DOI: 10.5061/dryad.0rxwdbsbr
title: Wound image and transcriptome datasets of swine acute wounds

description: Wound healing progresses through overlapping phases: hemostasis,
 inflammation, proliferation, and remodeling. Continuous characterization
 of these transitions remains limited. Here, we employed a swine excisional
 wound model to monitor cellular dynamics across the healing timeline. Both
 non-invasive imaging and wound biopsy samples from the wound edge and
 center were acquired. Wound photographs were analyzed using advanced
 artificial intelligence methods. Wound biopsy samples were subject to RNA
 sequencing to generate gene expression profiles for the course of healing.
 By combining the image and the gene expression analyses, we were able to
 create the comprehensive data for wound healing, which can serve as ground
 truth for building wound diagnostic and treatment algorithms.
description: Six domestic pigs (Yorkshire-mix breed, females, 45-50 Kg) were
 utilized and divided to 2 groups (3 animals/group) for wound biopsy
 collection in a rotation order (group 1 biopsy on post-op day 1, 3, 5, 7,
 11, 15, and 21/endpoint; group 2 biopsy on day 2, 4, 6, 9, 13, 16, and
 19/endpoint).  Twelve full-thickness, excisional wounds at 2cm in diameter
 were created bilaterally on each side of the dorsum of each animal after
 shaving, depilation, and skin preparation.  Wound images (day 0-21) were
 captured with a DSLR camera at a set distance of 1 foot above the wounds,
 and a photo scale (Medline NE1 Wound Assessment Tool) was used for
 calibration in each image.  To determine the wound healing timeline, open
 wound areas were analyzed by manual tracking in ImageJ or automatically
 cropped and analyzed by algorithms. RNA samples (a
 total of 150 samples of 72 paired samples from the wound edge and center,
 and 6 healthy skin samples as controls) were extracted from the wound
 biopsies with Qiagen RNeasy Fibrous Tissue Mini Kit (Qiagen, German). 
 Around 200ng mRNA/sample were sent to Novogene (Beijiang, China) for
 RNAseq analysis, including RNA sample quality control, library preparation
 with poly-A enrichment, sequencing by Illumina sequencing system NovaSeq X
 Plus (PE150) for &gt;20 millions paired reads, generation of raw data
 in the FASTQ format, and aligned for gene counts.   The
 transcriptome data is represented by the table of gene expression counts
 "gene_count.xlsx", where each row represents a gene and each
 column represents a sample.  The column names are SampleID labels.  The
 encoding of sample labels is explained in the table
 "CodesDaVinci.xlsx".  This table contains the pig ID, wound
 number, day of collection from the wound onset, and wound location label
 (center or edge). The expression time series plots of other genes can be
 found through an online tool at https://geneexpressionsearch.pythonanywhere.com.
description: # Wound image and transcriptome datasets of swine acute wounds Dataset
 DOI: [10.5061/dryad.0rxwdbsbr](10.5061/dryad.0rxwdbsbr) **Description of
 the data and file structure** The dataset contains observations from an
 acute wound healing experiment in pigs. Wound photographs and RNAseq data
 were collected at multiple time points from day 0 to day 21 post-wound
 onset. Tissue samples for RNAseq were taken from both wound edges and
 wound centers. Experiment description: Six domestic pigs (Yorkshire-mix
 breed, females, 45-50 Kg, pig ID: 1323, 1324, 1325, 1326, 1327, and 1328)
 were utilized. Twelve full-thickness, circular excision wounds (2 cm in
 diameter, wound ID: A, B, C, D, E, F, G, H, I, J, K, and L) were created
 in each animal. Baseline (Day 0) wound images and the excised skin tissue
 were collected. During the post-operative period, wound images and biopsy
 samples from the wound edge and wound center were collected on
 post-operative days 1, 2, 3, 4, 5, 6, 7, 9, 11, 13, 15, 16, 19, and 21.
 The biopsy samples were sent for RNA sequencing analysis. Wound images are
 provided as `.JPG` files. For some images, both the standard compressed
 `.JPG` file and the corresponding source `.CR2` file are available. The
 `.CR2` files are Canon RAW images, which are uncompressed and may be
 useful for users requiring the highest image quality for re-analysis.
