[ Objective ] The paper was to confirrm the effect of hrpZpsg12 gene on the pathogenicity of Pseudomonas syringae pv. glycinea. [ Method ] hrpZpsg12 gene was cloned from P. syringae using PCR method. The knockout plas...[ Objective ] The paper was to confirrm the effect of hrpZpsg12 gene on the pathogenicity of Pseudomonas syringae pv. glycinea. [ Method ] hrpZpsg12 gene was cloned from P. syringae using PCR method. The knockout plasmid pKNOCK-Cm with suicide characteristics and cosmid pUFR034 with complementation func- tion were used to construct the mutation vector pKNOCK477-7 and complementary vector pUFR1026-68 of hrpZpsg12 gene, the mutant 477-1 and the functional com- plementation unit 1026-5 of the gene was also screened out. Three strains including wild-type Psg12, mutant 477-1 and complementary unit 1026-5 were simultane- ously inoculated into soybean leaves and tobacco leaves, then pathogenicity determination and hypersensitive reaction analysis were carried out. [ Result] All the inoculated leaves of soybean and tobacco produced reaction lesion. However, the sizes of reaction lesion were different. The lesion in the leaves inoculated with Psgl2 was relatively large, while the lesion in the leaves inoculated with 477-1 was relatively small; the lesion of complementary unit 1026-5 was similar to wild- type Psgl2. Analysis of reproduction quantity of bacteria in lesions showed that the reproduction quantity of wild-type Psg12 was the highest, while that of mutant 477-1 was the lowest. The reproduction quantity of complementary unit 1026-5 was similar to that of wild-type Psg12. [ Conclusion] hrpZpsg12 gene could enhance the pathogenicity of P. syrimgae on Soybean and produce hypersensitive response in tobacco.展开更多
Soybean bacterial spot disease caused by Pseudomonas syringae pv.Glycinea which is a bacterial disease seriously affects soybean yield.Ten soybean germplasms and recombinant inbred lines(RILs)population were used to i...Soybean bacterial spot disease caused by Pseudomonas syringae pv.Glycinea which is a bacterial disease seriously affects soybean yield.Ten soybean germplasms and recombinant inbred lines(RILs)population were used to identify the resistant trait after inoculated with P.sg(P.sgneau001)in this study.High-density genetic mapping was obtained by specific length amplified fragment sequencing(SLAF-seq)of 149 RILs population which was derived from the crossing between Charleston and Dongnong594.The results indicated that 10 germplasm resources had four resistant germplasms included highly resistant cultivar Charleston,four susceptible varieties included Dongnong594 and two moderately resistant cultivars.Five quantitative trait locus(QTLs)were detected in RILs population by the composite interval mapping(CIM)method,and located on Linkage Group(LG)D1b(chromosome two),LG C2(chromosome six)and LG H(chromosome 12),respectively.LOD scores ranged from 2.68 to 4.95 and the phenotypic variation percentage was from 6%to 11%.Six candidate genes were detected,according to the result of gene annotation information.Four of them had relationship with protein kinase activity,protein phosphorylation and leucine rich repeat(LRR)transmembrane protein,which had high expression after inoculated with P.sg by qRT-PCR.展开更多
功率预测是实现电能供需平衡、维持电网稳定运行的一项重要任务.随着分布式海上光伏系统的发展,光伏利用率不断提升,同时对光伏功率预测提出了更高的要求.针对机器学习方法在光伏功率时间序列预测中存在的样本数量不足、预测精度低以及...功率预测是实现电能供需平衡、维持电网稳定运行的一项重要任务.随着分布式海上光伏系统的发展,光伏利用率不断提升,同时对光伏功率预测提出了更高的要求.针对机器学习方法在光伏功率时间序列预测中存在的样本数量不足、预测精度低以及隐私泄露等问题,提出一种基于联邦学习和变分模态分解的长短期记忆神经网络功率预测模型(long short-term memory neural network power forecasting model based on federated learning and variational mode decomposition,FL-VMD-LSTM).利用主成分分析法和三次样条插值对气象数据进行预处理,同时利用VMD将光伏功率时间序列分解为多个分量进行分步预测,降低光伏功率时间序列的非平稳性和复杂度.通过横向联邦学习的本地训练和参数聚合方法,实现在保证数据隐私安全情况下的光伏功率预测.通过4个算例进行仿真实验,验证结果表明FL-VMD-LSTM模型在光伏功率预测方面具有较高精度,与传统算法相比,RMSE和MAE分别降低了55.7%和55.5%.展开更多
