Identification method for influence of FGFR3 mutation on epiphyseal growth plate soft backbone progenitor cell subpopulation and application thereof
By using single-cell sequencing technology in HCH mouse models, the impact of FGFR3 mutations on cartilage progenitor cells on epiphyseal growth plates was solved, and a new therapeutic direction was provided .
Patent Information
- Application Number
- CN202411430961.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-14
- Publication Date
- 2025-02-14
AI Technical Summary
The existing research mainly focuses on the effect of FGFR3 mutation on proliferating and hypertrophic chondrocytes, and pays less attention to its indirect effect on the epiphyseal growth plate cartilage progenitor cells, resulting in a lack of effective targets for therapeutic interventions for chondrosis.
By using single-cell sequencing technology (scRNA-seq) in HCH mouse models, cartilage tissue samples were extracted in epiphyseal growth plates, gene expression matrix was constructed, cell screening, clustering and dimensionality reduction, and correlation with cartilage progenitor cell differentiation was identified. Four chondrocyte subpopulations and quasi-temporal analysis were performed to reveal the effect of FGFR3 mutations on cartilage progenitor cells.
This method can accurately identify the chondrocyte subpopulation in chondrocytes in epiphyseal growth plates, reveal the lesion mechanism of FGFR3 mutation on chondrocyte progenitor cells, and provide a new direction for targeting skeletal stem cells to treat diseases.
Smart Images
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Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of biotechnology, and in particular to an identification method and application thereof for a subpopulation of cartilage stem progenitor cells in an epiphyseal growth plate affected by FGFR3 mutation. Background Art
[0002] Hypochondrodysplasia chondromatis (HCH) is an autosomal dominant skeletal disorder characterized by disproportionate short stature, short arms and legs, and mild joint laxity. The clinical and radiographic features of this dwarfism are milder than those of achondroplasia (ACH) and thanatophoric dyschondrodysplasia (TDI; TDII). These disorders are caused by activating mutations in fibroblast growth factor receptor 3 (FGFR3) and are collectively referred to as FGFR3-related osteochondrodysplasia. The clinical and radiographic features of HCH are usually less pronounced than those of ACH and may not become apparent until early or middle childhood. The incidence and prevalence of HCH are similar to those of ACH, with an incidence of 1 in 15,000 births. More than 250,000 people have been diagnosed with HCH worldwide. Defects such as macrocephaly, frontal bossing, midface depression, and narrow foramen magnum are often present in patients with FGFR3-related osteochondrodysplasia. Spinal defects are common in children and adults with ACH and HCH due to abnormalities of the vertebral bodies and intervertebral discs (IVDs) resulting in kyphosis, scoliosis, and lumbar lordosis. Obstructive apnea and intellectual disability are also common in patients with HCH. Patients with chondrodysplasia present with significant medical, functional, and psychosocial challenges throughout the lifespan.
[0003] Existing studies have shown that abnormal activation of FGFR3 leads to a series of pathological phenotypes of chondrodysplasia, which is closely related to the impact on multiple downstream pathways and the joint effects between pathways. However, most studies are limited to the direct effects of FGFR3 mutations on the proliferation and hypertrophy of chondrocytes, and little is known about whether the mutation indirectly affects growth plate stem and progenitor cells. This means that in order to intervene in the treatment of chondrodysplasia, it is necessary to have a more comprehensive and systematic understanding of the molecular mechanisms related to the impact of FGFR3 on the development of stem and progenitor cells, and to find more effective intervention targets. Summary of the invention
[0004] In order to solve the above problems, the present invention proposes a method for identifying epiphyseal growth plate cartilage stem cell subpopulations affected by FGFR3 mutations and its application. This method uses the HCH mouse model to understand FGFR3-related osteochondrodysplasia from the starting point of cartilage development-skeletal stem cells, which is of great significance for broadening the pathogenic mechanism of such diseases and targeting skeletal stem cells to treat diseases.
