Single-nucleus RNA-seq identifies transcriptional heterogeneity in multinucleated skeletal myofibers

Petrany, Michael J.; Swoboda, Casey O; Sun, Chengyi; Chetal, Kashish; Rothenberg, Marc E.; Weirauch, Matthew T.; Salomonis, Nathan; Millay, Douglas P.

doi:10.1101/2020.04.14.041400

Cited by 13 publications

(26 citation statements)

References 53 publications

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“…We identified candidate surface markers and transcription factor regulators distinct to the stages of myogenic commitment and myocyte fusion (represented by PHATE bins 8-10 and 11-17, respectively), which could not be resolved with individual datasets. Interestingly, we observed transcriptional signatures of surface receptors, such as Erbb3 and Cd97, specific to fusing myocytes (bins [11][12][13][14][15][16][17], which may enable improved prospective isolation strategies compared to less stage-specific cell markers like β1-integrin (Itgb1). Notably ERBB3/HER3 (encoded by Errb3) has been identified as a myogenic progenitor marker of human pluripotent stem cell-derived myogenic progenitors 58 .…”

Section: Discussionmentioning

confidence: 96%

“…Data and code availability. Single-nucleus RNA sequencing data were kindly provided by the Millay lab 11 , prior to public release. Newly collected scRNAseq data for 2 samples from 7 mo mice have been deposited in GEO under accession GSE159500.…”

Section: Micementioning

confidence: 99%

“…Spot deconvolution was performed using the deconvolution module in BayesPrism (previously known as "Tumor microEnvironment Deconvolution", TED, v1.0; github.com/Danko-Lab/TED). First, myogenic cells were re-labeled, according to binning along the first PHATE dimension, as "Quiescent MuSCs" (bin 4), "Activated MuSCs" (bins 5-7), "Committed Myoblasts" (bins 8-10), and "Fusing Myoctes" (bins [11][12][13][14][15][16][17]. Dissociation-associated muscle stem cells were ignored and myonuclei labels were retained from as "Myonuclei (Type IIb)" and "Myonuclei Type IIx".…”

Section: Micementioning

confidence: 99%

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Strength in numbers: Large-scale integration of single-cell transcriptomic data reveals rare, transient muscle progenitor cell states in muscle regeneration

McKellar

Walter

Song

et al. 2020

Preprint

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Skeletal muscle repair is driven by the coordinated self-renewal and fusion of myogenic stem and progenitor cells. Single-cell gene expression analyses of myogenesis have been hampered by the poor sampling of rare and transient cell states that are critical for muscle repair, and do not provide spatial information that is needed to understand the context in which myogenic differentiation occurs. Here, we demonstrate how large-scale integration of new and public single-cell and spatial transcriptomic data can overcome these limitations. We created a large-scale single-cell transcriptomic dataset of mouse skeletal muscle by integration, consensus annotation, and analysis of 23 newly collected scRNAseq datasets and 79 public single-cell (scRNAseq) and single-nucleus (snRNAseq) RNA-sequencing datasets. The resulting compendium includes nearly 350,000 cells and spans a wide range of ages, injury, and repair conditions. Combined, these data enabled identification of the predominant cell types in skeletal muscle with robust, consensus gene expression profiles, and resolved cell subtypes, including endothelial subtypes distinguished by vessel-type of origin, fibro/adipogenic progenitors marked by stem potential, and many distinct immune populations. The representation of different experimental conditions and the depth of transcriptome coverage enabled robust profiling of sparsely expressed genes. We built a densely sampled transcriptomic model of myogenesis, from stem-cell quiescence to myofiber maturation and identified rare, short-lived transitional states of progenitor commitment and fusion that are poorly represented in individual datasets. We performed spatial RNA sequencing of mouse muscle at three time points after injury and used the integrated dataset as a reference to achieve a high-resolution, local deconvolution of cell subtypes. This analysis identified the temporal variation in cell subtype colocalized interactions during injury recovery. We will release an interactive public web tool to enable exploration and visualization of this rich single-cell transcriptomic resource. Our work supports the utility of large-scale integration of single-cell transcriptomic data as a tool for biological discovery.

