COMMENTARY

Decoding DMD transcriptional networks using single‐nucleus RNA sequencing nucleus COMMENTARY RNA sequencing Daniel J. Garrya,b,1, Satyabrata Dasa, and Wuming Gonga

Duchenne muscular dystrophy (DMD) is an X -linked disease, and it is the most com- mon form of muscular dystrophy caused by genetic mutations in the Dmd (1). The Dmd gene contains 79 exons, spans 2.4 Mb, and is the single largest gene in the (2). This gene encodes for dystro- phin, which is a component of the – glycoprotein complex that provides structural stability to the cell membrane (by connecting the and the extracellular matrix), and a dysfunctional or absent dystrophin leads to progressive muscle Fig. 1. Decoding the molecular mechanisms of DMD wasting with cycles of muscle degeneration and re- pathogenesis utilizing snRNA-seq. This figure schematizes the discoveries outlined in Chemello et al. generation that ultimately fail (3, 4). Young boys with (7) with the newly generated DMD mouse model DMD lose their ability to ambulate, become wheel- (ΔEx51) and the transcriptomic analysis of isolated chair bound, and die prematurely (1, 5). This disease nuclei from skeletal muscle cells. The snRNA-seq affects skeletal muscle, which is the single largest or- analysis was used to discover factors and pathways underlying DMD pathogenesis from previously gan in the body, and it normally has a remarkable ca- unrecognized cell clusters. These results in pacity for regeneration (6). In response to a severe combination with other databases provide a platform injury caused by genetic disorders, trauma, or expo- for developing new therapeutic interventions as well sure to toxins that destroys over 90% of the muscle, the as an enhanced understanding of the gene-regulatory networks involved in muscle biology and DMD. cytoarchitecture of the injured tissue is completely re- stored and is indistinguishable compared to unin- jured muscle within a 2- to 4-wk period. This displayed morphological and physiological deficits regenerative capacity is due to the myogenic stem consistent with the DMD phenotype (7). The ΔEx51 cell population (i.e., satellite cells) that is resident in mouse model is an important contribution to the adult skeletal muscle, and with repeated DMD- muscular dystrophy research field and will comple- mediated degeneration and regeneration this re- ment the extensively used, mdx mouse model (8, 9). generative process ultimately is exhausted (6). The mdx mice were discovered in the 1980s and While a number of studies have enhanced our un- found to have a myopathy due to a spontaneous derstanding of the myogenic stem cell population, nonsense point mutation causing a stop codon in new insights are needed regarding the factors that exon 23 of the Dmd gene resulting in an absence govern muscle regeneration and potentially serve as of dystrophin (8). While the mdx mice are exten- therapies for diseases like DMD. In PNAS, Chemello sively used in the research laboratory, they do not et al. (7) use emerging technologies to provide a mimic the human course of disease even though discovery science platform. First, they engineered there is muscle degeneration, impaired motor per- amousemodelbydeletingexon51oftheDmd formance, and a mildly reduced life span. The dia- gene. This gene-edited mouse (ΔEx51) was viable, phragm is the only muscle in the mdx mouse that lacked dystrophin in skeletal muscle and heart, and displays the remarkable and progressive myopathic

aDepartment of Medicine, University of Minnesota, Minneapolis, MN 55455; and bPaul and Sheila Wellstone Muscular Dystrophy Center, University of Minnesota, Minneapolis, MN 55455 Author contributions: D.J.G., S.D., and W.G. wrote the paper. Competing interest statement: D.J.G. is a cofounder of NorthStar Genomics. Published under the PNAS license. See companion article, “Degenerative and regenerative pathways underlying Duchenne muscular dystrophy revealed by single-nucleus RNA sequencing,” 10.1073/pnas.2018391117. 1To whom correspondence may be addressed. Email: [email protected].

