Cooperative interaction between retinoic acid receptor-alpha and estrogen receptor in breast cancer.

Retinoic acid receptor-alpha (RAR alpha) is a known estrogen target gene in breast cancer cells. The consequence of RAR alpha induction by estrogen was previously unknown. We now show that RAR alpha is required for efficient estrogen receptor-alpha (ER)-mediated transcription and cell proliferation. RAR alpha can interact with ER-binding sites, but this occurs in an ER-dependent manner, providing a novel role for RAR alpha that is independent of its classic role. We show, on a genome-wide scale, that RAR alpha and ER can co-occupy regulatory regions together within the chromatin. This transcriptionally active co-occupancy and dependency occurs when exposed to the predominant breast cancer hormone, estrogen--an interaction that is promoted by the estrogen-ER induction of RAR alpha. These findings implicate RAR alpha as an essential component of the ER complex, potentially by maintaining ER-cofactor interactions, and suggest that different nuclear receptors can cooperate for effective transcriptional activity in breast cancer cells.

Variability of ffDNA in maternal plasma does not prevent correct classification of trisomy 21 using MeDIP-qPCR methodology.

OBJECTIVE: The goal of this study is to evaluate the amount of free fetal DNA (ffDNA), total DNA, and 'fetal fraction' found in maternal plasma and whether these influence the enrichment ratios of differentially methylated regions (DMRs) and the correct classification of trisomy 21 using the methylated DNA immunoprecipitation-quantitative polymerase chain reaction (MeDIP-qPCR)-based noninvasive prenatal diagnostic methodology applied in peripheral blood. METHODS: Absolute quantification of ffDNA using DYS14 and total DNA using ß-globin was applied in 83 maternal plasma samples. The quantification values for all 83 samples were correlated with the enrichment ratios of all seven DMRs and D-values that were obtained from the diagnostic formula of MeDIP-qPCR method. RESULTS: Our analysis concluded that trisomy 21 samples had significantly higher ffDNA and total DNA levels compared with those of normal samples. Enrichment ratios of the majority of DMRs studied exhibited no association with ffDNA, total DNA, and 'fetal fraction', and only a small portion of DMRs exhibited moderate association. Correlation studies of ffDNA, total DNA, and fetal fraction with the diagnostic D-value showed weak to no association but without affecting the classification of trisomy 21. CONCLUSION: Overall, the variability of ffDNA and total DNA among maternal samples does not affect the correct trisomy 21 classification using MeDIP-qPCR methodology applied in peripheral blood.

BayesPeak--an R package for analysing ChIP-seq data.

MOTIVATION: Identification of genomic regions of interest in ChIP-seq data, commonly referred to as peak-calling, aims to find the locations of transcription factor binding sites, modified histones or nucleosomes. The BayesPeak algorithm was developed to model the data structure using Bayesian statistical techniques and was shown to be a reliable method, but did not have a full-genome implementation. RESULTS: In this note we present BayesPeak, an R package for genome-wide peak-calling that provides a flexible implementation of the BayesPeak algorithm and is compatible with downstream BioConductor packages. The BayesPeak package introduces a new method for summarizing posterior probability output, along with methods for handling overfitting and support for parallel processing. We briefly compare the package with other common peak-callers. AVAILABILITY: Available as part of BioConductor version 2.6. URL: http://bioconductor.org/packages/release/bioc/html/BayesPeak.html.

MeDIP real-time qPCR of maternal peripheral blood reliably identifies trisomy 21.

OBJECTIVE: To reevaluate the efficiency of the 12 differentially methylated regions (DMRs) used in the methylated DNA immunoprecipitation (MeDIP) real-time quantitative polymerase chain reaction (real-time qPCR) based approach, develop an improved version of the diagnostic formula and perform a larger validation study. METHODS: Twelve selected DMRs were checked for copy number variants in the Database of Genomic Variants. The DMRs located within copy number variants were excluded from the analysis. One hundred and seventy-five maternal peripheral blood samples were used to reconstruct and evaluate the new diagnostic formula and for a larger-scale blinded validation study using MeDIP real-time qPCR. RESULTS: Seven DMRs entered the final model of the prediction equation and a larger blinded validation study demonstrated 100% sensitivity and 99.2% specificity. No significant evidence for association was observed between cell free fetal DNA concentration and D value. CONCLUSION: The MeDIP real-time qPCR method for noninvasive prenatal diagnosis of trisomy 21 was confirmed and revalidated in 175 samples with satisfactory results demonstrating that it is accurate and reproducible. We are currently working towards simplification of the method to make it more robust and therefore easily, accurately, and rapidly reproduced and adopted by other laboratories. Nevertheless, larger scale validation studies are necessary before the MeDIP real-time qPCR-based method could be applied in clinical practice.

