Goulphar: rapid access and expertise for standard two-color microarray normalization methods

BACKGROUND: Raw data normalization is a critical step in microarray data analysis because it directly affects data interpretation. Most of the normalization methods currently used are included in the R/BioConductor packages but it is often difficult to identify the most appropriate method. Furthermore, the use of R commands for functions and graphics can introduce mistakes that are difficult to trace. We present here a script written in R that provides a flexible means of access to and monitoring of data normalization for two-color microarrays. This script combines the power of BioConductor and R analysis functions and reduces the amount of R programming required. RESULTS: Goulphar was developed in and runs using the R language and environment. It combines and extends functions found in BioConductor packages (limma and marray) to correct for dye biases and spatial artifacts. Goulphar provides a wide range of optional and customizable filters for excluding incorrect signals during the pre-processing step. It displays informative output plots, enabling the user to monitor the normalization process, and helps adapt the normalization method appropriately to the data. All these analyses and graphical outputs are presented in a single PDF report. CONCLUSION: Goulphar provides simple, rapid access to the power of the R/BioConductor statistical analysis packages, with precise control and visualization of the results obtained. Complete documentation, examples and online forms for setting script parameters are available from

Highly dynamic and sex-specific expression of microRNAs during early ES cell differentiation.

International audienceEmbryonic stem (ES) cells are pluripotent cells derived from the inner cell mass of the mammalian blastocyst. Cellular differentiation entails loss of pluripotency and gain of lineage-specific characteristics. However, the molecular controls that govern the differentiation process remain poorly understood. We have characterized small RNA expression profiles in differentiating ES cells as a model for early mammalian development. High-throughput 454 pyro-sequencing was performed on 19-30 nt RNAs isolated from undifferentiated male and female ES cells, as well as day 2 and 5 differentiating derivatives. A discrete subset of microRNAs (miRNAs) largely dominated the small RNA repertoire, and the dynamics of their accumulation could be readily used to discriminate pluripotency from early differentiation events. Unsupervised partitioning around meloids (PAM) analysis revealed that differentiating ES cell miRNAs can be divided into three expression clusters with highly contrasted accumulation patterns. PAM analysis afforded an unprecedented level of definition in the temporal fluctuations of individual members of several miRNA genomic clusters. Notably, this unravelled highly complex post-transcriptional regulations of the key pluripotency miR-290 locus, and helped identify miR-293 as a clear outlier within this cluster. Accordingly, the miR-293 seed sequence and its predicted cellular targets differed drastically from those of the other abundant cluster members, suggesting that previous conclusions drawn from whole miR-290 over-expression need to be reconsidered. Our analysis in ES cells also uncovered a striking male-specific enrichment of the miR-302 family, which share the same seed sequence with most miR-290 family members. Accordingly, a miR-302 representative was strongly enriched in embryonic germ cells derived from primordial germ cells of male but not female mouse embryos. Identifying the chromatin remodelling and E2F-dependent transcription repressors Ari4a and Arid4b as additional targets of miR-302 and miR-290 supports and possibly expands a model integrating possible overlapping functions of the two miRNA families in mouse cell totipotency during early development. This study demonstrates that small RNA sampling throughout early ES cell differentiation enables the definition of statistically significant expression patterns for most cellular miRNAs. We have further shown that the transience of some of these miRNA patterns provides highly discriminative markers of particular ES cell states during their differentiation, an approach that might be broadly applicable to the study of early mammalian development

