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Bayesian statistical treatment of the fluorescence of AFLP bands leads to accurate genetic structure inference

机译:贝叶斯对AFLP带荧光的统计处理可导致准确的遗传结构推断

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摘要

Ever since the introduction of allozymes in the 1960s, evolutionary biologists and ecologists have continued to search for more powerful molecular markers to estimate important parameters such as effective population size and migration rates and to make inferences about the demographic history of populations, the relationships between individuals and the genetic architecture of phenotypic variation (Bensch & Akesson 2005; Bonin 2007). Choosing a marker requires a thorough consideration of the trade-offs associated with the different techniques and the type of data obtained from them. Some markers can be very informative but require substantial amounts of start-up time (e.g. microsatellites), while others require very little time but are much less polymorphic. Amplified fragment length polymorphism (AFLP) is a firmly established molecular marker technique that falls in this latter category. AFLPs are widely distributed throughout the genome and can be used on organisms for which there is no a priori sequence information (Meudt & Clarke 2007). These properties together with their moderate cost and short start-up time have made them the method of choice for many molecular ecology studies of wild species (Bensch & Akesson 2005). However, they have a major disadvantage, they are dominant. This represents a very important limitation because many statistical genetics methods appropriate for molecular ecology studies require the use of codominant markers. In this issue, Foll (2010) present an innovative hierarchical Bayesian method that overcomes this limitation. The proposed approach represents a comprehensive statistical treatment of the fluorescence of AFLP bands and leads to accurate inferences about the genetic structure of natural populations. Besides allowing a quasi-codominant treatment of AFLPs, this new method also solves the difficult problems posed by subjectivity in the scoring of AFLP bands.
机译:自从1960年代引入同工酶以来,进化生物学家和生态学家一直在寻找更强大的分子标记,以估计重要的参数,例如有效的种群数量和迁移率,并推断出种群的人口历史,个体之间的关系。以及表型变异的遗传结构(Bensch&Akesson 2005; Bonin 2007)。选择标记需要彻底考虑与不同技术相关的权衡以及从中获得的数据类型。一些标记可能非常有用,但需要大量的启动时间(例如,微卫星),而其他标记则只需要很少的时间,但多态性要少得多。扩增片段长度多态性(AFLP)是一种牢固建立的分子标记技术,属于后一类。 AFLP广泛分布在整个基因组中,可用于没有先验序列信息的生物(Meudt&Clarke 2007)。这些特性以及适中的成本和较短的启动时间使其成为许多野生物种分子生态学研究的首选方法(Bensch&Akesson 2005)。但是,它们有一个主要缺点,即占主导地位。这代表了一个非常重要的局限性,因为许多适合分子生态学研究的统计学遗传学方法要求使用共性标记。在本期杂志中,Foll(2010)提出了一种创新的分层贝叶斯方法,该方法克服了这一局限性。所提出的方法代表了AFLP条带荧光的全面统计处理,并导致对自然种群遗传结构的准确推断。除了允许对AFLP进行准共轭处理外,这种新方法还解决了AFLP频段评分中的主观性带来的难题。

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