Translation is a crucial step in gene expression.Over the past decade,the development and application of ribosome profiling(Ribo-seq)have significantly advanced our understanding of translational regulation in vivo.Ho...Translation is a crucial step in gene expression.Over the past decade,the development and application of ribosome profiling(Ribo-seq)have significantly advanced our understanding of translational regulation in vivo.However,the analysis and visualization of Ribo-seq data remain challenging.Despite the availability of various analytical pipelines,improvements in comprehensiveness,accuracy,and user-friendliness are still necessary.In this study,we develop RiboParser/RiboShiny,a robust framework for analyzing and visualizing Ribo-seq data.Building on published methods,we optimize ribosome structure-based and start/stopbased models to improve the accuracy and stability of P-site detection,even in species with a high proportion of leaderless transcripts.Leveraging these improvements,RiboParser offers comprehensive analyses,including quality control,gene-level analysis,codon-level analysis,and the analysis of Ribo-seq variants.Meanwhile,RiboShiny provides a user-friendly and adaptable platform for data visualization,facilitating deeper insights into the translational landscape.Furthermore,the integration of standardized genome annotation renders our platform universally applicable to various organisms with sequenced genomes.This framework has the potential to significantly improve the precision and efficiency of Ribo-seq data interpretation,thereby deepening our understanding of translational regulation.展开更多
基金supported by the National Key Research and Development Program of China(2022YFA0912100)the National Natural Science Foundation of China(32270098 and 32470073)+1 种基金the Fundamental Research Funds for the Central Universities(2662024JC015)the National Key Laboratory of Agricultural Microbiology(AML2024D02)to Z.Z.
文摘Translation is a crucial step in gene expression.Over the past decade,the development and application of ribosome profiling(Ribo-seq)have significantly advanced our understanding of translational regulation in vivo.However,the analysis and visualization of Ribo-seq data remain challenging.Despite the availability of various analytical pipelines,improvements in comprehensiveness,accuracy,and user-friendliness are still necessary.In this study,we develop RiboParser/RiboShiny,a robust framework for analyzing and visualizing Ribo-seq data.Building on published methods,we optimize ribosome structure-based and start/stopbased models to improve the accuracy and stability of P-site detection,even in species with a high proportion of leaderless transcripts.Leveraging these improvements,RiboParser offers comprehensive analyses,including quality control,gene-level analysis,codon-level analysis,and the analysis of Ribo-seq variants.Meanwhile,RiboShiny provides a user-friendly and adaptable platform for data visualization,facilitating deeper insights into the translational landscape.Furthermore,the integration of standardized genome annotation renders our platform universally applicable to various organisms with sequenced genomes.This framework has the potential to significantly improve the precision and efficiency of Ribo-seq data interpretation,thereby deepening our understanding of translational regulation.
文摘目的发展具有空间分辨的腐蚀电化学研究方法。方法用电沉积方法在铜基体上制备Ni和Ni-P涂层,应用扫描电镜和XRD检测涂层表面形貌和晶体结构,采用扫描电化学显微镜(SECM)研究Ni和Ni-P涂层在不同浓度Na Cl溶液中的失效行为,并结合COMSOL多物理场软件建立二维和三维模型,模拟量化活性点大小和反馈机制。结果低浓度Cl-对于纯Ni涂层具有活化作用,增加Cl-浓度会促进腐蚀发生。Ni-P合金涂层在低浓度Na Cl溶液中,短时间内保持良好的稳定性,浸泡6 h后,低P合金涂层出现典型的活性点和腐蚀产物,而高P合金涂层在浸泡24 h后出现腐蚀产物和活性区域。0.1 mol/L的Na Cl溶液促进低P合金涂层局部腐蚀的发生,而涂层在0.3 mol/L Na Cl溶液中则以发生均匀腐蚀为主。逼近曲线及其模拟结果表明,腐蚀产物对于Fc Me OH的电化学过程完全失活,而新鲜Cu表面对Fc Me OH氧化还原过程受扩散控制。三维模拟结果显示,低P合金涂层失效过程中活性点大小接近10μm。结论 Ni和Ni-P合金涂层的失效过程中活性点的形成、腐蚀产物的生成和累积过程与SECM面扫描图谱中正负反馈效应相关,Cl-促进腐蚀发生,其浓度影响腐蚀类型。COMSOL多物理场模拟明确反馈效应与探针和基底的距离有关,Ni-P涂层失效活性点大小在微米级。
