Covariation of GC content and the silent site substitution rate in rodents: implications for methodology and for the evolution of isochores
Covariation of GC content and the silent site substitution rate in rodents: implications for methodology and for the evolution of isochores
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DOI：
10.1016/s0378-1119(00)00489-3
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发表时间：
2000-12-30
期刊：
影响因子：
3.5
通讯作者：
Williams, EJB
中科院分区：
文献类型：
--
作者：
Hurst, LD;Williams, EJB
许多测试选择主义和中立主义模型的尝试使用了对同源基因的同义(Ks)和非同义(Ka)替换率的估计。例如，在中性条件下，比预期更强的Ka-Ks相关性被认为表明了选择的作用，而Ks-GC4相关性的缺失被认为与中性等温线演化模型不一致。然而，我们前面已经表明，这两个结果对估计Ka和Ks的方法都很敏感。使用最大似然(ML)估计(GY94)，我们发现Ks和GC4之间存在正相关，Ka和Ks之间只有弱相关，低于中性预期下的预期。这种ML方法在计算上很慢。最近，提供了这种ML方法的一种新的特殊近似(YN00)。这实际上是李的协议的扩展，但这也允许密码子的使用偏向。这种方法在计算上几乎是瞬时的，因此在大数据集的分析中具有很大的实用价值。在这里，我们问这种方法是否可能具有这样的适用性。为此，我们问它是否也恢复了这两个不寻常的结果。我们报告说，当ML和早期的特别方法不一致时，YN00恢复了ML方法所描述的结果，即GC4和Ks之间的正相关，Ks和Ka之间的弱相关。如果ML方法是可信的，那么YN00也可以被认为是分析大型数据集的一种足够可靠的方法。假设是这样的话，我们也会进一步分析模式。例如，我们发现GC4和Ks之间的正相关可能在一定程度上是一种突变偏向，在GC富集区有更多的甲基诱导的CpG-->；TPG突变。至于等值线的进化，似乎不适合用GC和Ks之间缺乏相关性作为反对或支持任何模型的确凿证据。我们认为，如果正相关是真实的，那么这就很难与等厚线形成的有偏见的基因转换模型相协调，因为这预示着负相关。(C)2000 Elsevier Science B.V.保留所有权利。
Many attempts to test selectionist and neutralist models employ estimates of synonymous (Ks) and non-synonymous (Ka) substitution rates of orthologous genes. For example, a stronger Ka-Ks correlation than expected under neutrality has been argued to indicate a role for selection and the absence of a Ks-GC4 correlation has been argued to be inconsistent with neutral models for isochore evolution. However, both of these results, we have shown previously, are sensitive to the method by which Ka and Ks are estimated. Using a maximum likelihood (ML) estimator (GY94) we found a positive correlation between Ks and GC4 and only a weak correlation between Ka and Ks, lower than expected under neutral expectations. This ML method is computationally slow. Recently, a new ad hoc approximation of this ML method has been provided (YN00). This is effectively an extension of Li's protocol but that also allows for codon usage bias. This method is computationally near-instantaneous and therefore potentially of great utility for analysis of large datasets. Here we ask whether this method might have such applicability. To this end we ask whether it too recovers the two unusual results. We report that when the ML and earlier ad hoc methods disagree, YN00 recovers the results described by the ML methods, i.e. a positive correlation between GC4 and Ks and only a weak correlation between Ks and Ka. If the ML method can be trusted, then YN00 can also be considered an adequately reliable method for analysis of large datasets. Assuming this to be so we also analyze further the patterns. We show, for example, that the positive correlation between GC4 and Ks is probably in part a mutational bias, there being more methyl induced CpG --> TpG mutations in GC rich regions. As regards the evolution of isochores, it seems inappropriate to use the claimed lack of a correlation between GC and Ks as definitive evidence either against or for any model. If the positive correlation is real then, we argue, this is hard to reconcile with the biased gene conversion model for isochore formation as this predicts a negative correlation. (C) 2000 Elsevier Science B.V. All rights reserved.