https://doi.org/10.5061/dryad.qrfj6q5nx

A detailed description of methodology and analysis that were followed in order to generate and process all included files can be found in the associated publication "Materials and Methods" section (https://pubmed.ncbi.nlm.nih.gov/38669575/).

1. Dataset: Fos-Seq

• Description: This dataset contains the results of a computational correlation analysis between brain-wide FOS expression (measured via whole-brain clearing) and the Allen Institute’s in situ hybridization (ISH) gene expression atlas.
• Methodology: Custom code was used to correlate spatial FOS patterns across experimental conditions with the expression patterns of specific genes to identify genetic markers associated with neuronal activation.

2. Dataset: snRNA-seq

• Description: Single-nucleus RNA sequencing (snRNA-seq) data from the Nucleus Accumbens (NAc).
• Sample Info: Samples were collected from dissected NAc tissue where virally delivered guide RNAs (gRNAs) were expressed.

3. Dataset: FOS_expression

• Description: Z-scored datasets of brain-wide FOS expression levels.
• Methodology: Samples were processed using whole-brain clearing (LifeCanvas Technologies) and stained with FOS-specific antibodies to map neuronal activity. Z-score transformation was applied along the sample axis per batch in order to correct for batch effects.

4. Dataset: FOS_expression_by_sample

• Description: Z-scored datasets of brain-wide FOS expression levels from individual samples.
• Methodology: Samples with repeated exposure to cocaine or morphine were processed using whole-brain clearing (LifeCanvas Technologies) and stained with FOS-specific antibodies to map neuronal activity. Samples with acute exposure to cocaine and morphine or withdrawal from repeated exposure were processed using a section-based approach and stained with FOS-specific antibodies to map neuronal activity. Z-score transformation was applied along the sample axis per batch in order to correct for batch effects.

Description of the data and file structure

1. Fos-Seq Dataset

File/Folder: Fos-Seq.zip

Sub-folder: PearsonR

Contains 6 CSV files. These files represent the output of the correlation analysis across different experimental conditions.

• Variables:
  • Gene: Official gene symbol.
  • Pearson_R: Computed Pearson correlation coefficient representing the spatial relationship between FOS and gene expression.
  • P-value: Statistical significance of the correlation.

Sub-folder: Fos-Seq (Implementation Files)

These 6 files are required to run the custom analysis code provided in the Jupyter Notebook.

• allGeneStructureInfo_allgenes_summary_struct.csv: Dataset derived from the Allen Institute ISH datasets; contains gene expression values mapped to specific brain structures.
• brain_region_dict.pkl: Python dictionary mapping brain region names to their specific Structure IDs.
• cfos_brain_acronym.pkl: Pickled list of brain acronyms used in the whole-brain FOS mapping datasets.
• gene_list_across_regions.pkl: Pickled data containing specific gene sets categorized by brain region.
• structure_tree_2017.csv: Hierarchical tree structure for brain regions (2017 Allen Brain Atlas version).
• Fos-Seq_function_Dryad.ipynb: Jupyter Notebook containing the Python code to implement the Fos-Seq analysis.

2. snRNA-seq Dataset

File/Folder: snRNA-seq.zip

Description: This dataset consists of single-nucleus RNA sequencing (snRNA-seq) data from dissected Nucleus Accumbens (NAc) samples. The experiment utilized virally delivered guide RNAs (gRNAs) to identify cell-type-specific transcriptomic responses.

Sub-folder: HH2NKDRX3

• Description: This folder contains the raw sequencing datasets (e.g., FASTQ or sparse matrix files) required for single-cell sequencing analysis and alignment, as well as a 230731_A00815_0649_BHH2NKDRX3.md5 file containing hashes for all FASTQ files to verify data integrity. These files serve as the primary data for processing through pipelines such as Cell Ranger.

Metadata File: feature_reference.csv

• Description: A reference file used during the sequencing analysis to map and recover specific guide RNA (gRNA) sequences from the raw data.

3. FOS_expression Dataset

File/Folder: FOS_expression.zip

Included Files:

• acute_cocaine_morphine_zscore.csv: Z-scored FOS expression data comparing responses to a single (acute) dose of cocaine and morphine.
• chronic_cocaine_morphine_zscore.csv: Z-scored FOS expression data following repeated exposure to cocaine and morphine.
• withdrawal_cocaine_morphine_zscore.csv: Z-scored FOS expression data during spontaneous withdrawal from repeated cocaine and morphine exposure.

Key Variables & Interpretation:

• Specificity (Categorical Key): This variable identifies the drug-specific nature of the FOS response:
  • 0: No significant response relative to the saline group.
  • 1: Cocaine-specific response.
  • 2: Morphine-specific response.
  • 3: Shared response (significant for both cocaine and morphine).

4. FOS_expression_by_sample Dataset

File/Folder: FOS_expression_by_sample.zip

Included Files:

• acute_withdrawal_cocaine_morphine_saline.xlsx: Z-scored FOS expression data comparing responses to a single (acute) dose of cocaine and morphine, or withdrawal from repeated exposure to cocaine and morphine per sample.
• chronic_cocaine_morphine_saline.xlsx: Z-scored FOS expression data following repeated exposure to cocaine and morphine per sample.

Key Variables & Interpretation:

• Row 1 (Categorical Key): each sample
• Column A (Categorical Key): each brain region

Sharing/Access information

For additional details or specific inquiries regarding this dataset, please contact the authors by email.

Code/Software

Please refer to the file Fos-Seq_function_Dryad.ipynb located within the Fos-Seq.zip dataset for the custom Python code used to perform the analysis and generate the correlations.