DNA Methylation Profiling of the Human Major Histocompatibility Complex: A Pilot Study for the Human Epigenome Project

The Human Epigenome Project aims to identify, catalogue, and interpret genome-wide DNA methylation phenomena. Occurring naturally on cytosine bases at cytosine–guanine dinucleotides, DNA methylation is intimately involved in diverse biological processes and the aetiology of many diseases. Differentially methylated cytosines give rise to distinct profiles, thought to be specific for gene activity, tissue type, and disease state. The identification of such methylation variable positions will significantly improve our understanding of genome biology and our ability to diagnose disease. Here, we report the results of the pilot study for the Human Epigenome Project entailing the methylation analysis of the human major histocompatibility complex. This study involved the development of an integrated pipeline for high-throughput methylation analysis using bisulphite DNA sequencing, discovery of methylation variable positions, epigenotyping by matrix-assisted laser desorption/ionisation mass spectrometry, and development of an integrated public database available at http://www.epigenome.org. Our analysis of DNA methylation levels within the major histocompatibility complex, including regulatory exonic and intronic regions associated with 90 genes in multiple tissues and individuals, reveals a bimodal distribution of methylation profiles (i.e., the vast majority of the analysed regions were either hypo- or hypermethylated), tissue specificity, inter-individual variation, and correlation with independent gene expression data

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

BRCA2 Arg372His polymorphism and epithelial ovarian cancer risk

The BRCA2 372 HH genotype defined by the BRCA2 N372H nonconservative amino acid substitution polymorphism was recently reported to be associated with a small increased risk of breast cancer. We investigated whether this polymorphism was associated with ovarian cancer risk by conducting British and Australian case-control comparisons in parallel, including a total sample of 1,121 ovarian cancer cases and 2,643 controls. There was no difference in genotype frequency between control groups from the 2 studies (p = 0.9). The HH genotype was associated with an increased risk of ovarian cancer in both studies, and the risk estimate for the pooled studies was 1.36 (95% CI 1.04-1.77, p = 0.03). There was also a suggestion that this risk may be greater for ovarian cancers of the serous subtype for both studies, with an OR (95% CI) of 1.66 (1.17-2.54) for the 2 studies combined (p = 0.005). The BRCA2 372 HH genotype appears to be associated with an increased risk of ovarian cancer of a similar magnitude to that reported for breast cancer

Polymorphisms associated with circulating sex hormone levels in postmenopausal women

BACKGROUND: Reports suggest a relationship between circulating sex hormone levels and breast cancer risk, but genetic association studies have been inconclusive. We investigated the association between levels of sex hormones and single nucleotide polymorphisms (SNPs) in genes coding for the enzymes that regulate them.METHODS: We assayed circulating levels of estradiol, testosterone, estrone, androstenedione, 17alpha-hydroxyprogesterone, and sex hormone-binding globulin (SHBG) in 1975 normal postmenopausal women. Fifteen SNPs in the CYP17, CYP19, EDH17B2, SHBG, COMT, and CYP1B1 genes were genotyped in these postmenopausal women and in a breast cancer case-control study. Associations of genotypes with breast cancer risk were evaluated in the case-control study and with hormone levels in the postmenopausal women using multiple linear regression with assay batch, body mass index, parity, peri- or postmenopausal status, and age band as covariates.RESULTS: CYP19 SNPs (rs10046 and [TCT]+/-) were associated with differences in estradiol level (P =.0006 and P =.0003, respectively) and the estradiol : testosterone ratio (P =.000001() and P =.002). SNP rs10046 explained 1.6% of the variance (r2) in the estradiol : testosterone ratio. SHBG SNPs (5' untranslated region [5'UTR] g-a and D356N) were associated with both SHBG levels (P&lt;10(-6) and P =.005) and the estradiol : SHBG ratio (P =().000008() and P =.01). These SNPs explained 2.4% and 0.6% of the variance in SHBG levels, respectively. SNPs in the other genes were not associated with differences in any hormone levels, and none were statistically significantly associated with breast cancer risk.CONCLUSION: Genetic variation in CYP19 and SHBG contributes to variance in circulating hormone levels between postmenopausal women, but low r2 values may explain why these genes have given inconclusive results in breast cancer case-control studies.</p

Bimodal Distribution of DNA Methylation within the Human MHC

<div><p>(A) Determined by direct sequencing/ESME analysis (based on 86,374 single CpGs in different tissue samples building the median for measurement repetitions).</p> <p>(B) Determined by MALDI-MS (based on 1,019 MALDI measurements).</p></div

