Spatially resolved transcriptomic profiling of degraded and challenging fresh frozen samples

Reza Mirzazadeh, Zaneta Andrusivova, Ludvig Larsson, Phillip T. Newton, Leire Alonso Galicia, Xesús M. Abalo, Mahtab Avijgan, Linda Kvastad, Alexandre Denadai-Souza, Nathalie Stakenborg, Alexandra B. Firsova, Alia Shamikh, Aleksandra Jurek, Niklas Schultz, Monica Nistér, Christos Samakovlis, Guy Boeckxstaens and Joakim Lundeberg ()
Additional contact information
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
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

Nature Communications, 2023, vol. 14, issue 1, 1-16

Abstract: 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.

Date: 2023
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DOI: 10.1038/s41467-023-36071-5

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