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Article ; Online: Churros: a Docker-based pipeline for large-scale epigenomic analysis.

Wang, Jiankang / Nakato, Ryuichiro

DNA research : an international journal for rapid publication of reports on genes and genomes

2024 Volume 31, Issue 1

Abstract: The epigenome, which reflects the modifications on chromatin or DNA sequences, provides crucial insight into gene expression regulation and cellular activity. With the continuous accumulation of epigenomic datasets such as chromatin immunoprecipitation ... ...

Abstract	The epigenome, which reflects the modifications on chromatin or DNA sequences, provides crucial insight into gene expression regulation and cellular activity. With the continuous accumulation of epigenomic datasets such as chromatin immunoprecipitation followed by sequencing (ChIP-seq) data, there is a great demand for a streamlined pipeline to consistently process them, especially for large-dataset comparisons involving hundreds of samples. Here, we present Churros, an end-to-end epigenomic analysis pipeline that is environmentally independent and optimized for handling large-scale data. We successfully demonstrated the effectiveness of Churros by analyzing large-scale ChIP-seq datasets with the hg38 or Telomere-to-Telomere (T2T) human reference genome. We found that applying T2T to the typical analysis workflow has important impacts on read mapping, quality checks, and peak calling. We also introduced a useful feature to study context-specific epigenomic landscapes. Churros will contribute a comprehensive and unified resource for analyzing large-scale epigenomic data.
MeSH term(s)	Humans ; Epigenomics ; Chromatin Immunoprecipitation Sequencing ; Chromatin/genetics ; Gene Expression Regulation ; Chromatin Immunoprecipitation ; Sequence Analysis, DNA ; High-Throughput Nucleotide Sequencing
Chemical Substances	Chromatin
Language	English
Publishing date	2024-01-08
Publishing country	England
Document type	Journal Article
ZDB-ID	1212508-8
ISSN	1756-1663 ; 1340-2838
ISSN (online)	1756-1663
ISSN	1340-2838
DOI	10.1093/dnares/dsad026
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Zs.A 4123: Show issues

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Article ; Online: Clover: An unbiased method for prioritizing differentially expressed genes using a data-driven approach.

Oba, Gina Miku / Nakato, Ryuichiro

Genes to cells : devoted to molecular & cellular mechanisms

2024

Abstract: Identifying key genes from a list of differentially expressed genes (DEGs) is a critical step in transcriptome analysis. However, current methods, including Gene Ontology analysis and manual annotation, essentially rely on existing knowledge, which is ... ...

Abstract	Identifying key genes from a list of differentially expressed genes (DEGs) is a critical step in transcriptome analysis. However, current methods, including Gene Ontology analysis and manual annotation, essentially rely on existing knowledge, which is highly biased depending on the extent of the literature. As a result, understudied genes, some of which may be associated with important molecular mechanisms, are often ignored or remain obscure. To address this problem, we propose Clover, a data-driven scoring method to specifically highlight understudied genes. Clover aims to prioritize genes associated with important molecular mechanisms by integrating three metrics: the likelihood of appearing in the DEG list, tissue specificity, and number of publications. We applied Clover to Alzheimer's disease data and confirmed that it successfully detected known associated genes. Moreover, Clover effectively prioritized understudied but potentially druggable genes. Overall, our method offers a novel approach to gene characterization and has the potential to expand our understanding of gene functions. Clover is an open-source software written in Python3 and available on GitHub at https://github.com/G708/Clover.
Language	English
Publishing date	2024-04-11
Publishing country	England
Document type	Journal Article
ZDB-ID	1330000-3
ISSN	1365-2443 ; 1356-9597
ISSN (online)	1365-2443
ISSN	1356-9597
DOI	10.1111/gtc.13119
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Zs.A 4539: Show issues

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Article ; Online: Comprehensive multiomics analyses reveal pervasive involvement of aberrant cohesin binding in transcriptional and chromosomal disorder of cancer cells.

Wang, Jiankang / Nakato, Ryuichiro

iScience

2023 Volume 26, Issue 6, Page(s) 106908

Abstract: Chromatin organization, whose malfunction causes various diseases including cancer, is fundamentally controlled by cohesin. While cancer cells have been found with mutated or misexpressed cohesin genes, there is no comprehensive survey about the presence ...

