Data from: Oxytocin and dopamine receptor expression: Cellular level implications for pair bonding
Data files
Jun 21, 2025 version files 4.83 MB
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R3_L1_NM_cellular_distribution_8_bit_v3.xlsx
900.54 KB
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R3_L1_NP_cellular_distribution_8_bit_v3.xlsx
939.89 KB
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R3_L1_Oxtr_Puncta_Counts_v3.xlsx
1.03 MB
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R3_L1_PM_cellular_distribution_8_bit_v4.xlsx
1.10 MB
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R3_L1_PP_cellular_distribution_8_bit_v3.xlsx
855.50 KB
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README.md
5.81 KB
Abstract
Oxytocin (Oxtr) and dopamine (Drd1, Drd2) receptors provide a canonical example for how differences in neuromodulatory receptors drive individual and species-level behavioral variation. These systems exhibit striking and functionally-relevant differences in nucleus accumbens (NAc) expression across monogamous prairie voles (Microtus ochrogaster) and promiscuous meadow voles (Microtus pennsylvanicus). However, their cellular organization remains largely unknown. Using multiplex in situ hybridization, we mapped Oxtr, Drd1, and Drd2 expression in sexually naïve and mate-paired prairie and meadow voles. Prairie voles have more Oxtr+ cells than meadow voles, but Oxtr distribution across dopamine-receptor cell class was similar, indicating a general upregulation rather than cell class bias. Oxtr was enriched in cells that express both dopamine receptors (Drd1+/Drd2+) in prairie voles, suggesting these cells may be particularly sensitive to oxytocin. We found no species or pairing-induced differences in Drd1+ or Drd2+ cell counts, suggesting prior reports of expression differences may reflect upregulation in cells already expressing these receptors. Finally, we used single-nucleus sequencing to provide the first comprehensive map of Oxtr and Drd1-5 across molecularly-defined NAc cell types in the prairie vole. These results provide a critical framework for understanding how nonapeptide and catecholamine systems may recruit distinct NAc cell types to shape social behavior.
Dataset DOI: 10.5061/dryad.s1rn8pkk3
Description of the data and file structure
Data Description
This dataset was collected from four cohorts of voles:
- Sexually naive prairie voles (NP)
- Sexually naive meadow voles (NM)
- Pairbonded prairie voles (PP)
- Paired meadow voles (PM)
Data was obtained through microscopy image analysis using Fiji ImageJ software.
Data Collection & Processing
Microscopy Analysis
- DAPI masks were generated using the Analyze Particles function in Fiji ImageJ. Each region of interest (ROI) represents a nucleus.
- The presence or absence of transcript was assessed for each ROI across three channels: D1DR (Drd1), D2DR (Drd2), and OXTR (Oxtr).
- Data collected per ROI included:
- ROI number
- ROI area
- Mean, minimum, and maximum gray values
- Percent area covered by pixels
Oxtr Puncta Quantification
- Oxtr puncta counts were recorded in the Oxtr Puncta Counts file for all four cohorts.
- Secondary Object Count (Sec_Object Count) was collected only for the OXTR channel, representing the number of puncta per ROI.
- Puncta detection utilized:
- Morphological Filters Plugin (GitHub link)
- Object Inspector (2D/3D) Plugin
Regional Classification
- Each ROI was assigned a Region1 category:
- Core1 = Core of the nucleus accumbens
- Shell1 = Medial shell
- Shell3 = Lateral shell
- The Region variable specifies subregion and hemisphere (left/right).
- Rostral-caudal levels (RC levels) of the nucleus accumbens were recorded.
Files and variables
File: R3_L1_PM_cellular_distribution_8_bit_v4.xlsx
Description: rostral-caudal level 1, paired meadow voles, transcript distribution data (8 bit)
Variables
- Region1 (nucleus accumbens subregion),
- Region (nucleus accumbens subregion with laterality indicated),
- Channel (label for transcript examined in that wavelength) ,
- ROI (region of interest = nucleus) ,
- Area (of nucleus/ROI),
- Mean (gray value of transcript in that ROI in that channel indicated),
- Min (gray value of transcript in that ROI in that channel indicated),
- Max (gray value of transcript in that ROI in that channel indicated),
- % Area (amount of area with nonzero pixels within ROI for that channel),
- Sec Object Count (Oxtr puncta for OXTR channel only). Values are blank for D1DR and D2DR channels in this column.