[0005] In order to achieve the above objectives, the embodiments of the present invention provide, in a first aspect, a method for identifying a subpopulation of cartilage stem progenitor cells in the epiphyseal growth plate affected by FGFR3 mutations, which comprises the following steps:
[0006] (1) extracting epiphyseal growth plate cartilage tissue samples from wild-type mice, heterozygous chondrodysplasia mice, and homozygous chondrodysplasia mice at the same time and preparing them into single cell suspensions;
[0007] (2) Use a single-cell processing system to obtain mRNA from a single cell, synthesize and fragment cDNA, connect it to a sequencing adapter for read sequencing, and construct an scRNA-seq library;
[0008] (3) Data analysis of the scRNA-seq library: using the CeleScope v1.9.0 pipeline to process the raw reads of scRNA-seq and generate a gene expression matrix file; performing cell screening, filtering and quality control on the gene expression matrix file, and then performing cell clustering and dimensionality reduction, identifying genes with significant differential expression between clusters, and dividing the cells into six clusters; determining the cell type identity of each cluster based on the expression of typical markers; performing secondary clustering after chondrocyte cluster extraction, analyzing differentially expressed genes and cell annotation, and identifying four chondrocyte subpopulations that are closely related to the stages of cartilage stem progenitor cell differentiation; performing pseudo-time series analysis on chondrocyte subpopulations, and comparing the changes in the number of cells in each chondrocyte subpopulation and the developmental trajectory of stem progenitor cells between chondrodysplastic mice and wild-type mice, revealing the pathological changes of cartilage stem progenitor cells in the context of chondrodysplasia.
[0009] According to the identification method of the present invention, single-cell sequencing technology (scRNA-seq) was used to analyze the three samples using the Scanpy package in Python to draw the overall cell type map of epiphyseal growth plate cells, and the genetic characteristics of the chondrocyte group were identified by the expression level of related differential genes, and the specific cartilage stem cell subpopulation was further characterized. By comparing the changes in the number of cells in each subpopulation of chondrocytes in chondrodysplastic mice and wild-type mice and the development trajectory of stem cells, the lesions of cartilage stem cells in the context of chondrodysplasia were revealed. In this way, understanding FGFR3-related osteochondrodysplasia from the starting point of cartilage development-skeletal stem cells is of great significance for broadening the pathogenic mechanism of such diseases and targeting skeletal stem cells to treat diseases.
[0010] Optionally, in step (2), use Singleron The single cell processing system loads a single cell suspension containing PBS into a microwell chip, and then collects the barcode beads from the microwell chip, that is, obtains the mRNA captured by the barcode beads.
[0011] Optionally, in step (3), the criteria for cell screening, filtering and quality control are: cells with less than 200 genes or more than 5000 genes are excluded; cells with a mitochondrial content greater than 10% are excluded; genes expressed in less than three cells are excluded.
[0012] Optionally, the four chondrocyte subpopulations are stem cells SCs, prehypertrophic chondrocytes Pre-HCs, hypertrophic chondrocytes HCs and Sox4+ chondrocytes Sox4+Cs.
[0013] In a second aspect, an embodiment of the present invention provides an application of the above-mentioned method for identifying a subpopulation of cartilage stem progenitor cells in the epiphyseal growth plate affected by FGFR3 mutations in determining therapeutic targets for FGFR3-related osteochondrodysplasia.
[0014] In a third aspect, the embodiments of the present invention propose the use of the above-mentioned method for identifying the subpopulation of epiphyseal growth plate cartilage stem progenitor cells affected by FGFR3 mutations in guiding the preparation of drugs for treating FGFR3-related osteochondrodysplasia.
