The central dogma(CD)of molecular biology is the transfer of genetic information from DNA to RNA to protein.Major CD processes governing genetic flow include the cell cycle,DNA replication,chromosome packaging,epigene...The central dogma(CD)of molecular biology is the transfer of genetic information from DNA to RNA to protein.Major CD processes governing genetic flow include the cell cycle,DNA replication,chromosome packaging,epigenetic changes,transcription,posttranscriptional alterations,translation,and posttranslational modifications.The CD processes are tightly regulated in plants to maintain genetic integrity throughout the life cycle and to pass genetic materials to next generation.Engineering of various CD processes involved in gene regulation will accelerate crop improvement to feed the growing world population.CRISPR technology enables programmable editing of CD processes to alter DNA,RNA,or protein,which would have been impossible in the past.Here,an overview of recent advancements in CRISPR tool development and CRISPR-based CD modulations that expedite basic and applied plant research is provided.Furthermore,CRISPR applications in major thriving areas of research,such as gene discovery(allele mining and cryptic gene activation),introgression(de novo domestication and haploid induction),and application of desired traits beneficial to farmers or consumers(biotic/abiotic stress-resilient crops,plant cell factories,and delayed senescence),are described.Finally,the global regulatory policies,challenges,and prospects for CRISPR-mediated crop improvement are discussed.展开更多
Background:The genetic central dogma(GCD)has been demonstrated its essential function in many biological processes and diseases.However,its roles in the process of osteogenic differentiation of mesenchymal stem cells(...Background:The genetic central dogma(GCD)has been demonstrated its essential function in many biological processes and diseases.However,its roles in the process of osteogenic differentiation of mesenchymal stem cells(MSCs)remain unclear.Methods:In this project,we analyzed an online database of osteogenic differentiation of MSCs after 14 days and 28 days by osteoinductive medium(GSE83770).The differentially expressed genes were screened by GEO2R,with further conducting of KEGG pathways using DAVID.In addition,protein-protein interactions of the enriched pathways were performed using STRING with marked hub genes measured by the CytoHubba.Hub genes were verified by quantitative reverse-transcription polymerase chain reaction.Results:Results showed that six pathways related to GCD,including DNA replication,Aminoacyl-tRNA biosynthesis,Mismatch repair,Ribosome,Spliceosome,and RNA degradation pathways enriched in the early stage(14 days vs.undifferentiated MSCs)of osteogenesis.The Lysosome pathway was highly enriched in the late stage(28 vs.14 days)of osteogenesis,and Ribosome pathway plays a key role throughout the entire process(28 days vs.undifferentiated MSCs)of osteogenesis.Conclusion:Both DNA replication and protein translation were functionally worked in the early stage of osteogenesis,whereas the Lysosome pathway was the only GCD-related one in the late stage of osteogenesis.The GCD-related Ribosome pathway occupied the entire process of osteogenesis.展开更多
Predicting the stages of cancer accurately is crucial for effective treatment planning. In this study, we aimed to develop a model using gene expression data and XGBoost (eXtreme Gradient Boosting) that include clinic...Predicting the stages of cancer accurately is crucial for effective treatment planning. In this study, we aimed to develop a model using gene expression data and XGBoost (eXtreme Gradient Boosting) that include clinical and demographic variables to predict specific lung cancer stages in patients. By conducting the feature selection using the Wilcoxon Rank Test, we picked the most impactful genes associated with lung cancer stage prediction. Our model achieved an overall accuracy of 82% in classifying lung cancer stages according to patients’ gene expression data. These findings demonstrate the potential of gene expression analysis and machine learning techniques in improving the accuracy of lung cancer stage prediction, aiding in personalized treatment decisions.展开更多
基金This work was supported by the National Research Foundation of Korea(grants NRF 2020M3A9I4038352,2020R1A6A1A03044344)by the Next-Generation BioGreen 21 Program(SSAC,grant PJ01322601)the Program for New Plant Breeding Techniques(NBT,grant PJ01478401),Rural Development Administration,Korea.
文摘The central dogma(CD)of molecular biology is the transfer of genetic information from DNA to RNA to protein.Major CD processes governing genetic flow include the cell cycle,DNA replication,chromosome packaging,epigenetic changes,transcription,posttranscriptional alterations,translation,and posttranslational modifications.The CD processes are tightly regulated in plants to maintain genetic integrity throughout the life cycle and to pass genetic materials to next generation.Engineering of various CD processes involved in gene regulation will accelerate crop improvement to feed the growing world population.CRISPR technology enables programmable editing of CD processes to alter DNA,RNA,or protein,which would have been impossible in the past.Here,an overview of recent advancements in CRISPR tool development and CRISPR-based CD modulations that expedite basic and applied plant research is provided.Furthermore,CRISPR applications in major thriving areas of research,such as gene discovery(allele mining and cryptic gene activation),introgression(de novo domestication and haploid induction),and application of desired traits beneficial to farmers or consumers(biotic/abiotic stress-resilient crops,plant cell factories,and delayed senescence),are described.Finally,the global regulatory policies,challenges,and prospects for CRISPR-mediated crop improvement are discussed.
文摘Background:The genetic central dogma(GCD)has been demonstrated its essential function in many biological processes and diseases.However,its roles in the process of osteogenic differentiation of mesenchymal stem cells(MSCs)remain unclear.Methods:In this project,we analyzed an online database of osteogenic differentiation of MSCs after 14 days and 28 days by osteoinductive medium(GSE83770).The differentially expressed genes were screened by GEO2R,with further conducting of KEGG pathways using DAVID.In addition,protein-protein interactions of the enriched pathways were performed using STRING with marked hub genes measured by the CytoHubba.Hub genes were verified by quantitative reverse-transcription polymerase chain reaction.Results:Results showed that six pathways related to GCD,including DNA replication,Aminoacyl-tRNA biosynthesis,Mismatch repair,Ribosome,Spliceosome,and RNA degradation pathways enriched in the early stage(14 days vs.undifferentiated MSCs)of osteogenesis.The Lysosome pathway was highly enriched in the late stage(28 vs.14 days)of osteogenesis,and Ribosome pathway plays a key role throughout the entire process(28 days vs.undifferentiated MSCs)of osteogenesis.Conclusion:Both DNA replication and protein translation were functionally worked in the early stage of osteogenesis,whereas the Lysosome pathway was the only GCD-related one in the late stage of osteogenesis.The GCD-related Ribosome pathway occupied the entire process of osteogenesis.
文摘Predicting the stages of cancer accurately is crucial for effective treatment planning. In this study, we aimed to develop a model using gene expression data and XGBoost (eXtreme Gradient Boosting) that include clinical and demographic variables to predict specific lung cancer stages in patients. By conducting the feature selection using the Wilcoxon Rank Test, we picked the most impactful genes associated with lung cancer stage prediction. Our model achieved an overall accuracy of 82% in classifying lung cancer stages according to patients’ gene expression data. These findings demonstrate the potential of gene expression analysis and machine learning techniques in improving the accuracy of lung cancer stage prediction, aiding in personalized treatment decisions.
