The Drosophila melanogaster Genetic Reference Panel

Mackay, Trudy F. C.; Richards, Stephen; Stone, Eric A.; Barbadilla, Antonio; Ayroles, Julien F.; Zhu, Dianhui; Casillas, Sònia; Han, Yi; Magwire, Michael M.; Cridland, Julie M.; Richardson, Mark F.; Anholt, Robert R. H.; Barrón, Maite G.; Bess, Crystal; Blankenburg, Kerstin P.; Carbone, Mary Anna; Castellano, David; Chaboub, Lesley; Duncan, Laura; Harris, Z. L.; Javaid, Mehwish; Jayaseelan, Joy C.; Jhangiani, Shalini N.; Jordan, Katherine; Lara, Fremiet; Lawrence, Faye; Lee, Sandra L.; Librado, Pablo; Linheiro, Raquel; Lyman, Richard F.; Mackey, Aaron J.; Munidasa, Mala; Muzny, Donna M.; Nazareth, Lynne V.; Newsham, Irene; Perales, Lora; Pu, Ling-Ling; Qu, Carson; Ràmia, Miquel; Reid, Jeffrey G.; Rollmann, Stephanie M.; Rozas, Julio; Saada, Nehad; Turlapati, Lavanya; Worley, Kim C.; Wu, Yuanqing; Yamamoto, Akihiko; Zhu, Yiping; Bergman, Casey M.; Thornton, Kevin R.; Mittelman, David; Gibbs, Richard A.

doi:10.1038/nature10811

Cited by 1,605 publications

(2,690 citation statements)

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“…However, very few studies have assayed natural fly populations—mainly various mutant and inversion‐baring strains have been studied, or experiments were performed with a single isofemale line. By utilizing the DGRP, we could test the effects of competition on naturally occurring genetic variation (Mackay et al., 2012) and draw ecologically relevant conclusions about variation for the studied traits. Moreover, studying a panel of genotypes provided us with the opportunity to test for important evolutionary questions, such as how does evolvability of traits change with the increasing level of density stress?…”

Section: Discussionmentioning

confidence: 99%

“…We measured the phenotypic response of 31 DGRP strains ( D. melanogaster Genetic Reference Panel, Mackay et al., 2012), which are inbred strains derived from a wild North American population with completely sequenced genomes. The DGRP strains are characterized by high genetic (Mackay et al., 2012; Massouras et al., 2012) and phenotypic variation (Ayroles et al., 2009; Durham, Magwire, Stone, & Leips, 2014; Ellis et al., 2014; Harbison, McCoy, & Mackay, 2013; Mackay et al., 2012; Unckless, Rottschaefer, & Lazzaro, 2015).…”

Section: Methodsmentioning

confidence: 99%

“…The DGRP strains are characterized by high genetic (Mackay et al., 2012; Massouras et al., 2012) and phenotypic variation (Ayroles et al., 2009; Durham, Magwire, Stone, & Leips, 2014; Ellis et al., 2014; Harbison, McCoy, & Mackay, 2013; Mackay et al., 2012; Unckless, Rottschaefer, & Lazzaro, 2015). Fly stocks were ordered from the Bloomington Stock Center and are kept in standard molasses/soy‐corn flour/agar media‐containing vials.…”

Section: Methodsmentioning

confidence: 99%

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Effects of larval crowding on quantitative variation for development time and viability in Drosophila melanogaster

Hórvath

Kalinka

2016

Ecology and Evolution

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Competition between individuals belonging to the same species is a universal feature of natural populations and is the process underpinning organismal adaptation. Despite its importance, still comparatively little is known about the genetic variation responsible for competitive traits. Here, we measured the phenotypic variation and quantitative genetics parameters for two fitness‐related traits—egg‐to‐adult viability and development time—across a panel of Drosophila strains under varying larval densities. Both traits exhibited substantial genetic variation at all larval densities, as well as significant genotype‐by‐environment interactions (GEIs). GEI was attributable to changes in the rank order of reaction norms for both traits, and additionally to differences in the between‐line variance for development time. The coefficient of genetic variation increased under stress conditions for development time, while it was higher at both high and low densities for viability. While development time also correlated negatively with fitness at high larval densities—meaning that fast developers have high fitness—there was no correlation with fitness at low density. This result suggests that GEI may be a common feature of fitness‐related genetic variation and, further, that trait values under noncompetitive conditions could be poor indicators of individual fitness. The latter point could have significant implications for animal and plant breeding programs, as well as for conservation genetics.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Effects of larval crowding on quantitative variation for development time and viability in Drosophila melanogaster

