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Method Article
Here, we describe an optimized high-throughput ChIP-sequencing protocol and computational analyses pipeline for the determination of genome-wide chromatin state patterns from frozen tumor tissues and cell lines.
Histone modifications constitute a major component of the epigenome and play important regulatory roles in determining the transcriptional status of associated loci. In addition, the presence of specific modifications has been used to determine the position and identity non-coding functional elements such as enhancers. In recent years, chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq) has become a powerful tool in determining the genome-wide profiles of individual histone modifications. However, it has become increasingly clear that the combinatorial patterns of chromatin modifications, referred to as Chromatin States, determine the identity and nature of the associated genomic locus. Therefore, workflows consisting of robust high-throughput (HT) methodologies for profiling a number of histone modification marks, as well as computational analyses pipelines capable of handling myriads of ChIP-Seq profiling datasets, are needed for comprehensive determination of epigenomic states in large number of samples. The HT-ChIP-Seq workflow presented here consists of two modules: 1) an experimental protocol for profiling several histone modifications from small amounts of tumor samples and cell lines in a 96-well format; and 2) a computational data analysis pipeline that combines existing tools to compute both individual mark occupancy and combinatorial chromatin state patterns. Together, these two modules facilitate easy processing of hundreds of ChIP-Seq samples in a fast and efficient manner. The workflow presented here is used to derive chromatin state patterns from 6 histone mark profiles in melanoma tumors and cell lines. Overall, we present a comprehensive ChIP-seq workflow that can be applied to dozens of human tumor samples and cancer cell lines to determine epigenomic aberrations in various malignancies.
The majority of mammalian genomes (98 - 99%) are comprised of noncoding sequence, and these nocoding regions contain regulatory elements known to participate in controlling gene expression and chromatin organization1,2. In a normal cell, the specific assembly of genomic DNA into compacted chromatin structure is critical for the spatial organization, regulation and precise timing of various DNA-associated processes3,4,5. In a cancer cell however, chromatin modifications by aberrant epigenetic mechanisms can lead to improper organization of chromatin structure, including access to regulatory elements, chromosomal looping systems, and gene expression patterns6,7,8,9,10.
Despite recent advances, we have limited understanding of epigenetic alterations that are associated with tumor progression or therapeutic response. The epigenome consists of an array of modifications, including histone marks and DNA methylation, which collectively form a dynamic state (referred to as chromatin state) that impinges upon gene expression networks and other processes critical for maintaining cellular identity. Recently, alterations in enhancers have been shown in multiple malignancies by studying H3K27Ac profiles11. Although such studies provide insight into the correlation of isolated epigenetic marks, more than 100 epigenetic modifications have been identified12,13 without clear understanding of their biological roles and interdependence. Furthermore, there are an even larger number of possible combinatorial patterns of these histone and DNA modifications, and it is these combinatorial patterns - not individual modifications - that dictate epigenetic states14. Hence, there is tremendous need to identify alterations in these chromatin states during cancer progression or responses to therapy. Comprehensive knowledge of epigenome alterations in cancers has been lagging in part due to technical (e.g. generation of large-scale data from small amount of clinical material/single cells) and analytical (e.g. algorithms to define combinatorial states) challenges. Therefore, there is critical need for robust high-throughput methods for profiling large number of histone modification marks from clinical material and easy-to-implement computational approaches to predict combinatorial patterns which will facilitate determination of epigenetic states associated with different stages of tumorigenesis and therapeutic resistance. Further, data available from recent epigenome profiling studies15,16,17,18,19,20,21,22,23 in normal tissues and cell lines can be integrated with chromatin profiles of tumors for further insights into epigenome contribution to tumor biology.
Chromatin profiling has become a powerful tool for identifying the global binding patterns of various chromatin modifications15,24. In recent years, ChIP-seq has become the "gold standard" for studying DNA-protein interactions on a global scale25,26,27. For any ChIP-seq experiment, there are critical steps necessary for its success, including tissue processing and disassociation, determing optimal sonication conditions, determing optimal antibody concentration for precipitation, library preparation, post-sequencing data processing, and downstream analysis. Each of these steps contain key quality control checkpoints, and when taken together, are crucial for properly identifying potential targets for functional validation. Through innovation in these steps, several prior studies have developed methodologies to perform ChIP or ChIP-Seq from small amount of tissues28,29,30,31,32. Further, some studies have suggested protocols for high-throughput ChIP experiments followed by PCR based quantitation33,34. Finally, some publically available analysis platforms for ChIP-Seq data are now available such as Easeq35 and Galaxy36. However, an integrated platform for performing ChIP-Seq in a high-throughput fashion in combination with a computational pipeline to perform single mark as well as chromatin state analyses has been lacking.
This protocol describes a complete and comprehensive ChIP-seq workflow for genome-wide mapping of chromatin states in tumor tissues and cell lines, with easy to follow guidelines encompassing all of the steps necessary for a successful experiment. By adopting a high-throughput method previously described by Blecher-Gonen et al.37, this protocol can be performed on dozens of samples in parallel and has been applied successfully on cancer cell lines and human tumors such as melanoma, colon, prostate, and glioblastoma multiforme. We demonstrate the methodology for six core histone modifications that represent key components of the epigenetic regulatory landscape in human melanoma cell lines and tumor samples. These modifications include H3K27ac (enhancers), H3K4me1 (active and poised enhancers), H3K4me3 (promoters), H3K79me2 (transcribed regions), H3K27me3 (polycomb repression), and H3K9me3 (heterochromatic repression). These marks can be used either alone or in combination to identify functionally distinct chromatin states representing both repressive and active domains.