[0015] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] Figure 1 is the sequence before and after mutation of the FGFR3 gene according to an embodiment of the present invention;
[0017] Figure 2 This is the principle of modifying the FGFR3 gene using CRISPR / Cas9 technology according to an embodiment of the present invention;
[0018] Figure 3 This is an operation process of modifying the FGFR3 gene using CRISPR / Cas9 technology according to an embodiment of the present invention;
[0019] Figure 4 is a UMAP atlas of epiphyseal growth plate chondrocytes according to an embodiment of the present invention;
[0020] Figure 5 is a dot plot of gene enrichment of each group of epiphyseal growth plate chondrocytes according to an embodiment of the present invention;
[0021] Figure 6 is a distribution diagram of chondrocyte subpopulations according to an embodiment of the present invention;
[0022] Figure 7 is a pseudo-time series analysis diagram of chondrocyte subpopulations according to an embodiment of the present invention;
[0023] Figure 8It is a GO and KEGG analysis map of differential genes between stem and progenitor cell subpopulations and hypertrophic chondrocyte subpopulations of chondrodysplastic mice and wild-type mice according to an embodiment of the present invention. DETAILED DESCRIPTION
[0024] The technical solution of the present invention is described below through specific examples. It should be understood that the one or more method steps mentioned in the present invention do not exclude the existence of other method steps before and after the combination step or the insertion of other method steps between these explicitly mentioned steps; it should also be understood that these embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention. Moreover, unless otherwise specified, the numbering of each method step is only a convenient tool for identifying each method step, and is not intended to limit the order of arrangement of each method step or to limit the scope of the present invention. The change or adjustment of the relative relationship thereof shall also be regarded as the scope of the present invention without substantially changing the technical content.
[0025] In order to better understand the above technical scheme, the exemplary embodiments of the present invention are described in more detail below. Although exemplary embodiments of the present invention are shown, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present invention and to enable the scope of the present invention to be fully communicated to those skilled in the art.
[0026] The test materials used in the present invention are all common commercial products and can be purchased in the market.
[0027] Main reagents: staining buffer (BD bioscience), microspheres (01-3333-42, Invitrogen), anti-mouse CD16 / CD32 antibodies (BD Biosciences), DAPI solution (BD Biosciences); GFP-labeled Calcein antibody; APC-Cy7-labeled Ter119 antibody (BioLegend); BV421-labeled CD45 antibody (BD Biosciences); APC-labeled CD3, CD19, Gr1, CD11b6 antibodies (BioLegend); PE-Cy7-labeled CD31, CD71 antibodies (BioLegend).
[0028] Main instruments and consumables: desktop centrifuge (eppendorf Centrifuge 5418R), flow sorter (Becton Dickinson Aria Fusion).
[0029] The present invention is described below with reference to specific embodiments. It should be noted that these embodiments are merely illustrative and do not limit the present invention in any way.
[0030] Example 1 Establishment of animal model
[0031] Human FGFR3 G382 corresponds to mouse FGFR3 V376. The FGFR3 gene has 12 transcripts. This application makes a V376D site-directed mutation in exon9 of the FGFR3-202 (ENSMUST0000016921 2.2) transcript, and the corresponding amino acid V at position 376 is mutated to D. Figure 1 As shown, the blue area is FGFR3 exon 9, and the red box is the mutation site. The 376th amino acid codon mutated from GTC to GAC, and the corresponding amino acid changed from V to D. At the same time, three synonymous amino acid mutations were made: the 373rd amino acid codon mutated from TAC to TAT, the 374th amino acid codon mutated from GGG to GGC, and the 375th amino acid codon mutated from GTG to GTC. After the mutation, there was an additional restriction endonuclease SalⅠ site near the 375th amino acid, and its sequence was GTCGAC, which facilitated the subsequent genotype identification.
[0032] The mouse FGFR3-202 transcript includes 18 exons, the translation start site ATG is located in exon2, the translation stop site TGA is located in exon18, and encodes 800aa. This application uses CRISPR / Cas9 technology to modify the FGFR3 gene.
[0033] Its principle is as follows Figure 2 As shown, the operation steps are as follows (such as Figure 3 shown):
[0034] (1) Find a suitable target sequence in the coding sequence of the target gene (usually select 20bp in the coding region, and its 3' end ends with NGG). To facilitate the subsequent genotype identification, design two target sites and inject them simultaneously.
