Identification of Key Candidate Genes Related to Cartilage development during Murine embryonic limb development by single cell RNA-sequencing and Experimental Confirmation

Identification of Key Candidate Genes Related to Cartilage development during Murine embryonic limb development by single cell RNA-sequencing and Experimental Confirmation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Identification of Key Candidate Genes Related to Cartilage development during Murine embryonic limb development by single cell RNA-sequencing and Experimental Confirmation Fei Xiong, Wenxuan Chen, Jiyang Tan, Xunhao Wang, Yang Qiu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4241968/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract Background Cartilage, characterized by its limited self-repair capacity due to avascularity and low metabolic activity of chondrocytes, poses a significant challenge for regenerative medicine. Osteoarthritis (OA), a prevalent cartilage disorder, highlights the urgent need for effective cartilage regenerative therapies. Understanding the molecular mechanisms underlying cartilage development during embryonic stages is crucial for advancing regenerative strategies and identifying potential therapeutic targets. Methods This study employed single-cell RNA sequencing (scRNA-seq) to explore the transcriptional landscape of mouse embryonic limb development at various stages, focusing on identifying genes pivotal for cartilage differentiation. Differentially expressed genes (DEGs) specific to cartilage development were pinpointed through comparative analysis. Functional validation of these marker genes was conducted using immunohistochemistry and RT-qPCR to confirm their roles in chondrocyte maturation and differentiation. Results Our scRNA-seq analysis identified a set of novel marker genes, including Bgn, Ucma, Fmod, Msmp, and 1500015O10Rik, as specific indicators of cartilage development. Functional experiments supported the crucial roles of these markers in the differentiation and maturation of chondrocytes. Additionally, our findings revealed the dynamic transcriptomic alterations during cartilage development, emphasizing the significance of specific regulatory factors in guiding mesenchymal stem cells towards chondrogenesis. Conclusions The study elucidates the complex transcriptomic landscape governing cartilage development in embryonic mice, highlighting the discovery of novel marker genes crucial for chondrocyte differentiation. These insights into the molecular mechanisms of cartilage formation lay the groundwork for developing targeted regenerative therapies for OA and related musculoskeletal disorders. Our research underscores the importance of identifying reliable regulatory factors that enhance the effectiveness of regenerative treatments, providing a valuable reference for future studies on cartilage repair and regeneration. single cell RNA-sequencing osteoarthritis cartilage development small leucine-rich proteoglycans mesenchymal stem cells Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Osteoarthritis (OA) is a debilitating condition characterized by the relentless degeneration of articular cartilage, imposing significant socio-economic burdens worldwide[ 1 ]. Articular cartilage, distinguished by its load-bearing and wear-resistant qualities, suffers from an inherent limitation in self-repair due to its avascular, aneural nature and alymphatic characteristics. Although autologous cartilage transplantation has emerged as a promising intervention, its applicability is hampered by the scarcity of transplantable chondrogenic tissue and the deleterious effects of extensive harvesting on donor sites[ 2 ]. This predicament underscores the urgent need for innovative cartilage regenerative therapies, propelling the field of tissue engineering towards the development of functional substitutes capable of replicating the complex biomechanical and biochemical environment of native cartilage. The evolution of tissue engineering over the last two decades has heralded the advent of living, functional constructs aimed at repairing or replacing damaged tissues. Initially, articular cartilage, with its comparatively simple structure and cellular composition, was deemed an ideal candidate for early tissue engineering endeavors. However, challenges such as the low metabolic activity of chondrocytes and the technical difficulties in replicating the cartilage's mechanical integrity have stymied progress[ 3 ]. Modern cartilage tissue engineering strategies focus on the triad of signaling stimuli, scaffolding materials, and cellular components, with a particular emphasis on the orchestration of chondrogenic differentiation and extracellular matrix synthesis through strategic manipulation of signaling pathways[ 4 ]. Yet, the complex roles of signaling molecules in chondrogenesis and hypertrophy, alongside the complexity of maintaining differentiated chondrocytes in a stable phenotypic state, remain formidable obstacles[ 5 ]. The embryonic development of cartilage, governed by tightly regulated genetic and molecular pathways, is crucial for understanding the mechanisms of cartilage formation and differentiation and identifying therapeutic targets for regeneration[ 6 ]. Recent advancements in single-cell mRNA sequencing (scRNA-seq) have unraveled the transcriptional intricacies of developmental processes, revealing cellular lineage trajectories and differentiation pathways in unprecedented detail[ 7 ]. In particular, Kelly et al. [ 8 ] used scRNA sequencing (GSE142425) to analyze gene expression during mouse limb development, with a focus on the trajectories of cellular lineage specification into joint tissues. However, while their study revealed significant cell type heterogeneity and identified distinct cell clusters representing known hindlimb cell types (including cartilage and bone), the differential gene expression patterns during cartilage development remained unclear. Therefore, identifying the precise gene expression signatures that differentiate cartilage from other skeletal tissues still remains an unresolved challenge. In response to these challenges and gaps in knowledge, our study leverages state-of-the-art scRNA-seq datasets, alongside rigorous in vitro and in vivo validation techniques, to explore the transcriptional divergence between cartilage and bone during key stages of mesenchymal progenitor differentiation. By pinpointing differentially expressed genes (DEGs) unique to cartilage, this research aims to illuminate the molecular framework underpinning cartilage formation and stability. Our investigation seeks not only to enrich our understanding of genomic and cellular mechanisms at the heart of cartilage development but also to lay the groundwork for innovative regenerative strategies. These strategies hold the potential to revolutionize the therapeutic landscape for osteoarthritis and related musculoskeletal disorders, addressing the critical need for effective cartilage regenerative therapies and advancing the field of tissue engineering towards the development of functional substitutes capable of emulating the complex biomechanical and biochemical environment of native cartilage. Methods Animals All animal procedures were approved by the WuXi 9th people's hospital (WuXi orthopaedics hospital ) Medical Ethical Committee. Wild-type animals used for hematoxylin-eosin staining, immunohistochemistry and RT-qPCR were two mice at gestational ages of 13.5 days and 18.5 days, respectively. Embryonic mice (8/litter) were removed by caesarean section from each pregnant mouse and euthanized. Before the experiment, the mice were maintained in a standard cages under a standard 12 h light/dark cycle with ad libitum access to food and water. Single-cell transcriptome analysis We downloaded the raw gene expression matrix of single–cell transcriptomes of the embryonic mouse hindlimb from the previous research (GSE142425) [ 8 ]. Firstly, we filtered the raw matrix and only retained the data of embryonic day 13.5 (E13.5) and E18.5 mouse embryos. Secondly, we utilized the R package Harmony [ 9 ] to merge the raw matrix from different developmental stages and removed the batch effects. Then, we utilized the R package Seurat [ 10 , 11 ] to process the merged dataset and perform quality control, log-normalization, dimensionality reduction, clustering and data visualization. For clustering, we utilized the top 20 principal components (PCs) to construct the unsupervised shared nearest neighbor clustering (SNN) graph, then we performed the improved graphbased clustering of the merged dataset by using louvain algorithm. The resolution parameter was set to 0.5. After clustering, the marker genes of each cell cluster were identified by using the R package COSG [ 12 ]. Cell clusters were annotated by the representative marker genes related to specific cell type. We exhibited the expression profiles of marker genes in different cell clusters (Fig. 2 C), thus the cell clusters with the specific expression of marker genes were annotated as the corresponding cell types. Specifically, cartilage ( Col2a1 ), bone ( Col1a1 ), skin ( Krt14 ), vasculature ( Cdh5 ) and blood ( Lyz2 ). Furthermore, the function ‘FindMarkers’ of the R package Seurat [ 10 , 11 ] was used to perform differential expression analysis of cells from different development stage in cartilage cells and bone cells. The DEGs were identified by the non-parametric Wilcoxon rank sum test, and the DEGs with the absolute values of the avg_log2FC greater than 2 and the p values adjusted by Benjamini-Hochberg less than 0.05 were considered to be significant (Tables 1 – 2 ). Table 1 The differentially expressed genes of mouse cartilage cells during development. Gene name avg_log2FC Adjusted p value Bgn -3.326417163 4.36E-148 Sparc -2.281090211 2.08E-124 Igfbp7 -2.575572357 2.69E-120 1500015O10Rik -2.54227103 6.87E-111 Dcn -2.808228981 2.90E-99 Ucma -4.198947745 1.82E-93 Fmod -2.688870875 7.41E-92 Hspa1a -3.964279352 1.17E-78 Col3a1 -2.175328212 1.26E-78 Col1a2 -2.441658937 5.36E-54 Msmp -3.630117175 2.58E-41 Col1a1 -3.132088181 7.54E-24 Table 2 The differentially expressed genes of mouse bone cells during development. Gene name avg_log2FC Adjusted p value Mdk 2.742212598 3.15E-183 Crip1 -3.622412689 1.32E-166 Sparc -2.358670829 2.55E-157 Col6a3 -2.204858963 7.22E-146 S100a6 -2.979058867 5.09E-139 Ndufa4l2 -3.212720457 1.07E-129 Cav1 -2.478384864 2.27E-122 Nnat 2.077083816 2.17E-119 Ifitm3 -2.348380812 5.06E-110 Cd24a 2.055891556 5.43E-110 Col4a1 -2.6945452 1.96E-109 Cebpb -2.614045631 1.83E-100 Sparcl1 -2.243612707 5.23E-99 Col6a2 -2.098009023 4.00E-98 Hspa1a -2.443833761 7.42E-96 Col6a1 -2.149184319 1.76E-95 Igfbp7 -3.223926633 3.04E-94 Rgs5 -3.608071462 4.07E-90 Gm13889 -2.852748292 1.29E-88 Dlk1 -2.634323432 6.08E-88 Nfkbia -2.03853582 5.29E-87 Col4a2 -2.022005123 2.76E-85 Cxcl1 -3.282083204 1.52E-78 Gng11 -2.288280896 2.59E-78 Mt1 -2.142230895 2.43E-77 Col3a1 -2.828789647 6.64E-73 Acta2 -3.852581603 7.07E-72 Tpm2 -2.142783849 2.61E-60 Ccl2 -2.729312764 2.28E-59 Cox4i2 -2.24746182 7.32E-56 Dcn -2.397021173 8.09E-48 Myl9 -2.407532919 5.98E-28 Col1a2 -2.06596405 8.54E-27 Tagln -2.451061583 1.03E-23 Lum -2.052885146 6.61E-21 Col1a1 -2.615008609 4.09E-20 Moreover, the protein-protein interaction networks (PPI) analysis of DEGs in cartilage cells were performed by the STRING APP of cytoscape software [ 13 ]. Functional enrichment analysis The Gene Ontology (GO) enrichment analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed by the R package clusterProfiler [ 14 ], the p values for enrichment were adjusted by the Benjamini-Hochberg method. Hematoxylin-eosin (HE) staining The mouse embryos were fixed in 10% paraformaldehyde for more than 24 hours. After fixation, the embryos were routinely embedded in paraffin, then cut into 4µm sections. The sections were dried, deparaffinized, rehydrated, and stained with hematoxylin-eosin for observation of the joint cartilage in mouse hindlimb. Specifically, for deparaffinization and rehydration, the sections were treated in xylene I for 20 minutes, xylene II for 20 minutes, absolute ethanol for 10 minutes, 90% ethanol for 3 minutes, 80% ethanol for 3 minutes, and 70% ethanol for 3 minutes. Subsequently, the sections were stained with safranin, immersed in safranin staining solution for 3 minutes, rinsed in water to remove excess stain, differentiated in 1% hydrochloric acid ethanol for 2 seconds until tissues turned red, washed three times in water to remove hydrochloric acid ethanol, and then soaked in water for 15 minutes. Then, the sections were treated in 75% ethanol for 2–3 seconds, 95% ethanol for 2–3 seconds for dehydration. Next, the sections were stained with eosin, immersed in eosin staining solution for 3 minutes, rinsed in water to remove excess eosin, dehydrated in 100% ethanol for 2–3 seconds. Finally, the sections were sealed with neutral resin. The images were taken by the Leica, DMi8. Immunohistochemistry The mouse embryos were fixed in 10% paraformaldehyde for more than 24 hours, then routinely embedded in paraffin. After that, the embryos were sectioned into 4µm sections, deparaffinized and rehydrated after drying the sections, followed by immunohistochemistry, mainly focusing on the cartilage of the mouse hindlimb. Specifically, for deparaffinization and rehydration of the sections, the sections were treated in xylene I for 20 minutes, xylene II for 20 minutes, anhydrous ethanol for 10 minutes, 90% ethanol for 3 minutes, 80% ethanol for 3 minutes, and 70% ethanol for 3 minutes. Subsequently, the sections were washed with PBS for three times, then fixed with EDTA antigen retrieval solution at 98°C for 20 minutes. Afterwards, the sections were washed with PBS for three times, and 3% hydrogen peroxide blocking agent was added dropwise to each section, left at room temperature for 20 minutes. Then, the sections were washed with PBS for three times, and each section was incubated overnight at 4°C in antibody diluted with 2% bovine serum. Then, the sections were washed with PBS for three times, and corresponding secondary antibodies diluted