Abstract	Chromatin organization, whose malfunction causes various diseases including cancer, is fundamentally controlled by cohesin. While cancer cells have been found with mutated or misexpressed cohesin genes, there is no comprehensive survey about the presence and role of abnormal cohesin binding in cancer cells. Here, we systematically identified ∼1% of cohesin-binding sites (701-2,633) as cancer-aberrant binding sites of cohesin (CASs). We integrated CASs with large-scale transcriptomics, epigenomics, 3D genomics, and clinical information. CASs represent tissue-specific epigenomic signatures enriched for cancer-dysregulated genes with functional and clinical significance. CASs exhibited alterations in chromatin compartments, loops within topologically associated domains, and
Language	English
Publishing date	2023-05-19
Publishing country	United States
Document type	Journal Article
ISSN	2589-0042
ISSN (online)	2589-0042
DOI	10.1016/j.isci.2023.106908
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Article ; Online: Protocol for identifying differentially expressed genes using the RumBall RNA-seq analysis platform.

Nagai, Luis Augusto Eijy / Lee, Seohyun / Nakato, Ryuichiro

STAR protocols

2024 Volume 5, Issue 1, Page(s) 102926

Abstract: Here, we present a protocol for the identification of differentially expressed genes through RNA sequencing analysis. Starting with FASTQ files from public datasets, this protocol leverages RumBall within a self-contained Docker system. We describe the ... ...

Abstract	Here, we present a protocol for the identification of differentially expressed genes through RNA sequencing analysis. Starting with FASTQ files from public datasets, this protocol leverages RumBall within a self-contained Docker system. We describe the steps for software setup, obtaining data, read mapping, sample normalization, statistical modeling, and gene ontology enrichment. We then detail procedures for interpreting results with plots and tables. RumBall internally utilizes popular tools, ensuring a comprehensive understanding of the analysis process.
MeSH term(s)	Gene Expression Profiling/methods ; Sequence Analysis, RNA/methods ; RNA-Seq ; Software ; Gene Expression
Language	English
Publishing date	2024-03-10
Publishing country	United States
Document type	Journal Article
ISSN	2666-1667
ISSN (online)	2666-1667
DOI	10.1016/j.xpro.2024.102926
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Article ; Online: Comprehensive multiomics analyses reveal pervasive involvement of aberrant cohesin binding in transcriptional and chromosomal disorder of cancer cells

Jiankang Wang / Ryuichiro Nakato

iScience, Vol 26, Iss 6, Pp 106908- (2023)

2023

Abstract: Summary: Chromatin organization, whose malfunction causes various diseases including cancer, is fundamentally controlled by cohesin. While cancer cells have been found with mutated or misexpressed cohesin genes, there is no comprehensive survey about the ...

Abstract	Summary: Chromatin organization, whose malfunction causes various diseases including cancer, is fundamentally controlled by cohesin. While cancer cells have been found with mutated or misexpressed cohesin genes, there is no comprehensive survey about the presence and role of abnormal cohesin binding in cancer cells. Here, we systematically identified ∼1% of cohesin-binding sites (701–2,633) as cancer-aberrant binding sites of cohesin (CASs). We integrated CASs with large-scale transcriptomics, epigenomics, 3D genomics, and clinical information. CASs represent tissue-specific epigenomic signatures enriched for cancer-dysregulated genes with functional and clinical significance. CASs exhibited alterations in chromatin compartments, loops within topologically associated domains, and cis-regulatory elements, indicating that CASs induce dysregulated genes through misguided chromatin structure. Cohesin depletion data suggested that cohesin binding at CASs actively regulates cancer-dysregulated genes. Overall, our comprehensive investigation suggests that aberrant cohesin binding is an essential epigenomic signature responsible for dysregulated chromatin structure and transcription in cancer cells.
Keywords	Epigenetics ; Cancer systems biology ; Omics ; Science ; Q
Subject code	610
Language	English
Publishing date	2023-06-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: CohesinDB: a comprehensive database for decoding cohesin-related epigenomes, 3D genomes and transcriptomes in human cells.

Wang, Jiankang / Nakato, Ryuichiro

Nucleic acids research

2022 Volume 51, Issue D1, Page(s) D70–D79

Abstract: Cohesin is a multifunctional protein responsible for transcriptional regulation and chromatin organization. Cohesin binds to chromatin at tens of thousands of distinct sites in a conserved or tissue-specific manner, whereas the function of cohesin varies ...

