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CastNet: a systems-level sequence evolution simulator
BACKGROUND: Simulating DNA evolution has been done through coevolution-agnostic probabilistic frameworks for the past 3 decades. The most common implementation is by using the converse of the probabilistic approach used to infer phylogenies which, in the simplest form, simulates a single sequence at...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10259028/ https://www.ncbi.nlm.nih.gov/pubmed/37308829 http://dx.doi.org/10.1186/s12859-023-05366-1 |
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author | Rivera-Rivera, Carlos J. Grbic, Djordje |
author_facet | Rivera-Rivera, Carlos J. Grbic, Djordje |
author_sort | Rivera-Rivera, Carlos J. |
collection | PubMed |
description | BACKGROUND: Simulating DNA evolution has been done through coevolution-agnostic probabilistic frameworks for the past 3 decades. The most common implementation is by using the converse of the probabilistic approach used to infer phylogenies which, in the simplest form, simulates a single sequence at a time. However, biological systems are multi-genic, and gene products can affect each other’s evolutionary paths through coevolution. These crucial evolutionary dynamics still remain to be simulated, and we believe that modelling them can lead to profound insights for comparative genomics. RESULTS: Here we present CastNet, a genome evolution simulator that assumes each genome is a collection of genes with constantly evolving regulatory interactions in between them. The regulatory interactions produce a phenotype in the form of gene expression profiles, upon which fitness is calculated. A genetic algorithm is then used to evolve a population of such entities through a user-defined phylogeny. Importantly, the regulatory mutations are a response to sequence mutations, thus making a 1–1 relationship between the rate of evolution of sequences and of regulatory parameters. This is, to our knowledge, the first time the evolution of sequences and regulation have been explicitly linked in a simulation, despite there being a multitude of sequence evolution simulators, and a handful of models to simulate Gene Regulatory Network (GRN) evolution. In our test runs, we see a coevolutionary signal among genes that are active in the GRN, and neutral evolution in genes that are not included in the network, showing that selective pressures imposed on the regulatory output of the genes are reflected in their sequences. CONCLUSION: We believe that CastNet represents a substantial step for developing new tools to study genome evolution, and more broadly, coevolutionary webs and complex evolving systems. This simulator also provides a new framework to study molecular evolution where sequence coevolution has a leading role. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05366-1. |
format | Online Article Text |
id | pubmed-10259028 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-102590282023-06-13 CastNet: a systems-level sequence evolution simulator Rivera-Rivera, Carlos J. Grbic, Djordje BMC Bioinformatics Software BACKGROUND: Simulating DNA evolution has been done through coevolution-agnostic probabilistic frameworks for the past 3 decades. The most common implementation is by using the converse of the probabilistic approach used to infer phylogenies which, in the simplest form, simulates a single sequence at a time. However, biological systems are multi-genic, and gene products can affect each other’s evolutionary paths through coevolution. These crucial evolutionary dynamics still remain to be simulated, and we believe that modelling them can lead to profound insights for comparative genomics. RESULTS: Here we present CastNet, a genome evolution simulator that assumes each genome is a collection of genes with constantly evolving regulatory interactions in between them. The regulatory interactions produce a phenotype in the form of gene expression profiles, upon which fitness is calculated. A genetic algorithm is then used to evolve a population of such entities through a user-defined phylogeny. Importantly, the regulatory mutations are a response to sequence mutations, thus making a 1–1 relationship between the rate of evolution of sequences and of regulatory parameters. This is, to our knowledge, the first time the evolution of sequences and regulation have been explicitly linked in a simulation, despite there being a multitude of sequence evolution simulators, and a handful of models to simulate Gene Regulatory Network (GRN) evolution. In our test runs, we see a coevolutionary signal among genes that are active in the GRN, and neutral evolution in genes that are not included in the network, showing that selective pressures imposed on the regulatory output of the genes are reflected in their sequences. CONCLUSION: We believe that CastNet represents a substantial step for developing new tools to study genome evolution, and more broadly, coevolutionary webs and complex evolving systems. This simulator also provides a new framework to study molecular evolution where sequence coevolution has a leading role. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05366-1. BioMed Central 2023-06-12 /pmc/articles/PMC10259028/ /pubmed/37308829 http://dx.doi.org/10.1186/s12859-023-05366-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Rivera-Rivera, Carlos J. Grbic, Djordje CastNet: a systems-level sequence evolution simulator |
title | CastNet: a systems-level sequence evolution simulator |
title_full | CastNet: a systems-level sequence evolution simulator |
title_fullStr | CastNet: a systems-level sequence evolution simulator |
title_full_unstemmed | CastNet: a systems-level sequence evolution simulator |
title_short | CastNet: a systems-level sequence evolution simulator |
title_sort | castnet: a systems-level sequence evolution simulator |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10259028/ https://www.ncbi.nlm.nih.gov/pubmed/37308829 http://dx.doi.org/10.1186/s12859-023-05366-1 |
work_keys_str_mv | AT riverariveracarlosj castnetasystemslevelsequenceevolutionsimulator AT grbicdjordje castnetasystemslevelsequenceevolutionsimulator |