[0035] (2) Microinjection of fertilized eggs: Use a microinjection instrument to mix the above sgRNA and Cas9mRNA at a concentration of 100ng / μl for sgRNA and 120ng / μl for Cas9 mRNA, and then inject them into the cytoplasm of the fertilized eggs of in vitro fertilized mice to construct specific mouse embryonic cells (fertilized eggs). After 1-2 hours of in vitro culture, the surviving fertilized eggs are transplanted into the oviduct of pseudopregnant female mice.
[0036] (3) Mouse genotype identification: ① Extract genomic DNA from the offspring mice obtained in the above steps for genotype identification; ② Cross the mice with the target gene knocked out with wild-type mice. Hypodycosis heterozygous mice (FGFR3 / +) and Hypodycosis homozygous mice (FGFR3 / FGFR3) were constructed respectively.
[0037] Example 2 Extraction of epiphyseal growth plate cartilage tissue
[0038] 1) Wipe the lower limbs of mice with 75% alcohol for disinfection; take the lower limbs of mice (cut off the distal femur and the proximal tibia after skinning, and do not separate the muscles at this time) and put them in a culture dish, separate the bones and muscles in a cell platform, and put the separated bones into a sterile PBS solution; the mice include wild-type mice (WT), heterozygous mice with chondrodysplasia (FGFR3 / +), and homozygous mice with chondrodysplasia (FGFR3 / FGFR3).
[0039] 2) Place the bones in a mortar, add 3 mL of digestion solution (1 / 1000 DispaseⅡ, 2.5 / 1000 Collagenaseα, the solvent is Hass solution) and grind the mouse bones until the bones turn white and flocculent, and use a Pasteur tube to draw the grinding solution into a 15 mL EP tube; place it horizontally in a shaker, digest at 200 rpm, 37°C for 15 min, pass the digestion solution supernatant through a 70 μm sieve to obtain a cell suspension, add an excess of FACS Buffer (PBS+1% FBS+2 mM EDTA) through the sieve at a ratio greater than 1:1 to terminate digestion, centrifuge and discard the supernatant, add 2 mL ACK lysis solution, place on ice for 3 min, add 3 mL FACS buffer to terminate lysis, centrifuge and discard the supernatant, resuspend with 1 mL FACS buffer and prepare a single cell suspension.
[0040] 3) Flow cytometry was performed using a Becton Dickinson Aria Fusion and analyzed using FlowJo software (Tree Star, Ashland, OR, USA). Initial compensation was set using microspheres to assess the background level of each stain. Gating was drawn to distinguish between positive and negative populations. Non-hematopoietic and non-immune single cell suspensions were sorted.
[0041] Example 3 Single Cell Sequencing Analysis
[0042] 1) RT, amplification and library construction
[0043] Using Singleron The single cell processing system was used to prepare a single cell suspension (2×10 5 cells / mL) into a microwell chip. The barcoded beads are then collected from the microwell chip, and the mRNA captured by the barcoded beads is reverse transcribed to obtain cDNA, which is then amplified by PCR.
[0044] ① System preparation: Thaw "Amplification Master Mix" and "A Primer Mix" at room temperature in advance, vortex centrifuge and place on ice, prepare PCR Mix on ice according to the following table, vortex mix and briefly centrifuge.
[0045] SD chip:
[0046] Components 1RXN(L)x1 2RXNs(μL)x2.2 Amplification Master Mix 172 378.4 A Primer Mix 32 70.4 Amplification Enzyme 8 17.6 Nuclease-free Water 188 413.6 Total 400 880
[0047] (2) HD chip:
[0048]
[0049]
[0050] ② Briefly centrifuge the reverse transcription product and place it on a 1.5 mL magnetic rack. After the solution is clarified, carefully remove the supernatant and leave only the Barcode Beads.
[0051] ③ Remove the centrifuge tube from the magnetic rack, add 400μL (SD chip) / 800μL (HD chip) PCR Mix to the tube, mix well by pipetting, and dispense into eight strip tubes, with a volume of 50mL per tube (two strip tubes of 8 can be used for HD chip).
