Transcriptional and open chromatin analysis of bovine skeletal muscle development by single‐cell sequencing

Abstract

Skeletal muscle is a complex heterogeneous tissue and characterizing its cellular heterogeneity and transcriptional and epigenetic signatures are important for understanding the details of its ontogeny. In our study, we applied scRNA‐seq and scATAC‐seq to investigate the cell types, molecular features, transcriptional and epigenetic regulation, and patterns of developing bovine skeletal muscle from gestational, lactational and adult stages. Detailed molecular analyses were used to dissect cellular heterogeneity, and we deduced the differentiation trajectory of myogenic cells and uncovered their dynamic gene expression profiles. SCENIC analysis was performed to demonstrate key regulons during cell fate decisions. We explored the future expression states of these heterogeneous cells by RNA velocity analysis and found extensive networks of intercellular communication using the toolkit CellChat. Moreover, the transcriptomic and chromatin accessibility modalities were confirmed to be highly concordant, and integrative analysis of chromatin accessibility and gene expression revealed key transcriptional regulators acting during myogenesis. In bovine skeletal muscle, by scRNA‐seq and scATAC‐seq analysis, different cell types such as adipocytes, endothelial cells, fibroblasts, lymphocytes, monocytes, pericyte cells and eight skeletal myogenic subpopulations were identified at the three developmental stages. The pseudotime trajectory exhibited a distinct sequential ordering for these myogenic subpopulations and eight distinct gene clusters were observed according to their expression pattern. Moreover, specifically expressed TFs (such as MSC, MYF5, MYOD1, FOXP3, ESRRA, BACH1, SIX2 and ATF4) associated with muscle development were predicted, and likely future transcriptional states of individual cells and the developmental dynamics of differentiation among neighbouring cells were predicted. CellChat analysis on the scRNA‐seq data set then classified many ligand–receptor pairs among these cell clusters, which were further categorized into significant signalling pathways, including BMP, IGF, WNT, MSTN, ANGPTL, TGFB, TNF, VEGF and FGF. Finally, scRNA‐seq and scATAC‐seq results were successfully integrated to reveal a series of specifically expressed TFs that are likely to be candidates for the promotion of cell fate transition during bovine skeletal muscle development. Overall, our results outline a single‐cell dynamic chromatin/transcriptional landscape for normal bovine skeletal muscle development; these provide an important resource for understanding the structure and function of mammalian skeletal muscle, which will promote research into its biology.

Single-Cell Sequencing Technology in Ruminant Livestock: Challenges and Opportunities

“…Single-cell sequencing, including sc/snRNA-seq and sc/snATAC-seq, is a powerful tool that provides insights into cellular heterogeneity, gene expression profiles across cell types, and regulatory networks. The most commonly used platform for single-cell sequencing in ruminant livestock is currently 10× Genomics Chromium [ 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 ]. The 10× Genomics Chromium workflow for sc/snRNA-seq broadly entails cell or nuclei isolation, encapsulation of cells or nuclei in oil droplets with barcoded beads using microfluidics, cell and/or nuclei lysis, and reverse transcription of mRNA while incorporating unique barcodes, adapter ligation, and sequencing ( Figure 1 ) [ 51 ].…”

“…Furthermore, the application of single-cell genomics in livestock research has the potential to accelerate the pace of genetic improvement by facilitating the identification of cell-type-specific gene expression, along with gene regulatory elements and networks associated with various traits important to livestock production . Adipose Nuclei RNA GEO GSE211707 [7] Embryo (8-and 16-cell stage) Cell RNA GEO GSE99210 [8] Embryo (peri-implantation) Cell RNA GEO GSE234335 [9] Embryo (SCNT) Cell RNA SRA PRJNA727165 [10] Embryo (trophectoderm) Cell RNA GEO GSE200216 [11] Fetal Gonads Cell RNA GEO GSE162952 [12] Milk Somatic Cells Cell RNA ENA PRJEB73560 [13] Muscle Cell RNA GEO GSE205347 [14] Muscle Cell RNA, ATAC GSA CRA006626 [15] PBMC * Cell RNA, ATAC GEO GSE225962 [16] PBMC * Cell RNA, ATAC GEO GSE166473 [17] Placenta (developing) Cell RNA GEO GSE234524 [18] Placenta (mature) Nuclei RNA GEO GSE214407 [19] Primary Mammary Epithelial Cells Cell RNA FAANG PRJEB41576 [20] Ruminal epithelial cells Cell RNA GEO GSE166473 [21] Satellite cells Cell RNA GEO GSE184128 [22] Satellite cells Cell RNA GEO GSE211428 [23] Despite the potential benefits, the application of sc/snRNA-seq and sc/snATAC-seq in ruminant livestock species presents challenges. Standardized computational analysis pipelines that are species-agnostic are essential, and the discovery and annotation of cell populations can be difficult in non-model organisms and for tissues such as the rumen, which are unique to these species [44][45][46].…”

“…While these techniques have been more extensively applied across studies in model organisms and humans, their adoption in livestock species is just beginning. Several studies in cattle, sheep, and goats have utilized sc/snRNA-seq and sc/snATAC-seq to characterize cellular heterogeneity within tissues, track cell population and gene expression changes across developmental time, and profile immune cell populations essential for disease resistance and resilience ( Table 1 , Table 2 and Table 3 ) [ 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 ]. There is immense potential to further utilize these technologies to advance the understanding of cellular and molecular mechanisms governing traits essential for more productive and sustainable livestock while supporting the welfare of these species.…”

“…Understanding the genetic and biological factors that contribute to these traits at single-cell resolution can provide valuable insights into the genetic and epigenetic factors that drive phenotypic variability [ 42 , 43 ]. Furthermore, the application of single-cell genomics in livestock research has the potential to accelerate the pace of genetic improvement by facilitating the identification of cell-type-specific gene expression, along with gene regulatory elements and networks associated with various traits important to livestock production [ 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 ].…”

Knockdown of NFIC Promotes Bovine Myoblast Proliferation through the CENPF/CDK1 Axis

“…From the perspective of livestock production, muscle growth and regeneration play crucial roles in skeletal muscle development, directly impacting meat production performance and economic value. , Furthermore, the significance of myoblast growth goes beyond traditional animal breeding and encompasses emerging fields such as tissue regeneration and in vitro meat production. , In these applications, the intricate process of myoblast proliferation is essential for muscle growth and regeneration in bovine species and involves a complex interplay of different regulatory elements and signaling pathways. , However, the molecular and cellular mechanisms controlling the growth and development of skeletal muscle are still not fully understood. − Understanding these mechanisms is important not only for optimizing beef production but also for advancing techniques in tissue regeneration and in vitro meat production. , …”