Jun 15, 2026
URMC TriState SenNet TMC Visium HD Spatial Transcriptomics of Human Lung Tissue
- 1University of Rochester;
- 2University of Rochester Medical Center
External link: https://data.sennetconsortium.org/
Protocol Citation: Sadiya Shaikh, Gloria Pryhuber, Irfan Rahman 2026. URMC TriState SenNet TMC Visium HD Spatial Transcriptomics of Human Lung Tissue. protocols.io https://dx.doi.org/10.17504/protocols.io.n92ldo338g5b/v1
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
Created: June 05, 2026
Last Modified: June 15, 2026
Protocol Integer ID: 318559
Keywords: Visium HD, Spatial Transcriptomics, 10x Genomics, Human Lung, Pediatric Lung, Bronchopulmonary Dysplasia, BPD, Lung Development, Spatial Gene Expression, Spatial Omics, Single-Nucleus RNA Sequencing, Cellular Senescence, urmc tristate sennet tmc visium hd spatial transcriptomic, downstream analysis of human pediatric lung tissue, comprehensive pediatric lung atlas, 10x genomics visium hd spatial gene expression platform, spatial transcriptomic dataset, normal lung development, spatial proteomics dataset, resolution spatial maps of gene expression, human pediatric lung tissue, resolved transcriptomic profiling, transcriptomic profiling, lung tissue, human lung tissue, diseased lung, cellular states across health, donors with bronchopulmonary dysplasia, bronchopulmonary dysplasia, nucleus rna sequencing, cellular senescence network, rna, gene expression, tissue microenvironment
Funders Acknowledgements:
NIH Common Fund: Senescence Network
Grant ID: U54AG075931
NHLBI LungMAP BRINDL Repository
Grant ID: U01HL148861
Disclaimer
This protocol was developed for research use and is optimized for human pediatric lung tissue specimens processed using the 10x Genomics Visium HD Spatial Gene Expression platform. Users should adapt parameters as needed for their specific tissue type and experimental design.
Abstract
This protocol describes the preparation, processing, imaging, library construction, sequencing, and downstream analysis of human pediatric lung tissue specimens using the 10x Genomics Visium HD Spatial Gene Expression platform. The workflow was applied to lung tissues obtained from pediatric control donors and donors with bronchopulmonary dysplasia (BPD) to generate high-resolution spatial maps of gene expression within the developing and diseased lung.
The protocol preserves tissue architecture while enabling spatially resolved transcriptomic profiling of cellular and molecular heterogeneity associated with normal lung development and BPD pathology. Spatial transcriptomic datasets generated using this workflow was integrated with complementary single-nucleus RNA sequencing, multiplex fluorescence imaging, and spatial proteomics datasets to support construction of a comprehensive pediatric lung atlas, contributing to the Cellular Senescence Network (SenNet) efforts to map tissue microenvironments and cellular states across health and disease.
Materials
Reagents
- Visium HD Human Transcriptome Assay, 6.5 mm (10x Genomics; PN-1000673 or PN-1000675, depending on reaction format)
- Visium HD Human Whole Transcriptome (WT) Probe Panel (10x Genomics)
- Visium CytAssist Reagent Accessory Kit (10x Genomics; PN-1000499)
- Dual Index Kit TS Set A (10x Genomics; PN-1000251)
- Xylene or equivalent deparaffinization reagent
- Ethanol (100%, 95%, and 70%)
- Hematoxylin
- Eosin
- Nuclease-free water
- Agilent High Sensitivity DNA Kit (or equivalent)
- Qubit dsDNA Assay Kit
Equipment
- Microtome
- Water bath
- CytAssist Instrument (10x Genomics)
- Visium HD Slides
- Brightfield slide scanner or microscope
- Qubit Fluorometer
- Agilent Bioanalyzer or TapeStation
- Illumina Sequencing Platform
Software
- Space Ranger (10x Genomics)
- Loupe Browser (10x Genomics)
- R
- Seurat
- ggplot2
- dplyr
Section 1. FFPE Tissue Sectioning and Slide Preparation
Obtain formalin-fixed paraffin-embedded (FFPE) pediatric lung tissue blocks from control and bronchopulmonary dysplasia (BPD) donors.
