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Spatially resolved transcriptomic profiling of degraded and challenging fresh frozen samples

Author

Listed:
  • Reza Mirzazadeh

    (KTH Royal Institute of Technology, Science for Life Laboratory)

  • Zaneta Andrusivova

    (KTH Royal Institute of Technology, Science for Life Laboratory)

  • Ludvig Larsson

    (KTH Royal Institute of Technology, Science for Life Laboratory)

  • Phillip T. Newton

    (Karolinska University Hospital)

  • Leire Alonso Galicia

    (KTH Royal Institute of Technology, Science for Life Laboratory)

  • Xesús M. Abalo

    (KTH Royal Institute of Technology, Science for Life Laboratory)

  • Mahtab Avijgan

    (Karolinska University Hospital)

  • Linda Kvastad

    (KTH Royal Institute of Technology, Science for Life Laboratory)

  • Alexandre Denadai-Souza

    (Katholieke Universiteit te Leuven)

  • Nathalie Stakenborg

    (Katholieke Universiteit te Leuven)

  • Alexandra B. Firsova

    (Wenner-Gren Institute, Stockholm University, Science for Life Laboratory)

  • Alia Shamikh

    (Karolinska Institutet
    Karolinska University Hospital)

  • Aleksandra Jurek

    (10x Genomics)

  • Niklas Schultz

    (Karolinska Institutet, BioClinicum, Karolinska University Hospital)

  • Monica Nistér

    (Karolinska Institutet, BioClinicum, Karolinska University Hospital)

  • Christos Samakovlis

    (Wenner-Gren Institute, Stockholm University, Science for Life Laboratory)

  • Guy Boeckxstaens

    (Katholieke Universiteit te Leuven)

  • Joakim Lundeberg

    (KTH Royal Institute of Technology, Science for Life Laboratory)

Abstract

Spatially resolved transcriptomics has enabled precise genome-wide mRNA expression profiling within tissue sections. The performance of methods targeting the polyA tails of mRNA relies on the availability of specimens with high RNA quality. Moreover, the high cost of currently available spatial resolved transcriptomics assays requires a careful sample screening process to increase the chance of obtaining high-quality data. Indeed, the upfront analysis of RNA quality can show considerable variability due to sample handling, storage, and/or intrinsic factors. We present RNA-Rescue Spatial Transcriptomics (RRST), a workflow designed to improve mRNA recovery from fresh frozen specimens with moderate to low RNA quality. First, we provide a benchmark of RRST against the standard Visium spatial gene expression protocol on high RNA quality samples represented by mouse brain and prostate cancer samples. Then, we test the RRST protocol on tissue sections collected from five challenging tissue types, including human lung, colon, small intestine, pediatric brain tumor, and mouse bone/cartilage. In total, we analyze 52 tissue sections and demonstrate that RRST is a versatile, powerful, and reproducible protocol for fresh frozen specimens of different qualities and origins.

Suggested Citation

  • Reza Mirzazadeh & Zaneta Andrusivova & Ludvig Larsson & Phillip T. Newton & Leire Alonso Galicia & Xesús M. Abalo & Mahtab Avijgan & Linda Kvastad & Alexandre Denadai-Souza & Nathalie Stakenborg & Ale, 2023. "Spatially resolved transcriptomic profiling of degraded and challenging fresh frozen samples," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-36071-5
    DOI: 10.1038/s41467-023-36071-5
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    References listed on IDEAS

    as
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