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Section: Discussionmentioning

confidence: 96%

Section: Micementioning

confidence: 99%

Section: Micementioning

confidence: 99%

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Strength in numbers: Large-scale integration of single-cell transcriptomic data reveals rare, transient muscle progenitor cell states in muscle regeneration

McKellar

Walter

Song

et al. 2020

Preprint

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“…This snapshot of mRNA localization of one day post-eclosion DLMs can similarly be examined in maturing muscles and in those undergoing repair.Published data support localized transcription in mouse muscle syncytia, through the examination of transgene expression[33]. More recently, independent single nucleus RNA-seq studies on mouse muscle syncytia[34][35][36] concur on heterogenous transcription in mouse muscle nuclei. Data therein strongly support previous findings and hypotheses that muscle nuclei respond to neural and tendon signals locally.…”

mentioning

confidence: 90%

Heterogeneous distribution of mRNAs within flight muscle fibers, and implications for function

Parekh

Chakraborty

Purohit

et al. 2020

Preprint

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Muscle heterogeneity has been explored in terms of fiber-type distribution, structural organisation, and differences at their junctions with neurons and tendons. We amplify on such observation to additionally suggest that muscle syncytia have nonuniform protein requirements along their length, deployed for developmental and functional uses. An exploration of regionalized proteins or their mRNA across muscle syncytia has not been done. We investigated mRNA localization in regions of Drosophila melanogaster dorsal longitudinal muscle (DLM) syncytia over their entire transcriptome. Dissection of muscle regions, their RNA-seq and stringent Differential Gene Expression analysis indeed reveals statistically significant regionalization of nearly a hundred mRNA over the length of DLMs. Functions of over half of these genes require experimental verification. A preponderance of mRNA coding for catabolic and proteolytic enzymes is conspicuous among transcripts enriched in the posterior of DLMs. Our findings provide a foundation for exploring molecular processes that contribute to syncytial maturation and muscle homeostasis in a spatially non-homogenous manner.

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“…SC quiescence is actively maintained by paracrine-acting cues from the muscle fiber, serving as a niche cell (Bischoff, 1990;Eliazer et al, 2019;Goel et al, 2017). In contrast to niche cells across many stem cell compartments, each muscle fiber is a multi-nucleated syncytium, that exhibits transcriptional diversity across the myonuclei, to provide spatial control for specialized functions (Kim et al, 2020;Petrany et al, 2020). Does the multinucleated niche cell regulate the diversity of states across the QSC pool?…”

Section: Introductionmentioning

confidence: 99%

Spatial Heterogeneity of Delta-like 4 Within a Multinucleated Niche Cell Maintains Muscle Stem Cell Diversity

Eliazer

Sun

Brack

2020

Preprint

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The quiescent muscle stem cell (QSC) pool is heterogeneous and generally characterized by the presence and levels of intrinsic myogenic transcription factors. Whether extrinsic factors maintain the diversity of states across the QSC pool remains unknown. The muscle fiber is a multinucleated syncytium that serves as a niche to QSCs, raising the possibility that the muscle fiber regulates the diversity of states across the QSC pool. Here we show that the muscle fiber maintains a continuum of quiescent states, through a gradient of Notch ligand, Dll4, produced by the fiber and captured by QSCs. The abundance of Dll4 captured by the QSC correlates with levels of the SC identity gene, Pax7. Niche-specific loss of Dll4 decreases QSC diversity and shifts the continuum, towards more proliferative and committed states. We reveal that fiber-derived Mindbomb1 (Mib1), an E3 ubiquitin ligase activates Dll4 and controls the spatial localization of Dll4. In response to injury, with a Dll4-replenished niche, the normal continuum and diversity of SC pool is restored, demonstrating bi-directionality within the SC continuum. Our data shows that a post-translational mechanism controls spatial heterogeneity of Notch ligands in a multinucleated niche cell to maintain a continuum of diverse states within the SC pool during tissue homeostasis.

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Single-nucleus RNA-seq identifies transcriptional heterogeneity in multinucleated skeletal myofibers

Cited by 13 publications

References 53 publications

Strength in numbers: Large-scale integration of single-cell transcriptomic data reveals rare, transient muscle progenitor cell states in muscle regeneration

Strength in numbers: Large-scale integration of single-cell transcriptomic data reveals rare, transient muscle progenitor cell states in muscle regeneration

Heterogeneous distribution of mRNAs within flight muscle fibers, and implications for function

Spatial Heterogeneity of Delta-like 4 Within a Multinucleated Niche Cell Maintains Muscle Stem Cell Diversity

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