The genetic architecture of adaptive traits is of key importance to predict evolutionary responses. Most adaptive traits are polygenic—i.e., result from selection on a large number of genetic loci—but most molecularly characterized traits have a simple genetic basis. This discrepancy is best explained by the difficulty in detecting small allele frequency changes (AFCs) across many contributing loci. To resolve this, we use laboratory natural selection to detect signatures for selective sweeps and polygenic adaptation. We exposed 10 replicates of a Drosophila simulans population to a new temperature regime and uncovered a polygenic architecture of an adaptive trait with high genetic redundancy among beneficial alleles. We observed convergent responses for several phenotypes—e.g., fitness, metabolic rate, and fat content—and a strong polygenic response (99 selected alleles; mean s = 0.059). However, each of these selected alleles increased in frequency only in a subset of the evolving replicates. We discerned different evolutionary paradigms based on the heterogeneous genomic patterns among replicates. Redundancy and quantitative trait (QT) paradigms fitted the experimental data better than simulations assuming independent selective sweeps. Our results show that natural D. simulans populations harbor a vast reservoir of adaptive variation facilitating rapid evolutionary responses using multiple alternative genetic pathways converging at a new phenotypic optimum. This key property of beneficial alleles requires the modification of testing strategies in natural populations beyond the search for convergence on the molecular level. It is widely assumed that adaptation is mainly polygenic, with the underlying frequency changes being so small that they are difficult to detect and characterize. Taking advantage of laboratory-based natural selection of replicated populations of the fruit fly Drosophila simulans exposed to a high temperature regime, we identified a polygenic response with many (99) selected alleles having pronounced allele frequency changes (AFCs). Despite phenotypic convergence across the 10 replicates, the genomic response was highly heterogeneous, with different subsets of the selected alleles contributing to the convergent phenotype in each of the replicate populations. The observed genetic redundancy not only indicates lack of genetic constraint but also demonstrates that multiple genetic pathways lead to convergent phenotypic outcomes.

Genes that encode products with exogenous targets, which comprise an organism's “exogenome,” typically exhibit high rates of evolution. The genes encoding the venom peptides (conotoxins or conopeptides) in Conus sensu lato exemplify this class of genes. Their rapid diversification has been established and is believed to be linked to the high speciation rate in this genus. However, the molecular mechanisms that underlie venom peptide diversification and ultimately emergence of new species remain poorly understood. In this study, the sequences and expression levels of conotoxins from several specimens of two closely related worm-hunting species, Conus tribblei and Conus lenavati , were compared through transcriptome analysis. Majority of the identified putative conopeptides were novel, and their diversity, even in each specimen, was remarkably high suggesting a wide range of prey targets for these species. Comparison of the interspecific expression patterns of conopeptides at the superfamily level resulted in the discovery of both conserved as well as species-specific expression patterns, indicating divergence in the regulatory network affecting conotoxin gene expression. Comparison of the transcriptomes of the individual snails revealed that each specimen produces a distinct set of highly expressed conopeptides, reflecting the capability of individual snails to fine-tune the composition of their venoms. These observations reflect the role of sequence divergence and divergence in the control of expression for specific conopeptides in the evolution of the exogenome and hence venom composition in Conus .

The pervasive occurrence of sexual dimorphism demonstrates different adaptive strategies of males and females. While different reproductive strategies of the two sexes are well-characterized, very little is known about differential functional requirements of males and females in their natural habitats. Here, we study the impact environmental change on the selection response in both sexes. Exposing replicated Drosophila populations to a novel temperature regime, we demonstrate sex-specific changes in gene expression, metabolic and behavioral phenotypes in less than 100 generations. This indicates not only different functional requirements of both sexes in the new environment but also rapid sex-specific adaptation. Supported by computer simulations we propose that altered sex-biased gene regulation from standing genetic variation, rather than new mutations, is the driver of rapid sex-specific adaptation. Our discovery of environmentally driven divergent functional requirements of males and females has important implications-possibly even for gender aware medical treatments.

In molecular population genetics, adaptation is typically thought to occur via selective sweeps, where targets of selection have independent effects on the phenotype and rise to fixation, whereas in quantitative genetics, many loci contribute to the phenotype and subtle frequency changes occur at many loci during polygenic adaptation. The sweep model makes specific predictions about frequency changes of beneficial alleles and many test statistics have been developed to detect such selection signatures. Despite polygenic adaptation is probably the prevalent mode of adaptation, because of the traditional focus on the phenotype, we are lacking a solid understanding of the similarities and differences of selection signatures under the two models. Recent theoretical and empirical studies have shown that both selective sweep and polygenic adaptation models could result in a sweep-like genomic signature; therefore, additional criteria are needed to distinguish the two models. With replicated populations and time series data, experimental evolution studies have the potential to identify the underlying model of adaptation. Using the framework of experimental evolution, we performed computer simulations to study the pattern of selected alleles for two models: 1) adaptation of a trait via independent beneficial mutations that are conditioned for fixation, that is, selective sweep model and 2) trait optimum model (polygenic adaptation), that is adaptation of a quantitative trait under stabilizing selection after a sudden shift in trait optimum. We identify several distinct patterns of selective sweep and trait optimum models in populations of different sizes. These features could provide the foundation for development of quantitative approaches to differentiate the two models.