SNP discovery and genotyping for evolutionary genetics using RAD sequencing.
SNP discovery and genotyping for evolutionary genetics using RAD sequencing.
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DOI：
10.1007/978-1-61779-228-1_9
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发表时间：
2011
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影响因子：
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通讯作者：
Cresko, William A
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作者：
Etter, Paul D;Bassham, Susan;Hohenlohe, Paul A;Johnson, Eric A;Cresko, William A
下一代测序技术正在彻底改变进化生物学领域，为以前不可能的大规模遗传分析提供了可能性。几年前还无法想象的群体遗传学、数量性状图谱、比较基因组学和地理学研究现在已经成为可能。更重要的是，这些下一代测序研究可以在目前存在很少基因组资源的生物体中进行。为了加速进化遗传学的这场革命，我们开发了限制性位点相关DNA（RAD）基因分型，这是一种使用Illumina下一代测序的方法，可以同时发现和评分数百个个体中的数万至数十万个单核苷酸多态性（SNP）标记，以最小的资源投入。在本章中，我们描述了核心RAD-seq协议，可以对其进行修改以适应多种进化遗传问题。此外，我们还讨论了与传统的基于标记的方法相比，下一代测序数据的独特方面所引起的生物信息学考虑，并概述了RAD-seq和类似数据的一些一般分析方法。尽管取得了相当大的进展，但分析工具的开发仍处于起步阶段，需要进一步开展工作，以充分量化这些数据类型的抽样方差和偏差。
Next-generation sequencing technologies are revolutionizing the field of evolutionary biology, opening the possibility for genetic analysis at scales not previously possible. Research in population genetics, quantitative trait mapping, comparative genomics, and phylogeography that was unthinkable even a few years ago is now possible. More importantly, these next-generation sequencing studies can be performed in organisms for which few genomic resources presently exist. To speed this revolution in evolutionary genetics, we have developed Restriction site Associated DNA (RAD) genotyping, a method that uses Illumina next-generation sequencing to simultaneously discover and score tens to hundreds of thousands of single-nucleotide polymorphism (SNP) markers in hundreds of individuals for minimal investment of resources. In this chapter, we describe the core RAD-seq protocol, which can be modified to suit a diversity of evolutionary genetic questions. In addition, we discuss bioinformatic considerations that arise from unique aspects of next-generation sequencing data as compared to traditional marker-based approaches, and we outline some general analytical approaches for RAD-seq and similar data. Despite considerable progress, the development of analytical tools remains in its infancy, and further work is needed to fully quantify sampling variance and biases in these data types.