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Benchmarking orthology methods using phylogenetic patterns defined at the base of Eukaryotes

Insights into the evolution of ancestral complexes and pathways are generally achieved through careful and time-intensive manual analysis often using phylogenetic profiles of the constituent proteins. This manual analysis limits the possibility of including more protein-complex components, repeating...

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Autores principales: Deutekom, Eva S, Snel, Berend, van Dam, Teunis J P
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138875/
https://www.ncbi.nlm.nih.gov/pubmed/32935832
http://dx.doi.org/10.1093/bib/bbaa206
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author Deutekom, Eva S
Snel, Berend
van Dam, Teunis J P
author_facet Deutekom, Eva S
Snel, Berend
van Dam, Teunis J P
author_sort Deutekom, Eva S
collection PubMed
description Insights into the evolution of ancestral complexes and pathways are generally achieved through careful and time-intensive manual analysis often using phylogenetic profiles of the constituent proteins. This manual analysis limits the possibility of including more protein-complex components, repeating the analyses for updated genome sets or expanding the analyses to larger scales. Automated orthology inference should allow such large-scale analyses, but substantial differences between orthologous groups generated by different approaches are observed. We evaluate orthology methods for their ability to recapitulate a number of observations that have been made with regard to genome evolution in eukaryotes. Specifically, we investigate phylogenetic profile similarity (co-occurrence of complexes), the last eukaryotic common ancestor’s gene content, pervasiveness of gene loss and the overlap with manually determined orthologous groups. Moreover, we compare the inferred orthologies to each other. We find that most orthology methods reconstruct a large last eukaryotic common ancestor, with substantial gene loss, and can predict interacting proteins reasonably well when applying phylogenetic co-occurrence. At the same time, derived orthologous groups show imperfect overlap with manually curated orthologous groups. There is no strong indication of which orthology method performs better than another on individual or all of these aspects. Counterintuitively, despite the orthology methods behaving similarly regarding large-scale evaluation, the obtained orthologous groups differ vastly from one another. Availability and implementation The data and code underlying this article are available in github and/or upon reasonable request to the corresponding author: https://github.com/ESDeutekom/ComparingOrthologies.
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spelling pubmed-81388752021-05-25 Benchmarking orthology methods using phylogenetic patterns defined at the base of Eukaryotes Deutekom, Eva S Snel, Berend van Dam, Teunis J P Brief Bioinform Method Review Insights into the evolution of ancestral complexes and pathways are generally achieved through careful and time-intensive manual analysis often using phylogenetic profiles of the constituent proteins. This manual analysis limits the possibility of including more protein-complex components, repeating the analyses for updated genome sets or expanding the analyses to larger scales. Automated orthology inference should allow such large-scale analyses, but substantial differences between orthologous groups generated by different approaches are observed. We evaluate orthology methods for their ability to recapitulate a number of observations that have been made with regard to genome evolution in eukaryotes. Specifically, we investigate phylogenetic profile similarity (co-occurrence of complexes), the last eukaryotic common ancestor’s gene content, pervasiveness of gene loss and the overlap with manually determined orthologous groups. Moreover, we compare the inferred orthologies to each other. We find that most orthology methods reconstruct a large last eukaryotic common ancestor, with substantial gene loss, and can predict interacting proteins reasonably well when applying phylogenetic co-occurrence. At the same time, derived orthologous groups show imperfect overlap with manually curated orthologous groups. There is no strong indication of which orthology method performs better than another on individual or all of these aspects. Counterintuitively, despite the orthology methods behaving similarly regarding large-scale evaluation, the obtained orthologous groups differ vastly from one another. Availability and implementation The data and code underlying this article are available in github and/or upon reasonable request to the corresponding author: https://github.com/ESDeutekom/ComparingOrthologies. Oxford University Press 2020-09-16 /pmc/articles/PMC8138875/ /pubmed/32935832 http://dx.doi.org/10.1093/bib/bbaa206 Text en © The Author(s) 2020. Published by Oxford University Press. https://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/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Method Review
Deutekom, Eva S
Snel, Berend
van Dam, Teunis J P
Benchmarking orthology methods using phylogenetic patterns defined at the base of Eukaryotes
title Benchmarking orthology methods using phylogenetic patterns defined at the base of Eukaryotes
title_full Benchmarking orthology methods using phylogenetic patterns defined at the base of Eukaryotes
title_fullStr Benchmarking orthology methods using phylogenetic patterns defined at the base of Eukaryotes
title_full_unstemmed Benchmarking orthology methods using phylogenetic patterns defined at the base of Eukaryotes
title_short Benchmarking orthology methods using phylogenetic patterns defined at the base of Eukaryotes
title_sort benchmarking orthology methods using phylogenetic patterns defined at the base of eukaryotes
topic Method Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138875/
https://www.ncbi.nlm.nih.gov/pubmed/32935832
http://dx.doi.org/10.1093/bib/bbaa206
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