DUX4 regulates the expression of genic and nongenic elements and modulates chromatin accessibility during zygotic genome activation in cleavage stage embryos. Its misexpression in skeletal muscle causes facioscapulohumeral dystrophy (FSHD). By leveraging full-length RNA isoform sequencing with short-read RNA sequencing of DUX4-inducible myoblasts, we elucidate an isoform-resolved transcriptome featuring numerous unannotated isoforms from known loci and novel intergenic loci. While DUX4 activates similar programs in early embryos and FSHD muscle, the isoform usage of known DUX4 targets is notably distinct between the two contexts. DUX4 also activates hundreds of previously unannotated intergenic loci dominated by repetitive elements. The transcriptional and epigenetic profiles of these loci in myogenic and embryonic contexts indicate that the usage of DUX4-binding sites at these intergenic loci is influenced by the cellular environment. These findings demonstrate that DUX4 induces context-specific transcriptomic programs, enriching our understanding of DUX4-induced muscle pathology.

The sporadic nature of DUX4 expression in FSHD muscle challenges comparative transcriptome analyses between FSHD and control samples. A variety of DUX4 and FSHD-associated transcriptional changes have been identified, but bulk RNA-seq strategies prohibit comprehensive analysis of their spatiotemporal relation, interdependence and role in the disease process. In this study, we used single-nucleus RNA-sequencing of nuclei isolated from patient- and control-derived multinucleated primary myotubes to investigate the cellular heterogeneity in FSHD. Taking advantage of the increased resolution in snRNA-sequencing of fully differentiated myotubes, two distinct populations of DUX4-affected nuclei could be defined by their transcriptional profiles. Our data provides insights into the differences between these two populations and suggests heterogeneity in two well-known FSHD-associated transcriptional aberrations: increased oxidative stress and inhibition of myogenic differentiation. Additionally, we provide evidence that DUX4-affected nuclei share transcriptome features with early embryonic cells beyond the well-described cleavage stage, progressing into the 8-cell and blastocyst stages. Altogether, our data suggests that the FSHD transcriptional profile is defined by a mixture of individual and sometimes mutually exclusive DUX4-induced responses and cellular state-dependent downstream effects.

Facioscapulohumeral muscular dystrophy (FSHD) is characterized by sporadic de-repression of the transcription factor DUX4 in skeletal muscle. DUX4 activates a cascade of muscle disrupting events, eventually leading to muscle atrophy and apoptosis. Yet, how sporadic DUX4 expression leads to the generalized muscle wasting remains unclear. Transcriptome analyses have systematically been challenged by the majority of nuclei being DUX4neg, weakening the DUX4 transcriptome signature. Moreover, DUX4 has been shown to be expressed in a highly dynamic burst-like manner, likely resulting in the detection of the downstream cascade of events long after DUX4 expression itself has faded. Identifying the FSHD transcriptome in individual cells and unraveling the cascade of events leading to FSHD development may therefore provide important insights in the disease process. We employed single-cell RNA sequencing, combined with pseudotime trajectory modeling, to study FSHD disease etiology and cellular progression in human primary myocytes. We identified a small FSHD-specific cell population in all tested patient-derived cultures and detected new genes associated with DUX4 de-repression. We furthermore generated an FSHD cellular progression model, reflecting both the early burst-like DUX4 expression as well as the downstream activation of various FSHD-associated pathways, which allowed us to correlate DUX4 expression signature dynamics with that of regulatory complexes, thereby facilitating the prioritization of epigenetic targets for DUX4 silencing. Single-cell transcriptomics combined with pseudotime modeling thus holds valuable information on FSHD disease etiology and progression that can potentially guide biomarker and target selection for therapy.