All clinical specimens were obtained following the guidelines of Institutional Review Board.
1. Buffer Preparation
2. Tissue/cell Line Processing and Cross-linking
3. Tissue Lysis, Sonication, and Antibody Preparation
4. Chromatin Immunoprecipitation
5. Washing and Reverse Crosslinking of Immunoprecipitated DNA-protein Complexes
6. Purification and Quantification of Precipitated DNA
7. Library Generation using the NEBNext Ultra II DNA Library Preparation Kit
8. Post ChIP-seq Data Processing
This protocol allows the immunoprecipitation from frozen tumor tissues and cell lines that can be performed on dozens of samples in parallel using a high-throughput method (Figure 1A). Chromatin fragments should range between ~200 - 1000 bps for optimal immunoprecipitation. We have noted that the time needed to achieve same shearing length differs for different tissue and cell types. The success of ChIP from small amounts of tissue depends on...
This protocol describes a complete and comprehensive high-throughput ChIP-seq module for genome-wide mapping of chromatin states in human tumor tissues and cell lines. In any ChIP-seq protocol, one of the most important steps is antibody specificity. Here, this method illustrates immunoprecipitation conditions for the described six histone modifications, all of which are ChIP-grade and have been previously validated in our and other laboratories42,44,<...
Authors declare no conflicts.
We thank Marcus Coyle, Curtis Gumbs, SMF core at MDACC for sequencing support. The work described in this article was supported by grants from the NIH grant (CA016672) to SMF Core and NCI awards (1K99CA160578 and R00CA160578) to K. R.
Name | Company | Catalog Number | Comments |
ChIP-grade H3K4me1 antibody | Abcam | ab8895 | |
ChIP-grade H3K27ac antibody | Abcam | ab4729 | |
ChIP-grade H3K4me3 antibody | Abcam | ab8580 | |
ChIP-grade H3K79me2 antibody | Abcam | ab3594 | |
ChIP-grade H3K27me3 antibody | Abcam | ab6002 | |
ChIP-grade H3K9me3 antibody | Abcam | ab8898 | |
1M Tris HCl, pH 8.0 | Teknova | T1080 | |
EDTA | Sigma-Aldrich | E9884 | |
NaCl | Sigma-Aldrich | S7653 | |
Glycine | Sigma-Aldrich | G8898 | |
Sodium deoxycholate | Sigma-Aldrich | 30970 | |
DPBS | Sigma - Life Sciences | D8537-500ML | |
SDS | Sigma-Aldrich | 74255 | |
Triton-X | Sigma-Aldrich | X100-100ML | |
LiCl | Sigma-Aldrich | 746460 | |
NP-40 | Calbiochem | 492016-100ML | |
1% TWEEN-20 | Fisher Bioreagents | BP337-500 | |
BSA - IgG-free | Sigma - Life Sciences | A2058-5G | |
HBSS | Gibo | 14025092 | |
GentleMACS C tube | GentleMACS | 120-008-466 | disassociation tube |
16% Formaldehyde | Peierce | 28906 | |
miniProtease inhibitor | Roche Diagnostics | 11836153001 | protease inhibitor tablets |
Dynabeads Protein G | Invitrogen | 10009D | |
Bioruptor NGS tubes 0.65 mL | Diagenode | C30010011 | sonication tubes |
DynaMag - 96 Side Skirted | Invitrogen | 120.27 | 96-well magnetic stand |
TE buffer | Promega | V6231 | |
RNase A | Invitrogen | 12091021 | |
Proteinase K | Invitrogen | 100005393 | |
AMPure XP beads | Beckman Coulter | A63882 | paramagnetic beads |
Ethanol | Sigma-Aldrich | E7023 | |
Qubit ds DNA High Sensitivity Assay Kit | Invitrogen | Q32854 | high sensitivity DNA reagents |
NEBNext Ultra II DNA Library Prep Kit | New England BioLabs | E7645L | DNA Library Prep Kit |
Nuclease-free water | Ambion | AM9932 | |
High sensitivity D1000 ScreenTape | Agilent Technologies | 5067-5584 | high sensitivity DNA reagents |
High sensitivity D1000 reagents | Agilent Technologies | 5067-5585 | high sensitivity DNA reagents |
Multiplex Oligos (Index primers- Set 1) | New England BioLabs | E7335L | Multiplex Oligos |
Multiplex Oligos (Index primers- Set 2) | New England BioLabs | E7500L | Multiplex Oligos |
TapeStation 4200 | Agilent Technologies | G2991AA | high sensitivity DNA electropherogram instrument |
Bioruptor Pico sonication device | Diagenode | B01060001 | water bath disruputor |
Mixer | Nutator | 421105 | |
Bio-Rad C1000 Touch Thermal Cycler | Bio-Rad | 1851196 | PCR Thermal cycler |
Water Bath | Fisher Scientific | 2322 | |
Multichannel Pipet | Denville | 1003123 | |
Tube Revolver | Thermo-Scientific | 88881001 | |
96-Well Skirted Plate | Eppendorf | 47744-110 | |
Allegra X-12R Centrifuge | Beckman Coulter | A99464 | benchtop centrifuge |
Centrifuge 5424 | Eppendorf | 22620461 | tabletop centrifuge |
Optical tube strips (8x Strip) | Agilent Technologies | 401428 | |
Optical tube strip caps (8x strip) | Agilent Technologies | 401425 | |
Loading Tips, 10 Pk | Agilent Technologies | 5067-5599 | |
IKA MS3 vortex | IKA | 3617000 | vortex |
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