Sinais epigenéticos diferem ao longo dos alelos

sábado, fevereiro 13, 2010

Epigenetic Signals Differ Across Alleles

ScienceDaily (Feb. 13, 2010) — Researchers from the Institute of Psychiatry (IoP), King's College London, have identified numerous novel regions of the genome where the chemical modifications involved in controlling gene expression are influenced by either genetic variation or the parental origin of that particular stretch of DNA. This contradicts previous assumptions that epigenetic signals are generally equal across both copies of a given region of the genome, except at a small number of known imprinted genes.

Sequencing the genome was only the first step in our quest to understand how genes are expressed and regulated. Epigenetics is the study of alterations to gene function, traditionally believed to occur independently of the DNA sequence. The epigenome sits above the DNA sequence and provides a second layer of information, regulating several genomic functions, including when and where genes are turned on or off. One of the best understood epigenetic mechanisms is DNA methylation, a chemical modification to DNA that can interfere with gene expression.

In the first quantitative genomic survey of allele-specific DNA methylation, published in The American Journal of Human Genetics, scientists used sensitive high-throughput technology to detect evidence for skewed gene DNA methylation across both alleles -- or copies -- of the DNA sequence at almost 1 million positions in the genome.

Lead researcher Dr Jonathan Mill, Medical Research Council Social Genetic, Developmental and Psychiatry Centre at the IoP said: "Interestingly, we found numerous examples where DNA methylation was not equal across alleles -- in some instances this depended upon genotype, and in other cases it depended upon which parent that allele was inherited from."
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The American Journal of Human Genetics
Volume 86, Issue 2, 12 February 2010, Pages 196-212

Allelic Skewing of DNA Methylation Is Widespread across the Genome

Leonard C. Schalkwyk1, 4, Emma L. Meaburn1, 3, 4, Rebecca Smith1, Emma L. Dempster1, Aaron R. Jeffries2, Matthew N. Davies1, Robert Plomin1 and Jonathan Mill1, ,

1 MRC SGDP Research Centre, Institute of Psychiatry, King's College London, London SE5 8AF, UK

2 Department of Neuroscience, Institute of Psychiatry, King's College London, London SE5 8AF, UK

3 Birkbeck College, University of London, London WC1E 7HX, UK

Received 13 August 2009;
revised 21 December 2009;
accepted 18 January 2010.
Published online: February 11, 2010.
Available online 11 February 2010.

Abstract

DNA methylation is assumed to be complementary on both alleles across the genome, although there are exceptions, notably in regions subject to genomic imprinting. We present a genome-wide survey of the degree of allelic skewing of DNA methylation with the aim of identifying previously unreported differentially methylated regions (DMRs) associated primarily with genomic imprinting or DNA sequence variation acting in cis. We used SNP microarrays to quantitatively assess allele-specific DNA methylation (ASM) in amplicons covering 7.6% of the human genome following cleavage with a cocktail of methylation-sensitive restriction enzymes (MSREs). Selected findings were verified using bisulfite-mapping and gene-expression analyses, subsequently tested in a second tissue from the same individuals, and replicated in DNA obtained from 30 parent-child trios. Our approach detected clear examples of ASM in the vicinity of known imprinted loci, highlighting the validity of the method. In total, 2,704 (1.5%) of our 183,605 informative and stringently filtered SNPs demonstrate an average relative allele score (RAS) change ≥0.10 following MSRE digestion. In agreement with previous reports, the majority of ASM (90%) appears to be cis in nature, and several examples of tissue-specific ASM were identified. Our data show that ASM is a widespread phenomenon, with >35,000 such sites potentially occurring across the genome, and that a spectrum of ASM is likely, with heterogeneity between individuals and across tissues. These findings impact our understanding about the origin of individual phenotypic differences and have implications for genetic studies of complex disease.

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