Damian Roqueiro

Genome-wide analysis of local chromatin packing in Arabidopsis thaliana

The spatial arrangement of interphase chromosomes in the nucleus is important for gene expression and genome function in animals and in plants. The recently developed Hi-C technology is an efficacious method to investigate genome packing. Here we present a detailed Hi-C map of the three-dimensional genome organization of the plant Arabidopsis thaliana. We find that local chromatin packing differs from the patterns seen in animals, with kilobasepair-sized segments that have much higher intrachromosome interaction rates than neighboring regions, representing a dominant local structural feature of genome conformation in A. thaliana. These regions, which appear as positive strips on two-dimensional representations of chromatin interaction, are enriched in epigenetic marks H3K27me3, H3.1, and H3.3. We also identify more than 400 insulator-like regions. Furthermore, although topologically associating domains (TADs), which are prominent in animals, are not an obvious feature of A. thaliana genome packing, we found more than 1000 regions that have properties of TAD boundaries, and a similar number of regions analogous to the interior of TADs. The insulator-like, TAD-boundary-like, and TAD-interior-like regions are each enriched for distinct epigenetic marks and are each correlated with different gene expression levels. We conclude that epigenetic modifications, gene density, and transcriptional activity combine to shape the local packing of the A. thaliana nuclear genome.

Genome-Wide DNA Methylation Analysis Predicts an Epigenetic Switch for GATA Factor Expression in Endometriosis

Endometriosis is a gynecological disease defined by the extrauterine growth of endometrial-like cells that cause chronic pain and infertility. The disease is limited to primates that exhibit spontaneous decidualization, and diseased cells are characterized by significant defects in the steroid-dependent genetic pathways that typify this process. Altered DNA methylation may underlie these defects, but few regions with differential methylation have been implicated in the disease. We mapped genome-wide differences in DNA methylation between healthy human endometrial and endometriotic stromal cells and correlated this with gene expression using an interaction analysis strategy. We identified 42,248 differentially methylated CpGs in endometriosis compared to healthy cells. These extensive differences were not unidirectional, but were focused intragenically and at sites distal to classic CpG islands where methylation status was typically negatively correlated with gene expression. Significant differences in methylation were mapped to 403 genes, which included a disproportionally large number of transcription factors. Furthermore, many of these genes are implicated in the pathology of endometriosis and decidualization. Our results tremendously improve the scope and resolution of differential methylation affecting the HOX gene clusters, nuclear receptor genes, and intriguingly the GATA family of transcription factors. Functional analysis of the GATA family revealed that GATA2 regulates key genes necessary for the hormone-driven differentiation of healthy stromal cells, but is hypermethylated and repressed in endometriotic cells. GATA6, which is hypomethylated and abundant in endometriotic cells, potently blocked hormone sensitivity, repressed GATA2, and induced markers of endometriosis when expressed in healthy endometrial cells. The unique epigenetic fingerprint in endometriosis suggests DNA methylation is an integral component of the disease, and identifies a novel role for the GATA family as key regulators of uterine physiology–aberrant DNA methylation in endometriotic cells correlates with a shift in GATA isoform expression that facilitates progesterone resistance and disease progression.

Notch1 mediates uterine stromal differentiation and is critical for complete decidualization in the mouse.

Uterine receptivity implies a dialogue between the hormonally primed maternal endometrium and the free‐floating blastocyst. Endometrial stromal cells proliferate, avert apoptosis, and undergo decidualization in preparation for implantation; however, the molecular mechanisms that underlie differentiation into the decidual phenotype remain largely undefined. The Notch family of transmembrane receptors transduce extracellular signals responsible for cell survival, cell‐to‐cell communication, and differentiation, all fundamental processes for decidualization and pregnancy. Using a murine artificial decidualization model, pharmacological inhibition of Notch signaling by γ‐secretase inhibition resulted in a significantly decreased deciduoma. Furthermore, a progesterone receptor (PR)‐Cre Notch1 bigenic (Notch1d/d) confirmed a Notch1‐dependent hypomorphic decidual phenotype. Microarray and pathway analysis, following Notch1 ablation, demonstrated significantly altered signaling repertoire. Concomitantly, hierarchical clustering demonstrated Notch1‐dependent differences in gene expression. Uteri deprived of Notch1 signaling demonstrated decreased cellular proliferation; namely, reduced proliferation‐specific antigen, Ki67, altered p21, cdk6, and cyclinD activity and an increased apoptotic‐profile, cleaved caspase‐3, Bad, and attenuated Bcl2. The results demonstrate that the preimplantation uterus relies on Notch signaling to inhibit apoptosis of stromal fibroblasts and regulate cell cycle progression, which together promotes successful decidualization. In summary, Notch1 signaling modulates multiple signaling mechanisms crucial for decidualization and these studies provide additional perspectives to the coordination of multiple signaling modalities required during decidualization.—Afshar, Y., Jeong, J.‐W., Roqueiro, D., DeMayo, F., Lydon, J., Radtke, F., Radnor, R., Miele, L., Fazleabas, A. Notch1 mediates uterine stromal differentiation and is critical for complete decidualization in the mouse. FASEB J. 26, 282–294 (2012). www.fasebj.org

