Fixed-tissue ChIP-seq for H3K27 acetylation (H3K27ac) profiling (FiTAc-seq) is an epigenetic method for profiling active enhancers and promoters in formalin-fixed, paraffin-embedded (FFPE) tissues. We previously developed a modified ChIP-seq protocol (FiT-seq) for chromatin profiling in FFPE. FiT-seq produces high-quality chromatin profiles particularly for methylated histone marks but is not optimized for H3K27ac profiling. FiTAc-seq is a modified protocol that replaces the proteinase K digestion applied in FiT-seq with extended heating at 65 °C in a higher concentration of detergent and a minimized sonication step, to produce robust genome-wide H3K27ac maps from clinical samples. FiTAc-seq generates high-quality enhancer landscapes and super-enhancer (SE) annotation in numerous archived FFPE samples from distinct tumor types. This approach will be of great interest for both basic and clinical researchers. The entire protocol from FFPE blocks to sequence-ready library can be accomplished within 4 d.
Subscribe to Journal
Get full journal access for 1 year
only $41.25 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Cejas, P. & Long, H. W. Principles and methods of integrative chromatin analysis in primary tissues and tumors. Biochem. Biophys. Acta Rev. Cancer 1873, 188333 (2020).
Lin, C. Y. et al. Active medulloblastoma enhancers reveal subgroup-specific cellular origins. Nature 530, 57–62 (2016).
Consortium, T. E. P., The ENCODE Project Consortium. The ENCODE (ENCyclopedia Of DNA Elements) Project. Science 306, 636–640 (2004).
Bernstein, B. E. et al. The NIH Roadmap Epigenomics Mapping Consortium. Nat. Biotechnol. 28, 1045–1048 (2010).
Cejas, P. et al. Chromatin immunoprecipitation from fixed clinical tissues reveals tumor-specific enhancer profiles. Nat. Med 22, 685–691 (2016).
Creyghton, M. P. et al. Histone H3K27ac separates active from poised enhancers and predicts developmental state. Proc. Natl Acad. Sci. USA 107, 21931–21936 (2010).
Calo, E. & Wysocka, J. Modification of enhancer chromatin: what, how, and why? Mol. Cell 49, 825–837 (2013).
Zentner, G. E. & Scacheri, P. C. The chromatin fingerprint of gene enhancer elements. J. Biol. Chem. 287, 30888–30896 (2012).
Whyte, W. A. et al. Master transcription factors and mediator establish super-enhancers at key cell identity genes. Cell 153, 307–319 (2013).
Hnisz, D. et al. Super-enhancers in the control of cell identity and disease. Cell 155, 934–947 (2013).
Lovén, J. et al. Selective inhibition of tumor oncogenes by disruption of super-enhancers. Cell 153, 320–334 (2013).
Chipumuro, E. et al. CDK7 inhibition suppresses super-enhancer-linked oncogenic transcription in MYCN-driven cancer. Cell 159, 1126–1139 (2014).
Mack, S. C. et al. Therapeutic targeting of ependymoma as informed by oncogenic enhancer profiling. Nature 553, 101–105 (2018).
Cejas, P. et al. Enhancer signatures stratify and predict outcomes of non-functional pancreatic neuroendocrine tumors. Nat. Med 25, 1260–1265 (2019).
Zhong, J. et al. Enhanced and controlled chromatin extraction from FFPE tissues and the application to ChIP-seq. BMC Genomics 20, 249 (2019).
Amatori, S. et al. Epigenomic profiling of archived FFPE tissues by enhanced PAT-ChIP (EPAT-ChIP) technology. Clin. Epigenetics 10, 143 (2018).
Shi, S. R., Imam, S. A., Young, L., Cote, R. J. & Taylor, C. R. Antigen retrieval immunohistochemistry under the influence of pH using monoclonal antibodies. J. Histochem. Cytochem. 43, 193–201 (1995).
Qin, Q. et al. ChiLin: a comprehensive ChIP-seq and DNase-seq quality control and analysis pipeline. BMC Bioinforma. 17, 404 (2016).
Wang, S. et al. Modeling cis-regulation with a compendium of genome-wide histone H3K27ac profiles. Genome Res. 26, 1417–1429 (2016).
Zwart, W. et al. A carrier-assisted ChIP-seq method for estrogen receptor-chromatin interactions from breast cancer core needle biopsy samples. BMC Genomics 14, 232 (2013).
He, H. H. et al. Nucleosome dynamics define transcriptional enhancers. Nat. Genet. 42, 343–347 (2010).
Corces, M. R. et al. An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues. Nat. Methods 14, 959–962 (2017).
Hunt, J. L. & Finkelstein, S. D. Microdissection techniques for molecular testing in surgical pathology. Arch. Pathol. Lab. Med. 128, 1372–1378 (2004).
Mägel, L., Bartels, S. & Lehmann, U. Next- generation sequencing analysis of laser-microdissected formalin-fixed and paraffin-embedded (FFPE) tissue specimens. Methods Mol. Biol. 1723, 111–118 (2018).
Mes, S. W. et al. Development and validation of a novel and rapid molecular detection method for high-risk human papillomavirus in formalin-fixed, paraffin-embedded tumor tissue. J. Mol. Diagn. 22, 262–271 (2020).
Kuilman, T. et al. CopywriteR: DNA copy number detection from off-target sequence data. Genome Biol. 16, 49 (2015).
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).
Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008).
Thorvaldsdóttir, H., Robinson, J. T. & Mesirov, J. P. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief. Bioinform. 14, 178–192 (2013).
