为揭示长江中游冬油菜主要气象因子及重要农艺性状对产量形成的影响机制,本研究以北纬30°为界,系统比较分析该纬度线南北两侧冬油菜生态适应性与产量主导因子的异同,旨在为优化区域品种选育与精准栽培管理提供理论依据与实践指导...为揭示长江中游冬油菜主要气象因子及重要农艺性状对产量形成的影响机制,本研究以北纬30°为界,系统比较分析该纬度线南北两侧冬油菜生态适应性与产量主导因子的异同,旨在为优化区域品种选育与精准栽培管理提供理论依据与实践指导。本研究选取2006—2007、2009—2010、2016—2017和2019—2020等4个气候条件差异显著、涵盖典型油菜生长季节气候类型(温暖干燥、偏冷湿润、气候波动强)的年份,作为代表性试验年度,在北纬30°以北与北纬30°以南共6个国家冬油菜区域试验站点,收集全部参试品种的重要农艺性状,并结合气象数据,通过多元统计方法,解析区域气象因子差异及其对产量的影响、重要农艺性状的差异及其与产量的协同关系。结果表明,北纬30°以北地区冬季气温更低、昼夜温差更大、降水量相对较少、日照时数前期较少后期较多;而北纬30°以南地区则相对温暖但后期多雨寡照,两地区气候差异显著。北纬30°以北地区平均产量比北纬30°以南地区高779.1 kg hm^(-2)(P<0.01),北纬30°以北地区单株产量和角果数显著高于北纬30°以南地区,但病害压力较大。逐步回归分析显示,北纬30°以北地区产量主要受4月份降水等因素影响;而北纬30°以南地区则主要受12月份日照时数和3月份降水量影响。北纬30°以北地区产量主要由单株产量和每角粒数直接决定;而北纬30°以南地区则更依赖单株产量与千粒重的协同作用,同时需控制分枝数与千粒重的负向效应。广适性品系0112、9ZYYP27、科乐油4号在南北两区均表现优异;而品系华68P25、渝华7号、越优577等则表现出明显的地域专适性。长江中游北纬30°两侧冬油菜生态区在气候资源、产量构成及主导性状上存在显著分化,区域光温水格局显著影响产量形成机制。北纬30°以北地区应注重苗期光照利用与后期排涝,优选耐渍、抗菌核病强、单株产量高、粒数粒重兼优的品种;北纬30°以南地区则应重视中后期光照利用,注意选育高光效、耐渍、单株产量高、粒数多、含油量高品种。建议构建“广适性+专适性”相结合的区域化品种推广体系,协同推进精准育种与高效栽培,以实现长江中游冬油菜高产、稳产与绿色可持续发展。展开更多
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
文摘为揭示长江中游冬油菜主要气象因子及重要农艺性状对产量形成的影响机制,本研究以北纬30°为界,系统比较分析该纬度线南北两侧冬油菜生态适应性与产量主导因子的异同,旨在为优化区域品种选育与精准栽培管理提供理论依据与实践指导。本研究选取2006—2007、2009—2010、2016—2017和2019—2020等4个气候条件差异显著、涵盖典型油菜生长季节气候类型(温暖干燥、偏冷湿润、气候波动强)的年份,作为代表性试验年度,在北纬30°以北与北纬30°以南共6个国家冬油菜区域试验站点,收集全部参试品种的重要农艺性状,并结合气象数据,通过多元统计方法,解析区域气象因子差异及其对产量的影响、重要农艺性状的差异及其与产量的协同关系。结果表明,北纬30°以北地区冬季气温更低、昼夜温差更大、降水量相对较少、日照时数前期较少后期较多;而北纬30°以南地区则相对温暖但后期多雨寡照,两地区气候差异显著。北纬30°以北地区平均产量比北纬30°以南地区高779.1 kg hm^(-2)(P<0.01),北纬30°以北地区单株产量和角果数显著高于北纬30°以南地区,但病害压力较大。逐步回归分析显示,北纬30°以北地区产量主要受4月份降水等因素影响;而北纬30°以南地区则主要受12月份日照时数和3月份降水量影响。北纬30°以北地区产量主要由单株产量和每角粒数直接决定;而北纬30°以南地区则更依赖单株产量与千粒重的协同作用,同时需控制分枝数与千粒重的负向效应。广适性品系0112、9ZYYP27、科乐油4号在南北两区均表现优异;而品系华68P25、渝华7号、越优577等则表现出明显的地域专适性。长江中游北纬30°两侧冬油菜生态区在气候资源、产量构成及主导性状上存在显著分化,区域光温水格局显著影响产量形成机制。北纬30°以北地区应注重苗期光照利用与后期排涝,优选耐渍、抗菌核病强、单株产量高、粒数粒重兼优的品种;北纬30°以南地区则应重视中后期光照利用,注意选育高光效、耐渍、单株产量高、粒数多、含油量高品种。建议构建“广适性+专适性”相结合的区域化品种推广体系,协同推进精准育种与高效栽培,以实现长江中游冬油菜高产、稳产与绿色可持续发展。
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.
