Computational Protocol for DNA Methylation Profiling in Plants Using Restriction Enzyme-Based Genome Reduction

• Published in: Methods in molecular biology (Clifton, N.J.) Vol. 2638; p. 23
• Main Authors: Pereira, Wendell Jacinto, de Castro Rodrigues Pappas, Marília, Pappas, Jr, Georgios Joannis
• Format: Journal Article
• Language: English
• Published: United States 2023
• Subjects: DNA Methylation; DNA Restriction Enzymes - genetics; Epigenesis, Genetic; Genomics - methods; Sequence Analysis, DNA - methods; Sulfites; DNA methylation; Restriction enzymes; Next-generation sequencing; Differential expression; Computational protocol; Methylation sensitivity
• ISSN: 1940-6029
• DOI: 10.1007/978-1-0716-3024-2_3

Epigenetics can be described as heritable phenotype changes that do not involve alterations in the underlying DNA sequence. Having widespread implications in fundamental biological phenomena, there is an increased interest in characterizing epigenetic modifications and studying their functional implications. DNA methylation, particularly 5-methylcytosine (5mC), stands out as the most studied epigenetic mark and several methodologies have been created to investigate it. With the development of next-generation sequencing technologies, several approaches to DNA methylation profiling were conceived, with differences in resolution and genomic scope. Besides the gold standard whole-genome bisulfite sequencing, which is costly for population-scale studies, genomic reduced representation methods emerged as viable alternatives to investigate methylation loci. Whole-genome bisulfite sequencing provides single-base methylation resolution but is costly for population-scale studies. Genomic reduction methods emerged as viable alternatives to investigate a fraction of methylated loci. One of such approaches uses double digestion with the restriction enzymes PstI and one of the isoschizomers, MspI and HpaII, with differential sensitivity to 5mC at the restriction site. Statistical comparison of sequencing reads counts obtained from the two libraries for each sample (PstI-MspI and PstI-HpaII) is used to infer the methylation status of thousands of cytosines. Here, we describe a general overview of the technique and a computational protocol to process the generated data to provide a medium-scale inventory of methylated sites in plant genomes. The software is available at https://github.com/wendelljpereira/DArTseqMet .