Objective:To evaluate the effect and profitability of using the quantitative trait loci (QTL)-linked direct marker (DR marker) in gene-assisted selection (GAS). Methods: Three populations (100, 200, or 300 sows plus 1...Objective:To evaluate the effect and profitability of using the quantitative trait loci (QTL)-linked direct marker (DR marker) in gene-assisted selection (GAS). Methods: Three populations (100, 200, or 300 sows plus 10 boars within each group) with segregating QTL were simulated stochastically. Five economic traits were investigated, including number of born alive (NBA), average daily gain to 100 kg body weight (ADG), feed conversion ratio (FCR), back fat at 100 kg body weight (BF) and intramuscular fat (IMF). Selection was based on the estimated breeding value (EBV) of each trait. The starting frequencies of the QTL's favorable allele were 0.1, 0.3 and 0.5, respectively. The economic return was calculated by gene flow method. Results: The selection efficiency was higher than 100% when DR markers were used in GAS for 5 traits. The selection efficiency for NBA was the highest, and the lowest was for ADG whose QTL had the lowest variance. The mixed model applied DR markers and obtained higher extra genetic gain and extra economic returns. We also found that the lower the frequency of the favorable allele of the QTL, the higher the extra return obtained. Conclusion: GAS is an effective selection scheme to increase the genetic gain and the eco- nomic returns in pig breeding.展开更多
Objective:To search and analyze the related genes of liver hepatocellular carcinoma(LIHC)by using bioinformatics technology.Methods:Gene expression omnibus(GEO)was used to retrieve the entry of"Liver hepatocellul...Objective:To search and analyze the related genes of liver hepatocellular carcinoma(LIHC)by using bioinformatics technology.Methods:Gene expression omnibus(GEO)was used to retrieve the entry of"Liver hepatocellular carcinoma",and GSE109903 chip data was downloaded.The differentially expressed genes in the control group and liver hepatocellular carcinoma group were screened by bioinformatics analysis.GO enrichment analysis,KEGG pathway analysis,differential gene expression analysis and visualization processing were performed for the differentially expressed genes;Protein interaction network analysis and visualization processing were used to screen core genes EEF1A1 and HK2 with strong correlation with liver hepatocellular carcinoma.GEPIA,Kaplan-Meier plotter,GeneMANIA and Timer 2.0 databases were used to analyze the differential expression,prognostic value and immune cell infiltration of key genes in LIHC.Results:A total of 1059 differentially expressed genes were screened,including 637 up-regulated genes and 872 downregulated genes.Functional analysis showed that differentially expressed genes were mainly involved in the process of positive transcription regulation,nucleosome function,chromatin function and RNA binding.Pathway analysis showed that differentially expressed genes were involved in systemic lupus erythematosus,alcoholism and RNA polymerase I promoter opening pathway.The analysis of differential gene expression showed that the drugs with similar gene characteristics were mainly CDC inhibitors,prostaglandins,serotonin receptor antagonists,BAF transcriptional repression inhibitors,tyrosine phosphatase inhibitors,etc;Protein interaction network analysis showed that the main genes associated with LIHC were EEF1A1,HK2,FAM38A and LAMB3;EEF1A1 and HK2 genes were further analyzed by GEPIA.The results showed that the expression of EEF1A1 and HK2 mRNA in LIHC tissues was higher than that in normal tissues,and was significantly correlated with the pathological stage,overall survival rate and disease-free survival rate of LIHC patients.EEF1A1 and HK2 may be potential prognostic biomarkers for LIHC patients.In addition,the functions of EEF1A1 and HK2 were mainly related to translation factor activity,molecular chaperone mediated autophagy and carbohydrate catabolism,and purine nucleoside diphosphate metabolism,respectively.Immunocyte infiltration showed that the expression of EEF1A1 and HK2 was significantly correlated with the infiltration of a variety of immune cells,including six types of immune cells:CD4+T cells,macrophages,neutrophils,B cells,CD8+T cells and dendritic cells.Conclusion:By screening differentially expressed genes,we can identify the key genes in the development of liver hepatocellular carcinoma,and screen potential prognostic biomarkers for the survival of patients with liver hepatocellular carcinoma.At the same time,this study provides new ideas and programs for clinical treatment of liver hepatocellular carcinoma.展开更多
