Biology subjects

Schloetterer, C.

Publications and source records attributed to Schloetterer, C..

9 recordsLinked to original sources

bioRxiv2024

Pleiotropy increases parallel selection signatures during adaptation from standing genetic variation

The phenomenon of parallel evolution, whereby similar genomic and phenotypic changes occur across replicated pairs of population or species, is widely studied. Nevertheless, the determining factors of parallel evolution remain poorly understood. Theoretical studies have proposed that pleiotropy, the influence of a single gene on multiple traits, is an important factor. In order to gain a deeper insight into the role of pleiotropy for parallel evolution from standing genetic variation, we characterized the interplay between parallelism, polymorphism and pleiotropy. The present study examined the parallel gene expression evolution in 10 replicated populations of Drosophila simulans, which were adapted from standing variation to the same new temperature regime. The data demonstrate that parallel evolution of gene expression from standing genetic variation is positively correlated with the strength of pleiotropic effects. The ancestral variation in gene expression is, however, negatively correlated with parallelism. Given that pleiotropy is also negatively correlated with gene expression variation, we conducted a causal analysis to distinguish cause and correlation and evaluate the role of pleiotropy. The causal analysis indicated that both direct (causative) and indirect (correlational) effects of pleiotropy contribute to parallel evolution. The indirect effect is mediated by historic selective constraint in response to pleiotropy. This results in parallel selection responses due to the reduced standing variation of pleiotropic genes. The direct effect of pleiotropy is likely to reflect a genetic correlation among adaptive traits, which in turn gives rise to synergistic effects and higher parallelism.

evolutionary biology↗

bioRxiv2023

Functional Adaptations of Endogenous Retroviruses to the Drosophila Host Underlie their Evolutionary Diversification

Transposable elements profoundly affect the biology and evolution of their hosts, yet their own evolutionary dynamics remain poorly understood. Here, we investigate insect endogenous retroviruses (iERVs), a monophyletic group of LTR retrotransposons that have acquired the trait of infectivity, likely through capture of a Baculovirus envelope gene. In Drosophila ovaries, iERVs with functional envelope have adapted their cis-regulatory sequences to be expressed in any somatic cell type, from where they infect the germline. Strikingly, related retroviruses show distinct expression patterns, indicating niche partitioning. In contrast, all non-infectious iERVs that emerged through secondary envelope-loss are specifically expressed in the germline. Co-evolving with iERVs, the genome-protecting piRNA pathway has assimilated iERV promoter and sequence information into piRNA clusters, underscoring the functional significance of iERV expression in somatic niches. We propose that the evolutionary innovation of cell-to-cell infectivity has triggered the adaptive radiation of iERVs through trait diversification and antagonistic virus-host interactions, processes that likely underpin niche-specific expression of endogenous retroviruses in vertebrates as well.

evolutionary biology↗

bioRxiv2021

The transposition rate has little influence on equilibrium copy numbers of the P-element

The invasion of transposable elements (TEs) in mammals and invertebrates, is likely stopped by piRNAs that emerge after insertion of the TE into a piRNA cluster (the trap model). It remains, however, still unclear which factors influence the dynamics of TE invasions. The activity of the TE (i.e. transposition rate) is one of the frequently discussed key factors. Here we take advantage of the temperature-dependent activity of the P-element, a widely studied eukaryotic TE, to test how TE activity affects the dynamics of a TE invasion. Taking advantage of the temperature-specific activity of the P-element, we monitored its invasion dynamics in experimental Drosophila simulans populations at hot and cold culture conditions. Despite marked differences in transposition rates, the P-element reached very similar copy numbers at both temperatures. The reduction of the insertion rate upon approaching the copy number plateau was accompanied by the emergence of similar amounts of piRNAs against the P-element at both temperatures. Interestingly, the ping-pong cycle, which degrades TE transcripts, becomes only active after the copy number has reached the plateau. We show that the P-element abundance is an order of magnitude lower and fewer P-element insertions in piRNA clusters were observed than expected under the trap model. We conclude that the transposition rate has at the most only a minor influence on TE abundance, but other factors, such as paramutations or selection against TE insertions are shaping the TE composition of organism.

evolutionary biology↗

bioRxiv2019

Distance to trait optimum is a crucial factor determining the genomic signature of polygenic adaptation

Polygenic adaptation is frequently associated with small allele frequency changes of many loci. Recent works suggest, that large allele frequency changes can be also expected. Laboratory natural selection (LNS) experiments provide an excellent experimental framework to study the adaptive architecture under controlled laboratory conditions: time series data in replicate populations evolving independently to the same trait optimum can be used to identify selected loci. Nevertheless, the choice of the new trait optimum in the laboratory is typically an ad hoc decision without consideration of the distance of the starting population to the new optimum. Here, we used forward-simulations to study the selection signatures of polygenic adaptation in populations evolving to different trait optima. Mimicking LNS experiments we analyzed allele frequencies of the selected alleles and population fitness at multiple time points. We demonstrate that the inferred adaptive architecture strongly depends on the choice of the new trait optimum in the laboratory and the significance cut-off used for identification of selected loci. Our results not only have a major impact on the design of future Evolve and Resequence (E&R) studies, but also on the interpretation of current E&R data sets.

evolutionary biology↗

bioRxiv2019

Secondary evolve and re-sequencing: an experimental confirmation of putative selection targets without phenotyping

