5 resultados para 060404 Epigenetics (incl. Genome Methylation and Epigenomics)

em Cambridge University Engineering Department Publications Database


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Plants use siRNAs to target cytosine DNA methylation to both symmetrical CG and nonsymmetrical (CHG and CHH) sequence contexts. DNA methylation and siRNA clusters most frequently overlap with transposons in the Arabidopsis thaliana genome. However, a significant number of protein-coding genes also show promoter DNA methylation, and this can be used to silence their expression. Loss of the majority of non-CG DNA methylation in drm1 drm2 cmt3 triple mutants leads to developmental phenotypes. We identified the gene responsible for these phenotypes as SUPPRESSOR OF drm1 drm2 cmt3 (SDC), which encodes an F-box protein and possesses seven promoter tandem repeats. The SDC repeats show a unique silencing requirement for non-CG DNA methylation directed redundantly by histone methylation and siRNAs, and display spreading of siRNAs and methylation beyond the repeated region. In addition to revealing the complexity of DNA methylation control in A. thaliana, SDC has important implications for how plant genomes utilize gene silencing to repress endogenous genes.

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DNA methylation has two essential roles in plants and animals - defending the genome against transposons and regulating gene expression. Recent experiments in Arabidopsis thaliana have begun to address crucial questions about how DNA methylation is established and maintained. One cardinal insight has been the discovery that DNA methylation can be guided by small RNAs produced through RNA-interference pathways. Plants and mammals use a similar suite of DNA methyltransferases to propagate DNA methylation, but plants have also developed a glycosylase-based mechanism for removing DNA methylation, and there are hints that similar processes function in other organisms.

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We present a nonparametric Bayesian method for disease subtype discovery in multi-dimensional cancer data. Our method can simultaneously analyse a wide range of data types, allowing for both agreement and disagreement between their underlying clustering structure. It includes feature selection and infers the most likely number of disease subtypes, given the data. We apply the method to 277 glioblastoma samples from The Cancer Genome Atlas, for which there are gene expression, copy number variation, methylation and microRNA data. We identify 8 distinct consensus subtypes and study their prognostic value for death, new tumour events, progression and recurrence. The consensus subtypes are prognostic of tumour recurrence (log-rank p-value of $3.6 \times 10^{-4}$ after correction for multiple hypothesis tests). This is driven principally by the methylation data (log-rank p-value of $2.0 \times 10^{-3}$) but the effect is strengthened by the other 3 data types, demonstrating the value of integrating multiple data types. Of particular note is a subtype of 47 patients characterised by very low levels of methylation. This subtype has very low rates of tumour recurrence and no new events in 10 years of follow up. We also identify a small gene expression subtype of 6 patients that shows particularly poor survival outcomes. Additionally, we note a consensus subtype that showly a highly distinctive data signature and suggest that it is therefore a biologically distinct subtype of glioblastoma. The code is available from https://sites.google.com/site/multipledatafusion/

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Campylobacter jejuni is a leading cause of human diarrheal illness in the world, and research on it has benefitted greatly by the completion of several genome sequences and the development of molecular biology tools. However, many hurdles remain for a full understanding of this unique bacterial pathogen. One of the most commonly used strains for genetic work with C. jejuni is NCTC11168. While this strain is readily transformable with DNA for genomic recombination, transformation with plasmids is problematic. In this study, we have identified a determinant of this to be cj1051c, predicted to encode a restriction-modification type IIG enzyme. Knockout mutagenesis of this gene resulted in a strain with a 1,000-fold-enhanced transformation efficiency with a plasmid purified from a C. jejuni host. Additionally, this mutation conferred the ability to be transformed by plasmids isolated from an Escherichia coli host. Sequence analysis suggested a high level of variability of the specificity domain between strains and that this gene may be subject to phase variation. We provide evidence that cj1051c is active in NCTC11168 and behaves as expected for a type IIG enzyme. The identification of this determinant provides a greater understanding of the molecular biology of C. jejuni as well as a tool for plasmid work with strain NCTC11168. © 2012, American Society for Microbiology.

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Cytosine methylation is important for transposon silencing and epigenetic regulation of endogenous genes, although the extent to which this DNA modification functions to regulate the genome is still unknown. Here we report the first comprehensive DNA methylation map of an entire genome, at 35 base pair resolution, using the flowering plant Arabidopsis thaliana as a model. We find that pericentromeric heterochromatin, repetitive sequences, and regions producing small interfering RNAs are heavily methylated. Unexpectedly, over one-third of expressed genes contain methylation within transcribed regions, whereas only approximately 5% of genes show methylation within promoter regions. Interestingly, genes methylated in transcribed regions are highly expressed and constitutively active, whereas promoter-methylated genes show a greater degree of tissue-specific expression. Whole-genome tiling-array transcriptional profiling of DNA methyltransferase null mutants identified hundreds of genes and intergenic noncoding RNAs with altered expression levels, many of which may be epigenetically controlled by DNA methylation.