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Microsatellite Markers in Plants and Insects Part II: Databases and in Silico Tools for Microsatellite Mining and Analyzing Population Genetic Stratification

机译:植物和昆虫中的微卫星标记第二部分:用于微卫星挖掘和分析种群遗传分层的数据库和计算机软件

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摘要

Nucleotide sequence information available in searchable sequence databases and the free in silico software with which to extract and analyze microsatellite data continues to grow at a rapid rate across eukaryote taxa. The sheer amount of information available means thai a comprehensive or exhaustive review of databases and free bioinformatic tools lies beyond the purview of any journal review. The purpose of this review is therefore to provide targeted information aimed at helping the insect and plant biologist effectively utilize in silico resources to find, navigate and analyze empirically derived data from sequence databases. The objectives are threefold. First, since the basic characteristics of microsatellites make them the markers of choice for studies of genetic structure that underlie adaptation and evolution, these will be delineated. Second, because sequence databases are increasingly mined for microsatellites, the major databases are discussed, as well as, available programs for in silico mining of sequence databases to retrieve microsatellites for a species of interest. Lastly, a general review is given of population genetics software for in silico genetic analyses of microsatellite data to determine population genetic structure, phylogenetic relationships, and genetic diversity in a species of interest.
机译:可搜索序列数据库和免费的用于提取和分析微卫星数据的in silico软件中提供的核苷酸序列信息在整个真核生物类群中持续快速增长。可获得的大量信息意味着对数据库和免费的生物信息学工具的全面或详尽的评论超出了任何期刊评论的范围。因此,本综述的目的是提供有针对性的信息,旨在帮助昆虫和植物生物学家有效利用计算机资源,从序列数据库中找到,导航和分析经验导出的数据。目标是三重的。首先,由于微卫星的基本特征使其成为适应和进化基础的遗传结构研究的选择标记,因此将对其进行描述。其次,由于越来越多地从微卫星中挖掘序列数据库,因此讨论了主要数据库以及可用的程序,以计算机方式对序列数据库进行计算机挖掘,以检索感兴趣物种的微卫星。最后,对种群遗传学软件进行了总体综述,以对微卫星数据进行计算机遗传学分析,以确定感兴趣物种的种群遗传结构,系统发育关系和遗传多样性。

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