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Protein ensembles link genotype to phenotype
Classically, phenotype is what is observed, and genotype is the genetic makeup. Statistical studies aim to project phenotypic likelihoods of genotypic patterns. The traditional genotype-to-phenotype theory embraces the view that the encoded protein shape together with gene expression level largely d...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6586255/ https://www.ncbi.nlm.nih.gov/pubmed/31220071 http://dx.doi.org/10.1371/journal.pcbi.1006648 |
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author | Nussinov, Ruth Tsai, Chung-Jung Jang, Hyunbum |
author_facet | Nussinov, Ruth Tsai, Chung-Jung Jang, Hyunbum |
author_sort | Nussinov, Ruth |
collection | PubMed |
description | Classically, phenotype is what is observed, and genotype is the genetic makeup. Statistical studies aim to project phenotypic likelihoods of genotypic patterns. The traditional genotype-to-phenotype theory embraces the view that the encoded protein shape together with gene expression level largely determines the resulting phenotypic trait. Here, we point out that the molecular biology revolution at the turn of the century explained that the gene encodes not one but ensembles of conformations, which in turn spell all possible gene-associated phenotypes. The significance of a dynamic ensemble view is in understanding the linkage between genetic change and the gained observable physical or biochemical characteristics. Thus, despite the transformative shift in our understanding of the basis of protein structure and function, the literature still commonly relates to the classical genotype–phenotype paradigm. This is important because an ensemble view clarifies how even seemingly small genetic alterations can lead to pleiotropic traits in adaptive evolution and in disease, why cellular pathways can be modified in monogenic and polygenic traits, and how the environment may tweak protein function. |
format | Online Article Text |
id | pubmed-6586255 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-65862552019-06-28 Protein ensembles link genotype to phenotype Nussinov, Ruth Tsai, Chung-Jung Jang, Hyunbum PLoS Comput Biol Review Classically, phenotype is what is observed, and genotype is the genetic makeup. Statistical studies aim to project phenotypic likelihoods of genotypic patterns. The traditional genotype-to-phenotype theory embraces the view that the encoded protein shape together with gene expression level largely determines the resulting phenotypic trait. Here, we point out that the molecular biology revolution at the turn of the century explained that the gene encodes not one but ensembles of conformations, which in turn spell all possible gene-associated phenotypes. The significance of a dynamic ensemble view is in understanding the linkage between genetic change and the gained observable physical or biochemical characteristics. Thus, despite the transformative shift in our understanding of the basis of protein structure and function, the literature still commonly relates to the classical genotype–phenotype paradigm. This is important because an ensemble view clarifies how even seemingly small genetic alterations can lead to pleiotropic traits in adaptive evolution and in disease, why cellular pathways can be modified in monogenic and polygenic traits, and how the environment may tweak protein function. Public Library of Science 2019-06-20 /pmc/articles/PMC6586255/ /pubmed/31220071 http://dx.doi.org/10.1371/journal.pcbi.1006648 Text en © 2019 Nussinov et al 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 use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Review Nussinov, Ruth Tsai, Chung-Jung Jang, Hyunbum Protein ensembles link genotype to phenotype |
title | Protein ensembles link genotype to phenotype |
title_full | Protein ensembles link genotype to phenotype |
title_fullStr | Protein ensembles link genotype to phenotype |
title_full_unstemmed | Protein ensembles link genotype to phenotype |
title_short | Protein ensembles link genotype to phenotype |
title_sort | protein ensembles link genotype to phenotype |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6586255/ https://www.ncbi.nlm.nih.gov/pubmed/31220071 http://dx.doi.org/10.1371/journal.pcbi.1006648 |
work_keys_str_mv | AT nussinovruth proteinensembleslinkgenotypetophenotype AT tsaichungjung proteinensembleslinkgenotypetophenotype AT janghyunbum proteinensembleslinkgenotypetophenotype |