Identification of physicochemical selective pressure on protein encoding nucleotide sequences

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Identification of physicochemical selective pressure on protein encoding nucleotide sequences. / Wong, Wendy S. W.; Sainudiin, Raazesh; Nielsen, Rasmus.

In: BMC Bioinformatics, Vol. 7, 148, 2006.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Wong, WSW, Sainudiin, R & Nielsen, R 2006, 'Identification of physicochemical selective pressure on protein encoding nucleotide sequences', BMC Bioinformatics, vol. 7, 148. https://doi.org/10.1186/1471-2105-7-148

APA

Wong, W. S. W., Sainudiin, R., & Nielsen, R. (2006). Identification of physicochemical selective pressure on protein encoding nucleotide sequences. BMC Bioinformatics, 7, [148]. https://doi.org/10.1186/1471-2105-7-148

Vancouver

Wong WSW, Sainudiin R, Nielsen R. Identification of physicochemical selective pressure on protein encoding nucleotide sequences. BMC Bioinformatics. 2006;7. 148. https://doi.org/10.1186/1471-2105-7-148

Author

Wong, Wendy S. W. ; Sainudiin, Raazesh ; Nielsen, Rasmus. / Identification of physicochemical selective pressure on protein encoding nucleotide sequences. In: BMC Bioinformatics. 2006 ; Vol. 7.

Bibtex

@article{2eefe3d967e6465fbff6665731d213a2,
title = "Identification of physicochemical selective pressure on protein encoding nucleotide sequences",
abstract = "Background: Statistical methods for identifying positively selected sites in protein coding regions are one of the most commonly used tools in evolutionary bioinformatics. However, they have been limited by not taking the physiochemical properties of amino acids into account. Results: We develop a new codon-based likelihood model for detecting site-specific selection pressures acting on specific physicochemical properties. Nonsynonymous substitutions are divided into substitutions that differ with respect to the physicochemical properties of interest, and those that do not. The substitution rates of these two types of changes, relative to the synonymous substitution rate, are then described by two parameters, γ and ω respectively. The new model allows us to perform likelihood ratio tests for positive selection acting on specific physicochemical properties of interest. The new method is first used to analyze simulated data and is shown to have good power and accuracy in detecting physicochemical selective pressure. We then re-analyze data from the class-I alleles of the human Major Histocompatibility Complex (MHC) and from the abalone sperm lysine. Conclusion: Our new method allows a more flexible framework to identify selection pressure on particular physicochemical properties.",
author = "Wong, {Wendy S. W.} and Raazesh Sainudiin and Rasmus Nielsen",
year = "2006",
doi = "10.1186/1471-2105-7-148",
language = "English",
volume = "7",
journal = "B M C Bioinformatics",
issn = "1471-2105",
publisher = "BioMed Central Ltd.",

}

RIS

TY - JOUR

T1 - Identification of physicochemical selective pressure on protein encoding nucleotide sequences

AU - Wong, Wendy S. W.

AU - Sainudiin, Raazesh

AU - Nielsen, Rasmus

PY - 2006

Y1 - 2006

N2 - Background: Statistical methods for identifying positively selected sites in protein coding regions are one of the most commonly used tools in evolutionary bioinformatics. However, they have been limited by not taking the physiochemical properties of amino acids into account. Results: We develop a new codon-based likelihood model for detecting site-specific selection pressures acting on specific physicochemical properties. Nonsynonymous substitutions are divided into substitutions that differ with respect to the physicochemical properties of interest, and those that do not. The substitution rates of these two types of changes, relative to the synonymous substitution rate, are then described by two parameters, γ and ω respectively. The new model allows us to perform likelihood ratio tests for positive selection acting on specific physicochemical properties of interest. The new method is first used to analyze simulated data and is shown to have good power and accuracy in detecting physicochemical selective pressure. We then re-analyze data from the class-I alleles of the human Major Histocompatibility Complex (MHC) and from the abalone sperm lysine. Conclusion: Our new method allows a more flexible framework to identify selection pressure on particular physicochemical properties.

AB - Background: Statistical methods for identifying positively selected sites in protein coding regions are one of the most commonly used tools in evolutionary bioinformatics. However, they have been limited by not taking the physiochemical properties of amino acids into account. Results: We develop a new codon-based likelihood model for detecting site-specific selection pressures acting on specific physicochemical properties. Nonsynonymous substitutions are divided into substitutions that differ with respect to the physicochemical properties of interest, and those that do not. The substitution rates of these two types of changes, relative to the synonymous substitution rate, are then described by two parameters, γ and ω respectively. The new model allows us to perform likelihood ratio tests for positive selection acting on specific physicochemical properties of interest. The new method is first used to analyze simulated data and is shown to have good power and accuracy in detecting physicochemical selective pressure. We then re-analyze data from the class-I alleles of the human Major Histocompatibility Complex (MHC) and from the abalone sperm lysine. Conclusion: Our new method allows a more flexible framework to identify selection pressure on particular physicochemical properties.

U2 - 10.1186/1471-2105-7-148

DO - 10.1186/1471-2105-7-148

M3 - Journal article

C2 - 16542458

AN - SCOPUS:33645649132

VL - 7

JO - B M C Bioinformatics

JF - B M C Bioinformatics

SN - 1471-2105

M1 - 148

ER -

ID: 222644168