Genome-Wide Progesterone Receptor Binding: Cell Type-Specific and Shared Mechanisms in T47D Breast Cancer Cells and Primary Leiomyoma Cells

Background Progesterone, via its nuclear receptor (PR), exerts an overall tumorigenic effect on both uterine fibroid (leiomyoma) and breast cancer tissues, whereas the antiprogestin RU486 inhibits growth of these tissues through an unknown mechanism. Here, we determined the interaction between common or cell-specific genome-wide binding sites of PR and mRNA expression in RU486-treated uterine leiomyoma and breast cancer cells. Principal Findings ChIP-sequencing revealed 31,457 and 7,034 PR-binding sites in breast cancer and uterine leiomyoma cells, respectively; 1,035 sites overlapped in both cell types. Based on the chromatin-PR interaction in both cell types, we statistically refined the consensus progesterone response element to G•ACA• • •TGT•C. We identified two striking differences between uterine leiomyoma and breast cancer cells. First, the cis-regulatory elements for HSF, TEF-1, and C/EBPα and β were statistically enriched at genomic RU486/PR-targets in uterine leiomyoma, whereas E2F, FOXO1, FOXA1, and FOXF sites were preferentially enriched in breast cancer cells. Second, 51.5% of RU486-regulated genes in breast cancer cells but only 6.6% of RU486-regulated genes in uterine leiomyoma cells contained a PR-binding site within 5 kb from their transcription start sites (TSSs), whereas 75.4% of RU486-regulated genes contained a PR-binding site farther than 50 kb from their TSSs in uterine leiomyoma cells. RU486 regulated only seven mRNAs in both cell types. Among these, adipophilin (PLIN2), a pro-differentiation gene, was induced via RU486 and PR via the same regulatory region in both cell types. Conclusions Our studies have identified molecular components in a RU486/PR-controlled gene network involved in the regulation of cell growth, cell migration, and extracellular matrix function. Tissue-specific and common patterns of genome-wide PR binding and gene regulation may determine the therapeutic effects of antiprogestins in uterine fibroids and breast cancer.

Changes in Eutopic Endometrial Gene Expression During the Progression of Experimental Endometriosis in the Baboon, Papio Anubis

ABSTRACT Endometriosis is associated with aberrant gene expression in the eutopic endometrium of women with disease. To determine if the development of endometriotic lesions directly impacts eutopic endometrial gene expression, we sequentially analyzed the eutopic endometrium across the time course of disease progression in a baboon model of induced disease. Endometriosis was induced in baboons (n = 4) by intraperitoneal inoculation of autologous menstrual endometrium. Eutopic endometria were collected during the midsecretory phase (Days 9–11 postovulation) at 1, 3, 6–7, 10–12, and 15–16 mo after disease induction and compared with tissue from disease-free baboons. RNA was hybridized to Human Genome U133 Plus 2.0 Arrays, and data were extracted using Gene-Chip Operating Software. Subsequently, both Gene Set Enrichment Analysis and Ingenuity Pathways Analysis were used to find biological states that have a statistically significant enrichment concomitant with pairwise comparison of human endometriosis arrays. Within 1 mo of induction of the disease, 4331 genes were differentially expressed (P < 0.05). Hierarchical clustering revealed self-segregation into two groups—a) 1, 3, and 10–12 mo and b) 6–7 and 15–16 mo—together with controls. Clustering analysis at each stage of disease validated dysregulation of several signaling pathways, including Nodal-like receptor, EGF, ERK/MAPK, and PI3/AKT. Sequential analysis of the same animals during disease progression demonstrated an early disease insult and a transitory dominance of an estrogenic phenotype; however, as the disease progressed, a progesterone-resistant phenotype became evident. Furthermore, we demonstrate a 38.6% differential gene expression overlap with endometrial samples in the midsecretory phase from women with endometriosis, concomitant with similar dysregulation in human disease candidate genes Fos, Nodal, Suclg2, and Kras, among others. Molecular changes in the eutopic endometrium, associated with endometriosis, are directly impacted by endometriotic lesions, providing strong evidence that it is the disease rather than inherent defective endometrium that results in aberrant gene expression in the eutopic endometrium. Furthermore, this baboon model provides a powerful means whereby the early events associated with the pathology of disease and the resulting infertility may be elucidated.

