Population genetics without intraspecific data.
Population genetics without intraspecific data.
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DOI：
10.1093/molbev/msm085
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发表时间：
2007-08
影响因子：
10.7
通讯作者：
J. Thorne;S. Choi;Jiaye Yu;P. Higgs;H. Kishino
中科院分区：
文献类型：
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作者：
J. Thorne;S. Choi;Jiaye Yu;P. Higgs;H. Kishino
计算生物学的一个中心目标是从DNA和蛋白质序列数据预测表型。最近的序列变化模型使用计算机预测系统，以纳入表型对进化速率的影响。这些模型已被设计用于分析来自不同物种的序列数据，并已伴随着统计技术，用于估计模型参数时，表型的掺入诱导序列位置之间的依赖性变化。一个困难，这些努力联系表型和种间进化是进化发生在人口，种间模型的参数应该有人口遗传学的解释。我们展示了两个例子，如何人口遗传学的解释可以分配到进化模型。第一个例子考虑了RNA二级结构对序列变化的影响，第二个例子反映了蛋白质三级结构影响非同义取代率的趋势。我们认为，数据的统计拟合不应该是评估序列变化模型的唯一标准。一个好的种间模型也应该产生一个明确的和生物学上合理的群体遗传解释。
A central goal of computational biology is the prediction of phenotype from DNA and protein sequence data. Recent models of sequence change use in silico prediction systems to incorporate the effects of phenotype on evolutionary rates. These models have been designed for analyzing sequence data from different species and have been accompanied by statistical techniques for estimating model parameters when the incorporation of phenotype induces dependent change among sequence positions. A difficulty with these efforts to link phenotype and interspecific evolution is that evolution occurs within populations, and parameters of interspecific models should have population genetic interpretations. We show, with two examples, how population genetic interpretations can be assigned to evolutionary models. The first example considers the impact of RNA secondary structure on sequence change, and the second reflects the tendency for protein tertiary structure to influence nonsynonymous substitution rates. We argue that statistical fit to data should not be the sole criterion for assessing models of sequence change. A good interspecific model should also yield a clear and biologically plausible population genetic interpretation.