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PubMed · 39554054

Pervasive fitness trade-offs revealed by rapid adaptation to shifting population densities in large experimental populations of Drosophila melanogaster.

Abstract

Trade-offs are an inherent feature of organismal biology that are expected play a fundamental role in the evolution of natural populations. Efforts to quantify trade-offs are largely confined to phenotypic measurements and the identification of negative genetic-correlations among fitness-relevant traits. Here, we use time-series genomic data collected during experimental evolution in large, genetically diverse populations of Drosophila melanogaster to directly measure the manifestation of trade-offs in response to fluctuating selection on ecological timescales. Specifically, we first conducted a lab-based selection experiment to quantify a genome-wide signal of antagonistic pleiotropy elicited in response to shifting population densities and associated with reproduction and stress tolerance selection. In doing so, we identified a putative role of two cosmopolitan inversions in these trade-offs. We then conducted an independent experiment to show that a simple manipulation of increasing population density under controlled lab-based conditions identified loci that are relevant to selection during population expansion and collapse in a complex, semi-natural setting. In concert, our results reveal how adaptation in complex, natural environments can be coarse-grained in such a manner to drive repeatable and predictable patterns of genomic variation, and further add credence to models positing a role of generic fitness trade-offs in the maintenance of variation in natural populations.

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BibTeXRIS

M C Bitter, S Greenblum, S Rajpurohit, A O Bergland, J A Hemker, Egor Lappo, N J Betancourt, S Tilk, S Berardi, H Oken, P Schmidt, D A Petrov. 2025-07-18. Pervasive fitness trade-offs revealed by rapid adaptation to shifting population densities in large experimental populations of Drosophila melanogaster.. https://doi.org/10.1101/2024.10.28.620721

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