Abstract	Cohesin is a multifunctional protein responsible for transcriptional regulation and chromatin organization. Cohesin binds to chromatin at tens of thousands of distinct sites in a conserved or tissue-specific manner, whereas the function of cohesin varies greatly depending on the epigenetic properties of specific chromatin loci. Cohesin also extensively mediates cis-regulatory modules (CRMs) and chromatin loops. Even though next-generation sequencing technologies have provided a wealth of information on different aspects of cohesin, the integration and exploration of the resultant massive cohesin datasets are not straightforward. Here, we present CohesinDB (https://cohesindb.iqb.u-tokyo.ac.jp), a comprehensive multiomics cohesin database in human cells. CohesinDB includes 2043 epigenomics, transcriptomics and 3D genomics datasets from 530 studies involving 176 cell types. By integrating these large-scale data, CohesinDB summarizes three types of 'cohesin objects': 751 590 cohesin binding sites, 957 868 cohesin-related chromatin loops and 2 229 500 cohesin-related CRMs. Each cohesin object is annotated with locus, cell type, classification, function, 3D genomics and cis-regulatory information. CohesinDB features a user-friendly interface for browsing, searching, analyzing, visualizing and downloading the desired information. CohesinDB contributes a valuable resource for all researchers studying cohesin, epigenomics, transcriptional regulation and chromatin organization.
MeSH term(s)	Humans ; CCCTC-Binding Factor/genetics ; CCCTC-Binding Factor/metabolism ; Cell Cycle Proteins/genetics ; Cell Cycle Proteins/metabolism ; Chromatin/genetics ; Epigenome ; Transcriptome/genetics ; Chromosomal Proteins, Non-Histone ; Databases, Genetic ; Cohesins
Chemical Substances	CCCTC-Binding Factor ; Cell Cycle Proteins ; Chromatin ; Chromosomal Proteins, Non-Histone
Language	English
Publishing date	2022-09-23
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	186809-3
ISSN	1362-4962 ; 1362-4954 ; 0301-5610 ; 0305-1048
ISSN (online)	1362-4962 ; 1362-4954
ISSN	0301-5610 ; 0305-1048
DOI	10.1093/nar/gkac795
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Zs.A 1067: Show issues

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Article ; Online: HiC1Dmetrics: framework to extract various one-dimensional features from chromosome structure data.

Wang, Jiankang / Nakato, Ryuichiro

Briefings in bioinformatics

2021 Volume 23, Issue 1

Abstract: Eukaryotic genomes are organized in a three-dimensional spatial structure. In this regard, the development of chromosome conformation capture methods has enabled studies of chromosome organization on a genomic scale. Hi-C, the high-throughput chromosome ... ...

Abstract	Eukaryotic genomes are organized in a three-dimensional spatial structure. In this regard, the development of chromosome conformation capture methods has enabled studies of chromosome organization on a genomic scale. Hi-C, the high-throughput chromosome conformation capture method, can reveal a population-averaged, hierarchical chromatin structure. The typical Hi-C analysis uses a two-dimensional (2D) contact matrix that indicates contact frequencies between all possible genomic position pairs. Oftentimes, however, such a 2D matrix is not amenable to handling quantitative comparisons, visualizations and integrations across multiple datasets. Although several one-dimensional (1D) metrics have been proposed to depict structural information in Hi-C data, their effectiveness is still underappreciated. Here, we first review the currently available 1D metrics for individual Hi-C samples or two-sample comparisons and then discuss their validity and suitable analysis scenarios. We also propose several new 1D metrics to identify additional unique features of chromosome structures. We highlight that the 1D metrics are reproducible and robust for comparing and visualizing multiple Hi-C samples. Moreover, we show that 1D metrics can be easily combined with epigenome tracks to annotate chromatin states in greater details. We develop a new framework, called HiC1Dmetrics, to summarize all 1D metrics discussed in this study. HiC1Dmetrics is open-source (github.com/wangjk321/HiC1Dmetrics) and can be accessed from both command-line and web-based interfaces. Our tool constitutes a useful resource for the community of chromosome-organization researchers.
MeSH term(s)	Chromatin/genetics ; Chromosomes/genetics ; Genome ; Genomics/methods ; Molecular Conformation
Chemical Substances	Chromatin
Language	English
Publishing date	2021-12-01
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2068142-2
ISSN	1477-4054 ; 1467-5463
ISSN (online)	1477-4054
ISSN	1467-5463
DOI	10.1093/bib/bbab509
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Zs.A 6262: Show issues

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Article ; Online: Large-scale multi-omics analysis suggests specific roles for intragenic cohesin in transcriptional regulation

Jiankang Wang / Masashige Bando / Katsuhiko Shirahige / Ryuichiro Nakato

Nature Communications, Vol 13, Iss 1, Pp 1-

2022 Volume 13

Abstract: Cohesin complex is essential for transcriptional regulation and chromosome folding. Here the authors provide a large-scale multi-omics analysis suggesting that cohesin bound on gene bodies has a specific role in transcriptional regulation. ...

