摘要
目的研究H9N2禽流感病毒进化规律,对其进化适应性进行分析。方法筛选H9N2禽流感病毒完整全基因组序列,构建系统生成树,基于LBI算法根据系统生成树以及基因组序列所蕴含信息对H9N2禽流感病毒序列进行适应性分析,并运用TreeTime对H9N2禽流感病毒时空分布等信息进行系统动力学分析。结果具有高适应性的H9N2禽流感病毒毒株分布于多个不同的支系中,除A/chicken/Shandong/H/2009、A/chicken/Zhejiang/C3188/2010等毒株所在支系外,绝大部分高适应性毒株支系来自于2013-2014年的中国地区。PB2节段的高适应性支系时间分布集中于2013年前后,HA、PB2、MP节段高适应性支系地区分布相对集中,其余各节段时间分布跨度相对较大、地区分布广泛。结论H9N2禽流感病毒在2013年前后变异速度的加快导致许多具有高适应性的毒株支系出现,大部分具有高适应性的毒株支系具备时间分布跨度大、地区分布范围广的特点。如何依据H9N2禽流感病毒进化规律预测其未来发展方向,亟需更多研究予以解决。
Objective To study the evolutionary pattern of H9N2 avian influenza virus and to analyze its evolutionary fitness.Methods The complete whole genome sequence of H9N2 avian influenza virus was retrieved and constructed as a data set.Phylogenetic trees were constructed,while a fitness analysis of H9N2 avian influenza virus sequences was performed based on the phylogenetic trees and the information contained in the genome sequences by the LBI algorithm.A system analysis of the spatial and temporal distribution of H9N2 avian influenza virus and other information was performed via TreeTime.Results The H9N2 avian influenza virus strains with high fitness were distributed in different clades,except for the clades where such strains as A/chicken/Shandong/H/2009 and A/chicken/Zhejiang/C3188/2010 belonged.The majority of high-fitness clades came from China between 2013 and 2014.The temporal distribution of high-fitness clades in PB2 segment centered around 2013,while the regional distribution of high-fitness clades in HA,PB2 and MP segments was relatively concentrated.The distribution of the remaining segments spanned a relatively large period with a wide regional distribution.Conclusion The accelerated mutation of H9N2 avian influenza viruses around 2013 has led to the emergence of many clades with high fitness,most of which are characterized by a large temporal distribution and a wide regional distribution.However,the question of how to predict the future evolution of H9N2 avian influenza virus based on its evolutionary pattern needs to be studied.
作者
杨浩艺
胡明达
龚行飞
靳远
王博千
梁龙
岳俊杰
陈微
任洪广
YANG Hao-yi;HU Ming-da;GONG Xing-fei;JIN Yuan;WANG Bo-qian;LIANG Long;YUE Jun-jie;CHEN Wei;REN Hong-guang(College of Computer,National University of Defense Technology,Changsha 410073,China;State Key Laboratory of Pathogen and Biosecurity,Beijing Institute of Biotechnology,Beijing 100071,China)
出处
《军事医学》
CAS
2022年第7期530-533,545,共5页
Military Medical Sciences
基金
国家自然科学基金(32070025,31800136)。