Section FFPE pediatric lung tissue blocks at 5 µm thickness using a microtome according to the Visium HD FFPE workflow.
Float sections on a water bath and mount onto Visium HD-compatible slides.
Dry tissue sections according to the manufacturer's recommendations before downstream processing.
Store prepared slides under appropriate conditions until deparaffinization and staining.
Section 2. Deparaffinization, H&E Staining, and Imaging
Deparaffinize FFPE tissue sections according to the 10x Genomics Visium HD FFPE protocol.
Perform hematoxylin and eosin (H&E) staining.
Acquire high-resolution brightfield images of stained tissue sections.
Evaluate tissue morphology and identify regions suitable for spatial transcriptomic analysis.
Section 3. CytAssist Transfer and Probe Hybridization
Load stained tissue slides and Visium HD capture slides into the CytAssist instrument.
Perform tissue transfer according to the manufacturer's instructions.
Verify successful transfer and proceed with probe hybridization.
Section 4. Library Construction and Quality Control
Generate Visium HD spatial gene expression libraries according to the 10x Genomics Visium HD FFPE protocol.
Perform cDNA amplification and library construction.
Assess library quality and fragment size distribution using an Agilent Bioanalyzer or equivalent platform.
Quantify final libraries using fluorometric methods.
Pool libraries for sequencing according to the manufacturer's recommendations.
Section 5. Sequencing
Sequence Visium HD libraries on an Illumina sequencing platform according to 10x Genomics specifications. Libraries were sequenced on an Illumina NovaSeq 6000 platform to a depth of ~200 million reads per sample
Generate raw base call files and convert them to FASTQ format.
Perform initial sequencing quality assessment prior to downstream analysis.
Section 6. Data Processing and Spatial Transcriptomic Analysis
Process raw sequencing data using Space Ranger HD software. Visualize using Loupe Browser.
Align sequencing reads to the human reference genome (GRCh38).
Generate spatial gene expression matrices and associated image outputs.
Import processed spatial transcriptomic data into Seurat v5. for downstream analysis.
Perform quality control, normalization, dimensionality reduction, clustering, and visualization. the Human Lung Cell Atlas reference was used for cell annotations.
Identify spatially variable genes and region-specific transcriptional programs.
Integrate Visium HD datasets with complementary single-nucleus RNA sequencing and spatial proteomic datasets.
Generate spatial expression maps to investigate cellular and molecular heterogeneity associated with pediatric lung development and bronchopulmonary dysplasia.
Protocol references
1. 10x Genomics. Visium HD Spatial Gene Expression for FFPE User Guide. 10x Genomics. Available at: https://www.10xgenomics.com/support/spatial-gene-expression-hd
2. Hao Y, Hao S, Andersen-Nissen E, Mauck WM, Zheng S, Butler A, Lee MJ, Wilk AJ, Darby C, Zager M, Hoffman P. Integrated analysis of multimodal single-cell data. Cell. 2021 Jun 24;184(13):3573-87.DOI: 10.1016/j.cell.2021.04.048
3.Stuart T, Butler A, Hoffman P, Hafemeister C, Papalexi E, Mauck WM, Hao Y, Stoeckius M, Smibert P, Satija R. Comprehensive integration of single-cell data. Cell. 2019 Jun 13;177(7):1888-902. DOI: 10.1016/j.cell.2019.05.031
4. Satija R, Farrell JA, Gennert D, Schier AF, Regev A. Spatial reconstruction of single-cell gene expression data. Nature Biotechnology. 2015 May;33(5):495-502.
5. Cellular Senescence Network (SenNet). SenNet Data Portal. Available at: https://data.sennetconsortium.org/. (No DOI available for the portal.)
Acknowledgements
This work was performed through the University of Rochester Medical Center (URMC) TriState Tissue Mapping Center (TMC) as part of the Cellular Senescence Network (SenNet) Consortium.
Human pediatric lung tissues from control and bronchopulmonary dysplasia (BPD) donors were processed and analyzed using the 10x Genomics Visium HD Spatial Gene Expression platform. We acknowledge the contributions of the University of Rochester Genomics Research Center (GRC), tissue procurement teams, and SenNet investigators who supported tissue processing, data generation, and computational analysis.