Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2021 Mar:187:92-103.
doi: 10.1016/j.ymeth.2020.09.008. Epub 2020 Sep 14.

Computational methods and next-generation sequencing approaches to analyze epigenetics data: Profiling of methods and applications

Itika Arora  1 , Trygve O Tollefsbol  2
Affiliations
Review

Computational methods and next-generation sequencing approaches to analyze epigenetics data: Profiling of methods and applications

Itika Arora et al. Methods. 2021 Mar.

Abstract

Epigenetics is mainly comprised of features that regulate genomic interactions thereby playing a crucial role in a vast array of biological processes. Epigenetic mechanisms such as DNA methylation and histone modifications influence gene expression by modulating the packaging of DNA in the nucleus. A plethora of studies have emphasized the importance of analyzing epigenetics data through genome-wide studies and high-throughput approaches, thereby providing key insights towards epigenetics-based diseases such as cancer. Recent advancements have been made towards translating epigenetics research into a high throughput approach such as genome-scale profiling. Amongst all, bioinformatics plays a pivotal role in achieving epigenetics-related computational studies. Despite significant advancements towards epigenomic profiling, it is challenging to understand how various epigenetic modifications such as chromatin modifications and DNA methylation regulate gene expression. Next-generation sequencing (NGS) provides accurate and parallel sequencing thereby allowing researchers to comprehend epigenomic profiling. In this review, we summarize different computational methods such as machine learning and other bioinformatics tools, publicly available databases and resources to identify key modifications associated with epigenetic machinery. Additionally, the review also focuses on understanding recent methodologies related to epigenome profiling using NGS methods ranging from library preparation, different sequencing platforms and analytical techniques to evaluate various epigenetic modifications such as DNA methylation and histone modifications. We also provide detailed information on bioinformatics tools and computational strategies responsible for analyzing large scale data in epigenetics.

Keywords: Computational epigenetics; DNA methylation; Epigenetics; Epigenome; Histone modifications; Machine learning; Next-generation sequencing; Transcriptional regulation.

PubMed Disclaimer

Conflict of interest statement

Conflict of Interest Statement:

Declarations of interest: none. The authors have no conflict of interests.

Figures

Figure 1.
Figure 1.
Bioinformatics pipeline NGS analysis. Raw datasets are generated either using single-end or pair-end sequencing which is then tested for quality control. Afterward, the data are aligned to the reference genome. The process of variant calling is diverse and based on the experiment and/or clinical research, numerous softwares or methods are employed. Finally, depending on different requirements, annotation is performed using different softwares as mentioned above.
Figure 2.
Figure 2.
NGS methods in DNA methylation profiling. Affinity-based enrichment methods: MeDIP-Seq: methylated DNA immunoprecipitation sequencing, MBD-Seq: methyl-CpG binding domain sequencing; Busulfite conversion-based methods: RRBS-Seq: reduced representation bisulfite sequencing, WGBS: whole-genome bisulfite sequencing.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA: a cancer journal for clinicians. 2019;69(1):7–34. - PubMed
    1. Chakravarthi BV, Nepal S, Varambally S. Genomic and epigenomic alterations in cancer. The American journal of pathology. 2016;186(7):1724–35. - PMC - PubMed
    1. Miller KD, Nogueira L, Mariotto AB, Rowland JH, Yabroff KR, Alfano CM, et al. Cancer treatment and survivorship statistics, 2019. CA: a cancer journal for clinicians. 2019;69(5):363–85. - PubMed
    1. Kumar S, Singh AK, Mohapatra T. Epigenetics: history, present status and future perspective. Indian J Genet Plant Breed. 2017;77:445–63.
    1. Zhu P, Li G. Structural insights of nucleosome and the 30-nm chromatin fiber. Current opinion in structural biology. 2016;36:106–15. - PubMed

Publication types

LinkOut - more resources