience Program, Department of Psychology, Ohio Wesleyan University, 43015, Delaware, OH, USA

    Chelsea A. Vadnie

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Contributions

LMD, KAP, KDK, RCM, MSP, CAV, DB-K performed experiments. LMD, WZ, RY, MRS, GCT, CAM performed data analysis. LMD, WZ, RY, CAM wrote the manuscript. All authors provided manuscript edits.

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Correspondence to Colleen A. McClung.

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DePoy, L.M., Petersen, K.A., Zong, W. et al. Cell-type and sex-specific rhythmic gene expression in the nucleus accumbens. Mol Psychiatry (2024). https://doi.org/10.1038/s41380-024-02569-7

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