File: R3_L1_NM_cellular_distribution_8_bit_v3.xlsx
Description: rostral-caudal level 1, naive meadow voles, transcript distribution data (8 bit)
Variables
- Region1 (nucleus accumbens subregion),
- Region (nucleus accumbens subregion with laterality indicated),
- Channel (label for transcript examined in that wavelength) ,
- ROI (region of interest = nucleus) ,
- Area (of nucleus/ROI),
- Mean (gray value of transcript in that ROI in that channel indicated),
- Min (gray value of transcript in that ROI in that channel indicated),
- Max (gray value of transcript in that ROI in that channel indicated),
- % Area (amount of area with nonzero pixels within ROI for that channel),
- Sec Object Count (Oxtr puncta for OXTR channel only). Values are blank for D1DR and D2DR channels in this column.
File: R3_L1_NP_cellular_distribution_8_bit_v3.xlsx
Description: rostral-caudal level 1, naive prairie voles, transcript distribution data (8 bit)
Variables
- Region1 (nucleus accumbens subregion),
- Region (nucleus accumbens subregion with laterality indicated),
- Channel (label for transcript examined in that wavelength) ,
- ROI (region of interest = nucleus) ,
- Area (of nucleus/ROI),
- Mean (gray value of transcript in that ROI in that channel indicated),
- Min (gray value of transcript in that ROI in that channel indicated),
- Max (gray value of transcript in that ROI in that channel indicated),
- % Area (amount of area with nonzero pixels within ROI for that channel),
- Sec Object Count (Oxtr puncta for OXTR channel only). Values are blank for D1DR and D2DR channels in this column.
File: R3_L1_PP_cellular_distribution_8_bit_v3.xlsx
Description: rostral-caudal level 1, pairbonded prairie voles, transcript distribution data (8 bit)
Variables
- Region1 (nucleus accumbens subregion),
- Region (nucleus accumbens subregion with laterality indicated),
- Channel (label for transcript examined in that wavelength) ,
- ROI (region of interest = nucleus) ,
- Area (of nucleus/ROI),
- Mean (gray value of transcript in that ROI in that channel indicated),
- Min (gray value of transcript in that ROI in that channel indicated),
- Max (gray value of transcript in that ROI in that channel indicated),
- % Area (amount of area with nonzero pixels within ROI for that channel),
- Sec Object Count (Oxtr puncta for OXTR channel only). Values are blank for D1DR and D2DR channels in this column.
File: R3_L1_Oxtr_Puncta_Counts_v2.xlsx
Description: Oxtr puncta counts per ROI for naive prairie voles, naive meadow voles, pairbonded prairie voles, and paired meadow voles
Variables
- Animal # (sex is M or F and number is corresponding number given in colony)
- Species (meadow or prairie vole)
- Bond status (sexually naive or paired(bonded)
- RC level (rostral caudal of nucleus accumbens; only level 1 is in this data set)
- Region1 (subregion of nucleus accumbens)
- Region (subregion of nucleus accumbens with laterality indicated)
- ROI (region of interest corresponds to each nuclei detected)
- Sec Object Count (# of Oxtr puncta detected within ROI)
- Volume (^3) (data not used)
Code/software
Data files are in Excel sheets. Data sorting was done through Python scripts found on Donaldson Lab Github
Images were analyzed using Fiji ImageJ software (version 2.14.0/1.54f). Images were split into four channels:
- Channel 0 = DAPI
- Channel 1 = Drd1
- Channel 2 = Drd2
- Channel 3 = Oxtr
Regions of interest (ROIs) outlining DAPI-stained nuclei were automatically generated in Fiji ImageJ. Thresholds for DAPI nuclear staining were manually established to eliminate background and accurately overlay nuclei.
DAPI Mask Validation
- Accuracy was verified in 10% of images (one per animal) by comparing experimenter-counted vs. automatic nuclei counts.
- Counts differed by ≤5%, supporting the reliability of automatic ROI generation.
Signal Detection & Quantification
- The DAPI mask overlay was applied to Drd1, Drd2, and Oxtr images (Fig. 1C).
- A white top-hat transformation enhanced contrast, improving bright feature detection.
- Collected signal data included:
- ROI number (nucleus number)
- Minimum, mean, and maximum intensity values
- % area (for both 16-bit and 8-bit data)
Data Processing & Analysis
- Cellular distribution data was analyzed via custom Python code (GitHub repository).
- This script identified:
- Positively labeled nuclei for each channel
- Double and triple-labeled cells (co-expression)
Oxtr Puncta Quantification
- Oxtr puncta were quantified using:
- Morphological Filters Plugin (GitHub link)
- Object Inspector (2D/3D) Plugin