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Alignment Modulates Ancestral Sequence Reconstruction Accuracy
Accurate reconstruction of ancestral states is a critical evolutionary analysis when studying ancient proteins and comparing biochemical properties between parental or extinct species and their extant relatives. It relies on multiple sequence alignment (MSA) which may introduce biases, and it remain...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5995191/ https://www.ncbi.nlm.nih.gov/pubmed/29618097 http://dx.doi.org/10.1093/molbev/msy055 |
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author | Vialle, Ricardo Assunção Tamuri, Asif U Goldman, Nick |
author_facet | Vialle, Ricardo Assunção Tamuri, Asif U Goldman, Nick |
author_sort | Vialle, Ricardo Assunção |
collection | PubMed |
description | Accurate reconstruction of ancestral states is a critical evolutionary analysis when studying ancient proteins and comparing biochemical properties between parental or extinct species and their extant relatives. It relies on multiple sequence alignment (MSA) which may introduce biases, and it remains unknown how MSA methodological approaches impact ancestral sequence reconstruction (ASR). Here, we investigate how MSA methodology modulates ASR using a simulation study of various evolutionary scenarios. We evaluate the accuracy of ancestral protein sequence reconstruction for simulated data and compare reconstruction outcomes using different alignment methods. Our results reveal biases introduced not only by aligner algorithms and assumptions, but also tree topology and the rate of insertions and deletions. Under many conditions we find no substantial differences between the MSAs. However, increasing the difficulty for the aligners can significantly impact ASR. The MAFFT consistency aligners and PRANK variants exhibit the best performance, whereas FSA displays limited performance. We also discover a bias towards reconstructed sequences longer than the true ancestors, deriving from a preference for inferring insertions, in almost all MSA methodological approaches. In addition, we find measures of MSA quality generally correlate highly with reconstruction accuracy. Thus, we show MSA methodological differences can affect the quality of reconstructions and propose MSA methods should be selected with care to accurately determine ancestral states with confidence. |
format | Online Article Text |
id | pubmed-5995191 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-59951912018-06-15 Alignment Modulates Ancestral Sequence Reconstruction Accuracy Vialle, Ricardo Assunção Tamuri, Asif U Goldman, Nick Mol Biol Evol Methods Accurate reconstruction of ancestral states is a critical evolutionary analysis when studying ancient proteins and comparing biochemical properties between parental or extinct species and their extant relatives. It relies on multiple sequence alignment (MSA) which may introduce biases, and it remains unknown how MSA methodological approaches impact ancestral sequence reconstruction (ASR). Here, we investigate how MSA methodology modulates ASR using a simulation study of various evolutionary scenarios. We evaluate the accuracy of ancestral protein sequence reconstruction for simulated data and compare reconstruction outcomes using different alignment methods. Our results reveal biases introduced not only by aligner algorithms and assumptions, but also tree topology and the rate of insertions and deletions. Under many conditions we find no substantial differences between the MSAs. However, increasing the difficulty for the aligners can significantly impact ASR. The MAFFT consistency aligners and PRANK variants exhibit the best performance, whereas FSA displays limited performance. We also discover a bias towards reconstructed sequences longer than the true ancestors, deriving from a preference for inferring insertions, in almost all MSA methodological approaches. In addition, we find measures of MSA quality generally correlate highly with reconstruction accuracy. Thus, we show MSA methodological differences can affect the quality of reconstructions and propose MSA methods should be selected with care to accurately determine ancestral states with confidence. Oxford University Press 2018-07 2018-04-03 /pmc/articles/PMC5995191/ /pubmed/29618097 http://dx.doi.org/10.1093/molbev/msy055 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Vialle, Ricardo Assunção Tamuri, Asif U Goldman, Nick Alignment Modulates Ancestral Sequence Reconstruction Accuracy |
title | Alignment Modulates Ancestral Sequence Reconstruction Accuracy |
title_full | Alignment Modulates Ancestral Sequence Reconstruction Accuracy |
title_fullStr | Alignment Modulates Ancestral Sequence Reconstruction Accuracy |
title_full_unstemmed | Alignment Modulates Ancestral Sequence Reconstruction Accuracy |
title_short | Alignment Modulates Ancestral Sequence Reconstruction Accuracy |
title_sort | alignment modulates ancestral sequence reconstruction accuracy |
topic | Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5995191/ https://www.ncbi.nlm.nih.gov/pubmed/29618097 http://dx.doi.org/10.1093/molbev/msy055 |
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