Complexities of recapitulating polygenic effects in natural populations: replication of genetic effects on wing shape in artificially selected and wild caught populations of<i>Drosophila melanogaster</i>

Pelletier, Katie; Pitchers, William; Mammel, Anna; Northrop-Albrecht, Emmalee J; Márquez, Eladio J.; Moscarella, Rosa A.; Houle, David; Dworkin, Ian

doi:10.1101/2022.05.12.491649

Cited by 3 publications

(5 citation statements)

References 64 publications

(156 reference statements)

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“…Alternatively, it is possible that these effect vectors do not estimate directions of effects well, and further titrating the strength of knockdowns may help to obtain better estimates. It is also possible that the RNAi knockdown does not correlate with the segregating allelic effect of the candidate genes, although previous studies have demonstrated correlation between segregating polymorphisms and genetic knockdown effects for wing shape (Pelletier et al, 2023; Pitchers et al, 2019). Quantitative complementation mapping experiments identified two regions that may be related to shape change in the same direction as the altitudinal effect vector (Figure 7).…”

Section: Discussionmentioning

confidence: 99%

“…For example, the Hippo developmental network is best known for its role in regulation of organ size, including the size of Drosophila wings. Variants in genes in the hippo signaling pathway influence wing shape variation, with correlated phenotypic effects (Pelletier et al, 2023; Pitchers et al, 2019). Interestingly, allele frequency changes across multiple hippo signaling loci following artificial selection for wing shape changes did not result in substantial wing size change (Pelletier et al, 2023).…”

Section: Discussionmentioning

confidence: 99%

“…Variants in genes in the hippo signaling pathway influence wing shape variation, with correlated phenotypic effects (Pelletier et al, 2023; Pitchers et al, 2019). Interestingly, allele frequency changes across multiple hippo signaling loci following artificial selection for wing shape changes did not result in substantial wing size change (Pelletier et al, 2023). In this study, we also see evidence for independent genetic bases of wing size and wing shape change (Figures 3,4).…”

Section: Discussionmentioning

confidence: 99%

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Polygenic architecture of adaptation to a high-altitude environment forDrosophila melanogasterwing shape and size

Pelletier,

Bilodeau,

Pellizzari-Delano

et al. 2024

Preprint

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As is typical of small insects, populations of Drosophila melanogaster adapted to high altitude environments evolved increased body size, disproportionality large wings, and differing wing shape compared to low-altitude ancestors. In one instance the colonization of high-altitude environments in Ethiopia is recent (2000 – 3000 years ago), and is a useful system to study alleles contributing to adaptive divergence. Unlike predictions derived from formulations Fisher-Kimura-Orr geometric model based on de novo mutations concurrent with selection, recent models predict segregating alleles in a population are more likely to contribute to adaptation on short time scales, particularly when populations are large and genetically diverse, like D. melanogaster. Strains derived from lowland (≈500m above sea level; ASL) and highland (≈ 3000m ASL) populations were used to generate F20 advanced-intercrosses. From each cross, phenotypically extreme individuals for size and shape were pool–sequenced, and genetic differentiation among pools of individuals demonstrated a polygenic architecture of divergence for size and shape. We identified one QTL of large effect, contributing to adaptive divergence in shape. This QTL is not observed in all crosses, pointing to the importance of examining independent genetic backgrounds when mapping alleles contributing to adaptation. Despite the intrinsic links between shape and size, we find a unique genetic basis of adaptation for these traits. This work demonstrates that many alleles, throughout the genome, rather than single, large effect alleles, contribute to adaption for Drosophila wing shape and size, adding to the growing body of evidence for polygenic adaptation.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Polygenic architecture of adaptation to a high-altitude environment forDrosophila melanogasterwing shape and size

Pelletier,

Bilodeau,

Pellizzari-Delano

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

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“…In this way, a population will evolve in the same direction of trait space by accumulating mutations in any of those equivalent elements. This redundancy can explain why genetic changes underlying parallel evolution often fail to be replicated (e.g., Pelletier et al 2023), since multiple changes at the genetic 20 level can explain the same phenotypic adaptations.…”

Section: Discussionmentioning

confidence: 99%

Using developmental dynamics for evolutionary prediction and control

Milocco,

Uller

2023

Preprint

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Understanding, predicting, and controlling the phenotypic consequences of genetic and environmental change is essential to many areas of fundamental and applied biology. In evolutionary biology, the generative process of development is a major source of organismal evolvability that constrains or facilitates adaptive change by shaping the distribution of phenotypic variation that selection can act upon. While the complex interactions between genetic and environmental factors during development may appear to make it impossible to infer the consequences of perturbations, the persistent observation that many perturbations result in similar phenotypes indicates that there is a logic to what variation is generated. Here, we show that a general representation of development as a dynamical system can reveal this logic. We build a framework that allows to predict the phenotypic effects of perturbations, and conditions for when the effects of perturbations of different origin are concordant. We find that this concordance is explained by two generic features of development, namely the dynamical dependence of the phenotype on itself and the fact that all perturbations must be funneled by the same developmental process. We apply our theoretical results to classical models of development and show that it can be used to predict the evolutionary response to selection using information of plasticity, and to accelerate evolution in a desired direction. The framework we introduce provides a way to quantitatively interchange perturbations, opening a new avenue of perturbation design to control the generation of variation, and thus evolution.

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“…Indeed, this is a commonly used multiple testing approach in practical applications with allele frequency testing (see e.g. [ 27 , 28 ]). We also considered the multiple testing approaches presented in " Multiple testing procedure " section.…”

Section: Methodsmentioning

confidence: 99%

Haplotype based testing for a better understanding of the selective architecture

Chen,

Pelizzola,

Futschik

2023

BMC Bioinformatics

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Background The identification of genomic regions affected by selection is one of the most important goals in population genetics. If temporal data are available, allele frequency changes at SNP positions are often used for this purpose. Here we provide a new testing approach that uses haplotype frequencies instead of allele frequencies. Results Using simulated data, we show that compared to SNP based test, our approach has higher power, especially when the number of candidate haplotypes is small or moderate. To improve power when the number of haplotypes is large, we investigate methods to combine them with a moderate number of haplotype subsets. Haplotype frequencies can often be recovered with less noise than SNP frequencies, especially under pool sequencing, giving our test an additional advantage. Furthermore, spurious outlier SNPs may lead to false positives, a problem usually not encountered when working with haplotypes. Post hoc tests for the number of selected haplotypes and for differences between their selection coefficients are also provided for a better understanding of the underlying selection dynamics. An application on a real data set further illustrates the performance benefits. Conclusions Due to less multiple testing correction and noise reduction, haplotype based testing is able to outperform SNP based tests in terms of power in most scenarios.

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Complexities of recapitulating polygenic effects in natural populations: replication of genetic effects on wing shape in artificially selected and wild caught populations ofDrosophila melanogaster

Cited by 3 publications

References 64 publications

Polygenic architecture of adaptation to a high-altitude environment forDrosophila melanogasterwing shape and size

Polygenic architecture of adaptation to a high-altitude environment forDrosophila melanogasterwing shape and size

Using developmental dynamics for evolutionary prediction and control

Haplotype based testing for a better understanding of the selective architecture

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