AGATHE: A tool for personalized rehabilitation of cognitive functions

Stroke, traumatic brain injury, multiple sclerosis, Parkinson's disease, Alzheimer's... Every year in France, tens of thousands of people fall victim to one of those neurological pathologies. Acquired brain injury leads to cognitive impairment and heavy loss of autonomy. Rehabilitation interventions are needed to enable people to recover capacity and return to Activities of Daily Living (ADL), such as grocery shopping. Unfortunately, the resources made available in cognitive rehabilitation are insufficient for the growing needs of victims of brain damage. The assets of virtual reality to address this big problem of public health are today scientifically recognized [Rizzo and Kim 2005; Klinger, et al. 2010]. In this context, we designed the AGATHE tool (Adaptable, configurable and upgradable tool for the generation of personalized therapeutic applications in cognitive rehabilitation) (AGATHE project, ANR-09-TECS-002).French National Research Agency (ANR) Laval Agglomération et Conseil Général de la Mayenn

ncPRO-seq: a tool for annotation and profiling of ncRNAs in sRNA-seq data

Summary: Non-coding RNA (ncRNA) PROfiling in small RNA (sRNA)-seq (ncPRO-seq) is a stand-alone, comprehensive and flexible ncRNA analysis pipeline. It can interrogate and perform detailed profiling analysis on sRNAs derived from annotated non-coding regions in miRBase, Rfam and RepeatMasker, as well as specific regions defined by users. The ncPRO-seq pipeline performs both gene-based and family-based analyses of sRNAs. It also has a module to identify regions significantly enriched with short reads, which cannot be classified under known ncRNA families, thus enabling the discovery of previously unknown ncRNA- or small interfering RNA (siRNA)-producing regions. The ncPRO-seq pipeline supports input read sequences in fastq, fasta and color space format, as well as alignment results in BAM format, meaning that sRNA raw data from the three current major platforms (Roche-454, Illumina-Solexa and Life technologies-SOLiD) can be analyzed with this pipeline. The ncPRO-seq pipeline can be used to analyze read and alignment data, based on any sequenced genome, including mammals and plants. Availability: Source code, annotation files, manual and online version are available at http://ncpro.curie.fr/. Contact: [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

Contribution of epigenetic landscapes and transcription factors to X-chromosome reactivation in the inner cell mass.

X-chromosome inactivation is established during early development. In mice, transcriptional repression of the paternal X-chromosome (Xp) and enrichment in epigenetic marks such as H3K27me3 is achieved by the early blastocyst stage. X-chromosome inactivation is then reversed in the inner cell mass. The mechanisms underlying Xp reactivation remain enigmatic. Using in vivo single-cell approaches (allele-specific RNAseq, nascent RNA-fluorescent in situ hybridization and immunofluorescence), we show here that different genes are reactivated at different stages, with more slowly reactivated genes tending to be enriched in H3meK27. We further show that in UTX H3K27 histone demethylase mutant embryos, these genes are even more slowly reactivated, suggesting that these genes carry an epigenetic memory that may be actively lost. On the other hand, expression of rapidly reactivated genes may be driven by transcription factors. Thus, some X-linked genes have minimal epigenetic memory in the inner cell mass, whereas others may require active erasure of chromatin marks

The Gut Microbiota Regulates Intestinal CD4 T Cells Expressing RORγt and Controls Metabolic Disease

SummaryA high-fat diet (HFD) induces metabolic disease and low-grade metabolic inflammation in response to changes in the intestinal microbiota through as-yet-unknown mechanisms. Here, we show that a HFD-derived ileum microbiota is responsible for a decrease in Th17 cells of the lamina propria in axenic colonized mice. The HFD also changed the expression profiles of intestinal antigen-presenting cells and their ability to generate Th17 cells in vitro. Consistent with these data, the metabolic phenotype was mimicked in RORγt-deficient mice, which lack IL17 and IL22 function, and in the adoptive transfer experiment of T cells from RORγt-deficient mice into Rag1-deficient mice. We conclude that the microbiota of the ileum regulates Th17 cell homeostasis in the small intestine and determines the outcome of metabolic disease

