目的西尼罗河病毒(West Nile Virus,WNV)是常见的蚊媒人畜共患传染病病毒,目前对病毒传播因素的研究主要涉及生态、宿主因素及相关病毒基因或基因位点等层面;对病毒基因组组成特征的关注较少。而基于病毒基因组组成特征的人工智能在识...目的西尼罗河病毒(West Nile Virus,WNV)是常见的蚊媒人畜共患传染病病毒,目前对病毒传播因素的研究主要涉及生态、宿主因素及相关病毒基因或基因位点等层面;对病毒基因组组成特征的关注较少。而基于病毒基因组组成特征的人工智能在识别和预测其他病毒宿主适应性方面成果颇多。本研究旨在建立一个卷积神经网络(CNN)模型,根据基因组特征预测WNV的宿主适应性。方法首先,采用二核苷酸组成性表征(DCR)编码WNV基因序列的基因组特征。其次,采用非监督学习对WNV样本进行基于DCR的分布差异分析。最后,利用基于DCR的卷积神经网络(CNN)模型预测来自鸟类、哺乳动物和蚊虫的WNV的适应性。此外,通过贝叶斯方法推断出适应性相关基因上的特异性氨基酸残基。结果DCR能有效区分宿主特异性WNV,CNN模型能准确预测哺乳动物和禽类高适应的WNV。贝叶斯模型可确定适应性相关的氨基酸残基。结论WNV的基因组组成特征具有宿主特异性,这种基因组偏差有助于通过深度学习方法预测WNV对禽类或哺乳动物宿主的适应性。本研究提供了关于有助于西尼罗河病毒(WNV)适应宿主的基因组特征的共性特征。展开更多
Soybean root diseases are associated with numerous fungal and oomycete pathogens;however,the community dynamics and interactions of these pathogens are largely unknown.We performed 13 loop-mediated isothermal amplific...Soybean root diseases are associated with numerous fungal and oomycete pathogens;however,the community dynamics and interactions of these pathogens are largely unknown.We performed 13 loop-mediated isothermal amplification(LAMP)assays that targeted specific soybean root pathogens,and traditional isolation assays.A total of 159 samples were collected from three locations in the Huang-Huai-Hai region of China at three soybean growth stages(30,60,and 90 days after planting)in 2016.In LAMP results,we found that pathogen communities differed slightly among locations,but changed dramatically between soybean growth stages.Phytophthora sojae,Rhizoctonia solani,and Fusarium oxysporum were most frequently detected at the early stage,whereas Phomopsis longicolla,Fusarium equiseti,and Fusarium virguliforme were most common in the later stages.Most samples(86%)contained two to six pathogen species.Interestingly,the less detectable species tended to exist in the samples containing more detected species,and some pathogens preferentially co-occurred in diseased tissue,including P.sojae–R.solani–F.oxysporum and F.virguliforme–Calonectria ilicicola,implying potential interactions during infection.The LAMP detection results were confirmed by traditional isolation methods.The isolated strains exhibited different virulence to soybean,further implying a beneficial interaction among some pathogens.展开更多
文摘目的西尼罗河病毒(West Nile Virus,WNV)是常见的蚊媒人畜共患传染病病毒,目前对病毒传播因素的研究主要涉及生态、宿主因素及相关病毒基因或基因位点等层面;对病毒基因组组成特征的关注较少。而基于病毒基因组组成特征的人工智能在识别和预测其他病毒宿主适应性方面成果颇多。本研究旨在建立一个卷积神经网络(CNN)模型,根据基因组特征预测WNV的宿主适应性。方法首先,采用二核苷酸组成性表征(DCR)编码WNV基因序列的基因组特征。其次,采用非监督学习对WNV样本进行基于DCR的分布差异分析。最后,利用基于DCR的卷积神经网络(CNN)模型预测来自鸟类、哺乳动物和蚊虫的WNV的适应性。此外,通过贝叶斯方法推断出适应性相关基因上的特异性氨基酸残基。结果DCR能有效区分宿主特异性WNV,CNN模型能准确预测哺乳动物和禽类高适应的WNV。贝叶斯模型可确定适应性相关的氨基酸残基。结论WNV的基因组组成特征具有宿主特异性,这种基因组偏差有助于通过深度学习方法预测WNV对禽类或哺乳动物宿主的适应性。本研究提供了关于有助于西尼罗河病毒(WNV)适应宿主的基因组特征的共性特征。
基金supported by the grants to Prof.Zheng Xiaobo and Prof.Wang Yuanchao from the National Key R&D Program of China(2018YFD0201000)the earmarked fund for China Agriculture Research System(CARS-004-PS14)+1 种基金the National Natural Science Foundation of China(31721004)by the grant to Associate Prof.Ye Wenwu from the National Natural Science Foundation of China(31772140)。
文摘Soybean root diseases are associated with numerous fungal and oomycete pathogens;however,the community dynamics and interactions of these pathogens are largely unknown.We performed 13 loop-mediated isothermal amplification(LAMP)assays that targeted specific soybean root pathogens,and traditional isolation assays.A total of 159 samples were collected from three locations in the Huang-Huai-Hai region of China at three soybean growth stages(30,60,and 90 days after planting)in 2016.In LAMP results,we found that pathogen communities differed slightly among locations,but changed dramatically between soybean growth stages.Phytophthora sojae,Rhizoctonia solani,and Fusarium oxysporum were most frequently detected at the early stage,whereas Phomopsis longicolla,Fusarium equiseti,and Fusarium virguliforme were most common in the later stages.Most samples(86%)contained two to six pathogen species.Interestingly,the less detectable species tended to exist in the samples containing more detected species,and some pathogens preferentially co-occurred in diseased tissue,including P.sojae–R.solani–F.oxysporum and F.virguliforme–Calonectria ilicicola,implying potential interactions during infection.The LAMP detection results were confirmed by traditional isolation methods.The isolated strains exhibited different virulence to soybean,further implying a beneficial interaction among some pathogens.
