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Lelandais, G.

Publications and source records attributed to Lelandais, G..

7 recordsLinked to original sources

Hi-C data from the filamentous fungus Podospora anserina and associated 3D models to visualize the spatial organization of its chromosomes

ObjectivesModel species are essential for fundamental research in biology. While a complete genomic sequence is a prerequisite for genetic studies, it is not enough on its own. Understanding the three-dimensional organization of the genome is also important, allowing researchers to gain a more realistic understanding of the mechanisms governing genome function. In the fungal model Podospora anserina, although the genomic sequence has been established for a long time, the three-dimensional organization remained unknown. Here we obtained the first Hi-C datasets and present associated 3D models, providing the research community with a valuable resource for better multi-omics data integration. Data descriptionHi-C experiments were performed in duplicate, using nuclei purified from wild-type fungal mycelium. Four FASTQ files were obtained (two per replicate) and used as inputs for the 3DGB workflow with four different output resolutions, to observe the genome organization of P. anserina at different levels of detail (50 kb, 20 kb, 10 kb, and 5 kb). In a context where researchers already have, for this species, a large amount of traditional omics data (ChIP-seq, RNA-seq, etc.), these 3D models are helpful for complementing the linear representation of the genome, which is traditionally used in bioinformatic analyses.

genomics↗

Sexual reproduction is controlled by successive transcriptomic waves in Podospora anserina

Despite the inherent challenge of finding suitable mating partners, most eukaryotes use sexual reproduction to produce offspring endowed with increase genetic diversity and fitness. The persistence of this mode of reproduction is a key question in evolutionary biology. Fungi offer valuable insights into this question, due to their diversity and short lifecycle. This study focuses on Podospora anserina, a pseudohomothallic ascomycete fungus that bypasses self-sterility by maintaining two compatible nuclei in one mycelium. We performed genome-wide gene expression profiling during ten stages of P. anserina sexual reproduction and identified five major expression patterns. Our expert annotation approaches identified differentially expressed genes related to secondary metabolite production, fungal vegetative incompatibility, programmed cell death, and epigenetic regulation. In addition, master transcriptional regulators and their target networks were uncovered. This study provides a comprehensive database for future functional genomics experiments and novel pathway characterization during sexual reproduction.

genomics↗

Inter-generational nuclear crosstalk links the control of gene expression to programmed genome rearrangements during the Paramecium sexual cycle

Multinucleate cells are found in many eukaryotes, but how multiple nuclei coordinate their functions is still poorly understood. In the cytoplasm of the ciliate Paramecium tetraurelia, two micronuclei (MIC) serving sexual reproduction coexist with a somatic macronucleus (MAC) dedicated to gene expression. During sexual processes, the MAC is progressively destroyed while still ensuring transcription and new MACs develop from copies of the zygotic MIC. Several gene clusters are successively induced and switched off before vegetative growth resumes. Concomitantly, programmed genome rearrangements (PGR) remove transposons and their relics from the new MACs. Development of the new MACs is controlled by the old MAC, since the latter expresses genes involved in PGR, including the PGM gene encoding the essential PiggyMac endonuclease that cleaves the ends of eliminated sequences. Using RNA deep sequencing and transcriptome analysis, we show that impairing PGR up-deregulates key PGR genes, together with [~]600 other genes possibly also involved in PGR. Among these genes, 42% are no longer induced when no new MACs are formed, including 180 genes that are co-expressed with PGM under all tested conditions. We propose that bi-directional crosstalk between the two coexisting generations of MACs links gene expression to the progression of MAC development.

genomics↗

Visual integration of omics data to improve 3D models of fungal chromosomes

The functions of eukaryotic chromosomes and their spatial architecture in the nucleus are reciprocally dependent. Hi-C experiments are routinely used to study chromosome 3D organization by probing chromatin interactions. Standard representation of the data has relied on contact maps that show the frequency of interactions between parts of the genome. In parallel, it has become easier to build 3D models of the entire genome based on the same Hi-C data, and thus benefit from the methodology and visualization tools developed for structural biology. 3D modeling of entire genomes leverages the understanding of their spatial organization. However, this opportunity for original and insightful modeling is under exploited. In this paper, we show how seeing the spatial organization of chromosomes can bring new perspectives to Hi-C data analysis. We assembled state-of-the-art tools into a workflow that goes from Hi-C raw data to fully annotated 3D models and we re-analysed public Hi-C datasets available for three fungal species. Besides the well-described properties of the spatial organization of their chromosomes (Rabl conformation, hypercoiling and chromosome territories), our 3D models highlighted i) in Saccharomyces cerevisiae, the backbones of the cohesin anchor regions, which were aligned all along the chromosomes, ii) in Schizosaccharomyces pombe, the oscillations of the coiling of chromosome arms throughout the cell cycle and iii) in Neurospora crassa, the massive relocalization of histone marks in mutants of heterochromatin regulators. 3D modeling of the chromosomes brings new opportunities for visual integration. This holistic perspective supports intuition and lays the foundation for building new concepts.