[0052] ④ Cover the tube caps of the eight-tube strips and place them in a PCR instrument for amplification. Set the hot cover temperature to 105℃ and the reaction volume to 50μL. Then fragment the amplified cDNA and connect it to the sequencing adapter. The single cell RNA library kit (Singleron) was used to construct the library. Individual libraries were diluted to 4 nM, pooled and sequenced on an Illumina novaseq 6000 using 150 bp paired-end reads.
[0053] 2) Preliminary analysis of raw read data
[0054] The raw reads of scRNA-seq were processed using the CeleScope (https: / / github.com / singleron-RD / CeleScope) v1.9.0 pipeline to generate gene expression matrices. In brief, the raw reads were first processed with CeleScope, and low-quality reads were removed using Cutadapt v1.17, and poly-A tails and adapter sequences were trimmed. Cell barcodes and UMIs were extracted. Afterwards, the reads were mapped to the reference genome GRCm38 (ensemblversion92annotation) using STAR v2.6.1a (Ref) and featureCounts v2.0.1 (Ref) software was used to obtain the UMI counts and gene counts of each cell, and an expression matrix file was generated for subsequent analysis.
[0055] 3) Quality control, dimensionality reduction and clustering
[0056] Scanpy (v1.9.6) was used for quality control, dimensionality reduction, and clustering under Python 3.9.18. For each sample dataset, the expression matrix was filtered according to the following criteria: (1) cells with less than 200 genes or more than 5000 genes were excluded; (2) cells with a mitochondrial content greater than 10% were excluded; (3) genes expressed in less than 3 cells were excluded. After filtering, 36,416 cells were retained for downstream analysis. The raw count matrix was normalized by the total count per cell and logarithmically transformed into a normalized data matrix. The top 3000 variable genes were selected by setting flavor = "seurat". Principal component analysis (PCA) was performed on the variable gene matrix, and the first 15 principal components were used for clustering and dimensionality reduction. Using the Leiden algorithm with a resolution parameter set to 0.7, the cells were divided into 18 clusters, and 8 cell types were defined by marker gene comparison. After filtering out blood cells and immune cells, 6 types of cells remained. The clustering is visualized using the Unified Surface Approximation and Projection (UMAP).
[0057] 4) Analysis of differentially expressed genes (DEGs)
[0058] To identify differentially expressed genes (DEGs), the rank_genes_groups function in Scanpy was used, and genes expressed in more than 10% of cells in the cluster and with an average fold change value greater than 0.25 were selected as DEGs. For the cell type annotation of each cluster, the expression of typical markers found in DEGs was combined with literature knowledge and the marker expression of each cell type was displayed using a dot plot generated by the Scanpy.pl.umap function. Double cells expressing markers of different cell types were identified and removed manually.
[0059] 5) Cell type annotation
[0060] The cell type identity of each cluster was determined based on the expression of typical markers found in DEGs using the SynEcoSys database combined with manual annotation of relevant literature. The expression of markers used to identify each cell type was displayed using Scanpy.pl.umapt and scanpy.pl.violin.
[0061] 6) Pathway enrichment analysis
[0062] To investigate the potential functions of DEGs, Gene Ontology (GO) and Kyoto Encyclopedia of Genomes (KEGG) were analyzed using the “clusterProfiler” R package 3.16.1. Pathways with p_adj values less than 0.05 were considered significantly enriched. Gene Ontology gene sets included molecular function (MF), biological process (BP), and cellular component (CC) categories as references. GSEA analysis was performed on 104,532 genes in four clusters of growth plate chondrocytes. The average gene expression of each cell type was used as input data in the GSVA pathway enrichment analysis using the GSVA package. Protein-protein interactions of DEGs in each cluster were predicted based on the interactions of known genes with relevant GO terms in StringDB v1.22.0.
