This project, led by Michael Totty, Rita Juanes, and Svitlana Bach, provides an in-depth transcriptomic analysis of amygdala cell types across human and two non-human primate (NHP) species. Using single nucleus RNA sequencing (10x Genomics), the study successfully characterizes the molecular diversity of neuronal cell types found within various subregions of the human and NHP amygdala, including the lateral (LA), basal (BA), accessory basal (aBA), and central nuclei (CeA).
This dataset includes high-quality snRNA-seq data generated from multiple human (n=5) and non-human primate donors (Olive Baboon, n=2; Rhesus Macaque, n=5), allowing for cross-species comparisons and the identification of conserved transcriptomic cell types. This dataset serves as a valuable resource for understanding the transcriptional architecture of the amygdala and its implications for psychiatric and neurological diseases. Both raw and processed data will be made publicly available upon preprint publication, making it a useful resource for future studies into BLA functionality, evolutionary conservation, and its role in neuropsychiatric conditions.
We have provided an interective website that allow you to explore all of the data at single nucleus resolution. This is powered by iSEE that allows you to add, hide, customize panels for visualizing the data. Due to the size of total dataset we have split the data into three separate apps, one for each species. You can create any custom visualizations that you want and download both the code to make them as well as the figures you make. Please check the iSEE documentation for instructions on how to customize the panels.
- Human BLA Shiny App: https://libd.shinyapps.io/BLA_Human/
- Macaque BLA Shiny App: https://libd.shinyapps.io/BLA_Macaque/
- Baboon BLA Shiny App: https://libd.shinyapps.io/BLA_Baboon/
Links to access the raw and processed data will be made avaiable here shortly.
Please cite the peer-reviewed publication when using this data in your research:
Citation information will be added here once the preprint is available.