Additional file 1 of Integrative single-cell RNA-seq and ATAC-seq analysis of myogenic differentiation in pig
Bibliographic record
Abstract
Additional file 1: Figure S1. Quality control and batch effect correction in scRNA-Seq, related to Figure 1 A. Violin plots showing the number of expressed genes, the number of reads uniquely mapped against the reference genome, and the fraction of mitochondrial genes compared to all genes per cell in scRNA-Seq data. B. Box plot showing the number of genes (left) and the number of uniquely mapped reads (right) per cell in each identified cell type in scRNA-Seq data. C. tSNE plot visualization of the sample source for all 70,201 cells. Each dot is a cell. Different colors represent different samples. D. tSNE plot visualization of unsupervised clustering analysis for all 70,201 cells based on scRNA-Seq data after quality control, which gave rise to 31 distinct clusters. Figure S2. Gene Ontology (GO) analysis of the DEGs for each cell type was performed and the representative enriched GO terms are presented, related to Figure 1. Figure S3. Expression of selected marker genes along the differentiation trajectory, related to Figure 2 A. tSNE plot demonstrating cell cycle regression (left). Visualization of myogenic differentiation trajectory by cell cycle phases (G1, S, and G2/M) (right). B. Donut plots showing the percentages of cells in G1, S, and G2M phase at different cell states. C. Expression levels of cell cycle-related genes in the myogenic cells organized into the Monocle trajectory. D. Expression levels of muscle related genes in the myogenic cells organized into the Monocle trajectory. Figure S4. Unsupervised clustering analysis for all cells in scATAC-Seq data and myogenic-specific scATAC-seq peaks, related to Figure 4 A-C. tSNE plot visualization of the sample source for all 48514 cells in scATAC-Seq. Each dot is a cell. Different colors represent different pigs (A), different embryonic stages (B), or different samples (C). D. tSNE plot visualization of unsupervised clustering analysis for all 48514 cells after quality control in scATAC-Seq data, which gave rise to 15 distinct clusters. E. tSNE plot visualization of myogenic cells and other cells. Clusters 4 and 8 in Figure S4D were annotated as myogenic cells due to their high levels of accessibility of marker genes associated with myogenic lineage. F. Genome browser view of myogenic-specific peaks at the TSS of MyoG and Myf5 for myogenic cells and other cells in the scATAC-seq dataset. Figure S5. Percentage distribution of open chromatin elements in scATAC-Seq data, related to Figure 4 A. Distribution of open chromatin elements in each snATAC-seq sample. B. Distribution of open chromatin elements in snATAC-seq of myogenic cell types. C. Percentage distribution of open chromatin elements among DAPs in myogenic cell types. Figure S6. Integrative analysis of transcription factors and target genes, related to Figure 5 A. tSNE depiction of regulon activity (“on-blue”, “off-gray”), TF gene expression (red scale), and expression of predicted target genes (purple scale) of MyoG, FOSB, and TCF12. B. Corresponding chromatin accessibility in scATAC data for TFs and predicted target genes are depicted. Figure S7. Pseudotime-dependent chromatin accessibility and gene expression changes, related to Figure 7. The first column shows the dynamics of the 10× Genomics TF enrichment score. The second column shows the dynamics of TF gene expression values, and the third and fourth columns represent the dynamics of the SCENIC-reported target gene expression values of corresponding TFs, respectively. Figure S8. Myogenesis related gene expression in DMD (Duchenne muscular dystrophy) mice. Comparison of RNA-seq data of flexor digitorum short (FDB), extensor digitorum long (EDL), and soleus (SOL) in DMD and wild-type mice including 2- month and 5-month age. A. The expression levels of myogenesis related genes (Myod1, Myog, Myf5, Pax7). B. The expression levels of related genes that were upregulated during porcine embryonic myogenesis (EGR1, RHOB, KLF4, SOX8, NGFR, MAX, RBFOX2, ANXA6, HES6, RASSF4, PLS3, SPG21). C. The expression levels of related genes that were downregulated during porcine embryonic myogenesis COX5A, HOMER2, BNIP3, CNCS). Data were obtained from the GEO database (GSE162455; WT, n = 4; DMD, n = 7). Figure S9. Genome browser view of differentially accessible peaks at the TSS of EGR1 and RHOB between myogenic cells in the scATAC-seq dataset, related to Figure 8. Figure S10. Functional analysis of EGR1 in myogenesis, related to Figure 8 A-B. EdU assays for the proliferation of pig primary myogenic cells (A) and C2C12 myoblasts following EGR1 overexpression. C. qPCR analysis of the mRNA levels of cell cycle regulators in C2C12 cells following EGR1 overexpression. D. Immunofluorescence staining for MyHC in C2C12 cells following EGR1 overexpression and differentiation for 3 d. Then, the fusion index was calculated. Figure S11. Functional analysis of RHOB in myogenesis, related to Figure 8 A-B. EdU assays for proliferation of pig primary myogenic cells (A) and C2C12 myoblasts following RHOB overexpression. C. qPCR analysis of the mRNA levels of cell-cycle regulators in C2C12 cells following RHOB overexpression. D. Immunofluorescence staining for MyHC in C2C12 cells following RHOB overexpression and differentiation for 3 d. Then, the fusion index was calculated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.772 | 0.146 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".