<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Tran MN</submitter><funding>NIDA NIH HHS</funding><funding>NIMH NIH HHS</funding><funding>NHGRI</funding><funding>NHGRI NIH HHS</funding><funding>National Institute of Mental Health</funding><funding>Lieber Institute for Brain Development</funding><funding>National Institute on Drug Abuse</funding><pagination>3088-3103.e5</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC8564763</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>109(19)</volume><pubmed_abstract>Single-cell gene expression technologies are powerful tools to study cell types in the human brain, but efforts have largely focused on cortical brain regions. We therefore created a single-nucleus RNA-sequencing resource of 70,615 high-quality nuclei to generate a molecular taxonomy of cell types across five human brain regions that serve as key nodes of the human brain reward circuitry: nucleus accumbens, amygdala, subgenual anterior cingulate cortex, hippocampus, and dorsolateral prefrontal cortex. We first identified novel subpopulations of interneurons and medium spiny neurons (MSNs) in the nucleus accumbens and further characterized robust GABAergic inhibitory cell populations in the amygdala. Joint analyses across the 107 reported cell classes revealed cell-type substructure and unique patterns of transcriptomic dynamics. We identified discrete subpopulations of D1- and D2-expressing MSNs in the nucleus accumbens to which we mapped cell-type-specific enrichment for genetic risk associated with both psychiatric disease and addiction.</pubmed_abstract><journal>Neuron</journal><pubmed_title>Single-nucleus transcriptome analysis reveals cell-type-specific molecular signatures across reward circuitry in the human brain.</pubmed_title><pmcid>PMC8564763</pmcid><funding_grant_id>R01 MH123183</funding_grant_id><funding_grant_id>R01 DA042090</funding_grant_id><funding_grant_id>1R01MH123183</funding_grant_id><funding_grant_id>R01DA042090</funding_grant_id><funding_grant_id>R00 HG009007</funding_grant_id><funding_grant_id>R00HG009007</funding_grant_id><pubmed_authors>Collado-Torres L</pubmed_authors><pubmed_authors>Kleinman JE</pubmed_authors><pubmed_authors>Maynard KR</pubmed_authors><pubmed_authors>Tippani M</pubmed_authors><pubmed_authors>Huuki LA</pubmed_authors><pubmed_authors>Sadashivaiah V</pubmed_authors><pubmed_authors>Tran MN</pubmed_authors><pubmed_authors>Hicks SC</pubmed_authors><pubmed_authors>Hyde TM</pubmed_authors><pubmed_authors>Montgomery KD</pubmed_authors><pubmed_authors>Martinowich K</pubmed_authors><pubmed_authors>Spangler A</pubmed_authors><pubmed_authors>Hancock DB</pubmed_authors><pubmed_authors>Jaffe AE</pubmed_authors><pubmed_authors>Barry BK</pubmed_authors></additional><is_claimable>false</is_claimable><name>Single-nucleus transcriptome analysis reveals cell-type-specific molecular signatures across reward circuitry in the human brain.</name><description>Single-cell gene expression technologies are powerful tools to study cell types in the human brain, but efforts have largely focused on cortical brain regions. We therefore created a single-nucleus RNA-sequencing resource of 70,615 high-quality nuclei to generate a molecular taxonomy of cell types across five human brain regions that serve as key nodes of the human brain reward circuitry: nucleus accumbens, amygdala, subgenual anterior cingulate cortex, hippocampus, and dorsolateral prefrontal cortex. We first identified novel subpopulations of interneurons and medium spiny neurons (MSNs) in the nucleus accumbens and further characterized robust GABAergic inhibitory cell populations in the amygdala. Joint analyses across the 107 reported cell classes revealed cell-type substructure and unique patterns of transcriptomic dynamics. We identified discrete subpopulations of D1- and D2-expressing MSNs in the nucleus accumbens to which we mapped cell-type-specific enrichment for genetic risk associated with both psychiatric disease and addiction.</description><dates><release>2021-01-01T00:00:00Z</release><publication>2021 Oct</publication><modification>2025-04-18T17:16:44.123Z</modification><creation>2025-04-07T04:46:28.84Z</creation></dates><accession>S-EPMC8564763</accession><cross_references><pubmed>34582785</pubmed><doi>10.1016/j.neuron.2021.09.001</doi></cross_references></HashMap>