Study of the Epigenetic Signals in the Human Genome

Epigenetics can be defined as changes in the genome that are inherited during cell division, but without direct modification of the DNA sequence. These genomic changes are supported by three major epigenetic mechanisms: DNA methylation, histone modification and small RNAs. Different epigenetic marks function regulate gene transcription, some of them when altered can trigger various diseases such as cancer. This work is focus on the epigenetic signals in the human genome, studding the dependency between the nucleotide word context and the occurrence of epigenomic marking. We based our study on histone epigenomes available in the NIH Roadmap Epigenomics Mapping Consortium database that contains various types of cells and various types of tissues. We compared genomic contexts of epigenetic marking among chromosomes and among epigenomes. We included a control scenario, the DNA sequence regions without epigenetic marking. We identified significant differences between context occurrence of control and epigenetic regions. The genomic words in epigenetic marking regions present significant association with chromosome and histone modification type

Ethnic differences in ovulatory function in nulliparous women

African-American women have a long-standing approximately 20% higher breast cancer incidence rate than USA White women under age 40 while rates among Latinas are lower than those of Whites. The reasons for this are not clear, however they may be due to ethnic differences in circulating oestradiol and progesterone levels. In a cross-sectional study, we investigated whether anovulation frequency and circulating serum oestradiol and/or progesterone levels vary among normally cycling nulliparous African-American (n=60), Latina (n=112) and non-Latina White (n=69) women. Blood and urine specimens were collected over two menstrual cycles among healthy 17- to 34-year-old women. Frequency of anovulation was greater among White women (nine out of 63, 14.3%) than African-American women (four out of 56, 7.1%) or Latina women (seven out of 102, 6.9%), although these differences were not statistically significant. African-American women had 9.9% (P=0.26) higher follicular phase oestradiol concentrations than Latina women and 17.4% (P=0.13) higher levels than White women. African-American women also had considerably higher levels of luteal phase oestradiol (vs Latinas, +9.4%, P=0.14; vs Whites, +25.3%, P=0.003) and progesterone (vs Latinas, +15.4%, P=0.07; vs Whites, +36.4%, P=0.002). Latina women were also observed to have higher follicular oestradiol, and luteal oestradiol and progesterone levels than White women (follicular oestradiol: +6.8%, P=0.48; luteal oestradiol: +14.6%, P=0.04; luteal progesterone: +18.2%, P=0.06). These results suggest that exposure to endogenous steroid hormones may be greater for young African-American and Latina women than for Whites

Predicting cell types and genetic variations contributing to disease by combining GWAS and epigenetic data

Genome-wide association studies (GWASs) identify single nucleotide polymorphisms (SNPs) that are enriched in individuals suffering from a given disease. Most disease-associated SNPs fall into non-coding regions, so that it is not straightforward to infer phenotype or function; moreover, many SNPs are in tight genetic linkage, so that a SNP identified as associated with a particular disease may not itself be causal, but rather signify the presence of a linked SNP that is functionally relevant to disease pathogenesis. Here, we present an analysis method that takes advantage of the recent rapid accumulation of epigenomics data to address these problems for some SNPs. Using asthma as a prototypic example; we show that non-coding disease-associated SNPs are enriched in genomic regions that function as regulators of transcription, such as enhancers and promoters. Identifying enhancers based on the presence of the histone modification marks such as H3K4me1 in different cell types, we show that the location of enhancers is highly cell-type specific. We use these findings to predict which SNPs are likely to be directly contributing to disease based on their presence in regulatory regions, and in which cell types their effect is expected to be detectable. Moreover, we can also predict which cell types contribute to a disease based on overlap of the disease-associated SNPs with the locations of enhancers present in a given cell type. Finally, we suggest that it will be possible to re-analyze GWAS studies with much higher power by limiting the SNPs considered to those in coding or regulatory regions of cell types relevant to a given disease

Easy detection of chromatin binding proteins by the histone association assay

The Histone Association Assay provides an easy approach for detecting proteins that bind chromatin in vivo. This technique is based on a chromatin immunoprecipitation protocol using histone H3-specific antibodies to precipitate bulk chromatin from crosslinked whole cell extracts. Proteins that co-precipitate with chromatin are subsequently detected by conventional SDS-PAGE and Western blot analysis. Unlike techniques that separate chromatin and non-chromatin interacting proteins by centrifugation, this method can be used to delineate whether a protein is chromatin associated regardless of its innate solubility. Moreover, the relative amount of protein bound to DNA can be ascertained under quantitative conditions. Therefore, this technique may be utilized for analyzing the chromatin association of proteins involved in diverse cellular processes

Fgfr3 Is a Transcriptional Target of Ap2δ and Ash2l-Containing Histone Methyltransferase Complexes

