A highly robust and optimized sequence-based approach for genetic polymorphism discovery and genotyping in large plant populations.
A highly robust and optimized sequence-based approach for genetic polymorphism discovery and genotyping in large plant populations.
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DOI：
10.1007/s00122-016-2736-9
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发表时间：
2016-09
期刊：
影响因子：
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通讯作者：
Luo Z
中科院分区：
文献类型：
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作者：
Jiang N;Zhang F;Wu J;Chen Y;Hu X;Fang O;Leach LJ;Wang D;Luo Z
这种优化的方法提供了计算工具和文库构建协议，可以最大限度地增加均匀覆盖植物基因组的基因组序列读取的数量，并最小化代表叶绿体DNA和rRNA基因的序列读取数量。人们可以实现开发的计算工具来可行地设计他们自己的RAD-SEQ实验，以使用基因组序列的信息以及理想但不一定的基因组中序列多态分布的信息来实现对大型植物种群的序列变异标记的预期覆盖。下一代测序技术的出现激发了人们最近对发展基于序列的大种群全基因组遗传变异的识别和基因分型的兴趣，RAD-SEQ就是一个典型的例子。如果没有适当地考虑到叶绿体和rRNA基因可能占据所产生的序列读数的60%的事实，目前的RAD-SEQ设计对于植物和作物物种来说可能是非常低效的。我们在这里提出了一个通用的计算工具来优化任何植物物种的RAD-seq设计，并通过在二倍体和同源四倍体拟南芥和马铃薯的四个植物群体中筛选和分型序列变异来实验测试优化的设计。来自优化的RAD-SEQ实验的序列数据表明，不希望的叶绿体和rRNA贡献的序列读数可以控制在3-10%。此外，与文献中的其他主流竞争对手相比，优化的RAD-SEQ方法能够预先设计所需的一致性和密度，覆盖感兴趣的基因组上的高质量序列多态标记，并以具有竞争力的成本对大型植物或作物种群进行基因分型。本文的在线版本(doi：10.1007/s00122-0162736-9)包含补充材料，授权用户可以使用。
This optimized approach provides both a computational tool and a library construction protocol, which can maximize the number of genomic sequence reads that uniformly cover a plant genome and minimize the number of sequence reads representing chloroplast DNA and rRNA genes. One can implement the developed computational tool to feasibly design their own RAD-seq experiment to achieve expected coverage of sequence variant markers for large plant populations using information of the genome sequence and ideally, though not necessarily, information of the sequence polymorphism distribution in the genome. Advent of the next generation sequencing techniques motivates recent interest in developing sequence-based identification and genotyping of genome-wide genetic variants in large populations, with RAD-seq being a typical example. Without taking proper account for the fact that chloroplast and rRNA genes may occupy up to 60 % of the resulting sequence reads, the current RAD-seq design could be very inefficient for plant and crop species. We presented here a generic computational tool to optimize RAD-seq design in any plant species and experimentally tested the optimized design by implementing it to screen for and genotype sequence variants in four plant populations of diploid and autotetraploid Arabidopsis and potato Solanum tuberosum. Sequence data from the optimized RAD-seq experiments shows that the undesirable chloroplast and rRNA contributed sequence reads can be controlled at 3–10 %. Additionally, the optimized RAD-seq method enables pre-design of the required uniformity and density in coverage of the high quality sequence polymorphic markers over the genome of interest and genotyping of large plant or crop populations at a competitive cost in comparison to other mainstream rivals in the literature. The online version of this article (doi:10.1007/s00122-016-2736-9) contains supplementary material, which is available to authorized users.