 Files with the same name but different extensions (`.JPG` and `.CR2`)
 represent the same image. The `.CR2` format can be opened with specialized
 image processing software such as Adobe Photoshop, ImageJ (with the
 appropriate plugins), or other RAW image converters. **Files and
 variables** **Data and files structure**: **RNAseq_dataset-20250825.zip:**
 1. RNAseq Codes.csv: Sample labels. 2. PigWoundRNAData.xlsx: Combined gene
 expression and sample data file.             Columns represent samples,
 rows represent genes.             Ensemble ID is provided in the last
 column.             Sample information (see last 4 rows):             Day:
 Day from wound onset.             Pig: 6 animals with the following IDs:
 1323, 1324, 1325, 1326, 1327, 1328.             Wound: Wound ID. Each
 animal had 12 wounds, labeled by letters A to L. Wound ID is not specified
 for day 0 samples, which are labeled as "U" (undefined).        
     Edge/Center: Location of the sample in the wound. "e"
 indicates the edge, and "c" indicates the center. Sample
 location is not specified for day 0 samples, which are labeled as
 "n". **Wound_photo_cropped.zip**: 1. Cropped image codes.csv: A
 list of images with the following metadata: day, pig ID, wound ID, image
 filename, and folder names. 2. Cropped Wound images: Pre-processed images
 cropped into circles containing the whole wound.
 **WoundPhotos-Day_0-Pig_1323.zip**: Original images of wound A to L from
 pig 1323 on day 0. A wound scale and ruler are included.
 **WoundPhotos-Day_0-Pig_1324.zip**: Original images of wound A to L from
 pig 1324 on day 0. **WoundPhotos-Day_0-Pig_1325.zip**: Original images of
 wound A to L from pig 1325 on day 0. **WoundPhotos-Day_0-Pig_1326.zip**:
 Original images of wound A to L from pig 1326 on day 0.
 **WoundPhotos-Day_0-Pig_1327.zip**: Original images of wound A to L from
 pig 1327 on day 0. **WoundPhotos-Day_0-Pig_1328.zip**: Original images of
 wound A to L from pig 1328 on day 0. **WoundPhotos-Day_1.zip**: Original
 images of wounds on day 1. **WoundPhotos-Day_2.zip**: Original images of
 wounds on day 2. **WoundPhotos-Day_3.zip**: Original images of wounds on
 day 3. **WoundPhotos-Day_4.zip**: Original images of wounds on day 4.
 **WoundPhotos-Day_5.zip**: Original images of wounds on day 5.
 **WoundPhotos-Day_6.zip**: Original images of wounds on day 6.
 **WoundPhotos-Day_7.zip**: Original images of wounds on day 7.
 **WoundPhotos-Day_9.zip**: Original images of wounds on day 9.
 **WoundPhotos-Day_11.zip**: Original images of wounds on day 11.
 **WoundPhotos-Day_13.zip**: Original images of wounds on day 13.
 **WoundPhotos-Day_15.zip**: Original images of wounds on day 15.
 **WoundPhotos-Day_16.zip**: Original images of wounds on day 16.
 **WoundPhotos-Day_19.zip**: Original images of wounds on day 19.
 **WoundPhotos-Day_21.zip**: Original images of wounds on day 21.
 **Code/software** This dataset is linked to an online gene time series
 plotting tool:     
  [https://geneexpressionsearch.pythonanywhere.com/](https://geneexpressionsearch.pythonanywhere.com/) The code for the tool is provided in a GitHub repository: [https://github.com/mkesapra/GeneExpressionSearch](https://github.com/mkesapra/GeneExpressionSearch) **Access information** Raw gene sequencing data, NCBI Sequence Read Archive: [https://www.ncbi.nlm.nih.gov/sra/?term=SRP591687](https://www.ncbi.nlm.nih.gov/sra/?term=SRP591687) [https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA1276066](https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA1276066) Original and normalized gene transcript counts, NCBI Gene Expression Omnibus:  [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE305817](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE305817) Related publication: Zlobina, K., Yang, H., Kesapragada, M., Lu, F., Gallegos, A., Villa-Martinez, G., Alhamo, M.A., Zhu, K., Recendez, C., Collins, C., Rolandi, M., Soulika, A., Aslankoohi, E., Zhao, M., Gomez, M., & Isseroff, R.R. (2025). A high-resolution temporal transcriptomic and imaging dataset of porcine wound healing. Scientific Data.