Objective:To search the the differentially expressed genes between breast cell carcinoma tissues and normal tissues by using bioinformatics technology,and the potential therapeutic drugs for breast cancer were identif...Objective:To search the the differentially expressed genes between breast cell carcinoma tissues and normal tissues by using bioinformatics technology,and the potential therapeutic drugs for breast cancer were identified,which can provide reference for clinical immune targeted therapy and drug therapy of breast cancer in the future.Methods:"Breast cancer"was searched by using Gene Expression Omnibus(GEO),and GSE79586 chip data was downloaded.The differentially expressed genes in the control group and the breast cancer model group were screened by using bio-communication technology and subjected to GO function analysis,KEGG pathway analysis,differential gene characteristic expression analysis and protein-protein interaction network(PPI)analysis,and the analysis results were further visualized.Prognosis analysis,related function prediction and immune infiltration analysis were performed using the GEPIA,GeneMANIA,and Timer2.0 databases,respectively.Finally,the compounds with potential therapeutic effects on breast cancer are identified through Connectivity Map(CMap).Western blotting and real-time PCR(RT-PCR)were used to verify the core genes and potential therapeutic agents with the highest correlation in vitro.Results:A total of 3916 differentially expressed genes including 1786 up-regulated genes and 2130 down-regulated genes were screened.GO analysis showed that the differential genes were mainly involved in the positive regulation of phosphorylation,secretory vesicles,racemase and epimerase activities.KEGG analysis showed that differential genes were involved in systemic lupus erythematosus,alcoholism,sticky spots,amoebic dysentery Ras signal pathways and other disease pathways.The characteristic expression analysis of differential genes showed that MEK inhibitors,HSP90 inhibitors and signal transduction pathway kinase inhibitors were drugs similar to the differential genes.PPI results showed that H2AFJ,TFF1,GATA3,FOXA1,and CDH1 were core genes related to breast cancer.Two core genes of H2AFJ and TFF1 with the highest correlation were further selected for GEPIA analysis.The results of the analysis showed that the mRNA expression levels of H2AFJ and TFF1 in breast cancer cells were significantly higher than those in normal tissues,and there was a significant correlation with the pathological staging,overall survival rate and disease-free survival rate of breast cancer patients.H2AFJ and TFF1 may be potential prognostic biomarkers for survival of breast cancer patients.The functions of differentially expressed H2AFJ and TFF1 are mainly related to hormone receptor binding,epithelial structure maintenance and epigenetic negative regulation of genes,chromatin tissue involved in negative regulation of transcription,etc.The results of immune infiltration showed that the expressions of H2AFJ and TFF1 had a significant correlation with the infiltration of macrophages,neutrophils,monocytes,CD4+T,CD8+T,B lymphocytes and other immune cells.CMap results showed that compounds such as Gefitinib,Alpelisib,Sorafenib,and Sunitinib had potential therapeutic effects on breast cancer.Western blot and RT-PCR results showed that H2AFJ and TFF1 were significantly overexpressed in breast cancer cells.Gefitinib significantly inhibited the expression of H2AFJ and TFF1 in breast cancer cells(P<0.05,P<0.01).Conclusion:In this study,differentially expressed genes between breast cell carcinoma tissues and normal tissues were screened out by bioinformatics means to further identify key genes and compounds with potential therapeutic effects in the onset process of breast cancer and to further verify the effectiveness of the screened drugs on breast cancer through experiments.It will provide reference for clinical research and development of new drugs against breast cancer in the future in order to develop more effective treatment options.展开更多
基金Project (No. 30300249) supported by the Natural Science Foundationof Guangdong Province, China
文摘Objective:To evaluate the effect and profitability of using the quantitative trait loci (QTL)-linked direct marker (DR marker) in gene-assisted selection (GAS). Methods: Three populations (100, 200, or 300 sows plus 10 boars within each group) with segregating QTL were simulated stochastically. Five economic traits were investigated, including number of born alive (NBA), average daily gain to 100 kg body weight (ADG), feed conversion ratio (FCR), back fat at 100 kg body weight (BF) and intramuscular fat (IMF). Selection was based on the estimated breeding value (EBV) of each trait. The starting frequencies of the QTL's favorable allele were 0.1, 0.3 and 0.5, respectively. The economic return was calculated by gene flow method. Results: The selection efficiency was higher than 100% when DR markers were used in GAS for 5 traits. The selection efficiency for NBA was the highest, and the lowest was for ADG whose QTL had the lowest variance. The mixed model applied DR markers and obtained higher extra genetic gain and extra economic returns. We also found that the lower the frequency of the favorable allele of the QTL, the higher the extra return obtained. Conclusion: GAS is an effective selection scheme to increase the genetic gain and the eco- nomic returns in pig breeding.
