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How Do Variable Substitution Rates Influence Ka and Ks Calculations?
The ratio of nonsynonymous substitution rate (Ka) to synonymous substitution rate (Ks) is widely used as an indicator of selective pressure at sequence level among different species, and diverse mutation models have been incorporated into several computing methods. We have previously developed a new...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5054415/ https://www.ncbi.nlm.nih.gov/pubmed/19944384 http://dx.doi.org/10.1016/S1672-0229(08)60040-6 |
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author | Wang, Dapeng Zhang, Song He, Fuhong Zhu, Jiang Hu, Songnian Yu, Jun |
author_facet | Wang, Dapeng Zhang, Song He, Fuhong Zhu, Jiang Hu, Songnian Yu, Jun |
author_sort | Wang, Dapeng |
collection | PubMed |
description | The ratio of nonsynonymous substitution rate (Ka) to synonymous substitution rate (Ks) is widely used as an indicator of selective pressure at sequence level among different species, and diverse mutation models have been incorporated into several computing methods. We have previously developed a new γ-MYN method by capturing a key dynamic evolution trait of DNA nucleotide sequences, in consideration of varying mutation rates across sites. We now report a further improvement of NG, LWL, MLWL, LPB, MLPB, and YN methods based on an introduction of gamma distribution to illustrate the variation of raw mutation rate over sites. The novelty comes in two ways: (1) we incorporate an optimal gamma distribution shape parameter a into γ-NG, γ-LWL, γ-MLWL, γ-LPB, γ-MLPB, and γ-YN methods; (2) we investigate how variable substitution rates affect the methods that adopt different models as well as the interplay among four evolutional features with respect to Ka/Ks computations. Our results suggest that variable substitution rates over sites under negative selection exhibit an opposite effect on ω estimates compared with those under positive selection. We believe that the sensitivity of our new methods has been improved than that of their original methods under diverse conditions and it is advantageous to introduce novel parameters for Ka/Ks computation. |
format | Online Article Text |
id | pubmed-5054415 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-50544152016-10-14 How Do Variable Substitution Rates Influence Ka and Ks Calculations? Wang, Dapeng Zhang, Song He, Fuhong Zhu, Jiang Hu, Songnian Yu, Jun Genomics Proteomics Bioinformatics Article The ratio of nonsynonymous substitution rate (Ka) to synonymous substitution rate (Ks) is widely used as an indicator of selective pressure at sequence level among different species, and diverse mutation models have been incorporated into several computing methods. We have previously developed a new γ-MYN method by capturing a key dynamic evolution trait of DNA nucleotide sequences, in consideration of varying mutation rates across sites. We now report a further improvement of NG, LWL, MLWL, LPB, MLPB, and YN methods based on an introduction of gamma distribution to illustrate the variation of raw mutation rate over sites. The novelty comes in two ways: (1) we incorporate an optimal gamma distribution shape parameter a into γ-NG, γ-LWL, γ-MLWL, γ-LPB, γ-MLPB, and γ-YN methods; (2) we investigate how variable substitution rates affect the methods that adopt different models as well as the interplay among four evolutional features with respect to Ka/Ks computations. Our results suggest that variable substitution rates over sites under negative selection exhibit an opposite effect on ω estimates compared with those under positive selection. We believe that the sensitivity of our new methods has been improved than that of their original methods under diverse conditions and it is advantageous to introduce novel parameters for Ka/Ks computation. Elsevier 2009-09 2009-11-25 /pmc/articles/PMC5054415/ /pubmed/19944384 http://dx.doi.org/10.1016/S1672-0229(08)60040-6 Text en © 2009 Beijing Institute of Genomics http://creativecommons.org/licenses/by-nc-sa/3.0/ This is an open access article under the CC BY-NC-SA license (http://creativecommons.org/licenses/by-nc-sa/3.0/). |
spellingShingle | Article Wang, Dapeng Zhang, Song He, Fuhong Zhu, Jiang Hu, Songnian Yu, Jun How Do Variable Substitution Rates Influence Ka and Ks Calculations? |
title | How Do Variable Substitution Rates Influence Ka and Ks Calculations? |
title_full | How Do Variable Substitution Rates Influence Ka and Ks Calculations? |
title_fullStr | How Do Variable Substitution Rates Influence Ka and Ks Calculations? |
title_full_unstemmed | How Do Variable Substitution Rates Influence Ka and Ks Calculations? |
title_short | How Do Variable Substitution Rates Influence Ka and Ks Calculations? |
title_sort | how do variable substitution rates influence ka and ks calculations? |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5054415/ https://www.ncbi.nlm.nih.gov/pubmed/19944384 http://dx.doi.org/10.1016/S1672-0229(08)60040-6 |
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