AGATHE: A tool for personalized rehabilitation of cognitive functions

Stroke, traumatic brain injury, multiple sclerosis, Parkinson's disease, Alzheimer's... Every year in France, tens of thousands of people fall victim to one of those neurological pathologies. Acquired brain injury leads to cognitive impairment and heavy loss of autonomy. Rehabilitation interventions are needed to enable people to recover capacity and return to Activities of Daily Living (ADL), such as grocery shopping. Unfortunately, the resources made available in cognitive rehabilitation are insufficient for the growing needs of victims of brain damage. The assets of virtual reality to address this big problem of public health are today scientifically recognized [Rizzo and Kim 2005; Klinger, et al. 2010]. In this context, we designed the AGATHE tool (Adaptable, configurable and upgradable tool for the generation of personalized therapeutic applications in cognitive rehabilitation) (AGATHE project, ANR-09-TECS-002).French National Research Agency (ANR) Laval Agglomération et Conseil Général de la Mayenn

The bipartite TAD organization of the X-inactivation center ensures opposing developmental regulation of Tsix and Xist

The mouse X-inactivation center (Xic) locus represents a powerful model for understanding the links between genome architecture and gene regulation, with the non-coding genes Xist and Tsix showing opposite developmental expression patterns while being organized as an overlapping sense/antisense unit. The Xic is organized into two topologically associating domains (TADs) but the role of this architecture in orchestrating cis-regulatory information remains elusive. To explore this, we generated genomic inversions that swap the Xist/Tsix transcriptional unit and place their promoters in each other’s TAD. We found that this led to a switch in their expression dynamics: Xist became precociously and ectopically upregulated, both in male and female pluripotent cells, while Tsix expression aberrantly persisted during differentiation. The topological partitioning of the Xic is thus critical to ensure proper developmental timing of X inactivation. Our study illustrates how the genomic architecture of cis-regulatory landscapes can affect the regulation of mammalian developmental processes

EMA - A R package for Easy Microarray data analysis

<p>Abstract</p> <p>Background</p> <p>The increasing number of methodologies and tools currently available to analyse gene expression microarray data can be confusing for non specialist users.</p> <p>Findings</p> <p>Based on the experience of biostatisticians of Institut Curie, we propose both a clear analysis strategy and a selection of tools to investigate microarray gene expression data. The most usual and relevant existing R functions were discussed, validated and gathered in an easy-to-use R package (EMA) devoted to gene expression microarray analysis. These functions were improved for ease of use, enhanced visualisation and better interpretation of results.</p> <p>Conclusions</p> <p>Strategy and tools proposed in the EMA R package could provide a useful starting point for many microarrays users. EMA is part of Comprehensive R Archive Network and is freely available at <url>http://bioinfo.curie.fr/projects/ema/</url>.</p

Bioinformatics for precision medicine in oncology: principles and application to the SHIVA clinical trial

Precision medicine (PM) requires the delivery of individually adapted medical care based on the genetic characteristics of each patient and his/her tumor. The last decade witnessed the development of high-throughput technologies such as microarrays and next-generation sequencing which paved the way to PM in the field of oncology. While the cost of these technologies decreases, we are facing an exponential increase in the amount of data produced. Our ability to use this information in daily practice relies strongly on the availability of an efficient bioinformatics system that assists in the translation of knowledge from the bench towards molecular targeting and diagnosis. Clinical trials and routine diagnoses constitute different approaches, both requiring a strong bioinformatics environment capable of (i) warranting the integration and the traceability of data, (ii) ensuring the correct processing and analyses of genomic data, and (iii) applying well-defined and reproducible procedures for workflow management and decision-making. To address the issues, a seamless information system was developed at Institut Curie which facilitates the data integration and tracks in real-time the processing of individual samples. Moreover, computational pipelines were developed to identify reliably genomic alterations and mutations from the molecular profiles of each patient. After a rigorous quality control, a meaningful report is delivered to the clinicians and biologists for the therapeutic decision. The complete bioinformatics environment and the key points of its implementation are presented in the context of the SHIVA clinical trial, a multicentric randomized phase II trial comparing targeted therapy based on tumor molecular profiling versus conventional therapy in patients with refractory cancer. The numerous challenges faced in practice during the setting up and the conduct of this trial are discussed as an illustration of PM application