Investigating Natural Variation in<i>Drosophila</i>Courtship Song by the Evolve and Resequence Approach

Turner, Thomas L.; Miller, Paige M.

doi:10.1534/genetics.112.139337

Cited by 119 publications

(169 citation statements)

References 62 publications

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“…By contrast, courtship song frequencies do not appear to play a significant role in either species recognition or female mate choice in D. melanogaster [38]. In the light of our findings that deletion of the flightin N-terminal domain significantly decreases the PDC, increases the IPI and results in a broader range of IPIs than expected from natural variation [39], we conclude that the N-terminal domain fulfils a functional role in courtship song definition that is just as important as its role in flight power mechanics. The limited courtship success of fln DN62 males when competing with fln þ males for female access, as evident by lower CI (time courting) and WEI (time singing) (figure 1k,l ), further supports this conclusion.…”

Section: (B) Courtship Songcontrasting

confidence: 58%

Flightin maintains myofilament lattice organization required for optimal flight power and courtship song quality inDrosophila

et al. 2017

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The indirect flight muscles (IFMs) of Drosophila and other insects with asynchronous flight muscles are characterized by a crystalline myofilament lattice structure. The high-order lattice regularity is considered an adaptation for enhanced power output, but supporting evidence for this claim is lacking. We show that IFMs from transgenic flies expressing flightin with a deletion of its poorly conserved N-terminal domain ( fln DN62 ) have reduced interthick filament spacing and a less regular lattice. This resulted in a decrease in flight ability by 33% and in skinned fibre oscillatory power output by 57%, but had no effect on wingbeat frequency or frequency of maximum power output, suggesting that the underlying actomyosin kinetics is not affected and that the flight impairment arises from deficits in force transmission. Moreover, we show that fln DN62 males produced an abnormal courtship song characterized by a higher sine song frequency and a pulse song with longer pulses and longer inter-pulse intervals (IPIs), the latter implicated in male reproductive success. When presented with a choice, wild-type females chose control males over mutant males in 92% of the competition events. These results demonstrate that flightin N-terminal domain is required for optimal myofilament lattice regularity and IFM activity, enabling powered flight and courtship song production. As the courtship song is subject to female choice, we propose that the low amino acid sequence conservation of the N-terminal domain reflects its role in fine-tuning species-specific courtship songs.

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Section: (B) Courtship Songcontrasting

confidence: 58%

Flightin maintains myofilament lattice organization required for optimal flight power and courtship song quality inDrosophila

et al. 2017

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“…Although the DGRP is underpowered to study the architecture of complex traits due to the relatively small number of lines (n = 159 in our study), it is a good resource to identify candidate genes for experimental follow-up (21,22). To that end, we performed an association study using a series of locusspecific mixed linear models (accounting for relatedness between lines and experimental block effect) and found 36 polymorphisms in 22 genes associated with variability in turning bias using a nominal P value (19, 21) of 5 × 10 −6 ( Fig.…”

Section: Resultsmentioning

confidence: 99%

Behavioral idiosyncrasy reveals genetic control of phenotypic variability

Ayroles

Buchanan²,

O’Leary

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

172

207

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Quantitative genetics has primarily focused on describing genetic effects on trait means and largely ignored the effect of alternative alleles on trait variability, potentially missing an important axis of genetic variation contributing to phenotypic differences among individuals. To study the genetic effects on individual-to-individual phenotypic variability (or intragenotypic variability), we used Drosophila inbred lines and measured the spontaneous locomotor behavior of flies walking individually in Y-shaped mazes, focusing on variability in locomotor handedness, an assay optimized to measure variability. We discovered that some lines had consistently high levels of intragenotypic variability among individuals, whereas lines with low variability behaved as although they tossed a coin at each left/right turn decision. We demonstrate that the degree of variability is itself heritable. Using a genome-wide association study (GWAS) for the degree of intragenotypic variability as the phenotype across lines, we identified several genes expressed in the brain that affect variability in handedness without affecting the mean. One of these genes, Ten-a, implicates a neuropil in the central complex of the fly brain as influencing the magnitude of behavioral variability, a brain region involved in sensory integration and locomotor coordination. We validated these results using genetic deficiencies, null alleles, and inducible RNAi transgenes. Our study reveals the constellation of phenotypes that can arise from a single genotype and shows that different genetic backgrounds differ dramatically in their propensity for phenotypic variabililty. Because traditional mean-focused GWASs ignore the contribution of variability to overall phenotypic variation, current methods may miss important links between genotype and phenotype.variability | variance QTL | DGRP | ten-a | personality

