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仿刺参微卫星标记的筛选及群体遗传结构分析
引用本文:潘传燕,臧云鹏,廖梅杰,王印庚,荣小军,张正,李彬,陈贵平.仿刺参微卫星标记的筛选及群体遗传结构分析[J].海洋水产研究,2012,33(4):72-82.
作者姓名:潘传燕  臧云鹏  廖梅杰  王印庚  荣小军  张正  李彬  陈贵平
作者单位:1. 中国海洋大学,青岛266003;农业部海洋渔业可持续发展重点实验室,青岛市海水鱼类种子工程与生物技术重点实验室,中国水产科学研究院黄海水产研究所,266071
2. 农业部海洋渔业可持续发展重点实验室,青岛市海水鱼类种子工程与生物技术重点实验室,中国水产科学研究院黄海水产研究所,266071;上海海洋大学水产与生命学院,201306
3. 农业部海洋渔业可持续发展重点实验室,青岛市海水鱼类种子工程与生物技术重点实验室,中国水产科学研究院黄海水产研究所,266071
基金项目:国家自然科学基金项目,国家高技术研究发展计划项目,山东省农业良种工程重大课题“速生、抗病、耐高温刺参良种选育”、科研院所技术开发研究专项,中央级公益性科研院所基本科研业务费专项资金项目
摘    要:采用FIASCO(Fast Isolation by AFLP Sequences Containing Repeats)方法构建了仿刺参基因组富集CA微卫星序列的基因组短片段文库,筛选得到118条微卫星DNA序列。根据重复单元的排列特点,完美型共83个,占70.4%;非完美型共30个;占25.4%;复合型标记5个,占4.2%。选取其中20条微卫星序列设计引物进行多态性检测,并利用这20对引物对采自中国、韩国(西海岸及东海岸)、俄罗斯和日本沿海的野生仿刺参以及美国沿海的具疣拟刺参进行遗传多样性水平和遗传结构分析。结果表明,所设计的20对引物的扩增产物均具有多态性,其中16个位点为高度多态(PIC>0.5)。遗传多样性分析结果显示,20个微卫星座位的平均观察杂合度(Ho)和平均期望杂合度(He)分别为0.39和0.69,共检测到231个等位基因(102个有效等位基因),在每个座位上获得3~20个等位基因,平均等位基因数为11.6个,20个位点在6个群体中不同程度偏离遗传平衡(P<0.05),所有群体在整体上均表现为杂合子缺失(Fis>0);5个仿刺参群体间的遗传相似系数在0.71以上,相似性较高,而仿刺参群体与具疣拟刺参的相似性则较低。聚类分析结果表明,中国群体与韩国西海岸群体聚类成一支,而俄罗斯群体、韩国东海岸群体和日本群体聚类成另外一支,聚类的先后与它们在地理分布上的海域位置有一定的相关性。

关 键 词:刺参  微卫星标记  FIASCO  遗传多样性  遗传结构
收稿时间:2011/4/14 0:00:00
修稿时间:2011/5/24 0:00:00

Development of microsatellite DNA markers of sea cucumber Apostichopus japonicus and their application in population genetic variation and structure analysis
PAN Chuan-yan , ZANG Yun-peng , LIAO Mei-jie , WANG Yin-geng , RONG Xiao-jun , ZHANG Zheng , LI Bin , CHEN Gui-ping.Development of microsatellite DNA markers of sea cucumber Apostichopus japonicus and their application in population genetic variation and structure analysis[J].Marine Fisheries Research,2012,33(4):72-82.
Authors:PAN Chuan-yan  ZANG Yun-peng  LIAO Mei-jie  WANG Yin-geng  RONG Xiao-jun  ZHANG Zheng  LI Bin  CHEN Gui-ping
Affiliation:1Ocean University of China,Qingdao 266003)(2 Key Laboratory of Sustainable Development of Marine Fisheries,Ministry of Agriculture,Qingdao Key Laboratory for Marine Fish Breeding and Biotechnology,Yellow Sea Fisheries Research Institute,Chinese Academy of Fishery Sciences,266071)(3 Shanghai Ocean University,201306)
Abstract:In order to evaluate the genetic diversity of sea cucumber Apostichopus japonicus and breed eugenic varieties, a CA microsatellite containing short fragment genomic DNA library of sea cucumber was constructed using the FIASCO(Fast Isolation by AFLP Sequences Containing Repeats)method. In 140 randomly selected and sequenced clones, 118 contained a CA repeat motif. According to Weber(1990) classification rules, the sequences were divided into three categories: 83 perfect repeat sequences without interruptions in the runs of CA or GT dinucleotides (70.4% of total), 30 imperfect repeat sequences with one or more interruptions in the run of repeats (25.4%), and 5 compound repeat sequences with adjacent tandem simple repeats of a different sequence (4.2%). Twenty pairs of primers were designed and used to investigate the polymorphism and genetic structure of wild A. japonicus collected from China(CH), Korea(KW, KE), Japan(JA) and Russia(RU). Cross amplification of twenty loci were also tested in Parastichopus parvimensis which were collected in USA(AM). The results demonstrated that all the markers were polymorphic and 16 loci had high polymorphism (PIC>0.5). The average observed and expected heterozygosities of the 20 loci were 0.39 and 0.69, respectively. In addition, a total of 231 alleles (102 effective alleles) were detected at 20 loci in the total samples and the alleles number of each locus ranges from 3 to 20 with average of 11.6. The Hardy-Weinberg Equilibrium (HWE) analysis showed that all the loci deviated from genetic equilibrium in the six populations and heterozygote deficiency occurred to different extent in total samples (Fis>0). Genetic identity of the five A. japonicus populations was 0.71, while the genetic identity between A. japonicus and P. parvimensis were quiet low. In the UPMGA tree, CH and KW populations formed a cluster, RU, JA and KE populations formed another cluster, while AM felt into a seperate cluster. The result of cluster analysis indicated that the clustering order had significant correlation with geographic distance.
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