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DNA methylation in plants is traditionally partitioned into CG, CHG and CHH contexts (with H any nucleotide but G). By investigating DNA methylation patterns in trinucleotide contexts in four angiosperm species, we show that such a representation hides spatial and functional partitioning of different methylation pathways and is incomplete. CG methylation (mCG) is largely context-independent whereas, at CHG motifs, there is under-representation of mCCG in pericentric regions of A. thaliana and tomato and throughout the chromosomes of maize and rice. In A. thaliana the biased representation of mCCG in heterochromatin is related to specificities of H3K9 methyltransferase SUVH family members. At CHH motifs there is an over-representation of different variant forms of mCHH that, similarly to mCCG hypomethylation, is partitioned into the pericentric regions of the two dicots but dispersed in the monocot chromosomes. The over-represented mCHH motifs in A. thaliana associate with specific types of transposon including both class I and II elements. At mCHH the contextual bias is due to the involvement of various chromomethyltransferases whereas the context-independent CHH methylation in A. thaliana and tomato is mediated by the RNA-directed DNA methylation process that is most active in the gene-rich euchromatin. This analysis therefore reveals that the sequence context of the methylome of plant genomes is informative about the mechanisms associated with maintenance of methylation and the overlying chromatin structure.
Pubmed ID: 27997534 RIS Download
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View all literature mentionsA commercial organization which provides assay technologies to isolate DNA, RNA, and proteins from any biological sample. Assay technologies are then used to make specific target biomolecules, such as the DNA of a specific virus, visible for subsequent analysis.
View all literature mentionsSoftware tool to map bisulfite converted sequence reads and determine cytosine methylation states. Flexible aligner and methylation caller for Bisulfite-Seq applications. Used to map bisulfite treated sequencing reads to genome of interest and perform methylation calls in single step.
View all literature mentionsA software tool developed to process and analyze small RNA-seq data with respect to a reference genome, and output a comprehensive and informative annotation of all discovered small RNA genes. ShortStack discovers small RNA ''clusters'' de novo, based on user-set thresholds, and annotates clusters with respect to small RNA size, orientation, and repetitiveness. ShortStack also discovers and annotates MIRNA genes, and other Hairpin-associated small RNA genes. In addition, ShortStack includes a robust method to detect genes producing small RNAs in a phased manner. It outputs a descriptive table of all results, useful genome browser tracks, a table describing the results of the hairpin / MIRNA analysis for each cluster, and detailed text-based alignments of all MIRNAs and hairpin-associated clusters. It can also be run in ''count'' mode, to quantify a set of input loci with genomic coordinates determined a priori by the user. ShortStack is a perl program. Besides perl, ShortStack also requires samtools and the RNALfold and RNAeval programs from the Vienna RNA Package to execute. When used to control the alignment of small RNA data to a reference genome, ShortStack also requires bowtie and bowtie-build. Finally, for optimal results, ShortStack uses a file of inverted repeats produced by the EMBOSS application einverted.
View all literature mentionsSoftware package for differential gene expression analysis based on the negative binomial distribution. Used for analyzing RNA-seq data for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates.
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