RAD Capture (Rapture): Flexible and Efficient Sequence-Based Genotyping
RAD Capture (Rapture): Flexible and Efficient Sequence-Based Genotyping
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DOI：
10.1534/genetics.115.183665
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发表时间：
2016-02-01
期刊：
影响因子：
3.3
通讯作者：
Miller, Michael R.
中科院分区：
文献类型：
--
作者：
Ali, Omar A.;O'Rourke, Sean M.;Miller, Michael R.
大规模并行测序已经彻底改变了生物学的许多领域，但是对许多个体的大量DNA进行测序成本高昂，并且对于许多研究来说是不必要的。基因组复杂性降低技术，如序列捕获和限制性内切酶为基础的方法，使每单位成本分析更多的个人。尽管它们的效用，目前的复杂性降低方法有局限性，特别是当大量的个人进行分析。在这里，我们开发了一个大大改进的限制性位点相关DNA（RAD）测序协议和一个新的方法称为Rapture（RAD捕获）。新的RAD方案通过将RAD标签分离和测序文库制备分为两个不同的步骤来提高通用性。该方案还回收了更多独特的（非克隆）RAD片段，这改善了标准RAD和Rapture分析。然后，Rapture使用所选RAD标签的溶液中捕获来将测序读数靶向至所需基因座。Rapture结合了RAD和序列捕获的优点，即，对于许多个体而言非常便宜和快速的文库制备以及所分析的基因组基因座的数量和位置的高特异性。我们的研究结果表明，Rapture是一种快速灵活的技术，能够以最小的测序和文库制备成本分析大量个体。这里提出的方法应该提高效率的遗传分析的许多方面的农业，环境和生物医学科学。
Massively parallel sequencing has revolutionized many areas of biology, but sequencing large amounts of DNA in many individuals is cost-prohibitive and unnecessary for many studies. Genomic complexity reduction techniques such as sequence capture and restriction enzyme-based methods enable the analysis of many more individuals per unit cost. Despite their utility, current complexity reduction methods have limitations, especially when large numbers of individuals are analyzed. Here we develop a much improved restriction site-associated DNA (RAD) sequencing protocol and a new method called Rapture (RAD capture). The new RAD protocol improves versatility by separating RAD tag isolation and sequencing library preparation into two distinct steps. This protocol also recovers more unique (nonclonal) RAD fragments, which improves both standard RAD and Rapture analysis. Rapture then uses an in-solution capture of chosen RAD tags to target sequencing reads to desired loci. Rapture combines the benefits of both RAD and sequence capture, i.e., very inexpensive and rapid library preparation for many individuals as well as high specificity in the number and location of genomic loci analyzed. Our results demonstrate that Rapture is a rapid and flexible technology capable of analyzing a very large number of individuals with minimal sequencing and library preparation cost. The methods presented here should improve the efficiency of genetic analysis for many aspects of agricultural, environmental, and biomedical science.