with 2% bovine serum were added dropwise to each section, then incubated at 37°C in the dark for 1 hour. Then, after washing with PBS for three times, DAB staining solution was added dropwise, stained in the dark at room temperature for 15 minutes. Then, the sections were washed with PBS for three times, stained with hematoxylin for 1 minute and 20 seconds, rinsed with tap water three times. Then, differentiation was done with 1% hydrochloric acid ethanol for 2–3 seconds, rinsed with tap water three times, and soaked for 15 minutes. Finally, after dehydration with an alcohol gradient, the sections were sealed. The images were taken by the Leica, DMi8. RT-qPCR analysis Firstly, after performing euthanasia for the mouse embryos, their hindlimb tissues were rapidly transferred to the − 80°C refrigerator for preservation. To extract the total RNA of mouse hindlimb, the hindlimb tissues were cut into appropriate sizes, thoroughly ground in liquid nitrogen, and then each 30-50mg of tissue was added to 1ml of Trizol reagent, well mixed, and incubated on ice for 10 minutes. Subsequently, the mixture was centrifuged at 4°C, 12000rpm for 5 minutes, and the supernatant was transferred to a new EP tube; 200µl of chloroform was added, vigorously shaken for 15 seconds, and incubated on ice for 5 minutes. Then, the mixture was centrifuged at 4°C, 12000rpm for 5 minutes, the upper aqueous phase was transferred to a new EP tube, an equal volume of isopropanol was added, gently inverted and mixed about 10 times, and left to stand at -20°C for 30 minutes. Subsequently, the mixture was centrifuged at 4°C, 12000rpm for 5 minutes, the supernatant was removed, and the RNA precipitate was washed twice with 85% ethanol. Then, the mixture was centrifuged at 4°C, 12000rpm for 5 minutes, the supernatant was removed, air-dried at room temperature for 5 minutes, and the RNA was dissolved in 20µl of DEPC water. Subsequently, the reverse transcription reaction was immediately carried out. Secondly, the reverse transcription reaction was performed by using Vazyme HiScriptIIQ RT SuperMix for qPCR reverse transcription kit, with the following program: incubated at 25°C for 5 minutes, 50°C for 15 minutes, heated at 85°C for 2 minutes, and stored at 4°C. Then the first strand cDNA was stored at -40°C. Tirdly, primer design. The primers used in RT-qPCR were designed using Primer Premier 5.0 software [ 15 ] and synthesized by Shanghai General Biology Company. The cDNA levels were normalized by the expression of GAPDH. Fourthly, the RT-qPCR reaction was performed by using the 2×Q3 SYBR qPCR Master mix (Universal) kit, with the reaction program settings shown in Table 3 . Table 3 The program settings of the RT-qPCR reaction. Temperature Time Cycle number 95℃ 2min 95℃ 10s 45cycles 60℃ 20s 45cycles 95℃ 15s 60℃ 1min 97℃ 40℃ 10s Finally, data processing. After PCR amplification, the real-time fluorescence quantitative PCR instrument automatically analyzed the results. The threshold and baseline were adjusted based on the negative control to determine the Ct value of each sample, and the validity of the Ct value was determined based on the melting curve. Then, the results were exported, and the 2-ΔΔCT method was used to analyze the expression differences of the target gene between the control group and various concentration groups. The calculation formula was as ΔCt = Ct target gene - Ct reference gene. Then, the average ΔCt of the control group was calculated and denoted as ΔCt control average. The ΔCt of each group was subtracted from ΔCt control to obtain the ΔΔCt value, which was ΔΔCt = ΔCt sample - ΔCt control average. The 2-ΔΔCT value of each group was then calculated, representing the relative expression level of the gene in each group. Statistical analysis For immunohistochemistry and RT-qPCR analysis, statistical differences were determined by the Unpaired t-test, and the p values < 0.05 were considered to indicate statistical significance. * p < 0.05, ** p < 0.01, *** p < 0.001. Results HE staining shows the morphological changes of the cartilage during the embryonic mouse hindlimb development Previous research have emphasized that the developmental period from E13.5 to E18.5 is critical for mouse cartilage development [ 8 ]. To further investigate the specific changes in tissue structure and cell morphology of cartilage during this developmental stage, we performed HE staining on the condylar cartilage and tibial growth plate cartilage of embryonic mouse at E13.5 and E18.5 (Fig. 1 A), respectively. The results showed that the condylar cartilage and tibial growth plate cartilage of mouse embryos at E13.5 and E18.5 both exhibited the basic morphology of cartilage (Fig. 1 B), however, there were certain differences in the morphology and structure of the condylar cartilage and tibial growth plate cartilage at different developmental stages (Fig. 1 B). Specifically, at E13.5, the condylar cartilage was formed by the aggregation of mesenchymal cells into cell clusters (Fig. 1 B), and the tibial growth plate cartilage of some embryos have started to develop (Fig. 1 B), especially, the differentiation of mesenchymal cells in tibial growth plate cartilage were later than that in condylar cartilage (Fig. 1 B). At E18.5, joint spaces appeared in the embryonic mouse tissues (Fig. 1 B), and there was no zone of cell condensation in the growth plate of the tibia (Fig. 1 B), meanwhile, cartilage cells were flat and arranged in a columnar manner along the long axis of the bone (Fig. 1 B). The condylar cartilage is an important growth area of the mandible, formed secondarily during individual development, which is defined as secondary cartilage; while tibial growth plate cartilage is the growth center of long bones, which is defined as primary cartilage. The different growth characteristics of these two types of cartilage drived them to play different important roles in joint functions. Our research results indicateed that from E13.5 to E18.5, the condylar cartilage and tibial growth plate cartilage of mouse embryos developed rapidly (Fig. 1 B), and the mesenchymal stem cells in them differentiated rapidly (Fig. 1 B), which provided a solid foundation for the normal function of cartilage. Therefore, it’s essential to explore the genetic mechanisms and the related regulatory factors that regulate the cartilage development in this stage. Comprehensive analysis of single-cell transcriptomes during cartilage development To examine the transcriptional landscape of mouse cartilage development, we utilized the single-cell transcriptomes of embryonic mouse hindlimb from previously published research [ 8 ] and performed integrated analyses based on the data from two developmental points, E13.5 and E18.5. After merging single-cell transcriptomes from two developmental stages, the cluster analysis totally yielded 16 distinct clusters (Fig. 2 A). Notably, some cell clusters showed high transcriptional similarities, indicating that they were all subgroups originated from the same cell type (Fig. 2 B). To accurately annotate these cell clusters, we utilized typical marker genes and identified 5 cell types representing cartilage ( Col2a1 ), bone ( Col1a1 ), skin ( Krt14 ), vasculature ( Cdh5 ) and blood ( Lyz2 ) (Fig. 2 C- 2 D). To further explore the transcriptional changes in cartilage during mouse hindlimb development, we performed differential expression analysis on cartilage cells between E13.5 and E18.5 (Fig. 3 A). The results indicated that some DEGs played important roles in cartilage development and function. For instance, gene Ucma significantly highly expressed in cartilage cells at E18.5 than that at E13.5 (Fig. 3 A); this gene encodes a chondrocyte-specific, highly charged protein that is abundantly expressed in the upper immature zone of fetal and juvenile epiphyseal cartilage, especially, undercarboxylation of the encoded protein is associated with osteoarthritis in humans [ 16 ]. Gene Fmod also showed significant increased expression in cartilage cells at E18.5 than that at E13.5 (Fig. 3 A), the encoded protein of gene Fmod may regulate TGF-beta activities by sequestering TGF-beta into the extracellular matrix, and the previous research suggested that TGF-beta plays a key role in the development, formation, and repair of articular cartilage [ 17 ]. Then we performed GO enrichment analysis and KEGG enrichment analysis on the DEGs of cartilage cells (Fig. 3 B- 3 C). The most significant enriched GO terms were “skeletal system development”, “cartilage development”, “extracellular matrix” and “structural molecule activity” (Fig. 3 B), indicating that our differential analysis results actually reflected the genetic drivers of mouse cartilage development. Furthermore, the enrichment results also suggested that these DEGs were involved in influencing cartilage development through the pathways of “protein digestion and absorption”, “extracellular matrix (ECM) − receptor interaction”, “focal adhesion” and “PI3K − Akt signaling pathway” (Fig. 3 C). Candidate regulatory factors for cartilage development defined by comparative analysis and PPI Above studies have identified the DEGs that were significantly related to cartilage development and function. However, we are more interested in the genetic factors that specifically regulate cartilage development, which not simultaneously regulated the bone development. Therefore, we utilized the above single-cell transcriptomes to performed differential expression analysis on bone cells between E13.5 and E18.5. Then we performed comparative analysis to identify the specific regulatory factors for cartilage development. Firstly, whether in cartilage cells or in bone cells, we only kept the DEGs with the absolute values of the avg_log2FC were greater than 2 and the adjusted p values were less than 0.05 (Tables 1 – 2 ) as candidate DEGs. Then, we removed the overlapping candidate DEGs between cartilage cells and bone cells from the candidate DEGs of cartilage cells. Finally, the remaining genes were defined as the potential markers of cartilage development, including genes Bgn , Ucma , Fmod , Msmp and 1500015O10Rik . In addition, the genes Bgn and Fmod that we mentioned in the above encodes a member of the small leucine-rich proteoglycans (SLRPs) family of proteins, the encoded preproprotein is proteolytically processed to generate the mature protein, which plays a role in bone growth, muscle development and regeneration, and collagen fibril assembly in multiple tissues, espically, this protein may also regulate inflammation and innate immunity [ 18 ]. Notably, there was no study suggested that genes Msmp and 1500015O10Rik played roles in bone or cartilage development, indicating that these genes may be novel markers for cartilage development, which were worthy of the further research. To further investigate the regulatory relationships between DEGs of cartilage cells and define the regulatory networks for cartilage development, we applied the PPI for all DEGs of cartilage cells and the potential marker genes for cartilage development, respectively. The results showed that DEGs of cartilage cells between E13.5 and E18.5 significantly interacted with each other (Fig. 4 A), indicating that these DEGs promoted the normal development of cartilage through synergistic actions. Furthermore, we identified the regulatory network of the potential marker genes for cartilage development (Fig. 4 B), which was likely to be the core regulatory network during development. RT-qPCR analyses were conducted on the candidate regulatory factors involved in cartilage development in embryonic mouse at E13.5 and E18.5 The results of differential expression analysis and PPI analysis indicated the candidate marker genes for cartilage development, we verified their expression in further detail by RT-qPCR analysis. Consistent with the results of the differential expression analysis, the expression levels of genes Dcn , Bgn , Fmod , Msmp , Ucma , Col2α1 , Sox9 and Acan were indeed highly elevated in cartilage of E18.5 mouse hindlimb compared with the cartilage of E13.5 mouse hindlimb (Fig. 5 A- 5 H). For the gene Bgn , the results of the RT-qPCR analysis were somewhat different from that of the differential expression analysis. Although the differential expression analysis indicated marked increase in the expression of gene Bgn in cartilage of embryonic mouse from E13.5 to E18.5 (Table 1 ), the RT-qPCR analysis revealed that the increase was modest (Fig. 5 B). Moreover, the expressional patterns of genes Acan and Sox9 differed considerably between the results of the RT-qPCR analysis and the differential expression analysis. Based on the differential expression analysis, their expression did not change markedly during development. In contrast, the RT-qPCR analysis revealed that the expression of genes Acan and Sox9 obviously increased from E13.5 to E18.5 (Fig. 5 G- 5 H), this result also corresponded to previous research that suggested genes Acan and Sox9 were essential for cartilage development [ 19 ]. Furthermore, the RT-qPCR analysis also indicated that the candidate marker genes (including genes Bgn , Ucma , Fmod and Msmp ) that we identified showed significantly increased expression during mouse cartilage development (Fig. 5 B- 5 E). Immunohistochemistry was performed on the candidate regulatory factors involved in cartilage development in embryonic mouse at E13.5 and E18.5 Since the results obtained through the bioinformatics analysis may have false positives, the experimental validation to be essential. To explore the candidate DEGs we identified could truly serve as marker genes for cartilage development, we selected three genes (including Col2α1 , Ucma and Bgn ) for immunohistochemical verification. As we mentioned above, the DEGs Ucma and Bgn showed specifically significantly increased expression during the cartilage development. And the DEG Col2α1 was a well known marker gene for cartilage development, this gene encodes the alpha-1 chain of type II collagen, a fibrillar collagen found in cartilage [ 20 , 21 ], thus the immunohistochemical result of this gene could be a useful control. The results of