genomics↗

Re-exploiting multiple RNA-seq data to identify transcript variations in Podospora anserina

BackgroundPublicly available RNA-seq datasets are often underused although being helpful to improve functional annotation of eukaryotic genomes. This is especially true for filamentous fungi genomes which structure differs from most well annotated yeast genomes. Podospora anserina is a filamentous fungal model, which genome has been sequenced and annotated in 2008. Still, the current annotation lacks information about cis-regulatory elements, including promoters, transcription starting sites and terminators, which are instrumental to integrate epigenomic features into global gene regulation strategies. ResultsHere we took advantage of 37 RNA-seq experiments that were obtained in contrasted developmental and physiological conditions, to complete the functional annotation of P. anserina genome. Out of the 10,800 previously annotated genes, 5UTR and 3UTR were defined for 7,554, among which, 3,328 showed differential transcriptional signal starts and/or transcriptional end sites. In addition, alternative splicing events were detected for 2350 genes, mostly due alternative 3splice site and 1,958 novel transcriptionally active regions (nTARs) in unannotated regions were identified. ConclusionsOur study provides a comprehensive genome-wide functional annotation release of P. anserina genome, including chromatin features, cis-acting elements such as UTRs, alternative splicing events and transcription of non-coding regions. These new findings will likely improve our understanding of gene regulation strategies in compact genomes, such as those of filamentous fungi. Characterization of alternative transcripts and nTARs paves the way to the discovery of putative new genes, alternative peptides or regulatory non-coding RNAs.

genomics↗

Characterization of the radiation desiccation response regulon of the radioresistant bacterium Deinococcus radiodurans by integrative genomic analyses.

Numerous genes are overexpressed in the radioresistant bacterium Deinococcus radiodurans after exposure to radiation or prolonged desiccation. The DdrO and IrrE proteins play a major role in regulating the expression of approximately predicted twenty of these genes. The transcriptional repressor DdrO blocks the expression of these genes under normal growth conditions. After exposure to genotoxic agents, the IrrE metalloprotease cleaves DdrO and relieves gene repression. Bioinformatic analyzes showed that this mechanism seems to be conserved in several species of Deinococcus, but many questions remain as such the number of genes regulated by DdrO. Here, by RNA-seq and CHiP-seq assays performed at a genome-wide scale coupled with bioinformatic analyses, we show that, the DdrO regulon in D. radiodurans includes many other genes than those previously described. These results thus pave the way to better understand the radioresistance mechanisms encoded by this bacterium. Author SummaryThe main response pathway to genotoxic conditions in the radioresistant bacterium Deinococcus radiodurans is regulated by the constitutively expressed metalloprotease IrrE that cleaves the transcriptional repressor DdrO, leading to the expression of the genes repressed by DdrO. One of the major goals to better understand how pathways involved in radioresistance are coordinated into this fascinating bacterium is to highlight genes regulated by DdrO. In this study, we mapped in vivo the DdrO regulon in D. radiodurans by using two genome-scale approaches, ChIP-seq and RNA-seq analyses, coupled with bioinformatic analyses. As homologs of these two proteins are also found in many other bacteria, these results also pave the way to compare the stress-induced responses mediated by this couple of proteins in diverse bacteria.

genomics↗

Pixel: a digital lab assistant to integrate biological data in multi-omics projects

BackgroundIn biology, high-throughput experimental technologies, also referred as "omics" technologies, are increasingly used in research laboratories. Several thousands of gene expression measurements can be obtained in a single experiment. Researchers are routinely facing the challenge to annotate, store, explore and mine all the biological information they have at their disposal. We present here the Pixel web application (Pixel Web App), an original content management platform to help people involved in a multi-omics biological project. MethodsThe Pixel Web App is built with open source technologies and hosted on the collaborative development platform GitHub (https://github.com/Candihub/pixel). It is written in Python using the Django framework and stores all the data in a PostgreSQL database. It is developed in the open and licensed under the BSD 3-clause license. The Pixel Web App is also heavily tested with both unit and functional tests, a strong code coverage and continuous integration provided by CircleCI. To ease the development and the deployment of the Pixel Web App, Docker and Docker Compose are used to bundle the application as well as its dependencies. ResultsThe Pixel Web App offers researchers an intuitive way to annotate, store, explore and mine their multi-omics results. It can be installed on a personal computer or on a server to fit the needs of many users. In addition, anyone can enhance the application to better suit their needs, either by contributing directly on GitHub (encouraged) or by extending Pixel on their own. The Pixel Web App does not provide any computational programs to analyze the data. Still, it helps to rapidly explore and mine existing results and holds a strategic position in the management of research data.

bioinformatics↗