Wingless-type MMTV integration site family, member 16 (wnt16), is a wnt ligand that participates in the regulation of vertebrate skeletal development. Studies have shown that wnt16 can regulate bone metabolism, but its molecular mechanism remains largely undefined. We obtained the wnt16-/- zebrafish model using the CRISPR-Cas9-mediated gene knockout screen with 11 bp deletion in wnt16, which led to the premature termination of amino acid translation and significantly reduced wnt16 expression, thus obtaining the wnt16-/- zebrafish model. The expression of wnt16 in bone-related parts was detected via in situ hybridization. The head, spine, and tail exhibited significant deformities, and the bone mineral density and trabecular bone decreased in wnt16-/- using light microscopy and micro-CT analysis. RNA sequencing was performed to explore the differentially expressed genes (DEGs). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis found that the down-regulated DEGs are mainly concentrated in mTOR, FoxO, and VEGF pathways. Protein–protein interaction (PPI) network analysis was performed with the detected DEGs. Eight down-regulated DEGs including akt1, bnip4, ptena, vegfaa, twsg1b, prkab1a, prkab1b, and pla2g4f.2 were validated by qRT-PCR and the results were consistent with the RNA-seq data. Overall, our work provides key insights into the influence of wnt16 gene on skeletal development.

BackgroundBoth obesity (OB) and periodontitis (PD) are chronic non-communicable diseases, and numerous epidemiological studies have demonstrated the association between these two diseases. However, the molecular mechanisms that could explain the association between OB and PD are largely unclear. This study aims to investigate the common gene signatures and biological pathways in OB and PD through bioinformatics analysis of publicly available transcriptome datasets.MethodsThe RNA expression profile datasets of OB (GSE104815) and PD (GSE106090) were used as training data, and GSE152991 and GSE16134 as validation data. After screening for differentially expressed genes (DEGs) shared by OB and PD, gene enrichment analysis, protein-protein interaction (PPI) network construction, GeneMANIA analysis, immune infiltration analysis and gene set enrichment analysis (GSEA) were performed. In addition, receiver operating characteristic (ROC) curves were used to assess the predictive accuracy of the hub gene. Finally, we constructed the hub gene-associated TF-miRNA-mRNA regulatory network.ResultsWe identified a total of 147 DEGs shared by OB and PD (38 down-regulated and 109 up-regulated). Functional analysis showed that these genes were mainly enriched in immune-related pathways such as B cell receptor signalling, leukocyte migration and cellular defence responses. 14 hub genes (FGR, MNDA, NCF2, FYB1, EVI2B, LY86, IGSF6, CTSS, CXCR4, LCK, FCN1, CXCL2, P2RY13, MMP7) showed high sensitivity and specificity in the ROC curve analysis. The results of immune infiltration analysis showed that immune cells such as macrophages, activated CD4 T cells and immune B cells were present at high infiltration levels in both OB and PD samples.The results of GeneMANIA analysis and GSEA analysis suggested that five key genes (FGR, LCK, FYB1, LY86 and P2RY13) may be strongly associated with macrophages. Finally, we constructed a TF-miRNA-mRNA regulatory network consisting of 233 transcription factors (TFs), 8 miRNAs and 14 mRNAs based on the validated information obtained from the database.ConclusionsFive key genes (FGR, LCK, FYB1, LY86, P2RY13) may be important biomarkers of OB and PD. These genes may play an important role in the pathogenesis of OB and PD by affecting macrophage activity and participating in immune regulation and inflammatory responses.

Allotetraploid is a new species produced by distant hybridization between red crucian carp (Carassius auratus red var., abbreviated as RCC) and common carp (Cyprinus carpio L., abbreviated as CC). There is a significant difference in growth rate between allotetraploid and its parents. However, the underlying molecular mechanism is largely unknown. In this study, to find direct evidence associated with metabolism and growth rate in protein level, we performed quantitative proteomics analysis on liver tissues between allotetraploid and its parents. A total of 2502 unique proteins were identified and quantified by SWATH‐MS in our proteomics profiling. Subsequently, comprehensive bioinformatics analyses including gene ontology enrichment analysis, pathway and network analysis, and protein–protein interaction analysis (PPI) were conducted based on differentially expressed proteins (DEPs) between allotetraploid and its parents. The results revealed several significant DEPs involved in metabolism pathways in liver. More specifically, the integrative analysis highlighted that the DEPs ACSBG1, OAT, and LDHBA play vital roles in metabolism pathways including “pentose phosphate pathway,” “TCA cycle,” and “glycolysis and gluconeogenesis.” These could directly affect the growth rate in fresh water fishes by regulating the metabolism, utilization, and exchange of substance and energy. Since the liver is the central place for metabolism activity in animals, we firstly established the comprehensive and quantitative proteomics knowledge base for liver tissue from freshwater fishes, our study may serve as an irreplaceable reference for further studies regarding fishes’ culture and growth.

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Background: People with type 1 diabetes mellitus (T1DM) are significantly more likely to have osteoporosis (OP). Astragali Radix is a Chinese herbal medicine containing various active ingredients, and several clinical trials have been reported to use it to treat OP and T1DM, respectively. Objective: To evaluate the targets and potential mechanisms of Astragali Radix administration on OP and T1DM. Methods: The targets of Astragali Radix were identified using the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. The OP and T1DM datasets were downloaded from the Gene Expression Omnibus (GEO) database. The weighted gene correlation network analysis (WGCNA) method was used to identify the co-expression genes associated with OP and T1DM. In addition, the common gene targets of OP and T1DM were screened using two public databases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the R tool. After the validation of key genes, molecular docking was performed to visualize small molecule-protein interactions. Results: The compound target network mainly contained 17 compounds and 147 corresponding targets. There were 561 GO items and 154 signaling pathways in KEGG, mainly including the AGE-RAGE signaling pathway in diabetic complications and osteoclast differentiation. The results of molecular docking showed that flavonoids were the top compound of Astragali Radix, which had a high affinity with CDK2, VEGFA, and MYC. Conclusion: Flavonoids in Astragali Radix may regulate multiple signaling pathways through MYC, CDK2, and VEGFA, which may play a therapeutic role in OP and T1DM.