Literature DB >> 33741028

Molecular and computational approaches to map regulatory elements in 3D chromatin structure.

Beoung Hun Lee1, Suhn K Rhie2.   

Abstract

Epigenetic marks do not change the sequence of DNA but affect gene expression in a cell-type specific manner by altering the activities of regulatory elements. Development of new molecular biology assays, sequencing technologies, and computational approaches enables us to profile the human epigenome in three-dimensional structure genome-wide. Here we describe various molecular biology techniques and bioinformatic tools that have been developed to measure the activities of regulatory elements and their chromatin interactions. Moreover, we list currently available three-dimensional epigenomic data sets that are generated in various human cell types and tissues to assist in the design and analysis of research projects.

Entities:  

Keywords:  Analysis tools; Chromatin interactions; Databases; Epigenomics; Regulatory elements

Mesh:

Substances:

Year:  2021        PMID: 33741028      PMCID: PMC7980343          DOI: 10.1186/s13072-021-00390-y

Source DB:  PubMed          Journal:  Epigenetics Chromatin        ISSN: 1756-8935            Impact factor:   4.954


  235 in total

1.  4C-seq from beginning to end: A detailed protocol for sample preparation and data analysis.

Authors:  Peter H L Krijger; Geert Geeven; Valerio Bianchi; Catharina R E Hilvering; Wouter de Laat
Journal:  Methods       Date:  2019-07-26       Impact factor: 3.608

2.  HiTC: exploration of high-throughput 'C' experiments.

Authors:  Nicolas Servant; Bryan R Lajoie; Elphège P Nora; Luca Giorgetti; Chong-Jian Chen; Edith Heard; Job Dekker; Emmanuel Barillot
Journal:  Bioinformatics       Date:  2012-08-24       Impact factor: 6.937

3.  Using the Wash U Epigenome Browser to examine genome-wide sequencing data.

Authors:  Xin Zhou; Ting Wang
Journal:  Curr Protoc Bioinformatics       Date:  2012-12

4.  The landscape of accessible chromatin in mammalian preimplantation embryos.

Authors:  Jingyi Wu; Bo Huang; He Chen; Qiangzong Yin; Yang Liu; Yunlong Xiang; Bingjie Zhang; Bofeng Liu; Qiujun Wang; Weikun Xia; Wenzhi Li; Yuanyuan Li; Jing Ma; Xu Peng; Hui Zheng; Jia Ming; Wenhao Zhang; Jing Zhang; Geng Tian; Feng Xu; Zai Chang; Jie Na; Xuerui Yang; Wei Xie
Journal:  Nature       Date:  2016-06-15       Impact factor: 49.962

5.  hichipper: a preprocessing pipeline for calling DNA loops from HiChIP data.

Authors:  Caleb A Lareau; Martin J Aryee
Journal:  Nat Methods       Date:  2018-02-28       Impact factor: 28.547

6.  Q&A: ChIP-seq technologies and the study of gene regulation.

Authors:  Edison T Liu; Sebastian Pott; Mikael Huss
Journal:  BMC Biol       Date:  2010-05-14       Impact factor: 7.431

7.  DNase footprint signatures are dictated by factor dynamics and DNA sequence.

Authors:  Myong-Hee Sung; Michael J Guertin; Songjoon Baek; Gordon L Hager
Journal:  Mol Cell       Date:  2014-09-18       Impact factor: 17.970

8.  ChIPOTle: a user-friendly tool for the analysis of ChIP-chip data.

Authors:  Michael J Buck; Andrew B Nobel; Jason D Lieb
Journal:  Genome Biol       Date:  2005-10-19       Impact factor: 13.583

9.  Fast and accurate short read alignment with Burrows-Wheeler transform.

Authors:  Heng Li; Richard Durbin
Journal:  Bioinformatics       Date:  2009-05-18       Impact factor: 6.937

10.  Global mapping of protein-DNA interactions in vivo by digital genomic footprinting.

Authors:  Jay R Hesselberth; Xiaoyu Chen; Zhihong Zhang; Peter J Sabo; Richard Sandstrom; Alex P Reynolds; Robert E Thurman; Shane Neph; Michael S Kuehn; William S Noble; Stanley Fields; John A Stamatoyannopoulos
Journal:  Nat Methods       Date:  2009-03-22       Impact factor: 28.547

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