Specific DMPK-promoter targeting by CRISPRi reverses myotonic dystrophy type 1-associated defects in patient muscle cells.

Myotonic dystrophy type 1 (DM1) is a neuromuscular disease that originates from an expansion of CTG microsatellites in the 3' untranslated region of the DMPK gene, thus leading to the expression of transcripts containing expanded CUG repeats (CUGexp). The pathophysiology is explained by a toxic RNA gain of function where CUGexp RNAs form nuclear aggregates that sequester and alter the function of MBNL splicing factors, triggering splicing misregulation linked to the DM1 symptoms. There is currently no cure for DM1, and most therapeutic strategies aim at eliminating CUGexp-DMPK transcripts. Here, we investigate a DMPK-promoter silencing strategy using CRISPR interference as a new alternative approach. Different sgRNAs targeting the DMPK promoter are evaluated in DM1 patient muscle cells. The most effective guides allowed us to reduce the level of DMPK transcripts and CUGexp-RNA aggregates up to 80%. The CUGexp-DMPK repression corrects the overall transcriptome, including spliceopathy, and reverses a physiological parameter in DM1 muscle cells. Its action is specific and restricted to the DMPK gene, as confirmed by genome-wide expression analysis. Altogether, our findings highlight DMPK-promoter silencing by CRISPRi as a promising therapeutic approach for DM1.

Muscle fibro-adipogenic progenitors from a single-cell perspective: Focus on their "virtual" secretome.

Skeletal muscle is a highly plastic tissue composed of a number of heterogeneous cell populations that, by interacting and communicating with each other, participate to the muscle homeostasis, and orchestrate regeneration and repair in healthy and diseased conditions. Although muscle regeneration relies on the activity of muscle stem cells (MuSCs), many other cellular players such as inflammatory, vascular and tissue-resident mesenchymal cells participate and communicate with MuSCs to sustain the regenerative process. Among them, Fibro-Adipogenic Progenitors (FAPs), a muscle interstitial stromal population, are crucial actors during muscle homeostasis and regeneration, interacting with MuSCs and other cellular players and dynamically producing and remodelling the extra-cellular matrix. Recent emerging single-cell omics technologies have resulted in the dissection of the heterogeneity of each cell populations within skeletal muscle. In this perspective we have reviewed the recent single-cell omics studies with a specific focus on FAPs in mouse and human muscle. More precisely, using the OutCyte prediction tool, we analysed the "virtual" secretome of FAPs, in resting and regenerating conditions, to highlight the potential of RNAseq data for the study of cellular communication.

Reversal of RNA toxicity in myotonic dystrophy via a decoy RNA-binding protein with high affinity for expanded CUG repeats.

Myotonic dystrophy type 1 (DM1) is an RNA-dominant disease whose pathogenesis stems from the functional loss of muscleblind-like RNA-binding proteins (RBPs), which causes the formation of alternative-splicing defects. The loss of functional muscleblind-like protein 1 (MBNL1) results from its nuclear sequestration by mutant transcripts containing pathogenic expanded CUG repeats (CUGexp). Here we show that an RBP engineered to act as a decoy for CUGexp reverses the toxicity of the mutant transcripts. In vitro, the binding of the RBP decoy to CUGexp in immortalized muscle cells derived from a patient with DM1 released sequestered endogenous MBNL1 from nuclear RNA foci, restored MBNL1 activity, and corrected the transcriptomic signature of DM1. In mice with DM1, the local or systemic delivery of the RBP decoy via an adeno-associated virus into the animals' skeletal muscle led to the long-lasting correction of the splicing defects and to ameliorated disease pathology. Our findings support the development of decoy RBPs with high binding affinities for expanded RNA repeats as a therapeutic strategy for myotonic dystrophies.

GPS2 Deficiency Triggers Maladaptive White Adipose Tissue Expansion in Obesity via HIF1A Activation.

Hypertrophic white adipose tissue (WAT) represents a maladaptive mechanism linked to the risk for developing type 2 diabetes in humans. However, the molecular events that predispose WAT to hypertrophy are poorly defined. Here, we demonstrate that adipocyte hypertrophy is triggered by loss of the corepressor GPS2 during obesity. Adipocyte-specific GPS2 deficiency in mice (GPS2 AKO) causes adipocyte hypertrophy, inflammation, and mitochondrial dysfunction during surplus energy. This phenotype is driven by HIF1A activation that orchestrates inadequate WAT remodeling and disrupts mitochondrial activity, which can be reversed by pharmacological or genetic HIF1A inhibition. Correlation analysis of gene expression in human adipose tissue reveals a negative relationship between GPS2 and HIF1A, adipocyte hypertrophy, and insulin resistance. We propose therefore that the obesity-associated loss of GPS2 in adipocytes predisposes for a maladaptive WAT expansion and a pro-diabetic status in mice and humans.

UROPA: a tool for Universal RObust Peak Annotation.

The annotation of genomic ranges of interest represents a recurring task for bioinformatics analyses. These ranges can originate from various sources, including peaks called for transcription factor binding sites (TFBS) or histone modification ChIP-seq experiments, chromatin structure and accessibility experiments (such as ATAC-seq), but also from other types of predictions that result in genomic ranges. While peak annotation primarily driven by ChiP-seq was extensively explored, many approaches remain simplistic ("most closely located TSS"), rely on fixed pre-built references, or require complex scripting tasks on behalf of the user. An adaptable, fast, and universal tool, capable to annotate genomic ranges in the respective biological context is critically missing. UROPA (Universal RObust Peak Annotator) is a command line based tool, intended for universal genomic range annotation. Based on a configuration file, different target features can be prioritized with multiple integrated queries. These can be sensitive for feature type, distance, strand specificity, feature attributes (e.g. protein_coding) or anchor position relative to the feature. UROPA can incorporate reference annotation files (GTF) from different sources (Gencode, Ensembl, RefSeq), as well as custom reference annotation files. Statistics and plots transparently summarize the annotation process. UROPA is implemented in Python and R.