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Updated: Jun 11, 2026

A Protocol for Functional Assessment of Whole-Protein Saturation Mutagenesis Libraries Utilizing High-Throughput Sequencing
Published on: July 3, 2016
iKa/Ks: Estimating the Selection Pressure and Evolutionary Rate of Proteins under the Non-neutral Hypothesis of
Jiachen Ye1, Chunmei Cui1, Rui Fan1
1Department of Biomedical Informatics, State Key Laboratory of Vascular Homeostasis and Remodeling, School of Basic Medical Sciences, Peking University, 38 Xueyuan Rd, Beijing 100191, China.
Abstract:
The Nonsynonymous/Synonymous substitution rate ratio (Ka/Ks) is a widely used metric to estimate the selection pressure and evolutionary rate of proteins in comparative genomics. A key assumption of Ka/Ks is that synonymous mutations are evolutionarily neutral and not subject to natural selection. However, growing evidence has demonstrated that synonymous mutations are non-neutral and contribute to diseases through a number of mechanisms, such as altering miRNA regulation. This suggests that synonymous mutations also undergo selection, and thus the Ka/Ks framework should be reconsidered. To address this, we propose iKa/Ks, an improved Ka/Ks model that redefines the neutral substitution rate by incorporating the functional impact of synonymous mutations on miRNA regulation. Our results show that iKa/Ks outperforms conventional Ka/Ks in capturing evolutionary constraints, as demonstrated by its stronger correlation with expression distance between human and mouse for genes with the largest rank differences between the two methods. Furthermore, case studies reveal that iKa/Ks can identify positively or negatively selected genes that are missed by conventional Ka/Ks. For example, protein TMEM72 is identified as positively selected by iKa/Ks (1.14) but negatively selected by the conventional Ka/Ks (0.21), with additional evidence supporting its rapid evolution. These results highlight the power of iKa/Ks in providing more biologically relevant insights into protein evolution. All source code and data are freely available at http://www.cuilab.cn/ikaks.
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