Abstract	Cohesin complex is essential for transcriptional regulation and chromosome folding. Here the authors provide a large-scale multi-omics analysis suggesting that cohesin bound on gene bodies has a specific role in transcriptional regulation.
Keywords	Science ; Q
Language	English
Publishing date	2022-06-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Large-scale multi-omics analysis suggests specific roles for intragenic cohesin in transcriptional regulation.

Wang, Jiankang / Bando, Masashige / Shirahige, Katsuhiko / Nakato, Ryuichiro

Nature communications

2022 Volume 13, Issue 1, Page(s) 3218

Abstract: Cohesin, an essential protein complex for chromosome segregation, regulates transcription through a variety of mechanisms. It is not a trivial task to assign diverse cohesin functions. Moreover, the context-specific roles of cohesin-mediated interactions, ...

Abstract	Cohesin, an essential protein complex for chromosome segregation, regulates transcription through a variety of mechanisms. It is not a trivial task to assign diverse cohesin functions. Moreover, the context-specific roles of cohesin-mediated interactions, especially on intragenic regions, have not been thoroughly investigated. Here we perform a comprehensive characterization of cohesin binding sites in several human cell types. We integrate epigenomic, transcriptomic and chromatin interaction data to explore the context-specific functions of intragenic cohesin related to gene activation. We identify a specific subset of cohesin binding sites, decreased intragenic cohesin sites (DICs), which are negatively correlated with transcriptional regulation. A subgroup of DICs is enriched with enhancer markers and RNA polymerase II, while the others are more correlated to chromatin architecture. DICs are observed in various cell types, including cells from patients with cohesinopathy. We also implement machine learning to our data and identified genomic features for isolating DICs from all cohesin sites. These results suggest a previously unidentified function of cohesin on intragenic regions for transcriptional regulation.
MeSH term(s)	CCCTC-Binding Factor/metabolism ; Cell Cycle Proteins/metabolism ; Chromatin/genetics ; Chromosomal Proteins, Non-Histone/metabolism ; Gene Expression Regulation ; Humans ; Cohesins
Chemical Substances	CCCTC-Binding Factor ; Cell Cycle Proteins ; Chromatin ; Chromosomal Proteins, Non-Histone
Language	English
Publishing date	2022-06-09
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-022-30792-9
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Methods for ChIP-seq analysis: A practical workflow and advanced applications.

Nakato, Ryuichiro / Sakata, Toyonori

Methods (San Diego, Calif.)

2020 Volume 187, Page(s) 44–53

Abstract: Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a central method in epigenomic research. Genome-wide analysis of histone modifications, such as enhancer analysis and genome-wide chromatin state annotation, enables systematic analysis ... ...

Abstract	Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a central method in epigenomic research. Genome-wide analysis of histone modifications, such as enhancer analysis and genome-wide chromatin state annotation, enables systematic analysis of how the epigenomic landscape contributes to cell identity, development, lineage specification, and disease. In this review, we first present a typical ChIP-seq analysis workflow, from quality assessment to chromatin-state annotation. We focus on practical, rather than theoretical, approaches for biological studies. Next, we outline various advanced ChIP-seq applications and introduce several state-of-the-art methods, including prediction of gene expression level and chromatin loops from epigenome data and data imputation. Finally, we discuss recently developed single-cell ChIP-seq analysis methodologies that elucidate the cellular diversity within complex tissues and cancers.
MeSH term(s)	Chromatin/genetics ; Chromatin/metabolism ; Chromatin Immunoprecipitation Sequencing/methods ; Epigenomics/methods ; Histone Code/genetics ; Histones/genetics ; Histones/metabolism ; Humans ; Single-Cell Analysis/methods ; Workflow
Chemical Substances	Chromatin ; Histones
Language	English
Publishing date	2020-03-30
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	1066584-5
ISSN	1095-9130 ; 1046-2023
ISSN (online)	1095-9130
ISSN	1046-2023
DOI	10.1016/j.ymeth.2020.03.005
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Zs.A 3239: Show issues

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