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Maximum mutational robustness in genotype–phenotype maps follows a self-similar blancmange-like curve
Phenotype robustness, defined as the average mutational robustness of all the genotypes that map to a given phenotype, plays a key role in facilitating neutral exploration of novel phenotypic variation by an evolving population. By applying results from coding theory, we prove that the maximum pheno...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10369032/ https://www.ncbi.nlm.nih.gov/pubmed/37491910 http://dx.doi.org/10.1098/rsif.2023.0169 |
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author | Mohanty, Vaibhav Greenbury, Sam F. Sarkany, Tasmin Narayanan, Shyam Dingle, Kamaludin Ahnert, Sebastian E. Louis, Ard A. |
author_facet | Mohanty, Vaibhav Greenbury, Sam F. Sarkany, Tasmin Narayanan, Shyam Dingle, Kamaludin Ahnert, Sebastian E. Louis, Ard A. |
author_sort | Mohanty, Vaibhav |
collection | PubMed |
description | Phenotype robustness, defined as the average mutational robustness of all the genotypes that map to a given phenotype, plays a key role in facilitating neutral exploration of novel phenotypic variation by an evolving population. By applying results from coding theory, we prove that the maximum phenotype robustness occurs when genotypes are organized as bricklayer’s graphs, so-called because they resemble the way in which a bricklayer would fill in a Hamming graph. The value of the maximal robustness is given by a fractal continuous everywhere but differentiable nowhere sums-of-digits function from number theory. Interestingly, genotype–phenotype maps for RNA secondary structure and the hydrophobic-polar (HP) model for protein folding can exhibit phenotype robustness that exactly attains this upper bound. By exploiting properties of the sums-of-digits function, we prove a lower bound on the deviation of the maximum robustness of phenotypes with multiple neutral components from the bricklayer’s graph bound, and show that RNA secondary structure phenotypes obey this bound. Finally, we show how robustness changes when phenotypes are coarse-grained and derive a formula and associated bounds for the transition probabilities between such phenotypes. |
format | Online Article Text |
id | pubmed-10369032 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-103690322023-07-27 Maximum mutational robustness in genotype–phenotype maps follows a self-similar blancmange-like curve Mohanty, Vaibhav Greenbury, Sam F. Sarkany, Tasmin Narayanan, Shyam Dingle, Kamaludin Ahnert, Sebastian E. Louis, Ard A. J R Soc Interface Life Sciences–Physics interface Phenotype robustness, defined as the average mutational robustness of all the genotypes that map to a given phenotype, plays a key role in facilitating neutral exploration of novel phenotypic variation by an evolving population. By applying results from coding theory, we prove that the maximum phenotype robustness occurs when genotypes are organized as bricklayer’s graphs, so-called because they resemble the way in which a bricklayer would fill in a Hamming graph. The value of the maximal robustness is given by a fractal continuous everywhere but differentiable nowhere sums-of-digits function from number theory. Interestingly, genotype–phenotype maps for RNA secondary structure and the hydrophobic-polar (HP) model for protein folding can exhibit phenotype robustness that exactly attains this upper bound. By exploiting properties of the sums-of-digits function, we prove a lower bound on the deviation of the maximum robustness of phenotypes with multiple neutral components from the bricklayer’s graph bound, and show that RNA secondary structure phenotypes obey this bound. Finally, we show how robustness changes when phenotypes are coarse-grained and derive a formula and associated bounds for the transition probabilities between such phenotypes. The Royal Society 2023-07-26 /pmc/articles/PMC10369032/ /pubmed/37491910 http://dx.doi.org/10.1098/rsif.2023.0169 Text en © 2023 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society 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 use, provided the original author and source are credited. |
spellingShingle | Life Sciences–Physics interface Mohanty, Vaibhav Greenbury, Sam F. Sarkany, Tasmin Narayanan, Shyam Dingle, Kamaludin Ahnert, Sebastian E. Louis, Ard A. Maximum mutational robustness in genotype–phenotype maps follows a self-similar blancmange-like curve |
title | Maximum mutational robustness in genotype–phenotype maps follows a self-similar blancmange-like curve |
title_full | Maximum mutational robustness in genotype–phenotype maps follows a self-similar blancmange-like curve |
title_fullStr | Maximum mutational robustness in genotype–phenotype maps follows a self-similar blancmange-like curve |
title_full_unstemmed | Maximum mutational robustness in genotype–phenotype maps follows a self-similar blancmange-like curve |
title_short | Maximum mutational robustness in genotype–phenotype maps follows a self-similar blancmange-like curve |
title_sort | maximum mutational robustness in genotype–phenotype maps follows a self-similar blancmange-like curve |
topic | Life Sciences–Physics interface |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10369032/ https://www.ncbi.nlm.nih.gov/pubmed/37491910 http://dx.doi.org/10.1098/rsif.2023.0169 |
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