Dataset DOI: 10.5061/dryad.s1rn8pkk3
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.
- 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 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
- 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.
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.
- 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.
- 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)
- 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 were quantified using:
- Morphological Filters Plugin (GitHub link)
- Object Inspector (2D/3D) Plugin
Description: rostral-caudal level 1, paired meadow voles, transcript distribution data (8 bit)
- 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.
Description: rostral-caudal level 1, naive meadow voles, transcript distribution data (8 bit)
- 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.
Description: rostral-caudal level 1, naive prairie voles, transcript distribution data (8 bit)
- 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.
Description: rostral-caudal level 1, pairbonded prairie voles, transcript distribution data (8 bit)
- 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.
Description: Oxtr puncta counts per ROI for naive prairie voles, naive meadow voles, pairbonded prairie voles, and paired meadow voles
- 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)
Data files are in Excel sheets. Data sorting was done through Python scripts found on Donaldson Lab Github