Literature DB >> 35920867

dN/dS-H, a New Test to Distinguish Different Selection Modes in Protein Evolution and Cancer Evolution.

Xun Gu1,2,3.   

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).
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Nearly-neutral evolution; Neutral evolution; Positive selection; Strong functional constraint; dN/dS test

Mesh:

Substances:

Year:  2022        PMID: 35920867     DOI: 10.1007/s00239-022-10064-2

Source DB:  PubMed          Journal:  J Mol Evol        ISSN: 0022-2844            Impact factor:   3.973


  57 in total

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Authors:  J P Bielawski; K A Dunn; Z Yang
Journal:  Genetics       Date:  2000-11       Impact factor: 4.562

2.  Ratios of radical to conservative amino acid replacement are affected by mutational and compositional factors and may not be indicative of positive Darwinian selection.

Authors:  Tal Dagan; Yael Talmor; Dan Graur
Journal:  Mol Biol Evol       Date:  2002-07       Impact factor: 16.240

3.  Tertiary windowing to detect positive diversifying selection.

Authors:  Ann-Charlotte Berglund; Björn Wallner; Arne Elofsson; David A Liberles
Journal:  J Mol Evol       Date:  2005-04       Impact factor: 2.395

4.  Molecular Evolution in Large Steps-Codon Substitutions under Positive Selection.

Authors:  Qingjian Chen; Ziwen He; Ao Lan; Xu Shen; Haijun Wen; Chung-I Wu
Journal:  Mol Biol Evol       Date:  2019-09-01       Impact factor: 16.240

5.  Adaptation of iso-tRNA concentration to mRNA codon frequency in the eukaryote cell.

Authors:  G Chavancy; A Chevallier; A Fournier; J P Garel
Journal:  Biochimie       Date:  1979       Impact factor: 4.079

6.  Comprehensive Characterization of Cancer Driver Genes and Mutations.

Authors:  Matthew H Bailey; Collin Tokheim; Eduard Porta-Pardo; Sohini Sengupta; Denis Bertrand; Amila Weerasinghe; Antonio Colaprico; Michael C Wendl; Jaegil Kim; Brendan Reardon; Patrick Kwok-Shing Ng; Kang Jin Jeong; Song Cao; Zixing Wang; Jianjiong Gao; Qingsong Gao; Fang Wang; Eric Minwei Liu; Loris Mularoni; Carlota Rubio-Perez; Niranjan Nagarajan; Isidro Cortés-Ciriano; Daniel Cui Zhou; Wen-Wei Liang; Julian M Hess; Venkata D Yellapantula; David Tamborero; Abel Gonzalez-Perez; Chayaporn Suphavilai; Jia Yu Ko; Ekta Khurana; Peter J Park; Eliezer M Van Allen; Han Liang; Michael S Lawrence; Adam Godzik; Nuria Lopez-Bigas; Josh Stuart; David Wheeler; Gad Getz; Ken Chen; Alexander J Lazar; Gordon B Mills; Rachel Karchin; Li Ding
Journal:  Cell       Date:  2018-04-05       Impact factor: 41.582

7.  Natural selection on protein-coding genes in the human genome.

Authors:  Carlos D Bustamante; Adi Fledel-Alon; Scott Williamson; Rasmus Nielsen; Melissa Todd Hubisz; Stephen Glanowski; David M Tanenbaum; Thomas J White; John J Sninsky; Ryan D Hernandez; Daniel Civello; Mark D Adams; Michele Cargill; Andrew G Clark
Journal:  Nature       Date:  2005-10-20       Impact factor: 49.962

8.  Targeting Epigenetic Crosstalk as a Therapeutic Strategy for EZH2-Aberrant Solid Tumors.

Authors:  Xun Huang; Juan Yan; Min Zhang; Yafang Wang; Yi Chen; Xuhong Fu; Rongrui Wei; Xing-Ling Zheng; Zhiwei Liu; Xiong Zhang; Hong Yang; Bingbing Hao; Yan-Yan Shen; Yi Su; Xiaoji Cong; Min Huang; Minjia Tan; Jian Ding; Meiyu Geng
Journal:  Cell       Date:  2018-09-13       Impact factor: 41.582

9.  MuSiC: identifying mutational significance in cancer genomes.

Authors:  Nathan D Dees; Qunyuan Zhang; Cyriac Kandoth; Michael C Wendl; William Schierding; Daniel C Koboldt; Thomas B Mooney; Matthew B Callaway; David Dooling; Elaine R Mardis; Richard K Wilson; Li Ding
Journal:  Genome Res       Date:  2012-07-03       Impact factor: 9.043

10.  EPAS1 gain-of-function mutation contributes to high-altitude adaptation in Tibetan horses.

Authors:  Xuexue Liu; Yanli Zhang; Yefang Li; Jianfei Pan; Dandan Wang; Weihuang Chen; Zhuqing Zheng; Xiaohong He; Qianjun Zhao; Yabin Pu; Weijun Guan; Jianlin Han; Ludovic Orlando; Yuehui Ma; Lin Jiang
Journal:  Mol Biol Evol       Date:  2019-07-02       Impact factor: 16.240

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