Assigning function to natural allelic variation via dynamic modeling of gene network induction
Abstract More and more natural DNA variants are being linked to physiological traits. Yet, understanding what differences they make on molecular regulations remains challenging. Important properties of gene regulatory networks can be captured by computational models. If model parameters can be “pers...
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| Format: | Article |
| Language: | English |
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Springer Nature
2018-01-01
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| Series: | Molecular Systems Biology |
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| Online Access: | https://doi.org/10.15252/msb.20177803 |
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| author | Magali Richard Florent Chuffart Hélène Duplus‐Bottin Fanny Pouyet Martin Spichty Etienne Fulcrand Marianne Entrevan Audrey Barthelaix Michael Springer Daniel Jost Gaël Yvert |
| author_facet | Magali Richard Florent Chuffart Hélène Duplus‐Bottin Fanny Pouyet Martin Spichty Etienne Fulcrand Marianne Entrevan Audrey Barthelaix Michael Springer Daniel Jost Gaël Yvert |
| author_sort | Magali Richard |
| collection | DOAJ |
| description | Abstract More and more natural DNA variants are being linked to physiological traits. Yet, understanding what differences they make on molecular regulations remains challenging. Important properties of gene regulatory networks can be captured by computational models. If model parameters can be “personalized” according to the genotype, their variation may then reveal how DNA variants operate in the network. Here, we combined experiments and computations to visualize natural alleles of the yeast GAL3 gene in a space of model parameters describing the galactose response network. Alleles altering the activation of Gal3p by galactose were discriminated from those affecting its activity (production/degradation or efficiency of the activated protein). The approach allowed us to correctly predict that a non‐synonymous SNP would change the binding affinity of Gal3p with the Gal80p transcriptional repressor. Our results illustrate how personalizing gene regulatory models can be used for the mechanistic interpretation of genetic variants. |
| format | Article |
| id | doaj-art-da4d897778de4a1fab0220c6da443b32 |
| institution | Kabale University |
| issn | 1744-4292 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Springer Nature |
| record_format | Article |
| series | Molecular Systems Biology |
| spelling | doaj-art-da4d897778de4a1fab0220c6da443b322025-08-20T03:43:31ZengSpringer NatureMolecular Systems Biology1744-42922018-01-0114111610.15252/msb.20177803Assigning function to natural allelic variation via dynamic modeling of gene network inductionMagali Richard0Florent Chuffart1Hélène Duplus‐Bottin2Fanny Pouyet3Martin Spichty4Etienne Fulcrand5Marianne Entrevan6Audrey Barthelaix7Michael Springer8Daniel Jost9Gaël Yvert10Laboratoire de Biologie et de Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, Université Lyon 1, Université de LyonLaboratoire de Biologie et de Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, Université Lyon 1, Université de LyonLaboratoire de Biologie et de Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, Université Lyon 1, Université de LyonLaboratoire de Biologie et de Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, Université Lyon 1, Université de LyonLaboratoire de Biologie et de Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, Université Lyon 1, Université de LyonLaboratoire de Biologie et de Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, Université Lyon 1, Université de LyonLaboratoire de Biologie et de Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, Université Lyon 1, Université de LyonLaboratoire de Biologie et de Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, Université Lyon 1, Université de LyonDepartment of Systems Biology, Harvard Medical SchoolUniv. Grenoble Alpes, CNRS, CHU Grenoble Alpes, Grenoble INP, TIMC‐IMAGLaboratoire de Biologie et de Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, Université Lyon 1, Université de LyonAbstract More and more natural DNA variants are being linked to physiological traits. Yet, understanding what differences they make on molecular regulations remains challenging. Important properties of gene regulatory networks can be captured by computational models. If model parameters can be “personalized” according to the genotype, their variation may then reveal how DNA variants operate in the network. Here, we combined experiments and computations to visualize natural alleles of the yeast GAL3 gene in a space of model parameters describing the galactose response network. Alleles altering the activation of Gal3p by galactose were discriminated from those affecting its activity (production/degradation or efficiency of the activated protein). The approach allowed us to correctly predict that a non‐synonymous SNP would change the binding affinity of Gal3p with the Gal80p transcriptional repressor. Our results illustrate how personalizing gene regulatory models can be used for the mechanistic interpretation of genetic variants.https://doi.org/10.15252/msb.20177803galactosepersonalized medicineSNP functionstochastic modelyeast |
| spellingShingle | Magali Richard Florent Chuffart Hélène Duplus‐Bottin Fanny Pouyet Martin Spichty Etienne Fulcrand Marianne Entrevan Audrey Barthelaix Michael Springer Daniel Jost Gaël Yvert Assigning function to natural allelic variation via dynamic modeling of gene network induction Molecular Systems Biology galactose personalized medicine SNP function stochastic model yeast |
| title | Assigning function to natural allelic variation via dynamic modeling of gene network induction |
| title_full | Assigning function to natural allelic variation via dynamic modeling of gene network induction |
| title_fullStr | Assigning function to natural allelic variation via dynamic modeling of gene network induction |
| title_full_unstemmed | Assigning function to natural allelic variation via dynamic modeling of gene network induction |
| title_short | Assigning function to natural allelic variation via dynamic modeling of gene network induction |
| title_sort | assigning function to natural allelic variation via dynamic modeling of gene network induction |
| topic | galactose personalized medicine SNP function stochastic model yeast |
| url | https://doi.org/10.15252/msb.20177803 |
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