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“…For plan I, there is a positive correlation between allele frequencies sampled t generations apart because they are both derived from the same population at generation 0. In contrast, for plan II, the initial sample and individuals contributing to the next generation can be considered as independent binomial samples; thus sample frequencies at generations 0 and t are uncorrelated.For a typical E&R study, outbred experimental populations are created by mixing a large number of inbred lines (e.g., Turner and Miller 2012;Huang et al 2014;Franssen et al 2015). The populations are then propagated under the desired experimental conditions while keeping the census size of the population controlled through time (Figure 1).…”

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confidence: 99%

Estimating effective population size from temporal allele frequency changes in experimental evolution

Jónás¹,

Taus²,

Kosiol³

et al. 2016

Preprint

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The effective population size (N e ) is a major factor determining allele frequency changes in natural and experimental populations. Temporal methods provide a powerful and simple approach to estimate short-term N e : They use allele frequency shifts between temporal samples to calculate the standardized variance, which is directly related to N e : Here we focus on experimental evolution studies that often rely on repeated sequencing of samples in pools (Pool-seq). Pool-seq is cost-effective and often outperforms individual-based sequencing in estimating allele frequencies, but it is associated with atypical sampling properties: Additional to sampling individuals, sequencing DNA in pools leads to a second round of sampling, which increases the variance of allele frequency estimates. We propose a new estimator of N e ; which relies on allele frequency changes in temporal data and corrects for the variance in both sampling steps. In simulations, we obtain accurate N e estimates, as long as the drift variance is not too small compared to the sampling and sequencing variance. In addition to genome-wide N e estimates, we extend our method using a recursive partitioning approach to estimate N e locally along the chromosome. Since the type I error is controlled, our method permits the identification of genomic regions that differ significantly in their N e estimates. We present an application to Pool-seq data from experimental evolution with Drosophila and provide recommendations for whole-genome data. The estimator is computationally efficient and available as an R package at https://github.com/ThomasTaus/Nest. KEYWORDS effective population size; genetic drift; Pool-seq; experimental evolution D URING experimental evolution studies, populations are maintained under specific laboratory conditions (Kawecki et al. 2012;Long et al. 2015;Schlötterer et al. 2015). In sexually reproducing organisms, the census population size is typically kept fixed at fairly low numbers, rarely exceeding 2000 individuals. With such small population sizes, genetic drift causes stochastic fluctuations in allele frequencies. Under neutrality, the level of random frequency changes is determined by the effective population size (N e ) (Wright 1931). Furthermore, the efficacy of selection is influenced by N e : For weakly selected alleles, the probability of fixation is directly proportional to the product of N e and the intensity of selection (Fisher 1930;Kimura 1964). As changes in allele frequency are greatly affected by the population size, it is fundamental to estimate N e accurately to understand molecular variation in experimental evolution studies. Krimbas and Tsakas (1971) estimated N e using the standardized variance of allele frequency (F, see also Falconer and Mackay 1996) from longitudinal samples in natural populations of olive flies. As F was calculated from these samples, they accounted for the sampling variance that also contributed to the true allele frequency variance. This approach was further improved and used by sev...

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Investigating Natural Variation inDrosophilaCourtship Song by the Evolve and Resequence Approach

Cited by 119 publications

References 62 publications

Flightin maintains myofilament lattice organization required for optimal flight power and courtship song quality inDrosophila

Flightin maintains myofilament lattice organization required for optimal flight power and courtship song quality inDrosophila

Behavioral idiosyncrasy reveals genetic control of phenotypic variability

Estimating effective population size from temporal allele frequency changes in experimental evolution

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