Linked Life Data

19589187

Source:http://linkedlifedata.com/resource/pubmed/id/19589187

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2009-7-10
pubmed:abstractText
Fine scale analyses of signatures of selection allow assessing quantitative aspects of a species' evolutionary genetic history, such as the strength of selection on genes. When several selected loci lie in the same genomic region, their epistatic interactions may also be investigated. Here, we study how the neutral polymorphism pattern was shaped by two close recombining loci that cause 'sex-ratio' meiotic drive in Drosophila simulans, as an example of strong selection with potentially strong epistasis. We compare the polymorphism data observed in a natural population with the results of forward stochastic simulations under several contexts of epistasis between the candidate loci for the drive. We compute the likelihood of different possible scenarios, in order to determine which configuration is most consistent with the data. Our results highlight that fine scale analyses of well-chosen candidate genomic regions provide information-rich data that can be used to investigate the genotype-phenotype-fitness map, which can hardly be studied in genome-wide analyses. We also emphasize that initial conditions and time of observation (here, time after the interruption of a partial selective sweep) are crucial parameters in the interpretation of real data, while these are often overlooked in theoretical studies.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
1469-5073
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
91
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
171-82
pubmed:dateRevised
2010-12-28
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Molecular signature of epistatic selection: interrogating genetic interactions in the sex-ratio meiotic drive of Drosophila simulans.
pubmed:affiliation
UMR de Génétique Végétale, Ferme du Moulon, 91190 Gif Sur Yvette, France. l.chevin@imperial.ac.uk
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't