Hórvath

Kalinka

2016

Ecology and Evolution

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“…Finally, the Drosophila Genetic Reference Panel (DGRP) represents a unique asset for population genomics and genome-wide association studies (GWAS) based on 168 fully sequenced strains that can be subjected to any number of infectious challenges [68]. Importantly, polymorphisms associated with changes in immune function coming from this kind of screen will bring to light regulatory, intergenic regions in addition to protein-encoding genes.…”

Section: Methods For Identifying Novel Immune Genes Based On Large Scmentioning

confidence: 99%

Methods to study Drosophila immunity

Neyen

Bretscher

Binggeli

et al. 2014

Methods

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a b s t r a c tInnate immune mechanisms are well conserved throughout evolution, and many theoretical concepts, molecular pathways and gene networks are applicable to invertebrate model organisms as much as vertebrate ones. Drosophila immunity research benefits from an easily manipulated genome, a fantastic international resource of transgenic tools and over a quarter century of accumulated techniques and approaches to study innate immunity. Here we present a short collection of ways to challenge the fruit fly immune system with various pathogens and parasites, as well as read-outs to assess its functions, including cellular and humoral immune responses. Our review covers techniques for assessing the kinetics and efficiency of immune responses quantitatively and qualitatively, such as survival analysis, bacterial persistence, antimicrobial peptide gene expression, phagocytosis and melanisation assays. Finally, we offer a toolkit of Drosophila strains available to the research community for current and future research.

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“…Indeed in Drosophila the fraction of loci affected by recent positive selection may be quite large (Begun et al 2007;Langley et al 2012). Numerous studies have estimated that the fraction of adaptive amino acid substitutions in D. melanogaster is considerable, with estimates ranging from 10 to 50% (Smith and EyreWalker 2002;Bierne and Eyre-Walker 2004;Langley et al 2012;Mackay et al 2012). Direct estimates of the rate of recurrent hitchhiking in Drosophila populations also indicate a substantial flux of adaptive substitution, with the population effective sweep rate varying between 1.1 3 10 25 and 2.6 3 10 23 sweeps per base pair per 2N generations (Li and Stephan 2006;Andolfatto 2007;Macpherson et al 2007;Jensen et al 2008).…”

Section: Discussionmentioning

confidence: 99%

Effects of Linked Selective Sweeps on Demographic Inference and Model Selection

2016

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The availability of large-scale population genomic sequence data has resulted in an explosion in efforts to infer the demographic histories of natural populations across a broad range of organisms. As demographic events alter coalescent genealogies, they leave detectable signatures in patterns of genetic variation within and between populations. Accordingly, a variety of approaches have been designed to leverage population genetic data to uncover the footprints of demographic change in the genome. The vast majority of these methods make the simplifying assumption that the measures of genetic variation used as their input are unaffected by natural selection. However, natural selection can dramatically skew patterns of variation not only at selected sites, but at linked, neutral loci as well. Here we assess the impact of recent positive selection on demographic inference by characterizing the performance of three popular methods through extensive simulation of data sets with varying numbers of linked selective sweeps. In particular, we examined three different demographic models relevant to a number of species, finding that positive selection can bias parameter estimates of each of these models-often severely. We find that selection can lead to incorrect inferences of population size changes when none have occurred. Moreover, we show that linked selection can lead to incorrect demographic model selection, when multiple demographic scenarios are compared. We argue that natural populations may experience the amount of recent positive selection required to skew inferences. These results suggest that demographic studies conducted in many species to date may have exaggerated the extent and frequency of population size changes.KEYWORDS population genetics; positive selection; demographic inference T HE widespread availability of population genomic data has spurred a new generation of studies aimed at understanding the histories of natural populations from a host of model and nonmodel organisms alike. In particular, genomescale variation data allows for inference of demographic factors such as population size changes, the timing and ordering of population splits, migration rates between populations, and the founding of admixed populations (Pool et al. 2010;Pickrell and Pritchard 2012;Sousa and Hey 2013). Such efforts can refine our picture of demographic events inferred from the archaeological record (e.g., Fagundes et al. 2007;Goebel et al. 2008), or reveal such events in species where no archaeological data are available, and can aid conservation efforts by complementing census data (e.g., Hájková et al. 2007;Garrick et al. 2015).Population genomic data sets are well suited for this task simply because demographic changes leave their mark on patterns of genetic variation. Recent population growth, for example, will result in an excess of rare variation compared to equilibrium expectations (Fu 1997), while population contraction will result in an excess of intermediate frequency alleles (Maruyama and Fuerst 198...

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The Drosophila melanogaster Genetic Reference Panel

Cited by 1,605 publications

References 44 publications

Effects of larval crowding on quantitative variation for development time and viability in Drosophila melanogaster

Effects of larval crowding on quantitative variation for development time and viability in Drosophila melanogaster

Methods to study Drosophila immunity

Effects of Linked Selective Sweeps on Demographic Inference and Model Selection

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