'Leveling' the playing field for analyses of single-base resolution DNA methylomes

Bioinformatics Program, University of California at San Diego, La Jolla, CA 92093, USA.
Trends in Genetics (Impact Factor: 9.92). 11/2012; 28(12). DOI: 10.1016/j.tig.2012.10.012
Source: PubMed
16 Reads
  • Source
    • "Methylated cytosines were extracted from aligned reads using the Bismark methylation extractor under standard parameters. The proportion of CG, CG, and CHH methylation was determined as weighted methylation levels [30] in 100bp non-overlapping windows across the genome. "
    [Show abstract] [Hide abstract]
    ABSTRACT: DNA methylation and dimethylation of lysine 9 of histone H3 (H3K9me2) are two chromatin modifications that can be associated with gene expression or recombination rate. The maize genome provides a complex landscape of interspersed genes and transposons. The genome-wide distribution of DNA methylation and H3K9me2 were investigated in seedling tissue for the maize inbred B73 and compared to patterns of these modifications observed in Arabidopsis thaliana. Most maize transposons are highly enriched for DNA methylation in CG and CHG contexts and for H3K9me2. In contrast to findings in Arabidopsis, maize CHH levels in transposons are generally low but some sub-families of transposons are enriched for CHH methylation and these families exhibit low levels of H3K9me2. The profile of modifications over genes reveals that DNA methylation and H3K9me2 is quite low near the beginning and end of genes. Although elevated CG and CHG methylation are found within gene bodies, CHH and H3K9me2 remain low. Maize has much higher levels of CHG methylation within gene bodies than observed in Arabidopsis and this is partially attributable to the presence of transposons within introns for some maize genes. These transposons are associated with high levels of CHG methylation and H3K9me2 but do not appear to prevent transcriptional elongation. Although the general trend is for a strong depletion of H3K9me2 and CHG near the transcription start site there are some putative genes that have high levels of these chromatin modifications. This study provides a clear view of the relationship between DNA methylation and H3K9me2 in the maize genome and how the distribution of these modifications is shaped by the interplay of genes and transposons.
    PLoS ONE 08/2014; 9(8):e105267. DOI:10.1371/journal.pone.0105267 · 3.23 Impact Factor
  • Source
    • "For cytosines within the symmetric CpG sequence context, reads from the both strands are used to give a single estimate. Besides methylation levels at individual cytosines, researchers are also interested in the methylation status in certain regions, which can be represented with mean methylation level, proportion of methylated cytosines or mean methylation level weighted by coverage [37]. These values can be computed for any single region using the levels program, and the weighted mean methylation level can be computed for a set of regions (such as promoters) using roimethstat. "
    [Show abstract] [Hide abstract]
    ABSTRACT: DNA methylation is implicated in a surprising diversity of regulatory, evolutionary processes and diseases in eukaryotes. The introduction of whole-genome bisulfite sequencing has enabled the study of DNA methylation at a single-base resolution, revealing many new aspects of DNA methylation and highlighting the usefulness of methylome data in understanding a variety of genomic phenomena. As the number of publicly available whole-genome bisulfite sequencing studies reaches into the hundreds, reliable and convenient tools for comparing and analyzing methylomes become increasingly important. We present MethPipe, a pipeline for both low and high-level methylome analysis, and MethBase, an accompanying database of annotated methylomes from the public domain. Together these resources enable researchers to extract interesting features from methylomes and compare them with those identified in public methylomes in our database.
    PLoS ONE 12/2013; 8(12):e81148. DOI:10.1371/journal.pone.0081148 · 3.23 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Whole genome methylation profiling at a single cytosine resolution is now feasible due to the advent of high-throughput sequencing techniques together with bisulfite treatment of the DNA. To obtain the methylation value of each individual cytosine, the bisulfite-treated sequence reads are first aligned to a reference genome, and then the profiling of the methylation levels is done from the alignments. A huge effort has been made to quickly and correctly align the reads and many different algorithms and programs to do this have been created. However, the second step is just as crucial and non-trivial, but much less attention has been paid to the final inference of the methylation states. Important error sources do exist, such as sequencing errors, bisulfite failure, clonal reads, and single nucleotide variants. We developed MethylExtract, a user friendly tool to: i) generate high quality, whole genome methylation maps and ii) detect sequence variation within the same sample preparation. The program is implemented into a single script and takes into account all major error sources. MethylExtract detects variation (SNVs - Single Nucleotide Variants) in a similar way to VarScan, a very sensitive method extensively used in SNV and genotype calling based on non-bisulfite-treated reads. The usefulness of MethylExtract is shown by means of extensive benchmarking based on artificial bisulfite-treated reads and a comparison to a recently published method, called Bis-SNP. MethylExtract is able to detect SNVs within High-Throughput Sequencing experiments of bisulfite treated DNA at the same time as it generates high quality methylation maps. This simultaneous detection of DNA methylation and sequence variation is crucial for many downstream analyses, for example when deciphering the impact of SNVs on differential methylation. An exclusive feature of MethylExtract, in comparison with existing software, is the possibility to assess the bisulfite failure in a statistical way. The source code, tutorial and artificial bisulfite datasets are available at and, and also permanently accessible from 10.5281/zenodo.7144.
    F1000 Research 01/2013; 2:217. DOI:10.12688/f1000research.2-217.v1
Show more