TRUFA: A user-friendly web server for de novo RNA-seq analysis using cluster computing.

Application of next-generation sequencing (NGS) methods for transcriptome analysis (RNA-seq) has become increasingly accessible in recent years and are of great interest to many biological disciplines including, eg, evolutionary biology, ecology, biomedicine, and computational biology. Although virtually any research group can now obtain RNA-seq data, only a few have the bioinformatics knowledge and computation facilities required for transcriptome analysis. Here, we present TRUFA (TRanscriptome User-Friendly Analysis), an open informatics platform offering a web-based interface that generates the outputs commonly used in de novo RNA-seq analysis and comparative transcriptomics. TRUFA provides a comprehensive service that allows performing dynamically raw read cleaning, transcript assembly, annotation, and expression quantification. Due to the computationally intensive nature of such analyses, TRUFA is highly parallelized and benefits from accessing high-performance computing resources. The complete TRUFA pipeline was validated using four previously published transcriptomic data sets. TRUFA's results for the example datasets showed globally similar results when comparing with the original studies, and performed particularly better when analyzing the green tea dataset. The platform permits analyzing RNA-seq data in a fast, robust, and user-friendly manner. Accounts on TRUFA are provided freely upon request at https://trufa.ifca.es

Myogenesis modelled by human pluripotent stem cells uncovers Duchenne muscular dystrophy phenotypes prior to skeletal muscle commitment

Duchenne muscular dystrophy (DMD) causes severe disability of children and death of young men, with an incidence of approximately 1/5,000 male births. Symptoms appear in early childhood, with a diagnosis made around 4 years old, a time where the amount of muscle damage is already significant, preventing early therapeutic interventions that could be more efficient at halting disease progression. In the meantime, the precise moment at which disease phenotypes arise - even asymptomatically - is still unknown. Thus, there is a critical need to better define DMD onset as well as its first manifestations, which could help identify early disease biomarkers and novel therapeutic targets. In this study, we have used human induced pluripotent stem cells (hiPSCs) from DMD patients to model skeletal myogenesis, and compared their differentiation dynamics to healthy control cells by a comprehensive multi-omics analysis. Transcriptome and miRnome comparisons combined with protein analyses at 7 time points demonstrate that hiPSC differentiation 1) mimics described DMD phenotypes at the differentiation endpoint; and 2) homogeneously and robustly recapitulates key developmental steps - mesoderm, somite, skeletal muscle - which offers the possibility to explore dystrophin functions and find earlier disease biomarkers. Starting at the somite stage, mitochondrial gene dysregulations escalate during differentiation. We also describe fibrosis as an intrinsic feature of skeletal muscle cells that starts early during myogenesis. In sum, our data strongly argue for an early developmental manifestation of DMD whose onset is triggered before the entry into the skeletal muscle compartment, data leading to a necessary reconsideration of dystrophin functions during muscle development

Myogenesis modelled by human pluripotent stem cells uncovers Duchenne muscular dystrophy phenotypes prior to skeletal muscle commitment

Duchenne muscular dystrophy (DMD) causes severe disability of children and death of young men, with an incidence of approximately 1/5,000 male births. Symptoms appear in early childhood, with a diagnosis made around 4 years old, a time where the amount of muscle damage is already significant, preventing early therapeutic interventions that could be more efficient at halting disease progression. In the meantime, the precise moment at which disease phenotypes arise - even asymptomatically - is still unknown. Thus, there is a critical need to better define DMD onset as well as its first manifestations, which could help identify early disease biomarkers and novel therapeutic targets. In this study, we have used human induced pluripotent stem cells (hiPSCs) from DMD patients to model skeletal myogenesis, and compared their differentiation dynamics to healthy control cells by a comprehensive multi-omics analysis. Transcriptome and miRnome comparisons combined with protein analyses at 7 time points demonstrate that hiPSC differentiation 1) mimics described DMD phenotypes at the differentiation endpoint; and 2) homogeneously and robustly recapitulates key developmental steps - mesoderm, somite, skeletal muscle - which offers the possibility to explore dystrophin functions and find earlier disease biomarkers. Starting at the somite stage, mitochondrial gene dysregulations escalate during differentiation. We also describe fibrosis as an intrinsic feature of skeletal muscle cells that starts early during myogenesis. In sum, our data strongly argue for an early developmental manifestation of DMD whose onset is triggered before the entry into the skeletal muscle compartment, data leading to a necessary reconsideration of dystrophin functions during muscle development

Impact of Gephyrin alternative splicing on inhibitory synapses function

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Myogenesis modelled by human pluripotent stem cells: a multi‐omic study of Duchenne myopathy early onset

