An in silico analysis of robust but fragile gene regulation links enhancer length to robustness.
Organisms must ensure that expression of genes is directed to the appropriate tissues at the correct times, while simultaneously ensuring that these gene regulatory systems are robust to perturbation. This idea is captured by a mathematical concept called r-robustness, which says that a system is ro...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2019-11-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1007497 |
| _version_ | 1819134620847833088 |
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| author | Kenneth Barr John Reinitz Ovidiu Radulescu |
| author_facet | Kenneth Barr John Reinitz Ovidiu Radulescu |
| author_sort | Kenneth Barr |
| collection | DOAJ |
| description | Organisms must ensure that expression of genes is directed to the appropriate tissues at the correct times, while simultaneously ensuring that these gene regulatory systems are robust to perturbation. This idea is captured by a mathematical concept called r-robustness, which says that a system is robust to a perturbation in up to r - 1 randomly chosen parameters. r-robustness implies that the biological system has a small number of sensitive parameters and that this number can be used as a robustness measure. In this work we use this idea to investigate the robustness of gene regulation using a sequence level model of the Drosophila melanogaster gene even-skipped. We consider robustness with respect to mutations of the enhancer sequence and with respect to changes of the transcription factor concentrations. We find that gene regulation is r-robust with respect to mutations in the enhancer sequence and identify a number of sensitive nucleotides. In both natural and in silico predicted enhancers, the number of nucleotides that are sensitive to mutation correlates negatively with the length of the sequence, meaning that longer sequences are more robust. The exact degree of robustness obtained is dependent not only on DNA sequence, but also on the local concentration of regulatory factors. We find that gene regulation can be remarkably sensitive to changes in transcription factor concentrations at the boundaries of expression features, while it is robust to perturbation elsewhere. |
| first_indexed | 2024-12-22T10:06:05Z |
| format | Article |
| id | doaj.art-39131be75cac4ee79bc8de2b37837bfd |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-22T10:06:05Z |
| publishDate | 2019-11-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-39131be75cac4ee79bc8de2b37837bfd2022-12-21T18:29:58ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582019-11-011511e100749710.1371/journal.pcbi.1007497An in silico analysis of robust but fragile gene regulation links enhancer length to robustness.Kenneth BarrJohn ReinitzOvidiu RadulescuOrganisms must ensure that expression of genes is directed to the appropriate tissues at the correct times, while simultaneously ensuring that these gene regulatory systems are robust to perturbation. This idea is captured by a mathematical concept called r-robustness, which says that a system is robust to a perturbation in up to r - 1 randomly chosen parameters. r-robustness implies that the biological system has a small number of sensitive parameters and that this number can be used as a robustness measure. In this work we use this idea to investigate the robustness of gene regulation using a sequence level model of the Drosophila melanogaster gene even-skipped. We consider robustness with respect to mutations of the enhancer sequence and with respect to changes of the transcription factor concentrations. We find that gene regulation is r-robust with respect to mutations in the enhancer sequence and identify a number of sensitive nucleotides. In both natural and in silico predicted enhancers, the number of nucleotides that are sensitive to mutation correlates negatively with the length of the sequence, meaning that longer sequences are more robust. The exact degree of robustness obtained is dependent not only on DNA sequence, but also on the local concentration of regulatory factors. We find that gene regulation can be remarkably sensitive to changes in transcription factor concentrations at the boundaries of expression features, while it is robust to perturbation elsewhere.https://doi.org/10.1371/journal.pcbi.1007497 |
| spellingShingle | Kenneth Barr John Reinitz Ovidiu Radulescu An in silico analysis of robust but fragile gene regulation links enhancer length to robustness. PLoS Computational Biology |
| title | An in silico analysis of robust but fragile gene regulation links enhancer length to robustness. |
| title_full | An in silico analysis of robust but fragile gene regulation links enhancer length to robustness. |
| title_fullStr | An in silico analysis of robust but fragile gene regulation links enhancer length to robustness. |
| title_full_unstemmed | An in silico analysis of robust but fragile gene regulation links enhancer length to robustness. |
| title_short | An in silico analysis of robust but fragile gene regulation links enhancer length to robustness. |
| title_sort | in silico analysis of robust but fragile gene regulation links enhancer length to robustness |
| url | https://doi.org/10.1371/journal.pcbi.1007497 |
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