Counting people using video cameras

The paper is devoted to the problem of estimating the number of people visible in a camera. It uses as features the ratio of foreground pixels in each cell of a rectangular grid. Using the above features and data mining techniques allowed reaching accuracy up to 85% for exact match and up to 95% for plus–minus one estimates for an indoor surveillance environment. Applying median filters to the sequence of estimation results increased the accuracy up to 91% for exact match. The architecture of a real-time people counting estimator is suggested. The results of analysis of experimental data are provided and discussed.

Multiple-Sensor Indoor Surveillance System

This paper describes a surveillance system that uses a network of sensors of different kind for localizing and tracking people in an office environment. The sensor network consists of video cameras, infrared tag readers, a fingerprint reader and a PTZ camera. The system implements a Bayesian framework that uses noisy, but redundant data from multiple sensor streams and incorporates it with the contextual and domain knowledge. The paper describes approaches to camera specification, dynamic background modeling, object modeling and probabilistic inference. The preliminary experimental results are presented and discussed.

Extremely Long-Range Chromatin Loops Link Topological Domains to Facilitate a Diverse Antibody Repertoire

Early B cell development is characterized by large-scale Igh locus contraction prior to V(D)J recombination to facilitate a highly diverse Ig repertoire. However, an understanding of the molecular architecture that mediates locus contraction remains unclear. We have combined high-resolution chromosome conformation capture (3C) techniques with 3D DNA FISH to identify three conserved topological subdomains. Each of these topological folds encompasses a major VH gene family that become juxtaposed in pro-B cells via megabase-scale chromatin looping. The transcription factor Pax5 organizes the subdomain that spans the VHJ558 gene family. In its absence, the J558 VH genes fail to associate with the proximal VH genes, thereby providing a plausible explanation for reduced VHJ558 gene rearrangements in Pax5-deficient pro-B cells. We propose that Igh locus contraction is the cumulative effect of several independently controlled chromatin subdomains that provide the structural infrastructure to coordinate optimal antigen receptor assembly.

easyGWAS: A Cloud-based Platform for Comparing the Results of Genome-wide Association Studies

The easyGWAS platform is a powerful online resource for computing, storing, sharing, and comparing the results of GWAS in both inbred and outbred plant and animal species. The ever-growing availability of high-quality genotypes for a multitude of species has enabled researchers to explore the underlying genetic architecture of complex phenotypes at an unprecedented level of detail using genome-wide association studies (GWAS). The systematic comparison of results obtained from GWAS of different traits opens up new possibilities, including the analysis of pleiotropic effects. Other advantages that result from the integration of multiple GWAS are the ability to replicate GWAS signals and to increase statistical power to detect such signals through meta-analyses. In order to facilitate the simple comparison of GWAS results, we present easyGWAS, a powerful, species-independent online resource for computing, storing, sharing, annotating, and comparing GWAS. The easyGWAS tool supports multiple species, the uploading of private genotype data and summary statistics of existing GWAS, as well as advanced methods for comparing GWAS results across different experiments and data sets in an interactive and user-friendly interface. easyGWAS is also a public data repository for GWAS data and summary statistics and already includes published data and results from several major GWAS. We demonstrate the potential of easyGWAS with a case study of the model organism Arabidopsis thaliana, using flowering and growth-related traits.

Identifying transcription factors and microRNAs as key regulators of pathways using Bayesian inference on known pathway structures

BackgroundTranscription factors and microRNAs act in concert to regulate gene expression in eukaryotes. Numerous computational methods based on sequence information are available for the prediction of target genes of transcription factors and microRNAs. Although these methods provide a static snapshot of how genes may be regulated, they are not effective for the identification of condition-specific regulators.ResultsWe propose a new method that combines: a) transcription factors and microRNAs that are predicted to target genes in pathways, with b) microarray expression profiles of microRNAs and mRNAs, in conjunction with c) the known structure of molecular pathways. These elements are integrated into a Bayesian network derived from each pathway that, through probability inference, allows for the prediction of the key regulators in the pathway. We demonstrate 1) the steps to discretize the expression data for the computation of conditional probabilities in a Bayesian network, 2) the procedure to construct a Bayesian network using the structure of a known pathway and the transcription factors and microRNAs predicted to target genes in that pathway, and 3) the inference results as potential regulators of three signaling pathways using microarray expression profiles of microRNA and mRNA in estrogen receptor positive and estrogen receptor negative tumors.ConclusionsWe displayed the ability of our framework to integrate multiple sets of microRNA and mRNA expression data, from two phenotypes, with curated molecular pathway structures by creating Bayesian networks. Moreover, by performing inference on the network using known evidence, e.g., status of differentially expressed genes, or by entering hypotheses to be tested, we obtain a list of potential regulators of the pathways. This, in turn, will help increase our understanding about the regulatory mechanisms relevant to the two phenotypes.