Evolve and re-sequencing (E&R) studies investigate the genomic responses of adaptation during experimental evolution. Because replicate populations evolve in the same controlled environment, consistent responses to selection across replicates are frequently used to identify reliable candidate regions that underlie adaptation to a new environment. However, recent work demonstrated that selection signatures can be restricted to one or a few replicate(s) only. These selection signatures frequently have a weak statistical support, and given the difficulties of functional validation, additional evidence is needed before considering them as candidates for functional analysis. Here, we introduce an experimental procedure to validate candidate loci with weak or replicate-specific selection signature(s). Crossing an evolved population from a primary E&R experiment to the ancestral founder population reduces the frequency of candidate alleles that have reached a high frequency. We hypothesize that genuine selection targets will experience a repeatable frequency increase after the mixing with the ancestral founders if they are exposed to the same environment (secondary E&R experiment). Using this approach, we successfully validate two overlapping selection targets, which showed a mutually exclusive selection signature in a primary E&R experiment of Drosophila simulans adapting to a novel temperature regime. We conclude that secondary E&R experiments provide a reliable confirmation of selection signatures that are either not replicated or show only a low statistical significance in a primary E&R experiment. Such experiments are particularly helpful to prioritize candidate loci for time-consuming functional follow-up investigations.

molecular biology↗

bioRxiv2019

A generalised approach to detect selected haplotype blocks in Evolve and Resequence experiments

Shifting from the analysis of single nucleotide polymorphisms to the reconstruction of selected haplotypes greatly facilitates the interpretation of Evolve and Resequence (E&R) experiments. Merging highly correlated hitchhiker SNPs into haplotype blocks reduces thousands of candidates to few selected regions. Current methods of haplotype reconstruction from Pool-Seq data need a variety of data-specific parameters that are typically defined ad hoc and require haplotype sequences for validation. Here, we introduce haplovalidate, a tool which detects selected haplotypes in a broad range of Pool-seq time series data without the need of sequenced haplotypes. Haplovalidate makes data-driven choices of two key parameters for the clustering procedure, the minimum correlation between SNPs constituting a cluster and the window size. Applying haplovalidate to simulated and experimental E&R data reliably detects selected haplotype blocks with low false discovery rates - independent if few or many selection targets are included. Our analyses identified an important restriction of the haplotype block-based approach to describe the genomic architecture of adaptation. We detected a substantial fraction of haplotypes containing multiple selection targets. These blocks were considered as one region of selection and therefore led to under-estimation of the number of selection targets. We demonstrate that the separate analysis of earlier time points can significantly increase the separation of selection targets into individual haplotype blocks. We conclude that the analysis of selected haplotype blocks has a large potential for the characterisation of the adaptive architecture with E&R experiments.

evolutionary biology↗

bioRxiv2019

Distinct patterns of selective sweep and polygenic adaptation

The central paradigm of molecular population genetics is selective sweeps, where targets of selection have independent effects on the phenotype and quickly rise to fixation. In quantitative genetics, many loci contribute epistatically to adaptation and subtle frequency changes occur at many loci. Since both paradigms could result in a sweep-like genomic signature, additional criteria are needed to distinguish them. Using the framework of experimental evolution, we performed computer simulations to study the pattern of selected alleles under both paradigms. We identify several distinct patterns of selective sweeps and polygenic adaptation in populations of different sizes. These features could provide the foundation for development of quantitative approaches to differentiate the two paradigms.\n\nAuthors summaryThe selective sweep model assumes an independent frequency increase of favorable alleles and has been the basis of many tests for selection. While, polygenic adaptation is typically modelled by small frequency shifts in many loci. Recently, some theoretical and empirical work demonstrated that polygenic adaptation, similar to sweep, could also results in pronounced allele frequency changes. These results suggest that other distinct features need to be identified. Using computer simulations, we identified distinctive features for each paradigm that can be used to differentiate the sweep model from polygenic adaptation. Features such as allele frequency trajectories, time-series fitness, distribution of selected alleles on haplotypes, and parallelism among replicates can be used for development of suitable tests to distinguish between different adaptive architectures. These features provide the basis for theoretical modeling, design of selection experiments and data analysis.

evolutionary biology↗

bioRxiv2019

Benchmarking software tools for detecting and quantifying selection in Evolve and Resequencing studies

The combination of experimental evolution with whole genome re-sequencing of pooled individuals, also called Evolve and Resequence (E&R) is a powerful approach to study selection processes and to infer the architecture of adaptive variation. Given the large potential of this method, a range of software tools were developed to identify selected SNPs and to measure their selection coefficients. In this benchmarking study, we are comparing 15 test statistics implemented in 10 software tools using three different scenarios. We demonstrate that the power of the methods differs among the scenarios, but some consistently outperform others. LRT-1, which takes advantage of time series data consistently performed best for all three scenarios. Nevertheless, the CMH test, which requires only two time points had almost the same performance. This benchmark study will not only facilitate the analysis of already existing data, but also affect the design of future data collections.

evolutionary biology↗

bioRxiv2018

Polygenic adaptation fuels genetic redundancy in Drosophila

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 across many contributing loci. To resolve this, we use laboratory natural selection, a framework that is powerful enough 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 adaptive alleles. We observed convergent phenotypic responses, e.g. fitness, metabolic rate and fat content, and a strong polygenic response (99 selected alleles; mean s=0.061). However, each of these selected alleles increased in frequency only in a subset of the evolving replicates. Our results show that natural D. simulans populations harbor a vast reservoir of adaptive variation facilitating rapid evolutionary responses. The observed genetic redundancy potentiates this genotypic variation through multiple genetic pathways leading to phenotypic convergence. This key property of adaptive alleles requires the modification of testing strategies in natural populations beyond the search for convergence on the molecular level.

evolutionary biology↗