dN/dS-H, a New Test to Distinguish Different Selection Modes in Protein Evolution and Cancer Evolution
- PMID: 35920867
- DOI: 10.1007/s00239-022-10064-2
dN/dS-H, a New Test to Distinguish Different Selection Modes in Protein Evolution and Cancer Evolution
Abstract
One of the most popular measures in the analysis of protein sequence evolution is the ratio of nonsynonymous distance (dN) to synonymous distance (dS). Under the assumption that synonymous substitutions in the coding region are selectively neutral, the dN/dS ratio can be used to statistically detect the adaptive evolution (or purifying selection) if dN/dS > 1 (or dN/dS < 1) significantly. However, due to strong structural constraints and/or variable functional constraints imposed on amino acid sites, most encoding genes in most species have demonstrated dN/dS < 1. Consequently, the statistical power for testing dN/dS = 1 may be insufficient to distinguish between different selection modes. In this paper, we propose a more powerful test, called dN/dS-H, in which a new parameter H, a relative measure of rate variation among sites, was introduced. Given the condition of strong purifying selections at some sites, the dN/dS-H model predicts dN/dS = 1-H for neutral evolution, dN/dS < 1-H for nearly neutral selection, and dN/dS > 1-H for adaptive evolution. The potential of this new method for resolving the neutral-adaptive debates is illustrated by the protein sequence evolution in vertebrates, Drosophila and yeasts, as well as somatic cancer evolution (specialized as the CN/CS-H test).
Keywords: Nearly-neutral evolution; Neutral evolution; Positive selection; Strong functional constraint; dN/dS test.
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Similar articles
-
Molecular evolution of the Bovini tribe (Bovidae, Bovinae): is there evidence of rapid evolution or reduced selective constraint in Domestic cattle?BMC Genomics. 2009 Apr 24;10:179. doi: 10.1186/1471-2164-10-179. BMC Genomics. 2009. PMID: 19393048 Free PMC article.
-
The influence of selection for protein stability on dN/dS estimations.Genome Biol Evol. 2014 Oct 28;6(10):2956-67. doi: 10.1093/gbe/evu223. Genome Biol Evol. 2014. PMID: 25355808 Free PMC article.
-
The roles of positive and negative selection in the molecular evolution of insect endosymbionts.Gene. 2005 Aug 1;355:1-10. doi: 10.1016/j.gene.2005.05.021. Gene. 2005. PMID: 16039807
-
Analysis of selection in protein-coding sequences accounting for common biases.Brief Bioinform. 2021 Sep 2;22(5):bbaa431. doi: 10.1093/bib/bbaa431. Brief Bioinform. 2021. PMID: 33479739 Review.
-
Extensive purifying selection acting on synonymous sites in HIV-1 Group M sequences.Virol J. 2008 Dec 23;5:160. doi: 10.1186/1743-422X-5-160. Virol J. 2008. PMID: 19105834 Free PMC article. Review.
Cited by
-
Unraveling the Drivers of Tumorigenesis in the Context of Evolution: Theoretical Models and Bioinformatics Tools.J Mol Evol. 2023 Aug;91(4):405-423. doi: 10.1007/s00239-023-10117-0. Epub 2023 May 29. J Mol Evol. 2023. PMID: 37246992 Review.
-
Strength of selection in lung tumors correlates with clinical features better than tumor mutation burden.Sci Rep. 2024 Jun 3;14(1):12732. doi: 10.1038/s41598-024-63468-z. Sci Rep. 2024. PMID: 38831004 Free PMC article.
References
-
- Akashi H, Osada N, Ohta T (2012) Weak selection and protein evolution. Genetics 192:15–31 - DOI
-
- Bailey MH, Tokheim C, Porta-Pardo E et al (2018) Comprehensive characterization of cancer driver genes and mutations. Cell 173:371. https://doi.org/10.1016/j.cell.2018.02.060 - DOI - PubMed - PMC
-
- Bailey C, Black JRM, Reading JL et al (2021) Tracking cancer evolution through the disease course. Cancer Discov 11:916–932 - DOI
-
- Bennetzen JL, Hall BD (1982) Codon selection in yeast. J Biol Chem 257:3026–3031 - DOI
-
- Berglund AC, Wallner B, Elofsson A, Liberles DA (2005) Tertiary windowing to detect positive diversifying selection. J Mol Evol. https://doi.org/10.1007/s00239-004-0223-4 - DOI - PubMed
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Medical
Molecular Biology Databases