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פותח על ידי קלירמאש פתרונות בע"מ -
Towards realistic codon models: Among site variability and dependency of synonymous and non-synonymous rates
Year:
2007
Source of publication :
bioinformatics (source)
Authors :
דורון-פייגנבאום, עדי
;
.
Volume :
23
Co-Authors:
Mayrose, I., The Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel-Aviv University, Tel Aviv 69978, Israel
Doron-Faigenboim, A., The Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel-Aviv University, Tel Aviv 69978, Israel
Bacharach, E., The Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel-Aviv University, Tel Aviv 69978, Israel
Pupko, T., The Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel-Aviv University, Tel Aviv 69978, Israel
Facilitators :
From page:
To page:
(
Total pages:
1
)
Abstract:
Codon evolutionary models are widely used to infer the selection forces acting on a protein. The non-synonymous to synonymous rate ratio (denoted by Ka/Ks) is used to infer specific positions that are under purifying or positive selection. Current evolutionary models usually assume that only the non-synonymous rates vary among sites while the synonymous substitution rates are constant. This assumption ignores the possibility of selection forces acting at the DNA or mRNA levels. Towards a more realistic description of sequence evolution, we present a model that accounts for among-site-variation of both synonymous and non-synonymous substitution rates. Furthermore, we alleviate the widespread assumption that positions evolve independently of each other. Thus, possible sources of bias caused by random fluctuations in either the synonymous or non-synonymous rate estimations at a single site is removed. Our model is based on two hidden Markov models that operate on the spatial dimension: one describes the dependency between adjacent non-synonymous rates while the other describes the dependency between adjacent synonymous rates. The presented model is applied to study the selection pressure across the HIV-1 genome. The new model better describes the evolution of all HIV-1 genes, as compared to current codon models. Using both simulations and real data analyses, we illustrate that accounting for synonymous rate variability and dependency greatly increases the accuracy of Ka/Ks estimation and in particular of positively selected sites. Finally, we discuss the applicability of the developed model to infer the selection forces in regulatory and overlapping regions of the HIV-1 genome. © 2007 The Author(s).
Note:
Related Files :
Base Sequence
computer simulation
Conference paper
genetic model
Molecular Evolution
Simulation
עוד תגיות
תוכן קשור
More details
DOI :
10.1093/bioinformatics/btm176
Article number:
Affiliations:
Database:
סקופוס
Publication Type:
מאמר מתוך כינוס
;
.
Language:
אנגלית
Editors' remarks:
ID:
32038
Last updated date:
02/03/2022 17:27
Creation date:
17/04/2018 01:07
Scientific Publication
Towards realistic codon models: Among site variability and dependency of synonymous and non-synonymous rates
23
Mayrose, I., The Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel-Aviv University, Tel Aviv 69978, Israel
Doron-Faigenboim, A., The Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel-Aviv University, Tel Aviv 69978, Israel
Bacharach, E., The Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel-Aviv University, Tel Aviv 69978, Israel
Pupko, T., The Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel-Aviv University, Tel Aviv 69978, Israel
Towards realistic codon models: Among site variability and dependency of synonymous and non-synonymous rates
Codon evolutionary models are widely used to infer the selection forces acting on a protein. The non-synonymous to synonymous rate ratio (denoted by Ka/Ks) is used to infer specific positions that are under purifying or positive selection. Current evolutionary models usually assume that only the non-synonymous rates vary among sites while the synonymous substitution rates are constant. This assumption ignores the possibility of selection forces acting at the DNA or mRNA levels. Towards a more realistic description of sequence evolution, we present a model that accounts for among-site-variation of both synonymous and non-synonymous substitution rates. Furthermore, we alleviate the widespread assumption that positions evolve independently of each other. Thus, possible sources of bias caused by random fluctuations in either the synonymous or non-synonymous rate estimations at a single site is removed. Our model is based on two hidden Markov models that operate on the spatial dimension: one describes the dependency between adjacent non-synonymous rates while the other describes the dependency between adjacent synonymous rates. The presented model is applied to study the selection pressure across the HIV-1 genome. The new model better describes the evolution of all HIV-1 genes, as compared to current codon models. Using both simulations and real data analyses, we illustrate that accounting for synonymous rate variability and dependency greatly increases the accuracy of Ka/Ks estimation and in particular of positively selected sites. Finally, we discuss the applicability of the developed model to infer the selection forces in regulatory and overlapping regions of the HIV-1 genome. © 2007 The Author(s).
Scientific Publication
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