immunohistochemistry of genes Col2α1 , Ucma and Bgn in embryonic mouse at E13.5 and E18.5 showed that the expression levels of the antibodies Col2α1, Ucma, and Bgn in the cartilage of the embryonic mouse hindlimb significantly increased during the development (Fig. 6 A- 6 B), indicating that these three genes could serve as the markers for cartilage development. Discussion Cartilage is a specialized tissue that provides mechanical support and contributes to joint function. The research of cartilage development and its disorders is crucial for understanding the etiology of various diseases, including osteoarthritis and chondrodysplasia [ 22 ]. Particularly, exploring the specific signaling molecules or regulatory factors for chondrogenic could provide important reference for the mesenchymal stem cells (MSC)-based therapy for cartilage regeneration [ 23 ]. For the past few years, single-cell transcriptomic analysis has emerged as a powerful tool for identifying key regulators and markers of cartilage development [ 8 , 24 ]. Our investigation into the dynamic processes of cartilage development and differentiation during critical embryonic stages in mice has provided a deeper understanding of the morphological changes, genetic underpinnings, and the identification of pivotal genetic regulators. Through the integration of hematoxylin-eosin staining, scRNA sequencing, RT-qPCR, and immunohistochemistry, we have uncovered significant gene expression differences that drive the development of cartilage, reflecting both the intrinsic developmental program and its biomechanical adaptation needs. These findings provide an important basis for further exploring the regulatory networks of cartilage development, which will hopefully serve to promote the research of cartilage regeneration and the prevention of osteoarthritis or other diseases. From E13.5 to E18.5, the condylar cartilage and tibial growth plate cartilage of embryonic mouse experienced rapid development, meanwhile, exhibited certain differences in the stratification, morphology and arrangement of chondrocytes[ 8 ]. The chondrocytes were derived from the mesenchymal cells. Interestingly, the differentiation of mesenchymal cells in tibial growth plate cartilage were later than that in condylar cartilage, at E13.5, the condylar cartilage of embryonic mouse was a cluster of mesenchymal cells, while the tibial growth plate cartilage of some embryos had not started to develop. This phenomenon suggested that the development of condylar cartilage may be regulated by the specific growth factors, previous research have indicated that the growth factor TGF-β and the transcription factor Sox9 both played key roles in the development, formation and repair of cartilage[ 25 , 26 ], thus the differences in the expression of these regulatory factors during early development may induce earlier differentiation of mesenchymal cells in condylar cartilage. However, the earlier development of condylar cartilage may also be influenced by other regulatory factors that newly identified by our research, which will be discussed in detail below. Mesenchymal stem cells originate from the mesoderm and ectoderm in the early stage of development, they are mature stem cells with self-replicating ability and multidirection differentiation potential [ 27 ]. Under specific induction conditions, mesenchymal stem cells could differentiate into adipose cells, cartilage cells, bone cells or other tissue cells [ 27 ]. Therefore, mesenchymal stem cell therapy is considered as a viable strategy for the treatment of cartilage injury[ 28 , 29 ], however, further investigation highlights the critical importance of precise regulation during the maturation and hypertrophy of chondrocytes. Chondrocyte hypertrophy is a pivotal phase in cartilage development; however, in therapeutic contexts aiming for cartilage repair, it is crucial to induce chondrogenesis without proceeding to unwanted bone formation[ 30 – 32 ]. Our research provided a valuable reference for solving this problem, utilizing scRNA-seq to identify genes that are highly expressed specifically during the chondrogenesis stage but do not show significant changes in expression during the subsequent hypertrophy phase. These genes, being differentially expressed at crucial stages of cartilage formation, suggest that their regulation could potentially allow for the growth of cartilage tissue while absent further hypertrophy and endochondral bone formation. This involves the application of specific biological factors at defined times, targeting these genes to guide MSCs towards chondrocyte differentiation and maturation without crossing the threshold into hypertrophy. Such insights could lead to more effective strategies in regenerative medicine, particularly for cartilage repair, by harnessing the potential of MSCs for precise tissue engineering. By removing the DEGs in chondrocyte clusters that also showed significantly increased expression during bone development, we further identified 5 genes Bgn , Ucma , Fmod , Msmp and 1500015O10Rik as the specific markers for cartilage development. Previous studies have confirmed that genes Bgn , Ucma , and Fmod could be involved in the regulation of cartilage development [ 16 – 18 ], however, no studies have deeply explored the roles of these genes in cartilage repair and cartilage regeneration, and the related functional mouse models were rarely studied. Interestingly, Bgn and Fmod , as members of the SLRPs family, play critical roles in the pathogenesis of OA[ 33 , 34 ]. These proteins interact with collagens to modulate fibril formation and bind to various cell surface receptors, growth factors, and other ECM components, thereby influencing cellular functions crucial for maintaining joint integrity. The disruption of these interactions, as observed in SLRP-deficient mouse models, leads to altered collagen networks, changes in chondrocyte proliferation and differentiation, and modifications in ECM turnover, which contribute to the development and progression of OA. Additionally, SLRPs are implicated in mechanisms beyond the cartilage itself, such as influencing subchondral bone structure and muscle weakness, further complicating the OA pathogenic landscape. Therefore, Bgn and Fmod , through their extensive involvement in regulating ECM structure and cellular signaling within the joint, underscore the complexity of OA pathogenesis, highlighting the interplay between genetic, molecular, and biomechanical factors in the disease's onset and progression. This comparative analysis has allowed us to identify potential markers specific to cartilage development, opening new avenues for understanding the complexity of cartilage formation and the distinct molecular pathways that govern it. The validation of these candidate regulatory factors through RT-qPCR and immunohistochemistry has confirmed their roles in cartilage development, reinforcing their potential as markers for cartilage development and as targets for therapeutic intervention. Otherwise, among these genes, we found several novel regulators, including Msmp and 1500015O10Rik , which were previously unknown to be involved in the cartilage development. Specifically, gene Msmp encodes a member of the beta-microseminoprotein family, the encoded protein may play a role in prostate cancer tumorigenesis [ 35 ]. The gene 1500015O10Rik is synonymous with gene Ecrg4 , previous research have suggested that gene Ecrg4 is a marker of articular chondrocyte differentiation and cartilage destruction [ 36 ]. And these genes were enriched in the pathways of “protein digestion and absorption”, “ECM − receptor interaction” and “focal adhesion”, which mainly affected the development of extracellular matrix. As an important part of the articular cartilage, extracellular matrix could maintain the living environment of chondrocytes and exchange signals with the outside of the chondrocytes. The homeostasis of extracellular matrix maintains the normal function of chondrocytes, and the loss of extracellular matrix could lead to diseases such as osteoarthritis and deformation of joint structure [ 37 ]. Thus these genes whose expression increased significantly during cartilage development could also serve as the key regulators for extracellular matrix remodeling, and these newly identified regulatory factors are whorthy of further research. Our study has identified key genes and pathways implicated in the developmental process of cartilage formation in embryonic mice, offering insights that could potentially guide future regenerative therapies. However, we acknowledge several limitations inherent to our experimental design and methodology that merit consideration. Firstly, our investigation employs a single species focus, relying exclusively on embryonic mouse models. While mice are widely used in biomedical research due to their genetic congruence with humans and their expedited developmental timelines, it is imperative to note that findings derived from mouse models may not invariably mirror human biological processes due to interspecies differences. This limitation underscores the necessity for cautious interpretation of our results within the broader context of human biology. Additionally, our analysis is constrained by a developmental stage limitation, focusing on cartilage development at two specific embryonic stages (E13.5 and E18.5). Although these stages are pivotal for understanding cartilage formation in mice, our study may overlook critical stages or transitions that could provide deeper insights into the regulatory mechanisms of differentiation. Future studies should consider a broader range of developmental stages to capture the full spectrum of cartilage development. Our research also confronts a limitation in the number of identified regulatory factors. Although we have successfully pinpointed five genes as specific markers for cartilage development, the intricate nature of cartilage formation suggests the involvement of a more extensive array of genes and regulatory factors. The genes identified herein serve as an important foundation, yet they represent only a segment of the vast regulatory network governing cartilage development. Concerning experimental validation, we employed hematoxylin-eosin staining, immunohistochemistry, and RT-qPCR. While these techniques are instrumental for our analysis, they come with limitations regarding quantification accuracy, sensitivity, and the potential omission of less abundant or transiently expressed regulatory factors. Exploring additional validation methods could enhance the robustness of our findings. In terms of functional analysis, our study incorporates functional enrichment analysis to elucidate the roles of differentially expressed genes. However, we did not conduct direct functional assays to validate the specific contributions of these genes to cartilage development and regeneration. Such empirical validation is crucial for confirming the biological significance of the identified genes and should be addressed in future work. Our investigation also highlights a gap in elucidating regulatory mechanisms, identifying key genes and pathways without delving into the precise regulatory dynamics. A comprehensive understanding of how these genes interact within the cellular environment to guide cartilage development is essential and warrants further study. Lastly, regarding the translation to therapeutics, our findings lay a foundational basis for informing future regenerative therapies. Nevertheless, translating this knowledge into viable treatments for human cartilage-related ailments demands extensive follow-up research, particularly focusing on safety, dosage, delivery mechanisms, and long-term efficacy. Conclusions In summary, our research identified reliable markers and regulators that were specific to mouse cartilage development, and a large number of functional experiments supported our findings. By uncovering the distinct molecular signatures associated with cartilage formation and differentiation, our comprehensive analysis not only enhances our genomic comprehension at the cellular level but also lays the foundation for novel cartilage regenerative strategies. These strategies hold the promise to revolutionize the therapeutic landscape for osteoarthritis and related musculoskeletal disorders, addressing the critical need for effective cartilage regenerative therapies and advancing the field towards the development of functional substitutes capable of emulating the complex biomechanical and biochemical environment of native cartilage. Future studies focusing on the functional characterization of the novel markers identified here are eagerly anticipated, poised to provide further insights into the molecular mechanisms of cartilage development and their implications for disease treatment and prevention. Declarations Clinical Trial Number Not applicable. The raw gene expression matrix of single–cell transcriptomes of the embryonic mouse hindlimb from the previous research (GSE142425). Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials We downloaded the raw gene expression matrix of single–cell transcriptomes of the embryonic mouse hindlimb from the previous research (GSE142425). This study employed single-cell RNA sequencing (scRNA-seq) to explore the transcriptional landscape of mouse embryonic limb development at various stages, focusing on identifying genes pivotal for cartilage differentiation. Competing interests All authors state that they have no competing interests conflicts of interest with this work. Funding This research was funded by Top Talent Support Program for young and middle-aged people of Wuxi Health Committee (2023, grant number: HB2023127) Scientific and technological breakthrough Project of "Light of the Taihu Lake Lake" (2023, Basic research, grant number: K20231064), and Duo-Innovative and Excellent Doctors Project of Wuxi 9th People’s Hospital (2021, grant number: YB202108). Authors' contributions Study design: FX. Study conduct: FX and WXC. Data collection: FX and JYT. Data analysis: FX, XHW and WXC. Data interpretation: FX, JYT and WXC. Drafting manuscript: FX and XHW. Revising manuscript content: YQ. Approving final version of manuscript: all authors. FX takes responsibility for the integrity of the data analysis. Acknowledgements Not applicable. References Szponder T, Latalski M, Danielewicz A, Krac K, Kozera A, Drzewiecka B, Nguyen Ngoc D, Dobko D, Wessely-Szponder J. Osteoarthritis: Pathogenesis, Animal Models, and New Regenerative Therapies. J Clin Med 2022, 12(1). Shim DW, Lee KM, Lee D, Kim JS, Jung YS, Oh SS, Lee SW, Lee JW, Kim BS. Osteochondral Repair with Autologous Cartilage Transplantation with or without Bone Grafting: A Short Pilot Study in Mini-Pigs. Cartilage 2023:19476035231199442. Uzieliene I, Bironaite D, Bagdonas E, Pachaleva J, Sobolev A, Tsai WB, Kvederas G, Bernotiene E. 