Project description:Using RNAseq, we evaluated transcriptomic changes in the ventral pallidum (VP) of mice 24h following 10 days of cocaine self-administration.
Project description:The ventral pallidum (VP) was defined as a basal ganglia nucleus and a major output of the nucleus accumbens. It is known to be involved in motivated behaviors, including feeding. We sought to further characterize VP by sequencing the RNA from individual nuclei in mouse and rat VP and analyzing neuronal expression patterns. We also investigated the impact of a high-fat diet on VP transcription. These data will be useful for understanding cell type diversity in VP, homology between mouse and rat VP, and the impact of diet on VP gene expression.
Project description:The ventral pallidum (VP) is critical for motivated behaviors. While contemporary work has begun to elucidate the functional diversity of VP neurons, the molecular heterogeneity underlying this functional diversity remains incompletely understood. We used snRNA-seq and in situ hybridization to define the transcriptional taxonomy of VP cell types in mice, macaques, and baboons. We found transcriptional conservation between all three species, within the broader neurochemical cell types. Unique dopaminoceptive and cholinergic subclusters were identified and conserved across both primate species but had no homolog in mice. This harmonized consensus VP cellular atlas will pave the way for understanding the structure and function of the VP and identified key neuropeptides, neurotransmitters, and neuro receptors that could be targeted within specific VP cell types for functional investigations.
Project description:Emerging imaging spatial transcriptomics (iST) platforms and coupled analytical methods can recover cell-to-cell interactions, groups of spatially covarying genes, and gene signatures associated with pathological features, and are thus particularly well-suited for applications in formalin fixed paraffin embedded (FFPE) tissues. Here, we benchmark the performance of three commercial iST platforms—10X Xenium, Vizgen MERSCOPE, and Nanostring CosMx—on serial sections from tissue microarrays (TMAs) containing 17 tumor and 16 normal tissue types for both relative technical and biological performance. On matched genes, we find that Xenium consistently generates higher transcript counts per gene without sacrificing specificity. Xenium and CosMx measure RNA transcripts in concordance with orthogonal single-cell transcriptomics. All three platforms can perform spatially resolved cell typing with varying degrees of sub-clustering capabilities, with Xenium and CosMx finding slightly more clusters than MERSCOPE, albeit with different false discovery rates and cell segmentation error frequencies. Taken together, our analyses provide a comprehensive benchmark to guide the choice of iST method as researchers design studies with precious samples in this rapidly evolving field.
Project description:Patients with treatment-refractory pancreatic cancer often succumb to widespread systemic metastases; however, the transcriptomic heterogeneity that underlies recalcitrance to therapy remains understudied, particularly in the spatial context. We constructed high-resolution spatial maps of transcriptional heterogeneity, clonal architecture and lineage plasticity using spatially resolved transcriptomics (SRT) from 13 primary cancers and 36 corresponding liver, lung, and peritoneal metastases, collected via a rapid (“warm”) autopsy program. To validate findings from our SRT dataset at single-cell resolution, we performed CosMX SMI profiling (Nanostring) on 7 samples from 3 patients, including primary and/or liver metastasis.
Project description:Inflammatory bowel diseases (IBDs) including ulcerative colitis (UC) and Crohn’s disease (CD) are chronic inflammatory diseases with increasing worldwide prevalence that show a perplexing heterogeneity in manifestations and response to treatment. We applied spatial transcriptomics at single-cell resolution (CosMx Spatial Molecular Imaging) to human inflamed and uninflamed intestine.
Project description:In 10X Genomics Visium Spatial Gene Expression (ST), the resolution for distinguishing neighboring cells can be improved using data integration with single-cell/single-nuclei transcriptomics profiles. Besides, depending on the cell type and tissue, nuclei size may vary significantly to an extent that it may exceed the thickness of tissue slices. This may jeopardize capturing full transcriptomics profile of single slice due to the improper/incomplete incision of nuclei during cryosectioning process and this may cause drawbacks in downstream analysis. To monitor the probable consequences, we monitored the effect of consecutive slices data integration (CSDI) on improvement of cell type clustering and annotation through transferring cell labels from a single-nuclei transcriptomics dataset to ST. To do so, two consecutive slices from the orbitofrontal neocortex and temporal neocortex of two post mortem brain samples were obtained and their spatial transcriptomics profiles were retrieved using 10x Genomics Visium Spatial Gene Expression protocol. Using CSDI, not only the number of identified clusters were increased and the inconsistency between the pattern of clusters in consecutive slices was resolved, but the layered-structure of gray matter was unveiled. Besides, only after CSDI the transferred annotations from single-nuclei transcriptomics to ST could match the microscopic results. CSDI can improve the ST clustering and cell type annotation by providing the full signals coming from all cell types of single slice of tissue. The codes in R programming language are publicly available at https://github.com/ElyasMo/ST_snRNA-seq