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Brief Bioinform. 2019 Apr 9. pii: bbz039. doi: 10.1093/bib/bbz039. [Epub ahead of print]

DNA methylation analysis in plants: review of computational tools and future perspectives.

Author information

1
Plant Genome and Systems Biology, Helmholtz Center Munich-German Research Center for Environmental Health, Neuherberg, Germany.
2
Institute of Network Biology, Department of Environmental Science, Helmholtz Center Munich, Neuherberg, Germany.
3
Institute of Environmental Medicine, UNIKA-T, Technical University of Munich and Helmholtz Center Munich, Research Center for Environmental Health, Augsburg, Germany; CK CARE Christine Kühne Center for Allergy Research and Education, Davos, Switzerland.
4
Gregor Mendel Institute of Molecular Plant Biology, Austrian Academy of Sciences, Vienna BioCenter (VBC), Vienna, Austria.

Abstract

Genome-wide DNA methylation studies have quickly expanded due to advances in next-generation sequencing techniques along with a wealth of computational tools to analyze the data. Most of our knowledge about DNA methylation profiles, epigenetic heritability and the function of DNA methylation in plants derives from the model species Arabidopsis thaliana. There are increasingly many studies on DNA methylation in plants-uncovering methylation profiles and explaining variations in different plant tissues. Additionally, DNA methylation comparisons of different plant tissue types and dynamics during development processes are only slowly emerging but are crucial for understanding developmental and regulatory decisions. Translating this knowledge from plant model species to commercial crops could allow the establishment of new varieties with increased stress resilience and improved yield. In this review, we provide an overview of the most commonly applied bioinformatics tools for the analysis of DNA methylation data (particularly bisulfite sequencing data). The performances of a selection of the tools are analyzed for computational time and agreement in predicted methylated sites for A. thaliana, which has a smaller genome compared to the hexaploid bread wheat. The performance of the tools was benchmarked on five plant genomes. We give examples of applications of DNA methylation data analysis in crops (with a focus on cereals) and an outlook for future developments for DNA methylation status manipulations and data integration.

KEYWORDS:

DNA methylation; bisulfite sequencing; differentially methylated regions; epigenetics; epigenomics; plants

PMID:
31220217
DOI:
10.1093/bib/bbz039

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