57 research outputs found
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
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
The Arabidopsis condensin CAP‐D subunits arrange interphase chromatin
Condensins are best known for their role in shaping chromosomes. Other functions such as organizing interphase chromatin and transcriptional control have been reported in yeasts and animals, but little is known about their function in plants. To elucidate the specific composition of condensin complexes and the expression of CAP-D2 (condensin I) and CAP-D3 (condensin II), we performed biochemical analyses in Arabidopsis. The role of CAP-D3 in interphase chromatin organization and function was evaluated using cytogenetic and transcriptome analysis in cap-d3 T-DNA insertion mutants. CAP-D2 and CAP-D3 are highly expressed in mitotically active tissues. In silico and pull-down experiments indicate that both CAP-D proteins interact with the other condensin I and II subunits. In cap-d3 mutants, an association of heterochromatic sequences occurs, but the nuclear size and the general histone and DNA methylation patterns remain unchanged. Also, CAP-D3 influences the expression of genes affecting the response to water, chemicals, and stress. The expression and composition of the condensin complexes in Arabidopsis are similar to those in other higher eukaryotes. We propose a model for the CAP-D3 function during interphase in which CAP-D3 localizes in euchromatin loops to stiffen them and consequently separates centromeric regions and 45S rDNA repeats
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>
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>
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