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Human Umbilical Cord Mesenchymal Stem Cell-Derived Extracellular Vesicles Carrying MicroRNA-181c-5p Promote BMP2-Induced Repair of Cartilage Injury through Inhibition of SMAD7 Expression. Stem Cells Int 2022, 2022:1157498. Chawla S, Mainardi A, Majumder N, Donges L, Kumar B, Occhetta P, Martin I, Egloff C, Ghosh S, Bandyopadhyay A et al. Chondrocyte Hypertrophy in Osteoarthritis: Mechanistic Studies and Models for the Identification of New Therapeutic Strategies. Cells 2022, 11(24). Thielen NGM, Neefjes M, Vitters EL, van Beuningen HM, Blom AB, Koenders MI, van Lent P, van de Loo FAJ, Blaney Davidson EN, van Caam APM et al. Identification of Transcription Factors Responsible for a Transforming Growth Factor-beta-Driven Hypertrophy-like Phenotype in Human Osteoarthritic Chondrocytes. Cells 2022, 11(7). Yoon DS, Kim EJ, Cho S, Jung S, Lee KM, Park KH, Lee JW, Kim SH. RUNX2 stabilization by long non-coding RNAs contributes to hypertrophic changes in human chondrocytes. Int J Biol Sci. 2023;19(1):13–33. Zhao F, Bai Y, Xiang X, Pang X. The role of fibromodulin in inflammatory responses and diseases associated with inflammation. Front Immunol. 2023;14:1191787. Ni GX, Li Z, Zhou YZ. The role of small leucine-rich proteoglycans in osteoarthritis pathogenesis. Osteoarthritis Cartilage. 2014;22(7):896–903. Mitamura T, Pradeep S, McGuire M, Wu SY, Ma S, Hatakeyama H, Lyons YA, Hisamatsu T, Noh K, Villar-Prados A, et al. Induction of anti-VEGF therapy resistance by upregulated expression of microseminoprotein (MSMP). Oncogene. 2018;37(6):722–31. Huh YH, Ryu JH, Shin S, Lee DU, Yang S, Oh KS, Chun CH, Choi JK, Song WK, Chun JS. Esophageal cancer related gene 4 (ECRG4) is a marker of articular chondrocyte differentiation and cartilage destruction. Gene. 2009;448(1):7–15. Shi Y, Hu X, Cheng J, Zhang X, Zhao F, Shi W, Ren B, Yu H, Yang P, Li Z, et al. A small molecule promotes cartilage extracellular matrix generation and inhibits osteoarthritis development. Nat Commun. 2019;10(1):1914. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editor assigned by journal 12 Apr, 2024 Submission checks completed at journal 11 Apr, 2024 First submitted to journal 09 Apr, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4241968","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":290404421,"identity":"3c931daa-5026-4990-8ebf-7b169b799122","order_by":0,"name":"Fei Xiong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYDACZhBhw8DDxt588DFEhLmBCC1pDDx8PMeSjRkYDIAijAS0MEC0MMhJ5JhJg7UwENBicJz52MMvCTYybDzH0qoLKv5E87cDtfyo2IZTi2QzW7qxTEIayC/Hbs84Y5A74zBjA2PPmds4tfAz85hJS/44zAOy5TZvm0FuA1ALM2Mbbi1sIC0SCf952IB+KQZpmU9IC8gWyQ8JB8BamEFaNhDSAvRLmjRDQjLIYcnSPGeMczcCtRzE5xeD84ePSf5IsLOXb28++JmnQi533vnDBx/8qMCtBQSYedBFDuBVDwSMPwipGAWjYBSMgpENAFSfT7Zq6dUPAAAAAElFTkSuQmCC","orcid":"","institution":"Wuxi 9th People’s Hospital Affiliated to Soochow University","correspondingAuthor":true,"prefix":"","firstName":"Fei","middleName":"","lastName":"Xiong","suffix":""},{"id":290404422,"identity":"4d48f6c0-1f02-4c74-9bae-3e304b25d772","order_by":1,"name":"Wenxuan Chen","email":"","orcid":"","institution":"Wuxi 9th People’s Hospital Affiliated to Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Wenxuan","middleName":"","lastName":"Chen","suffix":""},{"id":290404423,"identity":"6ead7dcd-c288-446a-b044-944a7515bd7a","order_by":2,"name":"Jiyang Tan","email":"","orcid":"","institution":"Wuxi 9th People’s Hospital Affiliated to Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Jiyang","middleName":"","lastName":"Tan","suffix":""},{"id":290404424,"identity":"1c0cf4f8-a2f9-41d5-b000-5859fa4ee3b6","order_by":3,"name":"Xunhao Wang","email":"","orcid":"","institution":"Wuxi 9th People’s Hospital Affiliated to Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Xunhao","middleName":"","lastName":"Wang","suffix":""},{"id":290404425,"identity":"90dfbac3-5647-4c34-90e3-3227b865f0f9","order_by":4,"name":"Yang Qiu","email":"","orcid":"","institution":"Wuxi 9th People’s Hospital Affiliated to Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Qiu","suffix":""}],"badges":[],"createdAt":"2024-04-09 12:43:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4241968/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4241968/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54771625,"identity":"9b50a115-51f9-4708-a4bd-74e096370700","added_by":"auto","created_at":"2024-04-16 14:26:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":859294,"visible":true,"origin":"","legend":"\u003cp\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Images of embryonic mouse at embryonic day 13.5 (left) and embryonic day 18.5 (right), respectively. (\u003cstrong\u003eB\u003c/strong\u003e) HE staining images of condylar cartilage and tibial growth plate cartilage of embryonic mouse at E13.5 and E18.5, respectively. The images were enlarged 50 and 200 times, respectively.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4241968/v1/83bbb08c7c5260c7e2d54240.png"},{"id":54771294,"identity":"b8970893-1519-4bdc-87c1-9ece6d36afcd","added_by":"auto","created_at":"2024-04-16 14:18:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":444275,"visible":true,"origin":"","legend":"\u003cp\u003eIntegrated analysis of the single-cell transcriptomes of the embryonic mouse hindlimbs. (\u003cstrong\u003eA\u003c/strong\u003e) UMAP plot of all cells from the embryonic mouse hindlimbs at E13.5 and E18.5, cells were colored by cell cluster. (\u003cstrong\u003eB\u003c/strong\u003e) Heatmap of top 10 marker genes of each cell cluster, with columns representing each cell cluster and rows representing identified marker genes. (\u003cstrong\u003eC\u003c/strong\u003e) Expression levels and locations of the representative gene markers. (\u003cstrong\u003eD\u003c/strong\u003e) UMAP plot of all cells from the embryonic mouse hindlimbs at E13.5 and E18.5, cells were colored by the specific cell type.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4241968/v1/7136e77d153ce8e07cf179f4.png"},{"id":54771296,"identity":"e48472cf-b1be-491e-a787-89ee192c50ed","added_by":"auto","created_at":"2024-04-16 14:18:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":443144,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential expression analysis of cartilage cells between E13.5 and E18.5. (\u003cstrong\u003eA\u003c/strong\u003e) Heatmap of differentially expressed genes of mouse cartilage cells between E13.5 and E18.5, with columns representing cells from two developmental stages and rows representing the differentially expressed genes. (\u003cstrong\u003eB\u003c/strong\u003e) Enriched GO terms of differentially expressed genes in the mouse cartilage cells. (\u003cstrong\u003eC\u003c/strong\u003e) Enriched KEGG pathways of differentially expressed genes in the mouse cartilage cells.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4241968/v1/f8ca3f7e86713d5012cb78fd.png"},{"id":54771623,"identity":"c1bdda0b-4c19-4d20-97e3-ef46833c949e","added_by":"auto","created_at":"2024-04-16 14:26:35","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":257735,"visible":true,"origin":"","legend":"\u003cp\u003eProtein-protein interaction networks of the differentially expressed genes of cartilage cells (\u003cstrong\u003eA\u003c/strong\u003e) and the candidate marker genes for cartilage development (\u003cstrong\u003eB\u003c/strong\u003e), respectively.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4241968/v1/31c6c420726c6041cfb4f57d.png"},{"id":54771292,"identity":"313304b3-64dd-43e4-b2c7-d2e689db534b","added_by":"auto","created_at":"2024-04-16 14:18:35","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":50765,"visible":true,"origin":"","legend":"\u003cp\u003eExpression levels of genes \u003cem\u003eDcn\u003c/em\u003e (\u003cstrong\u003eA\u003c/strong\u003e), \u003cem\u003eBgn \u003c/em\u003e(\u003cstrong\u003eB\u003c/strong\u003e), \u003cem\u003eFmod \u003c/em\u003e(\u003cstrong\u003eC\u003c/strong\u003e), \u003cem\u003eMsmp \u003c/em\u003e(\u003cstrong\u003eD\u003c/strong\u003e), \u003cem\u003eUcma \u003c/em\u003e(\u003cstrong\u003eE\u003c/strong\u003e), \u003cem\u003eCol2α1 \u003c/em\u003e(\u003cstrong\u003eF\u003c/strong\u003e), \u003cem\u003eSox9 \u003c/em\u003e(\u003cstrong\u003eG\u003c/strong\u003e) and \u003cem\u003eAcan \u003c/em\u003e(\u003cstrong\u003eH\u003c/strong\u003e) in embryonic mouse cartilage at E13.5 and E18.5, respectively. Bars represent the mean + SD. *, p \u0026lt; 0.05; **, p \u0026lt; 0.01; ***, p\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4241968/v1/f3892bfdc85693cc82f873ff.png"},{"id":54771624,"identity":"ed035deb-cea9-4a22-86b4-250d02ad0caa","added_by":"auto","created_at":"2024-04-16 14:26:35","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":875791,"visible":true,"origin":"","legend":"\u003cp\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Immunohistochemistry images of \u003cem\u003eCol2α1\u003c/em\u003e, \u003cem\u003eUcma\u003c/em\u003e and \u003cem\u003eBgn\u003c/em\u003e in embryonic mouse cartilage at E13.5 and E18.5, respectively. The images were enlarged 100 and 400 times, respectively. (\u003cstrong\u003eB\u003c/strong\u003e) Relative expression levels of genes \u003cem\u003eCol2α1\u003c/em\u003e, \u003cem\u003eUcma\u003c/em\u003e and \u003cem\u003eBgn \u003c/em\u003ein embryonic mouse cartilage at E13.5 and E18.5, respectively. Bars represent the mean + SD. *, p \u0026lt; 0.05; **, p \u0026lt; 0.01; ***, p\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-4241968/v1/cc8de179438b280768b59843.png"},{"id":54772192,"identity":"93a110cf-8bda-4c46-be37-45eee20b22af","added_by":"auto","created_at":"2024-04-16 14:34:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3245262,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4241968/v1/612ffce1-f2c3-4a27-8f0a-f9e7121d48ab.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Identification of Key Candidate Genes Related to Cartilage development during Murine embryonic limb development by single cell RNA-sequencing and Experimental Confirmation","fulltext":[{"header":"Background","content":"\u003cp\u003eOsteoarthritis (OA) is a debilitating condition characterized by the relentless degeneration of articular cartilage, imposing significant socio-economic burdens worldwide[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Articular cartilage, distinguished by its load-bearing and wear-resistant qualities, suffers from an inherent limitation in self-repair due to its avascular, aneural nature and alymphatic characteristics. Although autologous cartilage transplantation has emerged as a promising intervention, its applicability is hampered by the scarcity of transplantable chondrogenic tissue and the deleterious effects of extensive harvesting on donor sites[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This predicament underscores the urgent need for innovative cartilage regenerative therapies, propelling the field of tissue engineering towards the development of functional substitutes capable of replicating the complex biomechanical and biochemical environment of native cartilage.\u003c/p\u003e \u003cp\u003eThe evolution of tissue engineering over the last two decades has heralded the advent of living, functional constructs aimed at repairing or replacing damaged tissues. Initially, articular cartilage, with its comparatively simple structure and cellular composition, was deemed an ideal candidate for early tissue engineering endeavors. However, challenges such as the low metabolic activity of chondrocytes and the technical difficulties in replicating the cartilage's mechanical integrity have stymied progress[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Modern cartilage tissue engineering strategies focus on the triad of signaling stimuli, scaffolding materials, and cellular components, with a particular emphasis on the orchestration of chondrogenic differentiation and extracellular matrix synthesis through strategic manipulation of signaling pathways[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Yet, the complex roles of signaling molecules in chondrogenesis and hypertrophy, alongside the complexity of maintaining differentiated chondrocytes in a stable phenotypic state, remain formidable obstacles[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe embryonic development of cartilage, governed by tightly regulated genetic and molecular pathways, is crucial for understanding the mechanisms of cartilage formation and differentiation and identifying therapeutic targets for regeneration[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Recent advancements in single-cell mRNA sequencing (scRNA-seq) have unraveled the transcriptional intricacies of developmental processes, revealing cellular lineage trajectories and differentiation pathways in unprecedented detail[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In particular, Kelly et al. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] used scRNA sequencing (GSE142425) to analyze gene expression during mouse limb development, with a focus on the trajectories of cellular lineage specification into joint tissues. However, while their study revealed significant cell type heterogeneity and identified distinct cell clusters representing known hindlimb cell types (including cartilage and bone), the differential gene expression patterns during cartilage development remained unclear. Therefore, identifying the precise gene expression signatures that differentiate cartilage from other skeletal tissues still remains an unresolved challenge.