1写在前面
分享一下最近看到的2
篇paper
关于骨骼肌组织的细胞Marker
,绝对的Atlas
级好东西。👍
希望做单细胞的小伙伴觉得有用哦。😏
2常用marker(一)
general_mrkrs <- c(
'MYH7', 'TNNT1', 'TNNT3', 'MYH1', 'MYH2', "CKM", "MB", # Myofibers
'PAX7', 'DLK1', # MuSCs
'PDGFRA', 'DCN', 'ANGPTL7', 'OSR2', 'NGFR', 'SLC22A3','ITGA6', # Fibroblasts
'FMOD', 'TNMD' , 'MKX', # Tenocytes
'MPZ', 'MBP', # Schwann cells
'CDH2', 'L1CAM', # SCG
'MSLN', 'ITLN1', # mesothelium
"ADIPOQ", "PLIN1", # adipocytes
'PTPRC', 'CD3D', 'IL7R', # T cells
'NKG7', 'PRF1', #NK cells
'CD79A', "TCL1A", # B cells
'MZB1', 'JCHAIN', # B plasma
"CD14", "FCGR3A",'S100A8', 'S100A12', # Mono
"CD163", "C1QA", # Macrop
"XCR1", "CLEC9A", # cDC1 "CADM1",
"CD1C", "CLEC10A", "CCR7", # cDC2
'LILRA4', 'IL3RA', "IRF7", # pDC
'FCGR3B', 'CSF3R', 'SORL1', # Neutrophils
'EPX', 'PRG2', # Eosinophils 'CLC'
'TPSB2', 'MS4A2', # Mast cells
'PECAM1', 'HEY1','CLU', # art EC
'CA4', 'LPL', # capEC
'ACKR1', 'SELE', # venEC
'LYVE1', 'TFF3', # lymphEC
'RGS5','ABCC9', # pericytes
'MYH11', 'ACTA2', # SMC
'HBA1', #RBC
)
出自下面paper
:👇
Human skeletal muscle aging atlas. Veronika R. Kedlian, Yaning Wang, Tianliang Liu, Xiaoping Chen, Liam Bolt, Catherine Tudor, Zhuojian Shen, Eirini S. Fasouli, Elena Prigmore, Vitalii Kleshchevnikov, Jan Patrick Pett, Tong Li, John E G Lawrence, Shani Perera, Martin Prete, Ni Huang, Qin Guo, Xinrui Zeng, Lu Yang, Krzysztof Polański, Nana-Jane Chipampe, Monika Dabrowska, Xiaobo Li, Omer Ali Bayraktar, Minal Patel, Natsuhiko Kumasaka, Krishnaa T. Mahbubani, Andy Peng Xiang, Kerstin B. Meyer, Kourosh Saeb-Parsy, Sarah A Teichmann & Hongbo Zhang 2024 Apr.
3常用marker(二)
Mural Cell Markers
#SMOOTH MUSCLE CELLS
FeaturePlot(df.harmony, features = "MYH11", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "ACTA2", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "TAGLN", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
#PERICYTES
FeaturePlot(df.harmony, features = "RGS5", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "CSPG4", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "PDGFRB", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
Glial Cells Markers
FeaturePlot(df.harmony, features = "PROX1", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "MPZ", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "NCAM1", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "CDH19", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "SOX10", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "PLP1", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
Adipocites Markers
FeaturePlot(df.harmony, features = "PLIN1", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "ADIPOQ", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "MMRN1", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "CCL21", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
Tenocytes Markers
FeaturePlot(df.harmony, features = "FMOD", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "TNMD", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "COL22A1", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "SCX", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "DLG2", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "FBN1", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
Endothelial Markers
#FeaturePlot(df.harmony, features = "PCDHA6", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
#ARTERIAL
FeaturePlot(df.harmony, features = "FBLN5", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "DLL4", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "SEMA3G", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
#CAPILLARIES
FeaturePlot(df.harmony, features = "RGCC", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
#VENOUS
FeaturePlot(df.harmony, features = "EPHB4", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
Myonuclei Markers
FeaturePlot(df.harmony, features = "TTN", min.cutoff = "q9", order = T, cols = c("lightblue", "navy"), raster = FALSE)
#IMMATURE MYOCYTE
FeaturePlot(df.harmony, features = "MYMX", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "MYOG", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
#REG MYONUCLEI
FeaturePlot(df.harmony, features = "FLNC", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "MYH3", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "MYH8", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "XIRP1", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
NMJ Myonuclei Markers (Neuromuscular junction)
#NMJ
FeaturePlot(df.harmony, features = "CHRNE", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "CHRNA1", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "PRKAR1A", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "COL25A1", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "UTRN", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "COLQ", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "ABLIM2", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "VAV3", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "UFSP1", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
MTJ Myonuclei Markers (Myotendinous junction)
#MTJ
FeaturePlot(df.harmony, features = "COL22A1", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "PIEZO2", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "COL24A1", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "COL6A1", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "FSTL1", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "COL6A3", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(df.harmony, features = "TIGD4", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
FeaturePlot(mini_df.harmony.harmony, features = "EYS", min.cutoff = "q9", order = TRUE, cols = c("lightblue", "navy"), raster = FALSE)
出自下面paper
:👇
Lai, Y., Ramírez-Pardo, I., Isern, J. et al. Multimodal cell atlas of the ageing human skeletal muscle. Nature (2024).
点个在看吧各位~ ✐.ɴɪᴄᴇ ᴅᴀʏ 〰
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