Double digest RADseq: an inexpensive method for de novo SNP discovery and genotyping in model and non-model species.
Double digest RADseq: an inexpensive method for de novo SNP discovery and genotyping in model and non-model species.
复制标题
DOI：
10.1371/journal.pone.0037135
复制
发表时间：
2012
期刊：
影响因子：
3.7
通讯作者：
Hoekstra HE
中科院分区：
文献类型：
--
作者：
Peterson BK;Weber JN;Kay EH;Fisher HS;Hoekstra HE
有效和准确地确定基因型的能力是现代遗传学的关键技术，对于从临床诊断到基因型-表型关联，再到祖先重建和选择检测的研究至关重要。迄今为止，高容量、低成本的基因分型已在很大程度上通过基于“SNP芯片”的微阵列平台实现，该平台需要基因组序列和变异性的大量先验知识，并且一旦设计就仅适用于那些靶向的可变核苷酸位点。这种方法引入了大量的确定偏倚，并且固有地排除了罕见或群体特异性变异的检测，这是群体历史和基因型-表型关联的主要信息来源。在大规模并行测序仪（通常称为RAD标签或RADseq）上进行的简化代表性基因组测序实验的最新发展已经将直接测序带到了群体基因分型的问题中，但是增加的成本以及程序和分析复杂性限制了它们的广泛采用。在这里，我们描述了一个完整的实验室协议，包括自定义的组合索引方法，并附带的软件工具，以促进基因分型在大量（数百或更多）的个人的一系列标志物（数百至数十万）。我们的方法不需要事先的基因组知识，并且实现了低于当前SNP芯片技术的每个站点和每个个体的成本，同时需要类似的动手时间投资，可比的输入DNA量和下游分析时间。最后，我们提供了经验的结果，从应用这种方法在实验室交叉和野生种群的基因分型。由于其灵活性，这种改进的RADseq方法有望适用于各种生物体中的多种生物学问题。
The ability to efficiently and accurately determine genotypes is a keystone technology in modern genetics, crucial to studies ranging from clinical diagnostics, to genotype-phenotype association, to reconstruction of ancestry and the detection of selection. To date, high capacity, low cost genotyping has been largely achieved via “SNP chip” microarray-based platforms which require substantial prior knowledge of both genome sequence and variability, and once designed are suitable only for those targeted variable nucleotide sites. This method introduces substantial ascertainment bias and inherently precludes detection of rare or population-specific variants, a major source of information for both population history and genotype-phenotype association. Recent developments in reduced-representation genome sequencing experiments on massively parallel sequencers (commonly referred to as RAD-tag or RADseq) have brought direct sequencing to the problem of population genotyping, but increased cost and procedural and analytical complexity have limited their widespread adoption. Here, we describe a complete laboratory protocol, including a custom combinatorial indexing method, and accompanying software tools to facilitate genotyping across large numbers (hundreds or more) of individuals for a range of markers (hundreds to hundreds of thousands). Our method requires no prior genomic knowledge and achieves per-site and per-individual costs below that of current SNP chip technology, while requiring similar hands-on time investment, comparable amounts of input DNA, and downstream analysis times on the order of hours. Finally, we provide empirical results from the application of this method to both genotyping in a laboratory cross and in wild populations. Because of its flexibility, this modified RADseq approach promises to be applicable to a diversity of biological questions in a wide range of organisms.
登录
查看更多内容
影响因子：
48
作者：
Craig, David W.;Pearson, John V.;Szelinger, Szabolcs;Sekar, Aswin;Redman, Margot;Corneveaux, Jason J.;Pawlowski, Traci L.;Laub, Trisha;Nunn, Gary;Stephan, Dietrich A.;Homer, Nils;Huentelman, Matthew J.
通讯作者：
Huentelman, Matthew J.
影响因子：
3.7
作者：
Baird NA;Etter PD;Atwood TS;Currey MC;Shiver AL;Lewis ZA;Selker EU;Cresko WA;Johnson EA
通讯作者：
Johnson EA
影响因子：
7
作者：
Lunter, Gerton;Goodson, Martin
通讯作者：
Goodson, Martin
使用下一代 DNA 测序数据进行变异发现和基因分型的框架。
影响因子：
30.8
作者：
通讯作者：
--
影响因子：
4.1
作者：
Kenny, Elaine M.;Cormican, Paul;Morris, Derek W.
通讯作者：
Morris, Derek W.