\u003c/p\u003e \u003cp\u003eIn response to these challenges and gaps in knowledge, our study leverages state-of-the-art scRNA-seq datasets, alongside rigorous in vitro and in vivo validation techniques, to explore the transcriptional divergence between cartilage and bone during key stages of mesenchymal progenitor differentiation. By pinpointing differentially expressed genes (DEGs) unique to cartilage, this research aims to illuminate the molecular framework underpinning cartilage formation and stability. Our investigation seeks not only to enrich our understanding of genomic and cellular mechanisms at the heart of cartilage development but also to lay the groundwork for innovative regenerative strategies. These strategies hold the potential to revolutionize the therapeutic landscape for osteoarthritis and related musculoskeletal disorders, addressing the critical need for effective cartilage regenerative therapies and advancing the field of tissue engineering towards the development of functional substitutes capable of emulating the complex biomechanical and biochemical environment of native cartilage.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAnimals\u003c/h2\u003e \u003cp\u003e All animal procedures were approved by the WuXi 9th people's hospital (WuXi orthopaedics hospital ) Medical Ethical Committee. Wild-type animals used for hematoxylin-eosin staining, immunohistochemistry and RT-qPCR were two mice at gestational ages of 13.5 days and 18.5 days, respectively. Embryonic mice (8/litter) were removed by caesarean section from each pregnant mouse and euthanized. Before the experiment, the mice were maintained in a standard cages under a standard 12 h light/dark cycle with ad libitum access to food and water.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSingle-cell transcriptome analysis\u003c/h2\u003e \u003cp\u003eWe downloaded the raw gene expression matrix of single\u0026ndash;cell transcriptomes of the embryonic mouse hindlimb from the previous research (GSE142425) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Firstly, we filtered the raw matrix and only retained the data of embryonic day 13.5 (E13.5) and E18.5 mouse embryos. Secondly, we utilized the R package Harmony [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] to merge the raw matrix from different developmental stages and removed the batch effects. Then, we utilized the R package Seurat [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] to process the merged dataset and perform quality control, log-normalization, dimensionality reduction, clustering and data visualization. For clustering, we utilized the top 20 principal components (PCs) to construct the unsupervised shared nearest neighbor clustering (SNN) graph, then we performed the improved graphbased clustering of the merged dataset by using louvain algorithm. The resolution parameter was set to 0.5. After clustering, the marker genes of each cell cluster were identified by using the R package COSG [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCell clusters were annotated by the representative marker genes related to specific cell type. We exhibited the expression profiles of marker genes in different cell clusters (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eC), thus the cell clusters with the specific expression of marker genes were annotated as the corresponding cell types. Specifically, cartilage (\u003cem\u003eCol2a1\u003c/em\u003e), bone (\u003cem\u003eCol1a1\u003c/em\u003e), skin (\u003cem\u003eKrt14\u003c/em\u003e), vasculature (\u003cem\u003eCdh5\u003c/em\u003e) and blood (\u003cem\u003eLyz2\u003c/em\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFurthermore, the function \u0026lsquo;FindMarkers\u0026rsquo; of the R package Seurat [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] was used to perform differential expression analysis of cells from different development stage in cartilage cells and bone cells. The DEGs were identified by the non-parametric Wilcoxon rank sum test, and the DEGs with the absolute values of the avg_log2FC greater than 2 and the p values adjusted by Benjamini-Hochberg less than 0.05 were considered to be significant (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe differentially expressed genes of mouse cartilage cells during development.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eavg_log2FC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdjusted p value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBgn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-3.326417163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.36E-148\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSparc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.281090211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.08E-124\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIgfbp7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.575572357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.69E-120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1500015O10Rik\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.54227103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.87E-111\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDcn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.808228981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.90E-99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUcma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-4.198947745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.82E-93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFmod\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.688870875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.41E-92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHspa1a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-3.964279352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.17E-78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCol3a1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.175328212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.26E-78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCol1a2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.441658937\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.36E-54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMsmp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-3.630117175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.58E-41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCol1a1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-3.132088181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.54E-24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe differentially expressed genes of mouse bone cells during development.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eavg_log2FC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdjusted p value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMdk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.742212598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.15E-183\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrip1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-3.622412689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.32E-166\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSparc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.358670829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.55E-157\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCol6a3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.204858963\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.22E-146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS100a6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.979058867\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.09E-139\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNdufa4l2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-3.212720457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.07E-129\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCav1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.478384864\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.27E-122\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNnat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.077083816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.17E-119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIfitm3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.348380812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.06E-110\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCd24a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.055891556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.43E-110\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCol4a1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.6945452\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.96E-109\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCebpb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.614045631\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.83E-100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSparcl1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.243612707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.23E-99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCol6a2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.098009023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.00E-98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHspa1a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.443833761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.42E-96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCol6a1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.149184319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.76E-95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIgfbp7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-3.223926633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.04E-94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRgs5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-3.608071462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.07E-90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGm13889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.852748292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.29E-88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDlk1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.634323432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.08E-88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNfkbia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.03853582\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.29E-87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCol4a2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.022005123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.76E-85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCxcl1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-3.282083204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.52E-78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGng11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.288280896\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.59E-78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMt1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.142230895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.43E-77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCol3a1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.828789647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.64E-73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActa2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-3.852581603\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.07E-72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTpm2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.142783849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.61E-60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCcl2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.729312764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.28E-59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCox4i2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.24746182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.32E-56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDcn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.397021173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.09E-48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyl9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.407532919\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.98E-28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCol1a2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.06596405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.54E-27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTagln\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.451061583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.03E-23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.052885146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.61E-21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCol1a1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.615008609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.09E-20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMoreover, the protein-protein interaction networks (PPI) analysis of DEGs in cartilage cells were performed by the STRING APP of cytoscape software [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eFunctional enrichment analysis\u003c/h2\u003e \u003cp\u003eThe Gene Ontology (GO) enrichment analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed by the R package clusterProfiler [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], the p values for enrichment were adjusted by the Benjamini-Hochberg method.