Toxicological SciencesGeneticsPeer-reviewed journal article
Mining the archives: a cross-platform analysis of gene expression profiles in archival formalin-fixed paraffin-embedded (FFPE) tissue
Anna Francina Webster, Paul Zumbo, Jennifer Fostel, Jorge Gandara, Susan D Hester, Leslie RecioiD, Andrew WilliamsiD, Chales Wood, Carole Yauk, Christopher E Mason
Abstract
Formalin-fixed paraffin-embedded (FFPE) tissue samples represent a potentially invaluable resource for transcriptomic-based research into the molecular basis of disease. However, use of FFPE samples in gene expression studies has been limited by technical challenges resulting from degradation of nucleic acids. Here we evaluated gene expression profiles derived from fresh-frozen (FRO) and FFPE mouse liver tissues using two DNA microarray protocols and two whole transcriptome sequencing (RNA-seq) library preparation methodologies. The ribo-depletion protocol outperformed the other three methods by having the highest correlations of differentially expressed genes (DEGs) and best overlap of pathways between FRO and FFPE groups. We next tested the effect of sample time in formalin (18 hours or 3 weeks) on gene expression profiles. Hierarchical clustering of the datasets indicated that test article treatment, and not preservation method, was the main driver of gene expression profiles. Meta- and pathway analyses indicated that biological responses were generally consistent for 18-hour and 3-week FFPE samples compared to FRO samples. However, clear erosion of signal intensity with time in formalin was evident, and DEG numbers differed by platform and preservation method. Lastly, we investigated the effect of age in FFPE block on genomic profiles. RNA-seq analysis of 8-, 19-, and 26-year-old control blocks using the ribo-depletion protocol resulted in comparable quality metrics, including expected distributions of mapped reads to exonic, UTR, intronic, and ribosomal fractions of the transcriptome. Overall, our results suggest that FFPE samples are appropriate for use in genomic studies in which frozen samples are not available, and that ribo-depletion RNA-seq is the preferred method for this type of analysis in archival and long-aged FFPE samples.\n\nAuthor contributions\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@124589eorg.highwire.dtl.DTLVardef@1361ddeorg.highwire.dtl.DTLVardef@1e30065org.highwire.dtl.DTLVardef@2f0ed5org.highwire.dtl.DTLVardef@176fc83_HPS_FORMAT_FIGEXP M_TBL C_TBL
- organism: mouse
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: experimental assay
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Extraction-Free Whole Transcriptome Gene Expression Analysis of FFPE Sections and Histology-Directed Subareas of Tissue
Christy L. Trejo, Miloš Babić, … Bruce E. Seligmann·PLoS ONEPeer-reviewed·Feb 22, 2019
- Reproducible and sensitive micro-tissue RNA-sequencing from formalin-fixed paraffin-embedded tissue for spatial gene expression analysis
Hiroko Matsunaga, Koji Arikawa, … Haruko Takeyama·Scientific ReportsPeer-reviewed·Nov 14, 2022
- Generative and integrative modeling for transcriptomics with formalin fixed paraffin embedded material
Eliseos J. Mucaki, Wenhan Zhang, … Michael T. Hallett·Journal of Translational MedicinePeer-reviewed·Sep 30, 2025
- Impact of RNA Extraction and Target Capture Methods on RNA Sequencing Using Formalin-Fixed, Paraffin Embedded Tissues
Christopher A. Hilker, Aditya Vijay Bhagwate, … Jin Jen·bioRxiv·May 31, 2019
- Comprehensive characterization of genomic, transcriptomic and epigenomic artifacts introduced in formalin-fixed, paraffin-embedded tissues.
Erik J. Zmuda, Kyle R Covington, … Katherine A Hoadley·Cancer GeneticsPeer-reviewed·Jun 6, 2017
- Quantification of Human DNA from Century-Old Archived FFPE Samples for Retrospective Genomic Studies
Vincent Zvénigorosky, Angéla Gonzalez, … Christian Bonah·bioRxiv·Oct 17, 2025