The effect of scale-free topology on the robustness and evolvability of genetic regulatory networks.
We investigate how scale-free (SF) and Erdos-Renyi (ER) topologies affect the interplay between evolvability and robustness of model gene regulatory networks with Boolean threshold dynamics. In agreement with Oikonomou and Cluzel (2006) we find that networks with SF(in) topologies, that is SF topolo...
| Autori principali: | , , , , |
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| Natura: | Journal article |
| Lingua: | English |
| Pubblicazione: |
Elsevier
2010
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| _version_ | 1826256784382230528 |
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| author | Greenbury, S Johnston, I Smith, M Doye, J Louis, A |
| author_facet | Greenbury, S Johnston, I Smith, M Doye, J Louis, A |
| author_sort | Greenbury, S |
| collection | OXFORD |
| description | We investigate how scale-free (SF) and Erdos-Renyi (ER) topologies affect the interplay between evolvability and robustness of model gene regulatory networks with Boolean threshold dynamics. In agreement with Oikonomou and Cluzel (2006) we find that networks with SF(in) topologies, that is SF topology for incoming nodes and ER topology for outgoing nodes, are significantly more evolvable towards specific oscillatory targets than networks with ER topology for both incoming and outgoing nodes. Similar results are found for networks with SF(both) and SF(out) topologies. The functionality of the SF(out) topology, which most closely resembles the structure of biological gene networks (Babu et al. 2004), is compared to the ER topology in further detail through an extension to multiple target outputs, with either an oscillatory or a non-oscillatory nature. For multiple oscillatory targets of the same length, the differences between SF(out) and ER networks are enhanced, but for non-oscillatory targets both types of networks show fairly similar evolvability. We find that SF networks generate oscillations much more easily than ER networks do, and this may explain why SF networks are more evolvable than ER networks are for oscillatory phenotypes. In spite of their greater evolvability, we find that networks with SF(out) topologies are also more robust to mutations (mutational robustness) than ER networks. Furthermore, the SF(out) topologies are more robust to changes in initial conditions (environmental robustness). For both topologies, we find that once a population of networks has reached the target state, further neutral evolution can lead to an increase in both the mutational robustness and the environmental robustness to changes in initial conditions. |
| first_indexed | 2024-03-06T18:07:45Z |
| format | Journal article |
| id | oxford-uuid:01fdc971-5b67-4c18-a8b4-7d88daf0cb3f |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T18:07:45Z |
| publishDate | 2010 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | oxford-uuid:01fdc971-5b67-4c18-a8b4-7d88daf0cb3f2022-03-26T08:38:06ZThe effect of scale-free topology on the robustness and evolvability of genetic regulatory networks.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:01fdc971-5b67-4c18-a8b4-7d88daf0cb3fEnglishSymplectic Elements at OxfordElsevier2010Greenbury, SJohnston, ISmith, MDoye, JLouis, AWe investigate how scale-free (SF) and Erdos-Renyi (ER) topologies affect the interplay between evolvability and robustness of model gene regulatory networks with Boolean threshold dynamics. In agreement with Oikonomou and Cluzel (2006) we find that networks with SF(in) topologies, that is SF topology for incoming nodes and ER topology for outgoing nodes, are significantly more evolvable towards specific oscillatory targets than networks with ER topology for both incoming and outgoing nodes. Similar results are found for networks with SF(both) and SF(out) topologies. The functionality of the SF(out) topology, which most closely resembles the structure of biological gene networks (Babu et al. 2004), is compared to the ER topology in further detail through an extension to multiple target outputs, with either an oscillatory or a non-oscillatory nature. For multiple oscillatory targets of the same length, the differences between SF(out) and ER networks are enhanced, but for non-oscillatory targets both types of networks show fairly similar evolvability. We find that SF networks generate oscillations much more easily than ER networks do, and this may explain why SF networks are more evolvable than ER networks are for oscillatory phenotypes. In spite of their greater evolvability, we find that networks with SF(out) topologies are also more robust to mutations (mutational robustness) than ER networks. Furthermore, the SF(out) topologies are more robust to changes in initial conditions (environmental robustness). For both topologies, we find that once a population of networks has reached the target state, further neutral evolution can lead to an increase in both the mutational robustness and the environmental robustness to changes in initial conditions. |
| spellingShingle | Greenbury, S Johnston, I Smith, M Doye, J Louis, A The effect of scale-free topology on the robustness and evolvability of genetic regulatory networks. |
| title | The effect of scale-free topology on the robustness and evolvability of genetic regulatory networks. |
| title_full | The effect of scale-free topology on the robustness and evolvability of genetic regulatory networks. |
| title_fullStr | The effect of scale-free topology on the robustness and evolvability of genetic regulatory networks. |
| title_full_unstemmed | The effect of scale-free topology on the robustness and evolvability of genetic regulatory networks. |
| title_short | The effect of scale-free topology on the robustness and evolvability of genetic regulatory networks. |
| title_sort | effect of scale free topology on the robustness and evolvability of genetic regulatory networks |
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