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eHematoxylin-eosin (HE) staining\u003c/h2\u003e \u003cp\u003eThe mouse embryos were fixed in 10% paraformaldehyde for more than 24 hours. After fixation, the embryos were routinely embedded in paraffin, then cut into 4\u0026micro;m sections. The sections were dried, deparaffinized, rehydrated, and stained with hematoxylin-eosin for observation of the joint cartilage in mouse hindlimb. Specifically, for deparaffinization and rehydration, the sections were treated in xylene I for 20 minutes, xylene II for 20 minutes, absolute ethanol for 10 minutes, 90% ethanol for 3 minutes, 80% ethanol for 3 minutes, and 70% ethanol for 3 minutes. Subsequently, the sections were stained with safranin, immersed in safranin staining solution for 3 minutes, rinsed in water to remove excess stain, differentiated in 1% hydrochloric acid ethanol for 2 seconds until tissues turned red, washed three times in water to remove hydrochloric acid ethanol, and then soaked in water for 15 minutes. Then, the sections were treated in 75% ethanol for 2\u0026ndash;3 seconds, 95% ethanol for 2\u0026ndash;3 seconds for dehydration. Next, the sections were stained with eosin, immersed in eosin staining solution for 3 minutes, rinsed in water to remove excess eosin, dehydrated in 100% ethanol for 2\u0026ndash;3 seconds. Finally, the sections were sealed with neutral resin. The images were taken by the Leica, DMi8.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eImmunohistochemistry\u003c/h2\u003e \u003cp\u003eThe mouse embryos were fixed in 10% paraformaldehyde for more than 24 hours, then routinely embedded in paraffin. After that, the embryos were sectioned into 4\u0026micro;m sections, deparaffinized and rehydrated after drying the sections, followed by immunohistochemistry, mainly focusing on the cartilage of the mouse hindlimb. Specifically, for deparaffinization and rehydration of the sections, the sections were treated in xylene I for 20 minutes, xylene II for 20 minutes, anhydrous ethanol for 10 minutes, 90% ethanol for 3 minutes, 80% ethanol for 3 minutes, and 70% ethanol for 3 minutes. Subsequently, the sections were washed with PBS for three times, then fixed with EDTA antigen retrieval solution at 98\u0026deg;C for 20 minutes. Afterwards, the sections were washed with PBS for three times, and 3% hydrogen peroxide blocking agent was added dropwise to each section, left at room temperature for 20 minutes. Then, the sections were washed with PBS for three times, and each section was incubated overnight at 4\u0026deg;C in antibody diluted with 2% bovine serum. Then, the sections were washed with PBS for three times, and corresponding secondary antibodies diluted with 2% bovine serum were added dropwise to each section, then incubated at 37\u0026deg;C in the dark for 1 hour. Then, after washing with PBS for three times, DAB staining solution was added dropwise, stained in the dark at room temperature for 15 minutes. Then, the sections were washed with PBS for three times, stained with hematoxylin for 1 minute and 20 seconds, rinsed with tap water three times. Then, differentiation was done with 1% hydrochloric acid ethanol for 2\u0026ndash;3 seconds, rinsed with tap water three times, and soaked for 15 minutes. Finally, after dehydration with an alcohol gradient, the sections were sealed. The images were taken by the Leica, DMi8.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eRT-qPCR analysis\u003c/h2\u003e \u003cp\u003eFirstly, after performing euthanasia for the mouse embryos, their hindlimb tissues were rapidly transferred to the \u0026minus;\u0026thinsp;80\u0026deg;C refrigerator for preservation. To extract the total RNA of mouse hindlimb, the hindlimb tissues were cut into appropriate sizes, thoroughly ground in liquid nitrogen, and then each 30-50mg of tissue was added to 1ml of Trizol reagent, well mixed, and incubated on ice for 10 minutes. Subsequently, the mixture was centrifuged at 4\u0026deg;C, 12000rpm for 5 minutes, and the supernatant was transferred to a new EP tube; 200\u0026micro;l of chloroform was added, vigorously shaken for 15 seconds, and incubated on ice for 5 minutes. Then, the mixture was centrifuged at 4\u0026deg;C, 12000rpm for 5 minutes, the upper aqueous phase was transferred to a new EP tube, an equal volume of isopropanol was added, gently inverted and mixed about 10 times, and left to stand at -20\u0026deg;C for 30 minutes. Subsequently, the mixture was centrifuged at 4\u0026deg;C, 12000rpm for 5 minutes, the supernatant was removed, and the RNA precipitate was washed twice with 85% ethanol. Then, the mixture was centrifuged at 4\u0026deg;C, 12000rpm for 5 minutes, the supernatant was removed, air-dried at room temperature for 5 minutes, and the RNA was dissolved in 20\u0026micro;l of DEPC water. Subsequently, the reverse transcription reaction was immediately carried out.\u003c/p\u003e \u003cp\u003eSecondly, the reverse transcription reaction was performed by using Vazyme HiScriptIIQ RT SuperMix for qPCR reverse transcription kit, with the following program: incubated at 25\u0026deg;C for 5 minutes, 50\u0026deg;C for 15 minutes, heated at 85\u0026deg;C for 2 minutes, and stored at 4\u0026deg;C. Then the first strand cDNA was stored at -40\u0026deg;C.\u003c/p\u003e \u003cp\u003eTirdly, primer design. The primers used in RT-qPCR were designed using Primer Premier 5.0 software [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and synthesized by Shanghai General Biology Company. The cDNA levels were normalized by the expression of GAPDH.\u003c/p\u003e \u003cp\u003eFourthly, the RT-qPCR reaction was performed by using the 2\u0026times;Q3 SYBR qPCR Master mix (Universal) kit, with the reaction program settings shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe program settings of the RT-qPCR reaction.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperature\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTime\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCycle number\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e95℃\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e95℃\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45cycles\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60℃\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45cycles\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e95℃\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60℃\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e97℃\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40℃\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFinally, data processing. After PCR amplification, the real-time fluorescence quantitative PCR instrument automatically analyzed the results. The threshold and baseline were adjusted based on the negative control to determine the Ct value of each sample, and the validity of the Ct value was determined based on the melting curve. Then, the results were exported, and the 2-ΔΔCT method was used to analyze the expression differences of the target gene between the control group and various concentration groups. The calculation formula was as ΔCt\u0026thinsp;=\u0026thinsp;Ct target gene - Ct reference gene. Then, the average ΔCt of the control group was calculated and denoted as ΔCt control average. The ΔCt of each group was subtracted from ΔCt control to obtain the ΔΔCt value, which was ΔΔCt\u0026thinsp;=\u0026thinsp;ΔCt sample - ΔCt control average. The 2-ΔΔCT value of each group was then calculated, representing the relative expression level of the gene in each group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eFor immunohistochemistry and RT-qPCR analysis, statistical differences were determined by the Unpaired t-test, and the p values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered to indicate statistical significance. * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eHE staining shows the morphological changes of the cartilage during the embryonic mouse hindlimb development\u003c/h2\u003e \u003cp\u003ePrevious research have emphasized that the developmental period from E13.5 to E18.5 is critical for mouse cartilage development [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. To further investigate the specific changes in tissue structure and cell morphology of cartilage during this developmental stage, we performed HE staining on the condylar cartilage and tibial growth plate cartilage of embryonic mouse at E13.5 and E18.5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), respectively. The results showed that the condylar cartilage and tibial growth plate cartilage of mouse embryos at E13.5 and E18.5 both exhibited the basic morphology of cartilage (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), however, there were certain differences in the morphology and structure of the condylar cartilage and tibial growth plate cartilage at different developmental stages (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Specifically, at E13.5, the condylar cartilage was formed by the aggregation of mesenchymal cells into cell clusters (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), and the tibial growth plate cartilage of some embryos have started to develop (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), especially, the differentiation of mesenchymal cells in tibial growth plate cartilage were later than that in condylar cartilage (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). At E18.5, joint spaces appeared in the embryonic mouse tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), and there was no zone of cell condensation in the growth plate of the tibia (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), meanwhile, cartilage cells were flat and arranged in a columnar manner along the long axis of the bone (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe condylar cartilage is an important growth area of the mandible, formed secondarily during individual development, which is defined as secondary cartilage; while tibial growth plate cartilage is the growth center of long bones, which is defined as primary cartilage. The different growth characteristics of these two types of cartilage drived them to play different important roles in joint functions. Our research results indicateed that from E13.5 to E18.5, the condylar cartilage and tibial growth plate cartilage of mouse embryos developed rapidly (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), and the mesenchymal stem cells in them differentiated rapidly (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), which provided a solid foundation for the normal function of cartilage. Therefore, it\u0026rsquo;s essential to explore the genetic mechanisms and the related regulatory factors that regulate the cartilage development in this stage.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eComprehensive analysis of single-cell transcriptomes during cartilage development\u003c/h2\u003e \u003cp\u003eTo examine the transcriptional landscape of mouse cartilage development, we utilized the single-cell transcriptomes of embryonic mouse hindlimb from previously published research [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and performed integrated analyses based on the data from two developmental points, E13.5 and E18.5. After merging single-cell transcriptomes from two developmental stages, the cluster analysis totally yielded 16 distinct clusters (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Notably, some cell clusters showed high transcriptional similarities, indicating that they were all subgroups originated from the same cell type (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). To accurately annotate these cell clusters, we utilized typical marker genes and identified 5 cell types representing cartilage (\u003cem\u003eCol2a1\u003c/em\u003e), bone (\u003cem\u003eCol1a1\u003c/em\u003e), skin (\u003cem\u003eKrt14\u003c/em\u003e), vasculature (\u003cem\u003eCdh5\u003c/em\u003e) and blood (\u003cem\u003eLyz2\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eC-\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003eTo further explore the transcriptional changes in cartilage during mouse hindlimb development, we performed differential expression analysis on cartilage cells between E13.5 and E18.5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). The results indicated that some DEGs played important roles in cartilage development and function. For instance, gene \u003cem\u003eUcma\u003c/em\u003e significantly highly expressed in cartilage cells at E18.5 than that at E13.5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA); this gene encodes a chondrocyte-specific, highly charged protein that is abundantly expressed in the upper immature zone of fetal and juvenile epiphyseal cartilage, especially, undercarboxylation of the encoded protein is associated with osteoarthritis in humans [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Gene \u003cem\u003eFmod\u003c/em\u003e also showed significant increased expression in cartilage cells at E18.5 than that at E13.5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA), the encoded protein of gene \u003cem\u003eFmod\u003c/em\u003e may regulate TGF-beta activities by sequestering TGF-beta into the extracellular matrix, and the previous research suggested that TGF-beta plays a key role in the development, formation, and repair of articular cartilage [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Then we performed GO enrichment analysis and KEGG enrichment analysis on the DEGs of cartilage cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB-\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). The most significant enriched GO terms were \u0026ldquo;skeletal system development\u0026rdquo;, \u0026ldquo;cartilage development\u0026rdquo;, \u0026ldquo;extracellular matrix\u0026rdquo; and \u0026ldquo;structural molecule activity\u0026rdquo; (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB), indicating that our differential analysis results actually reflected the genetic drivers of mouse cartilage development. Furthermore, the enrichment results also suggested that