www.pnas.org/cgi/doi/10.1073/pnas.2022205117 PNAS Latest Articles | 1of3 Downloaded by guest on September 27, 2021 degeneration that mirrors the human disease (9). In contrast, the accepted analytical pipelines and the processing of a volumi- –dystrophin double-mutant mouse model has a much nous amount of data that typically requires bioinformatics more severe muscle disease and a markedly abbreviated life span expertise. and may have an even more severe disease than humans Chemello et al. (7) used snRNA-seq from the TA muscle of with DMD (10, 11). As is the case with a number of genetic disor- 4-wk-old wild-type (WT) and ΔEx51 mice. The TA muscle ders, including DMD, a major challenge for the field is to generate was selected as it is commonly analyzed in the research an animal model that reflects the clinical manifestations of the community and has a mixed fiber composition (slow twitch human disease. Therefore, future studies will be needed to fully oxidative and fast twitch glycolytic fibers). They sequenced characterize the ΔEx51 mouse model as it ages. Nevertheless, it 11,000 nuclei (WT and ΔEx51) and analyzed more than will be a valuable resource to the research community as its 20,000 in the WT and dystrophic TA muscles. Based mutation is more commonly observed in humans and therefore on transcriptional signatures, 14 different clusters of nuclei will be an important preclinical model for gene-editing repair were identified and supported a high-quality dataset (Fig. 1) and gene therapy initiatives (12, 13). (7). Among these cell clusters were myogenic stem cells + (Pax7 ), myoblasts (Myob vs. Myh3 and Myh8), cells associ- Δ In order to begin to characterize the Ex51 ated with the neuromuscular junction, smooth muscle cells, mouse model, Chemello et al. took an unbiased endothelialcells,fibroblasts,andothers.Inall,thesecellclus- approach and performed single-nucleus RNA ters were subdivided into three groups: nuclei of the regener- ative pathway, nuclei of mononucleated cells, and myonuclei sequencing (snRNA-seq) using nuclei isolated of myofibers (7). These analyses also demonstrated a reduc- from the tibialis anterior (TA) skeletal muscle. tion of mature myonuclei in the ΔEx51 TA muscle compared to the WT control, and the analysis suggested these changes The repeated cycles of muscle degeneration and regener- may have been a result of inflammation, fibrosis, or muscle re- ation that characterize DMD muscle ultimately exhaust the generation. The snRNA-seq analysis also uncovered degenera- regenerative capacity of the myogenic stem cells and result in tive pathways including the ubiquitination pathway as well as the replacement of the muscle with fibrosis (6). In order to markers associated with atrophy and apoptosis in the ΔEx51 Δ begin to characterize the Ex51 mouse model, Chemello muscle (7). Importantly, these studies also identified a cluster et al. took an unbiased approach and performed single- of cells (RegMyon) that was only found in the dystrophic mus- nucleus RNA sequencing (snRNA-seq) using nuclei isolated cle. This cluster of cells expressed embryonic and perinatal from the tibialis anterior (TA) skeletal muscle (7). The power of MyHC isoforms and inference of a hierarchical trajectory be- this technology is that it allows a whole-genome analysis of tween the three cell clusters was performed (muscle stem large cells such as the multinucleated myofibers (this technol- cells or MuSc, myoblasts or Myob, and RegMyon) to examine ogy could also be useful to analyze adult neurons, adipocytes, their fate. A heatmap gene expression analysis further sup- cardiomyocytes, or other cell types). These single-cell/nucleus ported the notion of the three distinct cell populations and technologies are revolutionizing our understanding of the cel- defined highly expressed genes in the RegMyon Cluster lular composition of tissues and their dynamic interactions in (Dclk1, Ncam1, and Baiap2l1 involved in muscle regenera- the unperturbed and stressed states. The use of these tech- tion and the transcription factors Runx1, Jdp2, and nologies has helped uncover previously undefined and rare Mef2a) (7). Moreover, enrichment analysis of the transcrip- cell populations, and they have successfully defined cell line- tion factor binding sites supported the notion that Jdp2 could age relationships. These technologies also provide insights into bind the promoters of myogenic regulatory factors and serve as the diversity or heterogeneity of cell types and the complex na- a regulator of muscle regeneration. In summary, using snRNA- ture of their organization in situ. Importantly, they also enhance seq, the authors were able to characterize the molecular pheno- our understanding of how cell types survive and respond to type of the dystrophic muscle, identify a unique cell cluster — changing microenvironments in short, the results of these tech- (RegMyon), and identify factors (Jdp2) that may have an impor- nologies have been a game changer. New platforms now al- tant transcriptional role in myogenesis and will require future low the analysis of thousands or hundreds of thousands of examination (Fig. 1). cells. Compared with single-cell RNA-seq (scRNA-seq), the While the studies presented in Chemello et al. introduce a snRNA-seq technique addresses tissues that cannot be muscular dystrophy mouse model that involves a mutation readily dissociated into single-cell suspension, such as skeletal commonly seen in DMD patients and outlines a number of muscle, and it reduces the gene expression variation that may discoveries, future studies and efforts will be essential (Fig. 1) be caused by dissociation. Thus, snRNA-seq technology en- (7). The molecular (snRNA-seq) characterization of muscle ables the discovery of new cell types that would be difficult to groups (the diaphragm, which is commonly affected in isolate. Moreover, recent studies found that snRNA-seq has DMD, slow twitch oxidative muscles, and fast twitch glycolytic superior performance for sensitivity and classification of com- muscles) will need to be expanded and examined at multiple plex cell types (14). Therefore, these advancements are further time periods as the ΔEx51 mouse model ages. As dystrophin is transforming science and medicine by giving us molecular in- expressed in skeletal muscle, heart, and brain (1), it will be impor- sights into the cellular changes related to diseases. As with all tant to evaluate each of these lineages in a similar fashion using technologies, there are also some drawbacks or associated snRNA-seq as outlined by Chemello et al. (7). Importantly, these challenges. For example, the single-cell/nuclear technologies large databases in combination with other publicly available da- are costly and there are batch effects that limit the analysis of tabases such as the Human Cell Atlas (15) and Tabula Muris (16) databases within and between laboratories. In addition, of will be valuable resources for discovery science for the community course, there are the issues related to the absence of well- and should be collectively mined.

2of3 | www.pnas.org/cgi/doi/10.1073/pnas.2022205117 Garry et al. Downloaded by guest on September 27, 2021 In summary, scRNA-seq/snRNA-seq analyses are powerful Chemello et al. provide the tools and the platform that should tools and they provide valuable insights into cellular heterogene- have a major impact on the field. ity and disease mechanisms. The mining of these databases will provide new discoveries that will be tested in the laboratory and Acknowledgments hopefully lead to therapeutic initiatives that can improve the mor- We thank Cynthia Faraday for providing us with figure illustration assistance. bidity and mortality of devastating diseases such as DMD (Fig. 1). Support was provided by a grant from the NIH (HL148599).

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