The Next Generation of Molecular Markers From Massively Parallel Sequencing of Pooled DNA Samples
The Next Generation of Molecular Markers From Massively Parallel Sequencing of Pooled DNA Samples
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DOI：
10.1534/genetics.110.114397
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发表时间：
2010-09-01
期刊：
影响因子：
3.3
通讯作者：
Schloetterer, Christian
中科院分区：
文献类型：
--
作者：
Futschik, Andreas;Schloetterer, Christian
下一代测序（NGS）即将彻底改变遗传分析。目前，NGS技术主要用于对单个基因组进行测序。由于所需的高序列覆盖率，群体规模分析的成本仍然太高，不允许扩展到非模式生物。在这里，我们表明，NGS的个人池往往是更有效的SNP发现，并提供更准确的等位基因频率估计，即使考虑到测序错误。我们修改人口遗传估计田岛的PI和沃特森的θ获得无偏估计NGS池数据。给定相同的测序工作，所得到的估计往往表现出更好的性能比那些从个人测序。虽然我们的分析也表明，NGS的池的个人将不是在所有情况下都是可取的，它提供了一个具有成本效益的方法来估计等位基因频率在全基因组范围内。
Next generation sequencing (NGS) is about to revolutionize genetic analysis. Currently NGS techniques are mainly used to sequence individual genomes. Due to the high sequence coverage required, the costs for population-scale analyses are still too high to allow an extension to nonmodel organisms. Here, we show that NGS of pools of individuals is often more effective in SNP discovery and provides more accurate allele frequency estimates, even when taking sequencing errors into account. We modify the population genetic estimators Tajima's pi and Watterson's theta to obtain unbiased estimates from NGS pooling data. Given the same sequencing effort, the resulting estimators often show a better performance than those obtained from individual sequencing. Although our analysis also shows that NGS of pools of individuals will not be preferable under all circumstances, it provides a cost-effective approach to estimate allele frequencies on a genome-wide scale.