Por favor, use este identificador para citar o enlazar a este item:
http://hdl.handle.net/10261/47932
COMPARTIR / EXPORTAR:
SHARE CORE BASE | |
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE | |
Campo DC | Valor | Lengua/Idioma |
---|---|---|
dc.contributor.author | Clune, Jeff | - |
dc.contributor.author | Misevic, Dusan | - |
dc.contributor.author | Ofria, Charles | - |
dc.contributor.author | Lenski, Richard E. | - |
dc.contributor.author | Elena, Santiago F. | - |
dc.contributor.author | Elena, Santiago F. | - |
dc.contributor.author | Sanjuán, Rafael | - |
dc.date.accessioned | 2012-04-04T11:07:28Z | - |
dc.date.available | 2012-04-04T11:07:28Z | - |
dc.date.issued | 2008-09-26 | - |
dc.identifier.citation | PLoS Computational Biology 4/9:e1000187 (2008) | es_ES |
dc.identifier.uri | http://hdl.handle.net/10261/47932 | - |
dc.description.abstract | The rate of mutation is central to evolution. Mutations are required for adaptation, yet most mutations with phenotypic effects are deleterious. As a consequence, the mutation rate that maximizes adaptation will be some intermediate value. Here, we used digital organisms to investigate the ability of natural selection to adjust and optimize mutation rates. We assessed the optimal mutation rate by empirically determining what mutation rate produced the highest rate of adaptation. Then, we allowed mutation rates to evolve, and we evaluated the proximity to the optimum. Although we chose conditions favorable for mutation rate optimization, the evolved rates were invariably far below the optimum across a wide range of experimental parameter settings. We hypothesized that the reason that mutation rates evolved to be suboptimal was the ruggedness of fitness landscapes. To test this hypothesis, we created a simplified landscape without any fitness valleys and found that, in such conditions, populations evolved near-optimal mutation rates. In contrast, when fitness valleys were added to this simple landscape, the ability of evolving populations to find the optimal mutation rate was lost. We conclude that rugged fitness landscapes can prevent the evolution of mutation rates that are optimal for long-term adaptation. This finding has important implications for applied evolutionary research in both biological and computational realms. | es_ES |
dc.description.sponsorship | This work was supported, in part, by the Defense Advanced Research Projects Agency ‘‘Fun Bio’’ Program, National Science Foundation grant CCF- 0643952, and the Cambridge Templeton Consortium. Work in Vale`ncia was supported by grant BFU2006-14819-C02-01/BMC and the Ramo´n y Cajal program from the Spanish MEC. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Public Library of Science | es_ES |
dc.relation.isversionof | Publisher's version | - |
dc.rights | openAccess | es_ES |
dc.subject | DNA Mismatch repair | es_ES |
dc.subject | Digital organisms | es_ES |
dc.subject | Replication fidelity | es_ES |
dc.subject | Asexual populations | es_ES |
dc.title | Natural Selection Fails to Optimize Mutation Rates for Long-Term Adaptation on Rugged Fitness Landscapes | es_ES |
dc.type | artículo | es_ES |
dc.identifier.doi | 10.1371/journal.pcbi.1000187 | - |
dc.description.peerreviewed | Peer reviewed | es_ES |
dc.identifier.e-issn | 1553-734X | - |
dc.identifier.pmid | 18818724 | - |
dc.type.coar | http://purl.org/coar/resource_type/c_6501 | es_ES |
item.openairetype | artículo | - |
item.cerifentitytype | Publications | - |
item.languageiso639-1 | en | - |
item.grantfulltext | open | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.fulltext | With Fulltext | - |
Aparece en las colecciones: | (IBMCP) Artículos |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
---|---|---|---|---|
Plos Computational Biology 4_9_e1000187.pdf | 281,45 kB | Adobe PDF | Visualizar/Abrir |
CORE Recommender
PubMed Central
Citations
35
checked on 23-mar-2024
SCOPUSTM
Citations
85
checked on 21-mar-2024
WEB OF SCIENCETM
Citations
80
checked on 26-feb-2024
Page view(s)
352
checked on 27-mar-2024
Download(s)
311
checked on 27-mar-2024
Google ScholarTM
Check
Altmetric
Altmetric
Artículos relacionados:
NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.