Comparison of Methylation Values Measured in Five Tissues and Eleven Amplicons Using MALDI-MS and ESME Analysis of Directly Sequenced PCR Products

<p>Each column is a tissue sample, each row a CpG site. Data are ordered in blocks by tissue type and amplicons. Positions of measurements for MALDI-MS (A) correspond to those for ESME analysis (B). The methylation values are colour coded from 0% methylation (yellow) to 100% methylation (blue), with intermediate methylation levels represented by shades of green. White indicates missing measurement values.</p

The HEP Database

<div><p>(A) We have created a Web-based, ENSEMBL-like genome browser for displaying HEP data that is publicly available at <a href="http://www.epigenome.org" target="_blank">http://www.epigenome.org</a>. The methylation levels calculated by the ESME software are displayed in the form of a matrix. Each matrix contains the data obtained from all the samples of one amplicon. Each colour-coded square (yellow represents 0% methylation, blue represents 100% methylation, and green represents intermediate levels) within the matrix represents one CpG site. Clicking on a square reveals the tissue source of the sample and the level of methylation observed at that particular CpG site. Grey squares indicate CpG sites for which methylation levels could not be determined. Each row of squares represents all the CpG sites for one sample of a particular amplicon, and the samples are grouped by tissue type. The red bar indicates the genomic region analysed. Also shown are chromosome coordinates, CpG islands, SNPs, and ENSEMBL and high-quality, manually curated VEGA transcript information. The HEP database links to the Ensembl genome browser, providing additional information about the region of interest. The example shows amplicons within the <i>SynGAP 1</i> gene that correspond to regions that were determined to be hypomethylated (second amplicon from the left), hypermethylated (first and fifth amplicons), and heterogeneously methylated (fourth amplicon). Insufficient data were obtained for the third amplicon.</p> <p>(B) By using the zoom function, the user can view the complete DNA sequence for the analysed amplicon.</p></div

Example of METHANE Output Showing Regions That Display Inter-Individual Variation of Methylation Profiles

<div><p>(A) Example of a region that displays significant inter-individual variation, especially in prostate. The matrix represents an amplicon that contains 27 CpG sites within a 527-bp region overlapping the last exon of the <i>CYP21A2</i> gene.</p> <p>(B) Another example of a region that displays significant inter-individual variation. The matrix represents an amplicon that contains 13 CpG sites within a 453-bp region overlapping the 5′ UTR and exon 1 of the <i>tumour necrosis factor</i> gene.</p></div

Comparison of DNA Methylation with Gene Expression

<p>Amplicons generated from prostate (yellow), lung (blue), and liver (green) samples were divided into two categories: “upstream” and “intragenic”. The median methylation values for the amplicons were calculated as described in the text, and these were then classified as hypomethylated (median methylation less than 50%) or hypermethylated (median methylation greater than 50%), and plotted against the cDNA microarray expression data available at <a href="http://expression.gnf.org" target="_blank">http://expression.gnf.org</a> (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0020405#pbio-0020405-Su1" target="_blank">Su et al. 2002</a>). The expression values are expressed as average difference values (ADVs) for each gene. The average difference value is computed using Affymetrix software and is proportional to mRNA content in the sample, with a value of 200 being a conservative cut-off below which a gene can be classified as being not expressed. The average difference values are the mean of 2 or 3 independent experiments. For prostate and liver, the expression levels associated with the hypermethylated upstream amplicons were significantly lower than the expression levels associated with the hypomethylated upstream amplicons (<i>p</i> < 0.0001 for prostate and <i>p</i> < 0.01 for liver). For lung, there was no significant difference between the expression levels associated with the hypermethylated upstream amplicons and those of the hypomethylated upstream amplicons (<i>p</i> > 0.3). There was no correlation between expression and methylation for the intragenic amplicons for any of the three tissues (<i>p</i> > 0.3). The width of the bars is indicative of the number of amplicons in each category: prostate upstream, hypermethylated (<i>n</i> = 9); prostate upstream, hypomethylated (<i>n</i> = 15); prostate intragenic, hypermethylated (<i>n</i> = 109); prostate intragenic, hypomethylated (<i>n</i> = 53); liver upstream, hypermethylated (<i>n</i> = 9); liver upstream, hypomethylated (<i>n</i> = 14); liver intragenic, hypermethylated (<i>n</i> = 115); liver intragenic, hypomethylated (<i>n</i> = 45); lung upstream, hypermethylated (<i>n</i> = 9); lung upstream, hypomethylated (<i>n</i> = 13); lung intragenic, hypermethylated (<i>n</i> = 112); and lung intragenic, hypomethylated (<i>n</i> = 57).</p