[0063] 7) Trajectory analysis
[0064] Cell differentiation trajectories were reconstructed by PAGA. Highly variable genes (HVGs) were used to sort cells according to the spatial-temporal differentiation order. sc.tl.paga was used to calculate the connectivity between cells and infer the link strength between different populations. Finally, the cell trajectories were visualized using the sc.pl.draw_graph function.
[0065] The results are as follows Figure 4-Figure 8 As shown, Figure 4After cell screening and quality control, the single-cell sequencing matrix data of three samples of fgfr3 / fgfr3, fgfr3 / +, and wt mice were divided into 6 clusters according to specific genes. Cells with high expression of genes such as Adipoq, Cxcl12, and Lepr were defined as mesenchymal stem cells; cells with high expression of genes such as Alpl and Wif1 were defined as pre-osteoblasts; cells with high expression of genes such as Bglap2 and Sp7 were defined as (Osteoblasts); cells with high expression of genes such as Co2a1 and Acan were defined as growth plate cells; cells with high expression of genes such as Prg4 were defined as articular chondrocytes; cells with high expression of genes such as Acta2 and Myh11 were defined as smooth muscle cells. Figure 5 To determine the cell type identity of each cluster based on the expression of typical markers, the expression of markers used to identify each cell type was displayed using Scanpy (v1.8.2) DotPlot. Figure 6 After the chondrocyte clusters were extracted, secondary clustering was performed, differentially expressed genes were analyzed and cells were annotated, and the four chondrocyte subpopulations (SCs, Pre-HCs, HCs and Sox4+Cs) identified were closely related to the stages of cartilage stem cell differentiation. Among them, SCs refers to Stem cells; Sox4+Cs refers to Sox4+chondrocytes; HCs refers to Hypertrophic chondrocytes; Pre-HCs refers to Pre-Hypertrophicchondrocytes. Figure 7 The pseudo-sequential analysis of chondrocyte subpopulations showed that compared with wild-type mice, the number of stem progenitor cells and prehypertrophic chondrocytes in chondrodysplastic mice increased significantly, while the number of hypertrophic chondrocytes decreased significantly, indicating that the FGFR3 point mutation affects the starting point of chondrocyte development - stem progenitor cells. Cartilage stem progenitor cells cannot differentiate downward, resulting in an abnormal increase in stem progenitor cells at the starting point of development, which may lead to the depletion of the stem cell pool. Figure 8GO and KEGG analysis maps of SCs subgroups and HCs subgroups, where (A) is the KEGG enrichment analysis of differentially expressed genes in SCs subgroups, (B) is the KEGG enrichment analysis of differentially expressed genes in HCs subgroups, (C) is the GO analysis of differentially expressed genes in SCs subgroups (upregulated), and (D) is the GO analysis of differentially expressed genes in SCs subgroups (downregulated); red represents the upregulated signaling pathways in fgfr3 / fgfr3 mice compared with wt mice, and blue represents the corresponding downregulated signaling pathways. The results showed that in the SCs subpopulation, the endoplasmic reticulum protein synthesis and processing modification signaling pathway of stem progenitor cells of chondrodysplastic mice was significantly upregulated, while the extracellular matrix receptor signal connection pathway related to cartilage development was significantly downregulated; in the HCs subpopulation, the endoplasmic reticulum protein synthesis and processing modification signaling pathway of hypertrophic chondrocytes was significantly downregulated, while the extracellular matrix receptor signal connection pathway related to chondrocyte hypertrophy was significantly upregulated, that is, the two signaling pathways of endoplasmic reticulum protein formation and extracellular matrix receptor signal connection were closely related to the abnormal increase of cartilage stem progenitor cells and the significant decrease of hypertrophic chondrocytes. At the same time, the GO analysis of the upregulated differential genes in the SCs subpopulation of fgfr3 / fgfr3 mice compared with wt mice showed that they were involved in energy metabolism, cell respiration, and protein synthesis and processing involving the endoplasmic reticulum and Golgi apparatus, while the GO analysis of the downregulated differential genes involved biological processes such as extracellular matrix synthesis and receptor signal connection. Both GO and KEGG analysis suggested that the self-renewal of stem progenitor cells in chondrodysplastic mice was abnormally active, but the extracellular matrix synthesis and signal transduction were inhibited, thus failing to differentiate downward. Therefore, further exploration of the differentiation trajectory of cartilage stem progenitor cells and the functional heterogeneity of chondrocyte subsets will help reveal the potential molecular mechanism by which FGFR3 point mutations affect the development of epiphyseal growth plates, which is of great significance for expanding the pathogenic mechanisms of such diseases and targeting skeletal stem cells to treat diseases.
