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利用转录组数据开发意大利蜜蜂的SSR分子标记
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  • 英文篇名:Exploitation of SSR markers for Apis mellifera ligustica based on transcriptome data
  • 作者:郭睿 ; 陈华枝 ; 庄天艺 ; 熊翠玲 ; 郑燕珍 ; 付中民 ; 陈恒 ; 陈大福
  • 英文作者:GUO Rui;CHEN Huazhi;ZHUANG Tianyi;XIONG Cuiling;ZHENG Yanzheng;FU Zhongmin;CHEN Hen;CHEN Dafu;College of Bee Science, Fujian Agriculture and Forestry University;
  • 关键词:转录组 ; 意大利蜜蜂 ; SSR ; 特异性引物
  • 英文关键词:transcriptome;;Apis mellifera ligustica;;SSR;;specific primer
  • 中文刊名:ANHU
  • 英文刊名:Journal of Anhui Agricultural University
  • 机构:福建农林大学蜂学学院;
  • 出版日期:2018-06-20 17:21
  • 出版单位:安徽农业大学学报
  • 年:2018
  • 期:v.45;No.163
  • 基金:现代农业产业技术体系建设专项基金(CARS-44-KXJ7);; 福建省教育厅中青年教师教育科研项目(JAT170158);; 福建省大学生创新创业训练计划项目(201610389113,20171038058)共同资助
  • 语种:中文;
  • 页:ANHU201803005
  • 页数:5
  • CN:03
  • ISSN:34-1162/S
  • 分类号:26-30
摘要
意大利蜜蜂(简称意蜂)是自然界重要的授粉昆虫,广泛用于世界各国的养蜂生产,具有很高的生态和经济价值。为了开发意蜂的SSR分子标记,利用MISA软件对基于前期获得的意蜂幼虫肠道转录组数据组装得到的12 115条unigenes进行搜索,共预测出分布于2 149条unigenes的6 312个SSR位点,其中主要的重复类型为二核苷酸重复(54.42%)和三核苷酸重复(32.49%),主要基元为AT/AT(31.2%)和AG/CT(18.6%)。进一步利用软件设计出18 444对特异性引物,随机选取24对引物对国内3个不同来源的意蜂幼虫样品进行SSR位点扩增,有22对成功扩增出目的片段。研究开发出的SSR分子标记可用于意蜂的种群遗传和分子进化等研究,结果表明利用转录组数据鉴定非模式生物SSR位点的方法可行且高效。
        Apis mellifera ligustica is an important pollinating insect and widely used in beekeeping industry in various countries in the world, thus it has high ecological and economic value. The aim of this study was to develop SSR markers for A. m. ligustica based on our previously obtained transcriptome data. Here, all unigenes were scanned using MISA software and 6 312 SSR loci within 2 149 unigenes were predicted. The largest SSRs were dinucleotide(54.42%) and trinucleotide(32.49%), and for the former, AT/AT(31.2%) and AG/CT(18.6%) were the most abundant. Furthermore, a total of 18 444 primer pairs were designed using softwares, and 24 pairs were randomly selected for amplifying SSR loci in A. m. ligustica from 3 different regions in China, and the result showed 22 target fragments were successfully amplified. The developed SSR markers can be applied to A. m. ligustica studies such as population genetics and molecular evolution. Our data demonstrated that developing SSR markers of non-model organism based on transcriptome data is feasible and efficient.
引文
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