Ramírez, F. et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res 44, W160–W165 (2016).
Kinkley, S. et al. reChIP-seq reveals widespread bivalency of H3K4me3 and H3K27me3 in CD4+ memory T cells. Nat. Commun. 7, 12514 (2016).
Shin, H., Liu, T., Duan, X., Zhang, Y. & Shirley Liu, X. Computational methodology for ChIP-seq analysis. Quant. Biol. 1, 54–70 (2013).
A.F.-T. has been supported by Associació per a la recerca oncològica (APRO) for the present study. P.C. acknowledges funding from the Ministry of Economy and Competitiveness, Instituto de Salud Carlos III (Institute of Health Carlos III)—PI18-01604. E.M.V.A acknowledges funding from US NIH grant R37CA222574. M.B. acknowledges funding from NIH grant 2PO1CA163227. We thank R. Vadhi, M. A. Berkeley and Z. Herbert from the Molecular Biology Core Facility (MBCF) at the Dana-Farber Cancer Institute for preparing and sequencing Illumina libraries. We acknowledge X. Qiu, K. Lim and S. Syamala for valuable technical support.
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Key references using this protocol
Cejas, P. et al. Nat. Med. 22, 685–691 (2016): https://doi.org/10.1038/nm.4085
Cejas, P. et al. Nat. Med. 25, 1260–1265 (2019): https://doi.org/10.1038/s41591-019-0493-4
(a) Bar plot of total and 10-fold enriched peaks called from H3K4Me2 and H3K27Ac data generated by the optimized original FiT-seq protocol. (b) Average H3K4Me2 and H3K27Ac signal distribution for normal mouse liver tissue obtained by the optimized original FiT-Seq protocol centered at H3K4Me2 called peaks. (c) IGV traces at GAPDH locus. Y axis indicates the number of reads per million per base pair (rbm). Appropriate institutional regulatory board permission was obtained for animal experiments.
Unsupervised hierarchical clustering of the sample-sample correlation of the H3K27Ac signal at the union of all enhancers annotated for the five tumor types (total enhancers = 117397): bladder cancers (BlCa), breast cancer brain metastasis (BrCaBM), melanomas (MEL), pancreatic neuroendocrine tumors (PNETs) and seminomas (SEM). Each row and column represents a different sample. Scale represents Pearson’s correlation.
Extended Data Fig. 3 Comparison of FiTAc-seq and ChromEX-PE performance for H3K27Ac on FFPE mouse liver tissue.
ChromEX-PE15 publicly available data was analyzed at the same sequencing depth and with the exact same analysis parameters as the FiTAc-seq data. (a) Average distribution of H3K27Ac signal at enhancers (TSS excluded) in normal mouse liver FFPE tissue obtained from FiTAc-seq and ChromEX-PE protocols in duplicate as indicated in the legend. The union of enhancer peaks from all the replicates was used to center the H3K27Ac signal to perform the aggregation plot. (b) Integrative genomics viewer (IGV) tracks at the Hnf4a locus comparing replicates of the FiTAc-seq (tracks 2 and 3) and ChromEX-PE (tracks 5 and 6) datasets. FF data from ChromEX-PE publication (track 4) and from our mouse model system (track 1) are used as reference. Y axis represents the number of reads per million per base pair (rbm). Appropriate institutional regulatory board permission was obtained for animal experiments.
(a) Fragment size distribution achieved with 5 min sonication (tissue homogenization at 65 °C, two replicates) and with 40 min sonication (tissue homogenization at 50 °C, 65 °C or 80 °C) for mouse liver tissue sample. (b) Fragment size distribution for several clinical FFPE archived samples.
(a) Bar plot of total, 10-fold and 20-fold enriched peaks for two replicates of mouse FFPE normal liver tissue (FiTAc-seq 65 °C_5min) called with and without input. (b) Corresponding IGV tracks at representative Hnf4a locus with annotation of peaks (black boxes below signal). Y axis indicates the number of reads per million per base pair (rbm). Appropriate institutional regulatory board permission was obtained for animal experiments.
(a) Plots representing evolutionary conservation across mammalian genomes for FF and FFPE 65 °C_5min and 65 °C_40min mouse liver samples. Appropriate institutional regulatory board permission was obtained for animal experiments. (b) Plots representing evolutionary conservation across mammalian genomes for all FiTAc-seq FFPE clinical samples. Y axis represents PhastCons score, X axis represents distance from center in kb.
Sequencing and peak calling statistics results from normal mouse liver FFPE FiTAc-seq and FF counterpart.
List of SE annotated by ROSE algorithm for H3K27Ac signal from FF and FiTAc-seq 65°C_5min FFPE mouse liver samples.
RP scores from marge-potential analysis on H3K27Ac signal for FF and FiTAc-seq 65°C_5min FFPE mouse liver samples.
Sequencing and peak calling statistics of FiTAc-seq in clinical tissue samples, including (a) mean values in each tissue-type and (b) specific results for each of the samples.
List of SE identified by ROSE algorithm for FiTAc-seq FFPE clinical tumor samples, including bladder cancers (BlCa), breast cancer brain metastasis (BrCaBM), melanoma (MEL), pancreatic neuroendocrine tumors (PNETs) and seminomas (SEM).
About this article
Cite this article
Font-Tello, A., Kesten, N., Xie, Y. et al. FiTAc-seq: fixed-tissue ChIP-seq for H3K27ac profiling and super-enhancer analysis of FFPE tissues. Nat Protoc (2020). https://doi.org/10.1038/s41596-020-0340-6