Using classical population genetics tools with heterochroneous data: time matters!
Using classical population genetics tools with heterochroneous data: time matters!
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DOI：
10.1371/journal.pone.0005541
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发表时间：
2009
期刊：
影响因子：
3.7
通讯作者：
Hänni C
中科院分区：
文献类型：
--
作者：
Depaulis F;Orlando L;Hänni C
由于实验和微生物分子进化的最新进展以及古DNA（aDNA）的测序，来自异时数据的新多态性数据集已经出现。然而，经典的群体遗传学分析工具不考虑亚群之间的异时性，尽管在中性和群体结构测试中存在潜在的偏倚。在这里，我们的特点，这种可能的偏见使用串行聚结模拟的程度。我们首先使用一个合并的框架来生成数据集，假设没有或不同水平的异时性和对比最经典的人口遗传统计。我们发现，即使是弱水平的异时性（标准种群树平均深度的约10%）也会显著影响多态性的分布，导致高估多态性θ的水平，形成星星状的树，具有过量的稀有突变和连锁不平衡的缺陷，这是例如种群扩张的标志（可能在剧烈的瓶颈之后）。大量偏离的测试检测在相反的方向更heterochronous和平衡的数据集，与平衡树模仿特别是人口收缩，平衡选择，和人口分化。因此，我们引入简单的校正经典的多态性和种群之间的遗传距离的估计，以消除异时性驱动的偏差。最后，我们表明，这些影响确实发生在真实的aDNA数据集上，利用目前可用的洞熊（Ursus spelaeus）的序列数据，在相当长的一段时间内（22- 13万年前（KYA）），大mtDNA单倍型已被报道。考虑系列抽样改变了几个测试的结论，表明忽略异时性可以提供显着的支持，虚假的过去历史的人口和不适当的保护决策。因此，我们认为，系统地考虑异时模型时，分析覆盖了很大的时间尺度的异时样本。
New polymorphism datasets from heterochroneous data have arisen thanks to recent advances in experimental and microbial molecular evolution, and the sequencing of ancient DNA (aDNA). However, classical tools for population genetics analyses do not take into account heterochrony between subsets, despite potential bias on neutrality and population structure tests. Here, we characterize the extent of such possible biases using serial coalescent simulations. We first use a coalescent framework to generate datasets assuming no or different levels of heterochrony and contrast most classical population genetic statistics. We show that even weak levels of heterochrony (∼10% of the average depth of a standard population tree) affect the distribution of polymorphism substantially, leading to overestimate the level of polymorphism θ, to star like trees, with an excess of rare mutations and a deficit of linkage disequilibrium, which are the hallmark of e.g. population expansion (possibly after a drastic bottleneck). Substantial departures of the tests are detected in the opposite direction for more heterochroneous and equilibrated datasets, with balanced trees mimicking in particular population contraction, balancing selection, and population differentiation. We therefore introduce simple corrections to classical estimators of polymorphism and of the genetic distance between populations, in order to remove heterochrony-driven bias. Finally, we show that these effects do occur on real aDNA datasets, taking advantage of the currently available sequence data for Cave Bears (Ursus spelaeus), for which large mtDNA haplotypes have been reported over a substantial time period (22–130 thousand years ago (KYA)). Considering serial sampling changed the conclusion of several tests, indicating that neglecting heterochrony could provide significant support for false past history of populations and inappropriate conservation decisions. We therefore argue for systematically considering heterochroneous models when analyzing heterochroneous samples covering a large time scale.
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影响因子：
4.9
作者：
Calvignac, Sebastien;Hughes, Sandrine;Hanni, Catherine
通讯作者：
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影响因子：
3.9
作者：
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DOI：
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发表时间：
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影响因子：
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通讯作者：
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影响因子：
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作者：
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