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The gene expression landscape of the human locus coeruleus revealed by single-nucleus and spatially-resolved transcriptomics.

Lukas M Weber | Heena R Divecha | Matthew N Tran | Sang Ho Kwon | Abby Spangler | Kelsey D Montgomery | Madhavi Tippani | Rahul Bharadwaj | Joel E Kleinman | Stephanie C Page | Thomas M Hyde | Leonardo Collado-Torres | Kristen R Maynard | Keri Martinowich | Stephanie C Hicks
eLife | 2024

Norepinephrine (NE) neurons in the locus coeruleus (LC) make long-range projections throughout the central nervous system, playing critical roles in arousal and mood, as well as various components of cognition including attention, learning, and memory. The LC-NE system is also implicated in multiple neurological and neuropsychiatric disorders. Importantly, LC-NE neurons are highly sensitive to degeneration in both Alzheimer's and Parkinson's disease. Despite the clinical importance of the brain region and the prominent role of LC-NE neurons in a variety of brain and behavioral functions, a detailed molecular characterization of the LC is lacking. Here, we used a combination of spatially-resolved transcriptomics and single-nucleus RNA-sequencing to characterize the molecular landscape of the LC region and the transcriptomic profile of LC-NE neurons in the human brain. We provide a freely accessible resource of these data in web-accessible and downloadable formats.

Pubmed ID: 38266073

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Associated grants

  • Agency: NIH HHS, United States
    Id: U01MH122849
  • Agency: NIMH NIH HHS, United States
    Id: U01 MH122849
  • Agency: NHGRI NIH HHS, United States
    Id: K99 HG012229
  • Agency: NIH HHS, United States
    Id: K99HG012229
  • Agency: NIH HHS, United States
    Id: R01DA053581
  • Agency: NIDA NIH HHS, United States
    Id: R01 DA053581

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Bioconductor (tool)

RRID:SCR_006442

Software repository for R packages related to analysis and comprehension of high throughput genomic data. Uses separate set of commands for installation of packages. Software project based on R programming language that provides tools for analysis and comprehension of high throughput genomic data.

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LIMMA (tool)

RRID:SCR_010943

Software package for the analysis of gene expression microarray data, especially the use of linear models for analyzing designed experiments and the assessment of differential expression.

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