[0066] In summary, according to the embodiments of the present invention, chondrocyte subpopulations in epiphyseal growth plate chondrocytes can be accurately identified, and the molecular mechanism of osteochondrodysplasia stem cell lesions and changes in related signaling pathways can be explained. Understanding FGFR3-related osteochondrodysplasia from the starting point of cartilage development - skeletal stem cells is of great significance for broadening the pathogenic mechanism of such diseases and targeting skeletal stem cells to treat diseases.
[0067] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms should not be understood as necessarily referring to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification.
[0068] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.
Claims
1. A method for identifying epiphyseal growth plate cartilage progenitor cell subpopulations affected by FGFR3 mutations, characterized in that: The following steps are involved: (1) extracting epiphyseal growth plate cartilage tissue samples from wild-type mice, heterozygous chondrodysplasia mice, and homozygous chondrodysplasia mice at the same time and preparing them into single cell suspensions; (2) Use a single-cell processing system to obtain mRNA from a single cell, synthesize and fragment cDNA, connect it to a sequencing adapter for read sequencing, and construct an scRNA-seq library; (3) Data analysis of the scRNA-seq library: using the CeleScope v1.9.0 pipeline to process the raw reads of scRNA-seq and generate a gene expression matrix file; performing cell screening, filtering and quality control on the gene expression matrix file, and then performing cell clustering and dimensionality reduction, identifying genes with significant differential expression between clusters, and dividing the cells into six clusters; determining the cell type identity of each cluster based on the expression of typical markers; performing secondary clustering after chondrocyte cluster extraction, analyzing differentially expressed genes and cell annotation, and identifying four chondrocyte subpopulations that are closely related to the stages of cartilage stem progenitor cell differentiation; performing pseudo-time series analysis on chondrocyte subpopulations, and comparing the changes in the number of cells in each chondrocyte subpopulation and the developmental trajectory of stem progenitor cells between chondrodysplastic mice and wild-type mice, revealing the pathological changes of cartilage stem progenitor cells in the context of chondrodysplasia.
2. The identification method according to claim 1, characterized in that In step (2), use Singleron The single cell processing system loads a single cell suspension containing PBS into a microwell chip, and then collects the barcode beads from the microwell chip, that is, obtains the mRNA captured by the barcode beads.
3. The identification method according to claim 1, characterized in that: In step (3), the criteria for cell screening, filtration and quality control are as follows: cells with less than 200 genes or more than 5000 genes are excluded; cells with a mitochondrial content greater than 10% are excluded; Genes expressed in less than three cells were excluded.
4. The identification method according to claim 1, characterized in that: The four chondrocyte subpopulations are stem cells (SCs), prehypertrophic chondrocytes (Pre-HCs), hypertrophic chondrocytes (HCs) and Sox4+ chondrocytes (Sox4+Cs).
5. Use of the method for identifying a subpopulation of epiphyseal growth plate cartilage stem progenitor cells affected by FGFR3 mutations according to any one of claims 1 to 4 in determining therapeutic targets for FGFR3-related osteochondrodysplasia diseases.
6. Use of the method for identifying a subpopulation of epiphyseal growth plate cartilage stem progenitor cells affected by FGFR3 mutations according to any one of claims 1 to 4 in guiding the preparation of a drug for treating FGFR3-related osteochondrodysplasia.