基金supported by National Natural Science Foundation of China(No.81603418)。
文摘Objective:To search and analyze the related genes of liver hepatocellular carcinoma(LIHC)by using bioinformatics technology.Methods:Gene expression omnibus(GEO)was used to retrieve the entry of"Liver hepatocellular carcinoma",and GSE109903 chip data was downloaded.The differentially expressed genes in the control group and liver hepatocellular carcinoma group were screened by bioinformatics analysis.GO enrichment analysis,KEGG pathway analysis,differential gene expression analysis and visualization processing were performed for the differentially expressed genes;Protein interaction network analysis and visualization processing were used to screen core genes EEF1A1 and HK2 with strong correlation with liver hepatocellular carcinoma.GEPIA,Kaplan-Meier plotter,GeneMANIA and Timer 2.0 databases were used to analyze the differential expression,prognostic value and immune cell infiltration of key genes in LIHC.Results:A total of 1059 differentially expressed genes were screened,including 637 up-regulated genes and 872 downregulated genes.Functional analysis showed that differentially expressed genes were mainly involved in the process of positive transcription regulation,nucleosome function,chromatin function and RNA binding.Pathway analysis showed that differentially expressed genes were involved in systemic lupus erythematosus,alcoholism and RNA polymerase I promoter opening pathway.The analysis of differential gene expression showed that the drugs with similar gene characteristics were mainly CDC inhibitors,prostaglandins,serotonin receptor antagonists,BAF transcriptional repression inhibitors,tyrosine phosphatase inhibitors,etc;Protein interaction network analysis showed that the main genes associated with LIHC were EEF1A1,HK2,FAM38A and LAMB3;EEF1A1 and HK2 genes were further analyzed by GEPIA.The results showed that the expression of EEF1A1 and HK2 mRNA in LIHC tissues was higher than that in normal tissues,and was significantly correlated with the pathological stage,overall survival rate and disease-free survival rate of LIHC patients.EEF1A1 and HK2 may be potential prognostic biomarkers for LIHC patients.In addition,the functions of EEF1A1 and HK2 were mainly related to translation factor activity,molecular chaperone mediated autophagy and carbohydrate catabolism,and purine nucleoside diphosphate metabolism,respectively.Immunocyte infiltration showed that the expression of EEF1A1 and HK2 was significantly correlated with the infiltration of a variety of immune cells,including six types of immune cells:CD4+T cells,macrophages,neutrophils,B cells,CD8+T cells and dendritic cells.Conclusion:By screening differentially expressed genes,we can identify the key genes in the development of liver hepatocellular carcinoma,and screen potential prognostic biomarkers for the survival of patients with liver hepatocellular carcinoma.At the same time,this study provides new ideas and programs for clinical treatment of liver hepatocellular carcinoma.
基金supported by Supported by the National Natural Science Foundation of China(81603418,82074271)Scientific Research Project of"Outstanding Innovative Talents Support Plan"of Heilongjiang University of Chinese Medicine(2020YQ05)。
文摘Objective:To search the the differentially expressed genes between breast cell carcinoma tissues and normal tissues by using bioinformatics technology,and the potential therapeutic drugs for breast cancer were identified,which can provide reference for clinical immune targeted therapy and drug therapy of breast cancer in the future.Methods:"Breast cancer"was searched by using Gene Expression Omnibus(GEO),and GSE79586 chip data was downloaded.The differentially expressed genes in the control group and the breast cancer model group were screened by using bio-communication technology and subjected to GO function analysis,KEGG pathway analysis,differential gene characteristic expression analysis and protein-protein interaction network(PPI)analysis,and the analysis results were further visualized.Prognosis analysis,related function prediction and immune infiltration analysis were performed using the GEPIA,GeneMANIA,and Timer2.0 databases,respectively.Finally,the compounds with potential therapeutic effects on breast cancer are identified through Connectivity Map(CMap).Western blotting and real-time PCR(RT-PCR)were used to verify the core genes and potential therapeutic agents with the highest correlation in vitro.Results:A total of 3916 differentially expressed genes including 1786 up-regulated genes and 2130 down-regulated genes were screened.GO analysis showed that the differential genes were mainly involved in the positive regulation of phosphorylation,secretory vesicles,racemase and epimerase activities.KEGG analysis showed that differential genes were involved in systemic lupus erythematosus,alcoholism,sticky spots,amoebic dysentery Ras signal pathways and other disease pathways.The characteristic expression analysis of differential genes showed that MEK inhibitors,HSP90 inhibitors and signal transduction pathway kinase inhibitors were drugs similar to the differential genes.PPI results showed that H2AFJ,TFF1,GATA3,FOXA1,and CDH1 were core genes related to breast cancer.Two core genes of H2AFJ and TFF1 with the highest correlation were further selected for GEPIA analysis.The results of the analysis showed that the mRNA expression levels of H2AFJ and TFF1 in breast cancer cells were significantly higher than those in normal tissues,and there was a significant correlation with the pathological staging,overall survival rate and disease-free survival rate of breast cancer patients.H2AFJ and TFF1 may be potential prognostic biomarkers for survival of breast cancer patients.The functions of differentially expressed H2AFJ and TFF1 are mainly related to hormone receptor binding,epithelial structure maintenance and epigenetic negative regulation of genes,chromatin tissue involved in negative regulation of transcription,etc.The results of immune infiltration showed that the expressions of H2AFJ and TFF1 had a significant correlation with the infiltration of macrophages,neutrophils,monocytes,CD4+T,CD8+T,B lymphocytes and other immune cells.CMap results showed that compounds such as Gefitinib,Alpelisib,Sorafenib,and Sunitinib had potential therapeutic effects on breast cancer.Western blot and RT-PCR results showed that H2AFJ and TFF1 were significantly overexpressed in breast cancer cells.Gefitinib significantly inhibited the expression of H2AFJ and TFF1 in breast cancer cells(P<0.05,P<0.01).Conclusion:In this study,differentially expressed genes between breast cell carcinoma tissues and normal tissues were screened out by bioinformatics means to further identify key genes and compounds with potential therapeutic effects in the onset process of breast cancer and to further verify the effectiveness of the screened drugs on breast cancer through experiments.It will provide reference for clinical research and development of new drugs against breast cancer in the future in order to develop more effective treatment options.