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snPATHO-seq: unlocking the FFPE archives for single nucleus RNA profiling

snPATHO-seq: unlocking the FFPE archives for single nucleus RNA profiling
snPATHO-seq: unlocking the FFPE archives for single nucleus RNA profiling
FFPE (formalin-fixed, paraffin-embedded) tissue archives are the largest repository of clinically annotated human specimens. Despite numerous advances in technology, current methods for sequencing of FFPE-fixed single-cells are slow, labour intensive, insufficiently sensitive and have a low resolution, making it difficult to fully exploit their enormous research and clinical potential. Here we introduce single nuclei pathology sequencing (snPATHO-Seq), a sensitive and efficient high-throughput platform to profile the transcriptome of single nuclei extracted from formalin-fixed paraffin-embedded (FFPE) samples. snPATHO-Seq combines an optimised nuclei extraction protocol from archival samples with 10x Genomics probe-based technology targeting the whole transcriptome. We performed direct comparison of the Fixed RNA Profiling (FRP) and established 3’ single cell RNA-Sequencing (scRNA-Seq) workflows through a comprehensive bioinformatics analysis of matched fresh and fixed samples derived from the LNCaP prostate cancer cell line. FRP detected 2.1 times more transcripts in the fixed sample than the 3’ kit did in the fresh sample. Low mitochondrial genes detection using the FRP was translated into 99.9 percent of cells passing the QC filters, compared to 81.6 percent of cells using the v3.1 chemistry. We then optimized snPATHO-Seq and applied it to a human breast cancer metastasis to the liver collected at autopsy and preserved in FFPE, a particularly challenging sample type. Remarkably, at 28,000 reads/cell snPATHO-Seq was able to detect a median of 1850 genes/cell and 3,216 UMI counts/cell. Comparison of snPATHO-Seq with spatial transcriptomics data (10x Genomics Visium FFPE v1) derived from an adjacent section of the same sample revealed a strong correlation, validating the accuracy of the snPATHO-Seq data. Gene expression data from snPATHO-Seq was used to predict cell type composition within each spatial transcriptomic location via deconvolution. Overall, snPATHO-Seq enables high quality and sensitivity snRNA-Seq from preserved tissue samples, unlocking the vast archives of FFPE tissues and thereby allowing extensive retrospective clinical genomic studies.
Vallejo, Andres F.
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Harvey, Kate
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Wang, Taopeng
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Wise, Kellie
dba28794-f4c1-4e69-90b9-dfc288747598
Butler, Lisa M.
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Polo, Jose
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Plummer, Jasmine
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Swarbrick, Alex
0eaeeeae-ab08-4828-a30e-5e650f7bc2bc
Martelotto, Luciano G
704436cf-1ee5-48be-a638-d18045571f3b
Vallejo, Andres F.
27bc0b94-0c40-4fd1-9533-7e267d588c0a
Harvey, Kate
93c6819e-7c23-4bfd-981f-c65d249d7692
Wang, Taopeng
a65a1b13-1e80-4ac4-ab18-b65747c1a808
Wise, Kellie
dba28794-f4c1-4e69-90b9-dfc288747598
Butler, Lisa M.
60f2fc74-9410-4f7f-afbc-c88670673855
Polo, Jose
f55d7039-bd9e-4e56-98e3-fdf3d118d4f3
Plummer, Jasmine
0a2ce6aa-77ca-4247-b7ce-fade57261d71
Swarbrick, Alex
0eaeeeae-ab08-4828-a30e-5e650f7bc2bc
Martelotto, Luciano G
704436cf-1ee5-48be-a638-d18045571f3b

[Unknown type: UNSPECIFIED]

Record type: UNSPECIFIED

Abstract

FFPE (formalin-fixed, paraffin-embedded) tissue archives are the largest repository of clinically annotated human specimens. Despite numerous advances in technology, current methods for sequencing of FFPE-fixed single-cells are slow, labour intensive, insufficiently sensitive and have a low resolution, making it difficult to fully exploit their enormous research and clinical potential. Here we introduce single nuclei pathology sequencing (snPATHO-Seq), a sensitive and efficient high-throughput platform to profile the transcriptome of single nuclei extracted from formalin-fixed paraffin-embedded (FFPE) samples. snPATHO-Seq combines an optimised nuclei extraction protocol from archival samples with 10x Genomics probe-based technology targeting the whole transcriptome. We performed direct comparison of the Fixed RNA Profiling (FRP) and established 3’ single cell RNA-Sequencing (scRNA-Seq) workflows through a comprehensive bioinformatics analysis of matched fresh and fixed samples derived from the LNCaP prostate cancer cell line. FRP detected 2.1 times more transcripts in the fixed sample than the 3’ kit did in the fresh sample. Low mitochondrial genes detection using the FRP was translated into 99.9 percent of cells passing the QC filters, compared to 81.6 percent of cells using the v3.1 chemistry. We then optimized snPATHO-Seq and applied it to a human breast cancer metastasis to the liver collected at autopsy and preserved in FFPE, a particularly challenging sample type. Remarkably, at 28,000 reads/cell snPATHO-Seq was able to detect a median of 1850 genes/cell and 3,216 UMI counts/cell. Comparison of snPATHO-Seq with spatial transcriptomics data (10x Genomics Visium FFPE v1) derived from an adjacent section of the same sample revealed a strong correlation, validating the accuracy of the snPATHO-Seq data. Gene expression data from snPATHO-Seq was used to predict cell type composition within each spatial transcriptomic location via deconvolution. Overall, snPATHO-Seq enables high quality and sensitivity snRNA-Seq from preserved tissue samples, unlocking the vast archives of FFPE tissues and thereby allowing extensive retrospective clinical genomic studies.

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2022.08.23.505054v4.full - Author's Original
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Published date: 6 December 2022

Identifiers

Local EPrints ID: 488838
URI: http://eprints.soton.ac.uk/id/eprint/488838
PURE UUID: bf27827c-b1b1-436d-bc07-02475ca43076
ORCID for Andres F. Vallejo: ORCID iD orcid.org/0000-0002-4688-0598

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Date deposited: 08 Apr 2024 16:35
Last modified: 13 Apr 2024 01:52

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Contributors

Author: Andres F. Vallejo ORCID iD
Author: Kate Harvey
Author: Taopeng Wang
Author: Kellie Wise
Author: Lisa M. Butler
Author: Jose Polo
Author: Jasmine Plummer
Author: Alex Swarbrick
Author: Luciano G Martelotto

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