International audienceBackground Duchenne muscular dystrophy (DMD) causes severe disability of children and death of young men, with an incidence of approximately 1/5000 male births. Symptoms appear in early childhood, with a diagnosis made mostly around 4 years old, a time where the amount of muscle damage is already significant, preventing early therapeutic interventions that could be more efficient at halting disease progression. In the meantime, the precise moment at which disease phenotypes arise-even asymptomatically-is still unknown. Thus, there is a critical need to better define DMD onset as well as its first manifestations, which could help identify early disease biomarkers and novel therapeutic targets. Methods We have used both human tissue-derived myoblasts and human induced pluripotent stem cells (hiPSCs) from DMD patients to model skeletal myogenesis and compared their differentiation dynamics with that of healthy control cells by a comprehensive multi-omic analysis at seven time points. Results were strengthened with the analysis of isogenic CRISPR-edited human embryonic stem cells and through comparisons against published transcriptomic and proteomic datasets from human DMD muscles. The study was completed with DMD knockdown/rescue experiments in hiPSC-derived skeletal muscle progenitor cells and adenosine triphosphate measurement in hiPSC-derived myotubes. Results Transcriptome and miRnome comparisons combined with protein analyses demonstrated that hiPSC differentiation (i) leads to embryonic/foetal myotubes that mimic described DMD phenotypes at the differentiation endpoint and (ii) homogeneously and robustly recapitulates key developmental steps-mesoderm, somite, and skeletal muscle. Starting at the somite stage, DMD dysregulations concerned almost 10% of the transcriptome. These include mitochondrial genes whose dysregulations escalate during differentiation. We also describe fibrosis as an intrinsic feature of DMD skeletal muscle cells that begins early during myogenesis. All the omics data are available online for exploration through a graphical interface at https://muscle-dmd.omics.ovh/. Conclusions Our data argue for an early developmental manifestation of DMD whose onset is triggered before the entry into the skeletal muscle compartment, data leading to a necessary reconsideration of dystrophin roles during muscle development. This hiPSC model of skeletal muscle differentiation offers the possibility to explore these functions as well as find earlier DMD biomarkers and therapeutic targets

Multi-tissue transcriptomes of caecilian amphibians highlight incomplete knowledge of vertebrate gene families

RNA sequencing (RNA-seq) has become one of the most powerful tools to unravel the genomic basis of biological adaptation & diversity. Although challenging, RNA-seq is particularly promising for research on non-model, secretive species that cannot be observed in nature easily and therefore remain comparatively understudied. Among such animals, the caecilians (order Gymnophiona) likely constitute the least known group of vertebrates, despite being an old and remarkably distinct lineage of amphibians. Here, we characterize multi-tissue transcriptomes for five species of caecilians that represent a broad level of diversity across the order. We identified vertebrate homologous elements of caecilian functional genes of varying tissue specificity that reveal a great number of unclassified gene families, especially for the skin. We annotated several protein domains for those unknown candidate gene families to investigate their function. We also conducted supertree analyses of a phylogenomic dataset of 1,955 candidate orthologous genes among five caecilian species and other major lineages of vertebrates, with the inferred tree being in agreement with current views of vertebrate evolution and systematics. Our study provides insights into the evolution of vertebrate protein-coding genes, and a basis for future research on the molecular elements underlying the particular biology and adaptations of caecilian amphibians

sequana/sequana_pipetools: v0.15.0

<h2>What's Changed</h2> <ul> <li>replace requirements.txt by tools.txt by @cokelaer in https://github.com/sequana/sequana_pipetools/pull/75</li> <li>add getmetadata</li> <li>remove useless code related to former rules</li> </ul> <p><strong>Full Changelog</strong>: https://github.com/sequana/sequana_pipetools/compare/v0.14.1...v0.15.0</p&gt

sequana/versionix: v0.2.0

What's Changed some cleanup and add singularity/seqtk cases by @cokelaer in https://github.com/sequana/versionix/pull/1 add click to requirements by @khourhin in https://github.com/sequana/versionix/pull/2 Simplify the main function to only accept registered entries by @cokelaer in https://github.com/sequana/versionix/pull/3 add bowtie, cutadapt by @rania-o in https://github.com/sequana/versionix/pull/4 Update test and improve README by @cokelaer in https://github.com/sequana/versionix/pull/5 adding more standalone and refactoring by @khourhin in https://github.com/sequana/versionix/pull/6 move metadata into registry.py; fix tests + black by @cokelaer in https://github.com/sequana/versionix/pull/7 New Contributors @cokelaer made their first contribution in https://github.com/sequana/versionix/pull/1 @khourhin made their first contribution in https://github.com/sequana/versionix/pull/2 @rania-o made their first contribution in https://github.com/sequana/versionix/pull/4 Full Changelog: https://github.com/sequana/versionix/commits/v0.2.

sequana/versionix: v0.2.2

<h2>What's Changed</h2> <ul> <li>implement --registered and --stats options by @cokelaer in https://github.com/sequana/versionix/pull/10</li> <li>add tools required by Sequana pipelines by @cokelaer in https://github.com/sequana/versionix/pull/11</li> </ul> <p><strong>Full Changelog</strong>: https://github.com/sequana/versionix/compare/v0.2.1...v0.2.2</p&gt

Expression of endogenous retroviruses reflects increased usage of atypical enhancers in T cells

International audienceSeveral autoimmune diseases including multiple sclerosis (MS) cause increased transcription of endogenous retroviruses (HERVs) normally repressed by heterochromatin. In parallel, HERV-derived sequences were reported to drive gene expression. Here, we have examined a possible link between promoter and enhancer divergent transcription and the production of HERV transcripts. We find that HERV-derived sequences are in general counter-selected at regulatory regions, a counter-selection that is strongest in brain tissues while very moderate in stem cells. By exposing T cells to the pesticide dieldrin, we further found that a series of HERV-driven enhancers otherwise active only at stem cell stages can be reactivated by stress. This in part relies on peptidylarginine deiminase activity, possibly participating in the reawakening of silenced enhancers. Likewise, usage of HERV-driven enhancers was increased in myelin-reactive T cells from patients with MS, correlating with activation of nearby genes at several sites. Altogether, we propose that HERV-driven enhancers constitute a reservoir of auxiliary enhancers transiently induced by stress while chronically active in diseases like MS