Chromatin Immunoprecipitation Followed by Next-Generation Sequencing (ChIP-Seq) Analysis in Ewing Sarcoma.

ChIP-seq is the method of choice for profiling protein-DNA interactions, and notably for characterizing the landscape of transcription factor binding and histone modifications. This technique has been widely used to study numerous aspects of tumor biology and led to the development of several promising cancer therapies. In Ewing sarcoma research, ChIP-seq provided important insights into the mechanism of action of the major oncogenic fusion protein EWSR1-FLI1 and related epigenetic and transcriptional changes. In this chapter, we provide a detailed pipeline to analyze ChIP-seq experiments from the preprocessing of raw data to tertiary analysis of detected binding sites. We also advise on best practice to prepare tumor samples prior to sequencing.

ATAC-seq with unique molecular identifiers improves quantification and footprinting.

ATAC-seq (Assay for Transposase-Accessible Chromatin with high-throughput sequencing) provides an efficient way to analyze nucleosome-free regions and has been applied widely to identify transcription factor footprints. Both applications rely on the accurate quantification of insertion events of the hyperactive transposase Tn5. However, due to the presence of the PCR amplification, it is impossible to accurately distinguish independently generated identical Tn5 insertion events from PCR duplicates using the standard ATAC-seq technique. Removing PCR duplicates based on mapping coordinates introduces increasing bias towards highly accessible chromatin regions. To overcome this limitation, we establish a UMI-ATAC-seq technique by incorporating unique molecular identifiers (UMIs) into standard ATAC-seq procedures. UMI-ATAC-seq can rescue about 20% of reads that are mistaken as PCR duplicates in standard ATAC-seq in our study. We demonstrate that UMI-ATAC-seq could more accurately quantify chromatin accessibility and significantly improve the sensitivity of identifying transcription factor footprints. An analytic pipeline is developed to facilitate the application of UMI-ATAC-seq, and it is available at https://github.com/tzhu-bio/UMI-ATAC-seq .

Linker histone epitopes are hidden by in situ higher-order chromatin structure.

BACKGROUND: Histone H1 is the most mobile histone in the cell nucleus. Defining the positions of H1 on chromatin in situ, therefore, represents a challenge. Immunoprecipitation of formaldehyde-fixed and sonicated chromatin, followed by DNA sequencing (xChIP-seq), is traditionally the method for mapping histones onto DNA elements. But since sonication fragmentation precedes ChIP, there is a consequent loss of information about chromatin higher-order structure. Here, we present a new method, xxChIP-seq, employing antibody binding to fixed intact in situ chromatin, followed by extensive washing, a second fixation, sonication and immunoprecipitation. The second fixation is intended to prevent the loss of specifically bound antibody during washing and subsequent sonication and to prevent antibody shifting to epitopes revealed by the sonication process. In many respects, xxChIP-seq is comparable to immunostaining microscopy, which also involves interaction of the primary antibody with fixed and permeabilized intact cells. The only epitopes displayed after immunostaining are the "exposed" epitopes, not "hidden" by the fixation of chromatin higher-order structure. Comparison of immunoprecipitated fragments between xChIP-seq versus xxChIP-seq should indicate which epitopes become inaccessible with fixation and identify their associated DNA elements. RESULTS: We determined the genomic distribution of histone variants H1.2 and H1.5 in human myeloid leukemia cells HL-60/S4 and compared their epitope exposure by both xChIP-seq and xxChIP-seq, as well as high-resolution microscopy, illustrating the influences of preserved chromatin higher-order structure in situ. We found that xChIP and xxChIP H1 signals are in general negatively correlated, with differences being more pronounced near active regulatory regions. Among the intriguing observations, we find that transcription-related regions and histone PTMs (i.e., enhancers, promoters, CpG islands, H3K4me1, H3K4me3, H3K9ac, H3K27ac and H3K36me3) exhibit significant deficiencies (depletions) in H1.2 and H1.5 xxChIP-seq reads, compared to xChIP-seq. These observations suggest the existence of in situ transcription-related chromatin higher-order structures stabilized by formaldehyde. CONCLUSION: Comparison of H1 xxChIP-seq to H1 xChIP-seq allows the development of hypotheses on the chromosomal localization of (stabilized) higher-order structure, indicated by the generation of "hidden" H1 epitopes following formaldehyde crosslinking. Changes in H1 epitope exposure surrounding averaged chromosomal binding sites or epigenetic modifications can also indicate whether these sites have chromatin higher-order structure. For example, comparison between averaged active or inactive promoter regions suggests that both regions can acquire stabilized higher-order structure with hidden H1 epitopes. However, the H1 xChIP-seq comparison cannot define their differences. Application of the xxChIP-seq versus H1 xChIP-seq method is particularly relevant to chromatin-associated proteins, such as linker histones, that play dynamic roles in establishing chromatin higher-order structure.

ATAC-seq normalization method can significantly affect differential accessibility analysis and interpretation.

BACKGROUND: Chromatin dysregulation is associated with developmental disorders and cancer. Numerous methods for measuring genome-wide chromatin accessibility have been developed in the genomic era to interrogate the function of chromatin regulators. A recent technique which has gained widespread use due to speed and low input requirements with native chromatin is the Assay for Transposase-Accessible Chromatin, or ATAC-seq. Biologists have since used this method to compare chromatin accessibility between two cellular conditions. However, approaches for calculating differential accessibility can yield conflicting results, and little emphasis is placed on choice of normalization method during differential ATAC-seq analysis, especially when global chromatin alterations might be expected. RESULTS: Using an in vivo ATAC-seq data set generated in our recent report, we observed differences in chromatin accessibility patterns depending on the data normalization method used to calculate differential accessibility. This observation was further verified on published ATAC-seq data from yeast. We propose a generalized workflow for differential accessibility analysis using ATAC-seq data. We further show this workflow identifies sites of differential chromatin accessibility that correlate with gene expression and is sensitive to differential analysis using negative controls. CONCLUSIONS: We argue that researchers should systematically compare multiple normalization methods before continuing with differential accessibility analysis. ATAC-seq users should be aware of the interpretations of potential bias within experimental data and the assumptions of the normalization method implemented.

Unique and assay specific features of NOMe-, ATAC- and DNase I-seq data.

Chromatin accessibility maps are important for the functional interpretation of the genome. Here, we systematically analysed assay specific differences between DNase I-seq, ATAC-seq and NOMe-seq in a side by side experimental and bioinformatic setup. We observe that most prominent nucleosome depleted regions (NDRs, e.g. in promoters) are roboustly called by all three or at least two assays. However, we also find a high proportion of assay specific NDRs that are often 'called' by only one of the assays. We show evidence that these assay specific NDRs are indeed genuine open chromatin sites and contribute important information for accurate gene expression prediction. While technically ATAC-seq and DNase I-seq provide a superb high NDR calling rate for relatively low sequencing costs in comparison to NOMe-seq, NOMe-seq singles out for its genome-wide coverage allowing to not only detect NDRs but also endogenous DNA methylation and as we show here genome wide segmentation into heterochromatic B domains and local phasing of nucleosomes outside of NDRs. In summary, our comparisons strongly suggest to consider assay specific differences for the experimental design and for generalized and comparative functional interpretations.