these DEGs were involved in influencing cartilage development through the pathways of \u0026ldquo;protein digestion and absorption\u0026rdquo;, \u0026ldquo;extracellular matrix (ECM)\u0026thinsp;\u0026minus;\u0026thinsp;receptor interaction\u0026rdquo;, \u0026ldquo;focal adhesion\u0026rdquo; and \u0026ldquo;PI3K\u0026thinsp;\u0026minus;\u0026thinsp;Akt signaling pathway\u0026rdquo; (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCandidate regulatory factors for cartilage development defined by comparative analysis and PPI\u003c/h2\u003e \u003cp\u003eAbove studies have identified the DEGs that were significantly related to cartilage development and function. However, we are more interested in the genetic factors that specifically regulate cartilage development, which not simultaneously regulated the bone development. Therefore, we utilized the above single-cell transcriptomes to performed differential expression analysis on bone cells between E13.5 and E18.5. Then we performed comparative analysis to identify the specific regulatory factors for cartilage development. Firstly, whether in cartilage cells or in bone cells, we only kept the DEGs with the absolute values of the avg_log2FC were greater than 2 and the adjusted p values were less than 0.05 (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) as candidate DEGs. Then, we removed the overlapping candidate DEGs between cartilage cells and bone cells from the candidate DEGs of cartilage cells. Finally, the remaining genes were defined as the potential markers of cartilage development, including genes \u003cem\u003eBgn\u003c/em\u003e, \u003cem\u003eUcma\u003c/em\u003e, \u003cem\u003eFmod\u003c/em\u003e, \u003cem\u003eMsmp\u003c/em\u003e and \u003cem\u003e1500015O10Rik\u003c/em\u003e. In addition, the genes \u003cem\u003eBgn\u003c/em\u003e and \u003cem\u003eFmod\u003c/em\u003e that we mentioned in the above encodes a member of the small leucine-rich proteoglycans (SLRPs) family of proteins, the encoded preproprotein is proteolytically processed to generate the mature protein, which plays a role in bone growth, muscle development and regeneration, and collagen fibril assembly in multiple tissues, espically, this protein may also regulate inflammation and innate immunity [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Notably, there was no study suggested that genes \u003cem\u003eMsmp\u003c/em\u003e and \u003cem\u003e1500015O10Rik\u003c/em\u003e played roles in bone or cartilage development, indicating that these genes may be novel markers for cartilage development, which were worthy of the further research.\u003c/p\u003e \u003cp\u003eTo further investigate the regulatory relationships between DEGs of cartilage cells and define the regulatory networks for cartilage development, we applied the PPI for all DEGs of cartilage cells and the potential marker genes for cartilage development, respectively. The results showed that DEGs of cartilage cells between E13.5 and E18.5 significantly interacted with each other (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA), indicating that these DEGs promoted the normal development of cartilage through synergistic actions. Furthermore, we identified the regulatory network of the potential marker genes for cartilage development (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB), which was likely to be the core regulatory network during development.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eRT-qPCR analyses were conducted on the candidate regulatory factors involved in cartilage development in embryonic mouse at E13.5 and E18.5\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe results of differential expression analysis and PPI analysis indicated the candidate marker genes for cartilage development, we verified their expression in further detail by RT-qPCR analysis. Consistent with the results of the differential expression analysis, the expression levels of genes \u003cem\u003eDcn\u003c/em\u003e, \u003cem\u003eBgn\u003c/em\u003e, \u003cem\u003eFmod\u003c/em\u003e, \u003cem\u003eMsmp\u003c/em\u003e, \u003cem\u003eUcma\u003c/em\u003e, \u003cem\u003eCol2α1\u003c/em\u003e, \u003cem\u003eSox9\u003c/em\u003e and \u003cem\u003eAcan\u003c/em\u003e were indeed highly elevated in cartilage of E18.5 mouse hindlimb compared with the cartilage of E13.5 mouse hindlimb (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor the gene \u003cem\u003eBgn\u003c/em\u003e, the results of the RT-qPCR analysis were somewhat different from that of the differential expression analysis. Although the differential expression analysis indicated marked increase in the expression of gene \u003cem\u003eBgn\u003c/em\u003e in cartilage of embryonic mouse from E13.5 to E18.5 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), the RT-qPCR analysis revealed that the increase was modest (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Moreover, the expressional patterns of genes \u003cem\u003eAcan\u003c/em\u003e and \u003cem\u003eSox9\u003c/em\u003e differed considerably between the results of the RT-qPCR analysis and the differential expression analysis. Based on the differential expression analysis, their expression did not change markedly during development. In contrast, the RT-qPCR analysis revealed that the expression of genes \u003cem\u003eAcan\u003c/em\u003e and \u003cem\u003eSox9\u003c/em\u003e obviously increased from E13.5 to E18.5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG-\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH), this result also corresponded to previous research that suggested genes \u003cem\u003eAcan\u003c/em\u003e and \u003cem\u003eSox9\u003c/em\u003e were essential for cartilage development [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurthermore, the RT-qPCR analysis also indicated that the candidate marker genes (including genes \u003cem\u003eBgn\u003c/em\u003e, \u003cem\u003eUcma\u003c/em\u003e, \u003cem\u003eFmod\u003c/em\u003e and \u003cem\u003eMsmp\u003c/em\u003e) that we identified showed significantly increased expression during mouse cartilage development (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB-\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003e \u003cb\u003eImmunohistochemistry was performed on the candidate regulatory factors involved in cartilage development in embryonic mouse at E13.5 and E18.5\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSince the results obtained through the bioinformatics analysis may have false positives, the experimental validation to be essential. To explore the candidate DEGs we identified could truly serve as marker genes for cartilage development, we selected three genes (including \u003cem\u003eCol2α1\u003c/em\u003e, \u003cem\u003eUcma\u003c/em\u003e and \u003cem\u003eBgn\u003c/em\u003e) for immunohistochemical verification. As we mentioned above, the DEGs \u003cem\u003eUcma\u003c/em\u003e and \u003cem\u003eBgn\u003c/em\u003e showed specifically significantly increased expression during the cartilage development. And the DEG \u003cem\u003eCol2α1\u003c/em\u003e was a well known marker gene for cartilage development, this gene encodes the alpha-1 chain of type II collagen, a fibrillar collagen found in cartilage [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], thus the immunohistochemical result of this gene could be a useful control.\u003c/p\u003e \u003cp\u003eThe results of immunohistochemistry of genes \u003cem\u003eCol2α1\u003c/em\u003e, \u003cem\u003eUcma\u003c/em\u003e and \u003cem\u003eBgn\u003c/em\u003e in embryonic mouse at E13.5 and E18.5 showed that the expression levels of the antibodies Col2α1, Ucma, and Bgn in the cartilage of the embryonic mouse hindlimb significantly increased during the development (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA-\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB), indicating that these three genes could serve as the markers for cartilage development.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eCartilage is a specialized tissue that provides mechanical support and contributes to joint function. The research of cartilage development and its disorders is crucial for understanding the etiology of various diseases, including osteoarthritis and chondrodysplasia [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Particularly, exploring the specific signaling molecules or regulatory factors for chondrogenic could provide important reference for the mesenchymal stem cells (MSC)-based therapy for cartilage regeneration [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. For the past few years, single-cell transcriptomic analysis has emerged as a powerful tool for identifying key regulators and markers of cartilage development [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Our investigation into the dynamic processes of cartilage development and differentiation during critical embryonic stages in mice has provided a deeper understanding of the morphological changes, genetic underpinnings, and the identification of pivotal genetic regulators. Through the integration of hematoxylin-eosin staining, scRNA sequencing, RT-qPCR, and immunohistochemistry, we have uncovered significant gene expression differences that drive the development of cartilage, reflecting both the intrinsic developmental program and its biomechanical adaptation needs. These findings provide an important basis for further exploring the regulatory networks of cartilage development, which will hopefully serve to promote the research of cartilage regeneration and the prevention of osteoarthritis or other diseases.\u003c/p\u003e \u003cp\u003eFrom E13.5 to E18.5, the condylar cartilage and tibial growth plate cartilage of embryonic mouse experienced rapid development, meanwhile, exhibited certain differences in the stratification, morphology and arrangement of chondrocytes[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The chondrocytes were derived from the mesenchymal cells. Interestingly, the differentiation of mesenchymal cells in tibial growth plate cartilage were later than that in condylar cartilage, at E13.5, the condylar cartilage of embryonic mouse was a cluster of mesenchymal cells, while the tibial growth plate cartilage of some embryos had not started to develop. This phenomenon suggested that the development of condylar cartilage may be regulated by the specific growth factors, previous research have indicated that the growth factor TGF-β and the transcription factor \u003cem\u003eSox9\u003c/em\u003e both played key roles in the development, formation and repair of cartilage[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], thus the differences in the expression of these regulatory factors during early development may induce earlier differentiation of mesenchymal cells in condylar cartilage. However, the earlier development of condylar cartilage may also be influenced by other regulatory factors that newly identified by our research, which will be discussed in detail below.\u003c/p\u003e \u003cp\u003eMesenchymal stem cells originate from the mesoderm and ectoderm in the early stage of development, they are mature stem cells with self-replicating ability and multidirection differentiation potential [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Under specific induction conditions, mesenchymal stem cells could differentiate into adipose cells, cartilage cells, bone cells or other tissue cells [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Therefore, mesenchymal stem cell therapy is considered as a viable strategy for the treatment of cartilage injury[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], however, further investigation highlights the critical importance of precise regulation during the maturation and hypertrophy of chondrocytes. Chondrocyte hypertrophy is a pivotal phase in cartilage development; however, in therapeutic contexts aiming for cartilage repair, it is crucial to induce chondrogenesis without proceeding to unwanted bone formation[\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Our research provided a valuable reference for solving this problem, utilizing scRNA-seq to identify genes that are highly expressed specifically during the chondrogenesis stage but do not show significant changes in expression during the subsequent hypertrophy phase. These genes, being differentially expressed at crucial stages of cartilage formation, suggest that their regulation could potentially allow for the growth of cartilage tissue while absent further hypertrophy and endochondral bone formation. This involves the application of specific biological factors at defined times, targeting these genes to guide MSCs towards chondrocyte differentiation and maturation without crossing the threshold into hypertrophy. Such insights could lead to more effective strategies in regenerative medicine, particularly for cartilage repair, by harnessing the potential of MSCs for precise tissue engineering.