Genome-wide nucleosome profiles are predominantly characterized using MNase-seq, which involves extensive MNase digestion and size selection to enrich for mononucleosome-sized fragments. Most available MNase-seq analysis packages assume that nucleosomes uniformly protect 147 bp DNA fragments. However, some nucleosomes with atypical histone or chemical compositions protect shorter lengths of DNA. The rigid assumptions imposed by current nucleosome analysis packages potentially prevent investigators from understanding the regulatory roles played by atypical nucleosomes. To enable the characterization of different nucleosome types from MNase-seq data, we introduce the size-based expectation maximization (SEM) nucleosome-calling package. SEM employs a hierarchical Gaussian mixture model to estimate nucleosome positions and subtypes. Nucleosome subtypes are automatically identified based on the distribution of protected DNA fragments. Benchmark analysis indicates that SEM is on par with existing packages in terms of standard nucleosome-calling accuracy metrics, while uniquely providing the ability to characterize nucleosome subtype identities. Applying SEM to a low-dose MNase-H2B-ChIP-seq data set from mouse embryonic stem cells, we identified three nucleosome types: short-fragment nucleosomes, canonical nucleosomes, and di-nucleosomes. Short-fragment nucleosomes can be divided further into two subtypes based on their chromatin accessibility. Short-fragment nucleosomes in accessible regions exhibit high MNase sensitivity and are enriched at transcription start sites (TSSs) and CTCF peaks, similar to previously reported "fragile nucleosomes." These SEM-defined accessible short-fragment nucleosomes are found not just in promoters but also in distal regulatory regions. Additional analyses reveal their colocalization with the chromatin remodelers CHD6, CHD8, and EP400. In summary, SEM provides an effective platform for exploration of nonstandard nucleosome subtypes.
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http://dx.doi.org/10.1101/gr.279138.124 | DOI Listing |
Genome Res
October 2024
Center for Eukaryotic Gene Regulation, Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, Pennsylvania 16802, USA;
Genome-wide nucleosome profiles are predominantly characterized using MNase-seq, which involves extensive MNase digestion and size selection to enrich for mononucleosome-sized fragments. Most available MNase-seq analysis packages assume that nucleosomes uniformly protect 147 bp DNA fragments. However, some nucleosomes with atypical histone or chemical compositions protect shorter lengths of DNA.
View Article and Find Full Text PDFbioRxiv
October 2023
Center for Eukaryotic Gene Regulation, Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, USA.
Genome-wide nucleosome profiles are predominantly characterized using MNase-seq, which involves extensive MNase digestion and size selection to enrich for mono-nucleosome-sized fragments. Most available MNase-seq analysis packages assume that nucleosomes uniformly protect 147bp DNA fragments. However, some nucleosomes with atypical histone or chemical compositions protect shorter lengths of DNA.
View Article and Find Full Text PDFBrief Bioinform
January 2022
CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, and China National Center for Bioinformation, Beijing 100101, China.
As the basal bricks, the dynamics and arrangement of nucleosomes orchestrate the higher architecture of chromatin in a fundamental way, thereby affecting almost all nuclear biology processes. Thanks to its rather simple protocol, assay for transposase-accessible chromatin using sequencing (ATAC)-seq has been rapidly adopted as a major tool for chromatin-accessible profiling at both bulk and single-cell levels; however, to picture the arrangement of nucleosomes per se remains a challenge with ATAC-seq. In the present work, we introduce a novel ATAC-seq analysis toolkit, named decoding nucleosome organization profile based on ATAC-seq data (deNOPA), to predict nucleosome positions.
View Article and Find Full Text PDFCell Rep
March 2018
School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel; Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel. Electronic address:
Transcription factor (TF) binding to DNA is crucial for transcriptional regulation. There are multiple methods for mapping such binding. These methods balance between input requirements, spatial resolution, and compatibility with high-throughput automation.
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