ChIP-seq: using high-throughput sequencing to discover protein-DNA interactions.

Chromatin immunoprecipitation (ChIP) allows specific protein-DNA interactions to be isolated. Combining ChIP with high-throughput sequencing reveals the DNA sequence involved in these interactions. Here, we describe how to perform ChIP-seq starting with whole tissues or cell lines, and ending with millions of short sequencing tags that can be aligned to the reference genome of the species under investigation. We also outline additional procedures to recover ChIP-chip libraries for ChIP-seq and discuss contemporary issues in data analysis.

BayesPeak: Bayesian analysis of ChIP-seq data.

BACKGROUND: High-throughput sequencing technology has become popular and widely used to study protein and DNA interactions. Chromatin immunoprecipitation, followed by sequencing of the resulting samples, produces large amounts of data that can be used to map genomic features such as transcription factor binding sites and histone modifications. METHODS: Our proposed statistical algorithm, BayesPeak, uses a fully Bayesian hidden Markov model to detect enriched locations in the genome. The structure accommodates the natural features of the Solexa/Illumina sequencing data and allows for overdispersion in the abundance of reads in different regions. Moreover, a control sample can be incorporated in the analysis to account for experimental and sequence biases. Markov chain Monte Carlo algorithms are applied to estimate the posterior distributions of the model parameters, and posterior probabilities are used to detect the sites of interest. CONCLUSION: We have presented a flexible approach for identifying peaks from ChIP-seq reads, suitable for use on both transcription factor binding and histone modification data. Our method estimates probabilities of enrichment that can be used in downstream analysis. The method is assessed using experimentally verified data and is shown to provide high-confidence calls with low false positive rates.

Inter-individual methylation variability in differentially methylated regions between maternal whole blood and first trimester CVS.

BACKGROUND: DNA methylation is the most studied form of epigenetic regulation, a process by which chromatin composition and transcription factor binding is altered to influence tissue specific gene expression and differentiation. Such tissue specific methylation patterns are investigated as biomarkers for cancer and cell-free fetal DNA using various methodologies. RESULTS: We have utilized methylation DNA immunoprecipitation (MeDIP) and real-time quantitative PCR to investigate the inter-individual methylation variability of differentially methylated regions (DMRs) on chromosomes 18 and 21. We have characterized 15 newly selected and seven previously validated DMRs in 50, 1(st) trimester Chorionic villus samplings (CVS) and 50 female non-pregnant peripheral blood (WBF) samples. qPCR results from MeDIP and genomic DNA (Input) assays were used to calculate fold enrichment values for each DMR. For all regions tested, enrichment was higher in CVS than in WBF samples with mean enrichments ranging from 0.22 to 6.4 and 0.017 to 1 respectively. Despite inter-individual variability, mean enrichment values for CVS were significantly different than those for WBF in all DMRs tested (p < 0.01). This observation is reinforced by the absence of overlap in CVS and WBF enrichment value distributions for 15 of 22 DMRs. CONCLUSIONS: Our work provides an expansion in the biomarker panel available for non-invasive prenatal diagnosis (NIPD) using the MeDIP-qPCR methology for Down syndrome and can eventually provide the starting point towards the development for assays towards the detection of Edwards syndrome. Furthermore, our data indicate that inter-experimental and inter-individual variation in methylation is apparent, yet the difference in methylation status across tissues is large enough to allow for robust tissue specific methylation identification.

Cell cycle genes are the evolutionarily conserved targets of the E2F4 transcription factor.

Maintaining quiescent cells in G0 phase is achieved in part through the multiprotein subunit complex known as DREAM, and in human cell lines the transcription factor E2F4 directs this complex to its cell cycle targets. We found that E2F4 binds a highly overlapping set of human genes among three diverse primary tissues and an asynchronous cell line, which suggests that tissue-specific binding partners and chromatin structure have minimal influence on E2F4 targeting. To investigate the conservation of these transcription factor binding events, we identified the mouse genes bound by E2f4 in seven primary mouse tissues and a cell line. E2f4 bound a set of mouse genes that was common among mouse tissues, but largely distinct from the genes bound in human. The evolutionarily conserved set of E2F4 bound genes is highly enriched for functionally relevant regulatory interactions important for maintaining cellular quiescence. In contrast, we found minimal mRNA expression perturbations in this core set of E2f4 bound genes in the liver, kidney, and testes of E2f4 null mice. Thus, the regulatory mechanisms maintaining quiescence are robust even to complete loss of conserved transcription factor binding events.