\u003c/p\u003e \u003cp\u003eBy removing the DEGs in chondrocyte clusters that also showed significantly increased expression during bone development, we further identified 5 genes \u003cem\u003eBgn\u003c/em\u003e, \u003cem\u003eUcma\u003c/em\u003e, \u003cem\u003eFmod\u003c/em\u003e, \u003cem\u003eMsmp\u003c/em\u003e and \u003cem\u003e1500015O10Rik\u003c/em\u003e as the specific markers for cartilage development. Previous studies have confirmed that genes \u003cem\u003eBgn\u003c/em\u003e, \u003cem\u003eUcma\u003c/em\u003e, and \u003cem\u003eFmod\u003c/em\u003e could be involved in the regulation of cartilage development [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], however, no studies have deeply explored the roles of these genes in cartilage repair and cartilage regeneration, and the related functional mouse models were rarely studied. Interestingly, \u003cem\u003eBgn\u003c/em\u003e and \u003cem\u003eFmod\u003c/em\u003e, as members of the SLRPs family, play critical roles in the pathogenesis of OA[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. These proteins interact with collagens to modulate fibril formation and bind to various cell surface receptors, growth factors, and other ECM components, thereby influencing cellular functions crucial for maintaining joint integrity. The disruption of these interactions, as observed in SLRP-deficient mouse models, leads to altered collagen networks, changes in chondrocyte proliferation and differentiation, and modifications in ECM turnover, which contribute to the development and progression of OA. Additionally, SLRPs are implicated in mechanisms beyond the cartilage itself, such as influencing subchondral bone structure and muscle weakness, further complicating the OA pathogenic landscape. Therefore, \u003cem\u003eBgn\u003c/em\u003e and \u003cem\u003eFmod\u003c/em\u003e, through their extensive involvement in regulating ECM structure and cellular signaling within the joint, underscore the complexity of OA pathogenesis, highlighting the interplay between genetic, molecular, and biomechanical factors in the disease's onset and progression. This comparative analysis has allowed us to identify potential markers specific to cartilage development, opening new avenues for understanding the complexity of cartilage formation and the distinct molecular pathways that govern it. The validation of these candidate regulatory factors through RT-qPCR and immunohistochemistry has confirmed their roles in cartilage development, reinforcing their potential as markers for cartilage development and as targets for therapeutic intervention.\u003c/p\u003e \u003cp\u003eOtherwise, among these genes, we found several novel regulators, including \u003cem\u003eMsmp\u003c/em\u003e and \u003cem\u003e1500015O10Rik\u003c/em\u003e, which were previously unknown to be involved in the cartilage development. Specifically, gene \u003cem\u003eMsmp\u003c/em\u003e encodes a member of the beta-microseminoprotein family, the encoded protein may play a role in prostate cancer tumorigenesis [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The gene \u003cem\u003e1500015O10Rik\u003c/em\u003e is synonymous with gene \u003cem\u003eEcrg4\u003c/em\u003e, previous research have suggested that gene \u003cem\u003eEcrg4\u003c/em\u003e is a marker of articular chondrocyte differentiation and cartilage destruction [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. And these genes were enriched in the pathways of \u0026ldquo;protein digestion and absorption\u0026rdquo;, \u0026ldquo;ECM\u0026thinsp;\u0026minus;\u0026thinsp;receptor interaction\u0026rdquo; and \u0026ldquo;focal adhesion\u0026rdquo;, which mainly affected the development of extracellular matrix. As an important part of the articular cartilage, extracellular matrix could maintain the living environment of chondrocytes and exchange signals with the outside of the chondrocytes. The homeostasis of extracellular matrix maintains the normal function of chondrocytes, and the loss of extracellular matrix could lead to diseases such as osteoarthritis and deformation of joint structure [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Thus these genes whose expression increased significantly during cartilage development could also serve as the key regulators for extracellular matrix remodeling, and these newly identified regulatory factors are whorthy of further research.\u003c/p\u003e \u003cp\u003eOur study has identified key genes and pathways implicated in the developmental process of cartilage formation in embryonic mice, offering insights that could potentially guide future regenerative therapies. However, we acknowledge several limitations inherent to our experimental design and methodology that merit consideration. Firstly, our investigation employs a single species focus, relying exclusively on embryonic mouse models. While mice are widely used in biomedical research due to their genetic congruence with humans and their expedited developmental timelines, it is imperative to note that findings derived from mouse models may not invariably mirror human biological processes due to interspecies differences. This limitation underscores the necessity for cautious interpretation of our results within the broader context of human biology. Additionally, our analysis is constrained by a developmental stage limitation, focusing on cartilage development at two specific embryonic stages (E13.5 and E18.5). Although these stages are pivotal for understanding cartilage formation in mice, our study may overlook critical stages or transitions that could provide deeper insights into the regulatory mechanisms of differentiation. Future studies should consider a broader range of developmental stages to capture the full spectrum of cartilage development. Our research also confronts a limitation in the number of identified regulatory factors. Although we have successfully pinpointed five genes as specific markers for cartilage development, the intricate nature of cartilage formation suggests the involvement of a more extensive array of genes and regulatory factors. The genes identified herein serve as an important foundation, yet they represent only a segment of the vast regulatory network governing cartilage development. Concerning experimental validation, we employed hematoxylin-eosin staining, immunohistochemistry, and RT-qPCR. While these techniques are instrumental for our analysis, they come with limitations regarding quantification accuracy, sensitivity, and the potential omission of less abundant or transiently expressed regulatory factors. Exploring additional validation methods could enhance the robustness of our findings. In terms of functional analysis, our study incorporates functional enrichment analysis to elucidate the roles of differentially expressed genes. However, we did not conduct direct functional assays to validate the specific contributions of these genes to cartilage development and regeneration. Such empirical validation is crucial for confirming the biological significance of the identified genes and should be addressed in future work. Our investigation also highlights a gap in elucidating regulatory mechanisms, identifying key genes and pathways without delving into the precise regulatory dynamics. A comprehensive understanding of how these genes interact within the cellular environment to guide cartilage development is essential and warrants further study. Lastly, regarding the translation to therapeutics, our findings lay a foundational basis for informing future regenerative therapies. Nevertheless, translating this knowledge into viable treatments for human cartilage-related ailments demands extensive follow-up research, particularly focusing on safety, dosage, delivery mechanisms, and long-term efficacy.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, our research identified reliable markers and regulators that were specific to mouse cartilage development, and a large number of functional experiments supported our findings. By uncovering the distinct molecular signatures associated with cartilage formation and differentiation, our comprehensive analysis not only enhances our genomic comprehension at the cellular level but also lays the foundation for novel cartilage regenerative strategies. These strategies hold the promise to revolutionize the therapeutic landscape for osteoarthritis and related musculoskeletal disorders, addressing the critical need for effective cartilage regenerative therapies and advancing the field towards the development of functional substitutes capable of emulating the complex biomechanical and biochemical environment of native cartilage. Future studies focusing on the functional characterization of the novel markers identified here are eagerly anticipated, poised to provide further insights into the molecular mechanisms of cartilage development and their implications for disease treatment and prevention.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eClinical Trial Number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. The raw gene expression matrix of single\u0026ndash;cell transcriptomes of the embryonic mouse hindlimb from the previous research (GSE142425).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe downloaded the raw gene expression matrix of single\u0026ndash;cell transcriptomes of the embryonic mouse hindlimb from the previous research (GSE142425). This study employed single-cell RNA sequencing (scRNA-seq) to explore the transcriptional landscape of mouse embryonic limb development at various stages, focusing on identifying genes pivotal for cartilage differentiation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors state that they have no competing interests conflicts of interest with this work.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by Top Talent Support Program for young and middle-aged people of Wuxi Health Committee (2023, grant number: HB2023127) Scientific and technological breakthrough Project of \u0026quot;Light of the Taihu Lake Lake\u0026quot; (2023, Basic research, grant number: K20231064), and Duo-Innovative and Excellent Doctors Project of Wuxi 9th People\u0026rsquo;s Hospital (2021, grant number: YB202108).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy design: FX. Study conduct: FX and WXC. Data collection: FX and JYT. Data analysis: FX, XHW and WXC. Data interpretation: FX, JYT and WXC. Drafting manuscript: FX and XHW. Revising manuscript content: YQ. Approving final version of manuscript: all authors. FX takes responsibility for the integrity of the data analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSzponder T, Latalski M, Danielewicz A, Krac K, Kozera A, Drzewiecka B, Nguyen Ngoc D, Dobko D, Wessely-Szponder J. Osteoarthritis: Pathogenesis, Animal Models, and New Regenerative Therapies. J Clin Med 2022, 12(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShim DW, Lee KM, Lee D, Kim JS, Jung YS, Oh SS, Lee SW, Lee JW, Kim BS. 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Nat Commun. 2019;10(1):1914.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-bioinformatics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"binf","sideBox":"Learn more about [BMC Bioinformatics](http://bmcbioinformatics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/binf","title":"BMC Bioinformatics","twitterHandle":"@BMC_Bioinformatics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"single cell RNA-sequencing, osteoarthritis, cartilage development, small leucine-rich proteoglycans, mesenchymal stem cells","lastPublishedDoi":"10.21203/rs.3.rs-4241968/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4241968/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eCartilage, characterized by its limited self-repair capacity due to avascularity and low metabolic activity of chondrocytes, poses a significant challenge for regenerative medicine. Osteoarthritis (OA), a prevalent cartilage disorder, highlights the urgent need for effective cartilage regenerative therapies. Understanding the molecular mechanisms underlying cartilage development during embryonic stages is crucial for advancing regenerative strategies and identifying potential therapeutic targets.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis study employed single-cell RNA sequencing (scRNA-seq) to explore the transcriptional landscape of mouse embryonic limb development at various stages, focusing on identifying genes pivotal for cartilage differentiation. Differentially expressed genes (DEGs) specific to cartilage development were pinpointed through comparative analysis. Functional validation of these marker genes was conducted using immunohistochemistry and RT-qPCR to confirm their roles in chondrocyte maturation and differentiation.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOur scRNA-seq analysis identified a set of novel marker genes, including Bgn, Ucma, Fmod, Msmp, and 1500015O10Rik, as specific indicators of cartilage development. Functional experiments supported the crucial roles of these markers in the differentiation and maturation of chondrocytes. Additionally, our findings revealed the dynamic transcriptomic alterations during cartilage development, emphasizing the significance of specific regulatory factors in guiding mesenchymal stem cells towards chondrogenesis.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe study elucidates the complex transcriptomic landscape governing cartilage development in embryonic mice, highlighting the discovery of novel marker genes crucial for chondrocyte differentiation. These insights into the molecular mechanisms of cartilage formation lay the groundwork for developing targeted regenerative therapies for OA and related musculoskeletal disorders. Our research underscores the importance of identifying reliable regulatory factors that enhance the effectiveness of regenerative treatments, providing a valuable reference for future studies on cartilage repair and regeneration.\u003c/p\u003e","manuscriptTitle":"Identification of Key Candidate Genes Related to Cartilage development during Murine embryonic limb development by single cell RNA-sequencing and Experimental Confirmation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-16 14:18:30","doi":"10.21203/rs.3.rs-4241968/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorAssigned","content":"","date":"2024-04-12T07:35:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-12T01:36:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Bioinformatics","date":"2024-04-09T12:42:01+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-bioinformatics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"binf","sideBox":"Learn more about [BMC Bioinformatics](http://bmcbioinformatics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/binf","title":"BMC Bioinformatics","twitterHandle":"@BMC_Bioinformatics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8a057969-17f1-455f-ac80-d98f7fc4dfbd","owner":[],"postedDate":"April 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-04-29T05:30:54+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-16 14:18:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4241968","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4241968","identity":"rs-4241968","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}