High-fidelity promoter profiling reveals widespread alternative promoter usage and transposon-driven developmental gene expression

Many Eukaryotic genes possess multiple alternative promoters with distinct expression specificities. Therefore, comprehensively annotating promoters and deciphering their individual regulatory dynamics is critical for gene expression profiling applications, and for our understanding of regulatory complexity. We introduce RAMPAGE, a novel promoter activity profiling approach that combines extremely specific 5'-complete cDNA sequencing with an integrated data analysis workflow to address the limitations of current techniques. RAMPAGE features a streamlined protocol for fast and easy generation of highly multiplexed sequencing libraries, offers very high transcription start site specificity, generates accurate and reproducible promoter expression measurements, and yields extensive transcript connectivity information through paired-end cDNA sequencing. We used RAMPAGE in a genome-wide study of promoter activity throughout 36 stages of the life cycle of Drosophila melanogaster, and describe here a comprehensive dataset that represents the first available developmental timecourse of promoter usage. We found that over 40% of developmentally expressed genes have at least 2 promoters, and that alternative promoters generally implement distinct regulatory programs. Transposable elements, long proposed to play a central role in the evolution of their host genomes through their ability to regulate gene expression, contribute at least 1,300 promoters shaping the developmental transcriptome of D. melanogaster. Hundreds of these promoters drive the expression of annotated genes, and transposons often impart their own expression specificity upon the genes they regulate. These observations provide support for the theory that transposons may drive regulatory innovation through the distribution of stereotyped cis-regulatory modules throughout their host genomes

An Approach Based on κ-Kӧhler Theory for Calculating CCN Activation Curves that Considers the Dry Particle Size Distribution and Morphology

International audienc

Conserved noncoding transcription and core promoter regulatory code in early Drosophila development

Multicellular development is driven by regulatory programs that orchestrate the transcription of protein-coding and noncoding genes. To decipher this genomic regulatory code, and to investigate the developmental relevance of noncoding transcription, we compared genome-wide promoter activity throughout embryogenesis in 5 Drosophila species. Core promoters, generally not thought to play a significant regulatory role, in fact impart restrictions on the developmental timing of gene expression on a global scale. We propose a hierarchical regulatory model in which core promoters define broad windows of opportunity for expression, by defining a range of transcription factors from which they can receive regulatory inputs. This two-tiered mechanism globally orchestrates developmental gene expression, including extremely widespread noncoding transcription. The sequence and expression specificity of noncoding RNA promoters are evolutionarily conserved, implying biological relevance. Overall, this work introduces a hierarchical model for developmental gene regulation, and reveals a major role for noncoding transcription in animal development

Random perfect lattices and the sphere packing problem

Motivated by the search for best lattice sphere packings in Euclidean spaces of large dimensions we study randomly generated perfect lattices in moderately large dimensions (up to d=19 included). Perfect lattices are relevant in the solution of the problem of lattice sphere packing, because the best lattice packing is a perfect lattice and because they can be generated easily by an algorithm. Their number however grows super-exponentially with the dimension so to get an idea of their properties we propose to study a randomized version of the algorithm and to define a random ensemble with an effective temperature in a way reminiscent of a Monte-Carlo simulation. We therefore study the distribution of packing fractions and kissing numbers of these ensembles and show how as the temperature is decreased the best know packers are easily recovered. We find that, even at infinite temperature, the typical perfect lattices are considerably denser than known families (like A_d and D_d) and we propose two hypotheses between which we cannot distinguish in this paper: one in which they improve Minkowsky's bound phi\sim 2^{-(0.84+-0.06) d}, and a competitor, in which their packing fraction decreases super-exponentially, namely phi\sim d^{-a d} but with a very small coefficient a=0.06+-0.04. We also find properties of the random walk which are suggestive of a glassy system already for moderately small dimensions. We also analyze local structure of network of perfect lattices conjecturing that this is a scale-free network in all dimensions with constant scaling exponent 2.6+-0.1.Comment: 19 pages, 22 figure

Linearizing torsion classes in the Picard group of algebraic curves over finite fields

We address the problem of computing in the group of $\ell^k$-torsion rational points of the jacobian variety of algebraic curves over finite fields, with a view toward computing modular representations.Comment: To appear in Journal of Algebr

ASaiM: A Galaxy-based framework to analyze microbiota data

Background: New generations of sequencing platforms coupled to numerous bioinformatics tools have led to rapid technological progress in metagenomics and metatranscriptomics to investigate complex microorganism communities. Nevertheless, a combination of different bioinformatic tools remains necessary to draw conclusions out of microbiota studies. Modular and user-friendly tools would greatly improve such studies. Findings: We therefore developed ASaiM, an Open-Source Galaxy-based framework dedicated to microbiota data analyses. ASaiM provides an extensive collection of tools to assemble, extract, explore, and visualize microbiota information from raw metataxonomic, metagenomic, or metatranscriptomic sequences. To guide the analyses, several customizable workflows are included and are supported by tutorials and Galaxy interactive tours, which guide users through the analyses step by step. ASaiM is implemented as a Galaxy Docker flavour. It is scalable to thousands of datasets but also can be used on a normal PC. The associated source code is available under Apache 2 license at https://github.com/ASaiM/framework and documentation can be found online (http://asaim.readthedocs.io). Conclusions: Based on the Galaxy framework, ASaiM offers a sophisticated environment with a variety of tools, workflows, documentation, and training to scientists working on complex microorganism communities. It makes analysis and exploration analyses of microbiota data easy, quick, transparent, reproducible, and shareable

The BMV experiment : a novel apparatus to study the propagation of light in a transverse magnetic field

In this paper, we describe in detail the BMV (Bir\'efringence Magn\'etique du Vide) experiment, a novel apparatus to study the propagation of light in a transverse magnetic field. It is based on a very high finesse Fabry-Perot cavity and on pulsed magnets specially designed for this purpose. We justify our technical choices and we present the current status and perspectives.Comment: To be published in the European Physical Journal

The RNA workbench: best practices for RNA and high-throughput sequencing bioinformatics in Galaxy

RNA-based regulation has become a major research topic in molecular biology. The analysis of epigenetic and expression data is therefore incomplete if RNA-based regulation is not taken into account. Thus, it is increasingly important but not yet standard to combine RNA-centric data and analysis tools with other types of experimental data such as RNA-seq or ChIP-seq. Here, we present the RNA workbench, a comprehensive set of analysis tools and consolidated workflows that enable the researcher to combine these two worlds. Based on the Galaxy framework the workbench guarantees simple access, easy extension, flexible adaption to personal and security needs, and sophisticated analyses that are independent of command-line knowledge. Currently, it includes more than 50 bioinformatics tools that are dedicated to different research areas of RNA biology including RNA structure analysis, RNA alignment, RNA annotation, RNA-protein interaction, ribosome profiling, RNA-seq analysis and RNA target prediction. The workbench is developed and maintained by experts in RNA bioinformatics and the Galaxy framework. Together with the growing community evolving around this workbench, we are committed to keep the workbench up-to-date for future standards and needs, providing researchers with a reliable and robust framework for RNA data analysis. Availability: The RNA workbench is available at https://github.com/bgruening/galaxy-rna-workbench