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TMRS: an algorithm for computing the time to the most recent substitution event from a multiple alignment column
BACKGROUND : As the number of sequenced genomes grows, researchers have access to an increasingly rich source for discovering detailed evolutionary information. However, the computational technologies for inferring biologically important evolutionary events are not sufficiently developed. RESULTS :...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6859643/ https://www.ncbi.nlm.nih.gov/pubmed/31832082 http://dx.doi.org/10.1186/s13015-019-0158-3 |
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author | Kiryu, Hisanori Ichikawa, Yuto Kojima, Yasuhiro |
author_facet | Kiryu, Hisanori Ichikawa, Yuto Kojima, Yasuhiro |
author_sort | Kiryu, Hisanori |
collection | PubMed |
description | BACKGROUND : As the number of sequenced genomes grows, researchers have access to an increasingly rich source for discovering detailed evolutionary information. However, the computational technologies for inferring biologically important evolutionary events are not sufficiently developed. RESULTS : We present algorithms to estimate the evolutionary time ([Formula: see text] ) to the most recent substitution event from a multiple alignment column by using a probabilistic model of sequence evolution. As the confidence in estimated [Formula: see text] values varies depending on gap fractions and nucleotide patterns of alignment columns, we also compute the standard deviation [Formula: see text] of [Formula: see text] by using a dynamic programming algorithm. We identified a number of human genomic sites at which the last substitutions occurred between two speciation events in the human lineage with confidence. A large fraction of such sites have substitutions that occurred between the concestor nodes of Hominoidea and Euarchontoglires. We investigated the correlation between tissue-specific transcribed enhancers and the distribution of the sites with specific substitution time intervals, and found that brain-specific transcribed enhancers are threefold enriched in the density of substitutions in the human lineage relative to expectations. CONCLUSIONS : We have presented algorithms to estimate the evolutionary time ([Formula: see text] ) to the most recent substitution event from a multiple alignment column by using a probabilistic model of sequence evolution. Our algorithms will be useful for Evo-Devo studies, as they facilitate screening potential genomic sites that have played an important role in the acquisition of unique biological features by target species. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13015-019-0158-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6859643 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-68596432019-12-12 TMRS: an algorithm for computing the time to the most recent substitution event from a multiple alignment column Kiryu, Hisanori Ichikawa, Yuto Kojima, Yasuhiro Algorithms Mol Biol Research BACKGROUND : As the number of sequenced genomes grows, researchers have access to an increasingly rich source for discovering detailed evolutionary information. However, the computational technologies for inferring biologically important evolutionary events are not sufficiently developed. RESULTS : We present algorithms to estimate the evolutionary time ([Formula: see text] ) to the most recent substitution event from a multiple alignment column by using a probabilistic model of sequence evolution. As the confidence in estimated [Formula: see text] values varies depending on gap fractions and nucleotide patterns of alignment columns, we also compute the standard deviation [Formula: see text] of [Formula: see text] by using a dynamic programming algorithm. We identified a number of human genomic sites at which the last substitutions occurred between two speciation events in the human lineage with confidence. A large fraction of such sites have substitutions that occurred between the concestor nodes of Hominoidea and Euarchontoglires. We investigated the correlation between tissue-specific transcribed enhancers and the distribution of the sites with specific substitution time intervals, and found that brain-specific transcribed enhancers are threefold enriched in the density of substitutions in the human lineage relative to expectations. CONCLUSIONS : We have presented algorithms to estimate the evolutionary time ([Formula: see text] ) to the most recent substitution event from a multiple alignment column by using a probabilistic model of sequence evolution. Our algorithms will be useful for Evo-Devo studies, as they facilitate screening potential genomic sites that have played an important role in the acquisition of unique biological features by target species. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13015-019-0158-3) contains supplementary material, which is available to authorized users. BioMed Central 2019-11-18 /pmc/articles/PMC6859643/ /pubmed/31832082 http://dx.doi.org/10.1186/s13015-019-0158-3 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Kiryu, Hisanori Ichikawa, Yuto Kojima, Yasuhiro TMRS: an algorithm for computing the time to the most recent substitution event from a multiple alignment column |
title | TMRS: an algorithm for computing the time to the most recent substitution event from a multiple alignment column |
title_full | TMRS: an algorithm for computing the time to the most recent substitution event from a multiple alignment column |
title_fullStr | TMRS: an algorithm for computing the time to the most recent substitution event from a multiple alignment column |
title_full_unstemmed | TMRS: an algorithm for computing the time to the most recent substitution event from a multiple alignment column |
title_short | TMRS: an algorithm for computing the time to the most recent substitution event from a multiple alignment column |
title_sort | tmrs: an algorithm for computing the time to the most recent substitution event from a multiple alignment column |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6859643/ https://www.ncbi.nlm.nih.gov/pubmed/31832082 http://dx.doi.org/10.1186/s13015-019-0158-3 |
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