基金Supported by Scientific Research Foundation Project of Jilin Agricultural University" hrpZ Psg12 Protein Function of Pseudomonas syringae pv.glycinea" (384)Major Project of Cultivation of Genetically Modified Biological New Varieties of "Eleventh Five-Year Plan" of Ministry of Agriculture"Cultivation of New Transgenic Varieties of Soybean with Diseases and Pests Resistance"(2008ZX08004-004)~~
文摘[ Objective ] The paper was to confirrm the effect of hrpZpsg12 gene on the pathogenicity of Pseudomonas syringae pv. glycinea. [ Method ] hrpZpsg12 gene was cloned from P. syringae using PCR method. The knockout plasmid pKNOCK-Cm with suicide characteristics and cosmid pUFR034 with complementation func- tion were used to construct the mutation vector pKNOCK477-7 and complementary vector pUFR1026-68 of hrpZpsg12 gene, the mutant 477-1 and the functional com- plementation unit 1026-5 of the gene was also screened out. Three strains including wild-type Psg12, mutant 477-1 and complementary unit 1026-5 were simultane- ously inoculated into soybean leaves and tobacco leaves, then pathogenicity determination and hypersensitive reaction analysis were carried out. [ Result] All the inoculated leaves of soybean and tobacco produced reaction lesion. However, the sizes of reaction lesion were different. The lesion in the leaves inoculated with Psgl2 was relatively large, while the lesion in the leaves inoculated with 477-1 was relatively small; the lesion of complementary unit 1026-5 was similar to wild- type Psgl2. Analysis of reproduction quantity of bacteria in lesions showed that the reproduction quantity of wild-type Psg12 was the highest, while that of mutant 477-1 was the lowest. The reproduction quantity of complementary unit 1026-5 was similar to that of wild-type Psg12. [ Conclusion] hrpZpsg12 gene could enhance the pathogenicity of P. syrimgae on Soybean and produce hypersensitive response in tobacco.
基金Supported by the National Key R&D Program of China(2016YFD0100201)Science Foundation for Distinguished Young Scholars of Heilongjiang Province(JC2016004)Harbin Science Technology Project(2015RQXXJ018)。
文摘Soybean bacterial spot disease caused by Pseudomonas syringae pv.Glycinea which is a bacterial disease seriously affects soybean yield.Ten soybean germplasms and recombinant inbred lines(RILs)population were used to identify the resistant trait after inoculated with P.sg(P.sgneau001)in this study.High-density genetic mapping was obtained by specific length amplified fragment sequencing(SLAF-seq)of 149 RILs population which was derived from the crossing between Charleston and Dongnong594.The results indicated that 10 germplasm resources had four resistant germplasms included highly resistant cultivar Charleston,four susceptible varieties included Dongnong594 and two moderately resistant cultivars.Five quantitative trait locus(QTLs)were detected in RILs population by the composite interval mapping(CIM)method,and located on Linkage Group(LG)D1b(chromosome two),LG C2(chromosome six)and LG H(chromosome 12),respectively.LOD scores ranged from 2.68 to 4.95 and the phenotypic variation percentage was from 6%to 11%.Six candidate genes were detected,according to the result of gene annotation information.Four of them had relationship with protein kinase activity,protein phosphorylation and leucine rich repeat(LRR)transmembrane protein,which had high expression after inoculated with P.sg by qRT-PCR.
文摘功率预测是实现电能供需平衡、维持电网稳定运行的一项重要任务.随着分布式海上光伏系统的发展,光伏利用率不断提升,同时对光伏功率预测提出了更高的要求.针对机器学习方法在光伏功率时间序列预测中存在的样本数量不足、预测精度低以及隐私泄露等问题,提出一种基于联邦学习和变分模态分解的长短期记忆神经网络功率预测模型(long short-term memory neural network power forecasting model based on federated learning and variational mode decomposition,FL-VMD-LSTM).利用主成分分析法和三次样条插值对气象数据进行预处理,同时利用VMD将光伏功率时间序列分解为多个分量进行分步预测,降低光伏功率时间序列的非平稳性和复杂度.通过横向联邦学习的本地训练和参数聚合方法,实现在保证数据隐私安全情况下的光伏功率预测.通过4个算例进行仿真实验,验证结果表明FL-VMD-LSTM模型在光伏功率预测方面具有较高精度,与传统算法相比,RMSE和MAE分别降低了55.7%和55.5%.
