2012
DOI: 10.1098/rspb.2012.1917
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Footprints in time: comparative quantitative trait loci mapping of the pitcher-plant mosquito,Wyeomyia smithii

Abstract: Identifying regions of the genome contributing to phenotypic evolution often involves genetic mapping of quantitative traits. The focus then turns to identifying regions of 'major' effect, overlooking the observation that traits of ecological or evolutionary relevance usually involve many genes whose individual effects are small but whose cumulative effect is large. Herein, we use the power of fully interfertile natural populations of a single species of mosquito to develop three quantitative trait loci (QTL) … Show more

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Cited by 18 publications
(16 citation statements)
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“…Specifically, the Sbf1 restriction enzyme binding sites (i.e. RAD sites) are scattered across genomes at random locations [27]. Random scattering means that Sbf1 sites are not biased a priori towards particular linkage groups, gene clusters, or genomic regions from correlated evolutionary histories.…”
Section: Methodsmentioning
confidence: 99%
“…Specifically, the Sbf1 restriction enzyme binding sites (i.e. RAD sites) are scattered across genomes at random locations [27]. Random scattering means that Sbf1 sites are not biased a priori towards particular linkage groups, gene clusters, or genomic regions from correlated evolutionary histories.…”
Section: Methodsmentioning
confidence: 99%
“…For diapause induction, empirical insights acquired from population crosses and QTL studies are consistent with Mendelian inheritance patterns (Doležel, Vaněčková, Šauman, & Hodkova, ; Han & Denlinger, ; Suwa & Gotoh, ) or indicate an architecture with few loci of large effect sizes (Chen, Xiao, He, Xu, & Xue, ; Danilevskii, ; Demont & Blanckenhorn, ; Fu, Chen, Xiao, He, & Xue, ; Hagen & Scriber, ; Ikten, Skoda, Hunt, Molina‐Ochoa, & Foster, ; Kim, Krafsur, Bailey, & Zhao, ; Kurahashi & Ohtaki, ; Lehmann, Margus, & Lindström, ; McCoy, Lloyd, & Bartlett, ; McWatters & Saunders, ; Pruisscher et al., ; Rockey, Hainze, & Scriber, ; Söderlind & Nylin, ; Xia, Chen, Tu, Yang, & Xue, ), with several reporting large sex‐linked effects (Chen et al., ; Fu et al., ; Hagen & Scriber, ; Ikten et al., ; Nylin, Wickman, & Wiklund, ; Pruisscher et al., ; Rockey et al., ). Studies on quantitative trait loci for CPP show that effect sizes can be highly variable depending on the genetic background of the crosses involved (Bradshaw, Emerson, Catchen, Cresko, & Holzapfel, ). Additionally, as diapause induction is a plastic threshold trait, inheritance patterns depend on the environmental conditions used for phenotyping (Pruisscher et al., ).…”
Section: Introductionmentioning
confidence: 99%
“…Accordingly, understanding the synchronization of growth and reproduction with permissive conditions and the physiological mechanisms that determine this synchrony has been an important focus of research on adaptive evolution. Through such studies, a general understanding has emerged of how life histories are shaped by environmental uncertainty (Childs et al, 2010;Cohen, 1970;Kingsolver, 1979), of environmental effects on growth and development (Amano et al, 2014;Powell et al, 2000;Taylor, 1981), and of the genetic architecture underlying seasonal timing (Bradshaw et al, 2012;Lair et al, 1997;Li et al, 2010;Schmidt et al, 2008). Similarly, the physiological mechanisms that regulate seasonal timing in animals and plants have been investigated, particularly endocrine mechanisms regulating dormant, overwintering life stages (diapause) in insects (Denlinger, 2002;Hahn and Denlinger, 2011).…”
Section: Introductionmentioning
confidence: 99%