Polycomb (PcG) and trithorax (trxG) proteins play important roles in establishing lineage-specific genetic programs through induction of chromatin modifications that lead to gene silencing or activation. Previously, we described an association between the MLL/SET1 complexes and a highly restricted, gene-specific DNA-binding protein Ap2δ that is required for recruitment of the MLL/SET1 complex to target Hoxc8 specifically. Here, we reduced levels of Ap2δ and Ash2l in the neuroblastoma cell line, Neuro2A, and analyzed their gene expression profiles using whole-genome mouse cDNA microarrays. This analysis yielded 42 genes that are potentially co-regulated by Ap2δ and Ash2l, and we have identified evolutionarily conserved Ap2-binding sites in 20 of them. To determine whether some of these were direct targets of the Ap2δ-Ash2l complex, we analyzed several promoters for the presence of Ap2δ and Ash2l by chromatin immunoprecipitation (ChIP). Among the targets we screened, we identified Fgfr3 as a direct transcriptional target of the Ap2δ-Ash2l complex. Additionally, we found that Ap2δ is necessary for the recruitment of Ash2l-containing complexes to this promoter and that this recruitment leads to trimethylation of lysine 4 of histone H3 (H3K4me3). Thus, we have identified several candidate targets of complexes containing Ap2δ and Ash2l that can be used to further elucidate their roles during development and showed that Fgfr3 is a novel direct target of these complexes

Genome-Scale Validation of Deep-Sequencing Libraries

Chromatin immunoprecipitation followed by high-throughput (HTP) sequencing (ChIP-seq) is a powerful tool to establish protein-DNA interactions genome-wide. The primary limitation of its broad application at present is the often-limited access to sequencers. Here we report a protocol, Mab-seq, that generates genome-scale quality evaluations for nucleic acid libraries intended for deep-sequencing. We show how commercially available genomic microarrays can be used to maximize the efficiency of library creation and quickly generate reliable preliminary data on a chromosomal scale in advance of deep sequencing. We also exploit this technique to compare enriched regions identified using microarrays with those identified by sequencing, demonstrating that they agree on a core set of clearly identified enriched regions, while characterizing the additional enriched regions identifiable using HTP sequencing

Background risk of breast cancer and the association between physical activity and mammographic density

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Reproductive factors and breast cancer risk according to joint estrogen and progesterone receptor status: a meta-analysis of epidemiological studies

INTRODUCTION: Although reproductive factors have been known for decades to be associated with breast cancer risk, it is unclear to what extent these associations differ by estrogen and progesterone receptor (ER/PR) status. This report presents the first meta-analysis of results from epidemiological studies that have investigated parity, age at first birth, breastfeeding, and age at menarche in relation to ER(+)PR(+ )and ER(-)PR(- )cancer risk. MATERIALS AND METHODS: We calculated summary relative risks (RRs) and corresponding 95% confidence intervals (CIs) using a fixed effects model. RESULTS: Each birth reduced the risk of ER(+)PR(+ )cancer by 11% (RR per birth = 0.89, 95% CI = 0.84–0.94), and women who were in the highest age at first birth category had, on average, 27% higher risk of ER(+)PR(+ )cancer compared with women who were in the youngest age at first birth category (RR = 1.27, 95% CI = 1.07–1.50). Neither parity nor age at first birth was associated with the risk of ER(-)PR(- )cancer (RR per birth = 0.99, 95% CI = 0.94–1.05; RR of oldest versus youngest age at first birth category = 1.01, 95% CI = 0.85–1.20). Breastfeeding and late age at menarche decreased the risk of both receptor subtypes of breast cancer. The protective effect of late age at menarche was statistically significantly greater for ER(+)PR(+ )than ER(-)PR(- )cancer (RR = 0.72 for ER(+)PR(+ )cancer; RR = 0.84 for ER(-)PR(- )cancer, p for homogeneity = 0.006). CONCLUSION: Our findings suggest that breastfeeding (and age at menarche) may act through different hormonal mechanisms than do parity and age at first birth

A single low-energy, iron-poor supernova as the source of metals in the star SMSS J 031300.36-670839.3

The element abundance ratios of four low-mass stars with extremely low metallicities indicate that the gas out of which the stars formed was enriched in each case by at most a few, and potentially only one low-energy, supernova. Such supernovae yield large quantities of light elements such as carbon but very little iron. The dominance of low-energy supernovae is surprising, because it has been expected that the first stars were extremely massive, and that they disintegrated in pair-instability explosions that would rapidly enrich galaxies in iron. What has remained unclear is the yield of iron from the first supernovae, because hitherto no star is unambiguously interpreted as encapsulating the yield of a single supernova. Here we report the optical spectrum of SMSS J031300.36- 670839.3, which shows no evidence of iron (with an upper limit of 10^-7.1 times solar abundance). Based on a comparison of its abundance pattern with those of models, we conclude that the star was seeded with material from a single supernova with an original mass of ~60 Mo (and that the supernova left behind a black hole). Taken together with the previously mentioned low-metallicity stars, we conclude that low-energy supernovae were common in the early Universe, and that such supernovae yield light element enrichment with insignificant iron. Reduced stellar feedback both chemically and mechanically from low-energy supernovae would have enabled first-generation stars to form over an extended period. We speculate that such stars may perhaps have had an important role in the epoch of cosmic reionization and the chemical evolution of early galaxies.Comment: 28 pages, 6 figures, Natur