摘要
Methods for estimating synonymous and nonsynonymous substitution rates among protein-coding sequences adopt different mutation (substitution) models with subtle yet significant differences, which lead to different estimates of evolutionary information. Little attention has been devoted to the comparison of methods for obtaining reliable estimates since the amount of sequence variations within targeted datasets is always unpredictable. To our knowledge, there is little information available in literature about evaluation of these different methods. In this study, we compared six widely used methods and provided with evaluation results using simulated sequences. The results indicate that incorporating sequence features (such as transition/transversion bias and nucleotide/codon frequency bias) into methods could yield better performance. We recommend that conclusions related to or derived from Ka and Ks analyses should not be readily drawn only according to results from one method.
Methods for estimating synonymous and nonsynonymous substitution rates among protein-coding sequences adopt different mutation (substitution) models with subtle yet significant differences, which lead to different estimates of evolutionary information. Little attention has been devoted to the comparison of methods for obtaining reliable estimates since the amount of sequence variations within targeted datasets is always unpredictable. To our knowledge, there is little information available in literature about evaluation of these different methods. In this study, we compared six widely used methods and provided with evaluation results using simulated sequences. The results indicate that incorporating sequence features (such as transition/transversion bias and nucleotide/codon frequency bias) into methods could yield better performance. We recommend that conclusions related to or derived from Ka and Ks analyses should not be readily drawn only according to results from one method.
基金
This work was supported by the Ministry of Science and Technology of China(Grant No.2001AA231061)
the National Natural Science Foundation of China(Grant No.30270748)awarded to JY.We thank Mr.Jun Li for valuable discussion.
