Biology subjects

Langmüller, A. M.

Publications and source records attributed to Langmüller, A. M..

4 recordsLinked to original sources

bioRxiv2024

Purifying Selection Shapes the Dynamics of P-element Invasion in Drosophila Populations

BackgroundTransposable elements (TEs) are DNA sequences that can move within a host genome. Many new TE insertions have deleterious effects on their host and are therefore removed by purifying selection. The genomic distribution of TEs thus reflects a balance between new insertions and purifying selection. However, the inference of purifying selection against deleterious TE insertions from the patterns observed in natural populations is challenged by the confounding effects of demographic events, such as population bottlenecks and migration. ResultsWe used Experimental Evolution to study the role of purifying selection during the invasion of the P-element, a highly invasive TE, in replicated Drosophila simulans populations under controlled laboratory conditions. Because the change in P-element copy number over time provides information about the transposition rate and the effect of purifying selection, we repeatedly sequenced the experimental populations to study the P-element invasion dynamics. Based on the empirical data, we used Gaussian Process surrogate models to efficiently explore the parameter space and identify parameter combinations that best reproduce the experimental P-element invasion trajectories. Assuming that beneficial P-element insertions are negligible, we found that, in our experimental populations, 73% (60.9% - 76.1%) of new P-element insertions are under purifying selection with a mean selection coefficient of -0.056 (-0.060 - -0.042), highlighting the central role of selection in shaping P-element invasion dynamics. ConclusionThis study underscores the power of Experimental Evolution as a tool for studying transposable element invasions and highlights the pivotal role of purifying selection in regulating P-element dynamics.

evolutionary biology↗

bioRxiv2021

A homing suppression gene drive with multiplexed gRNAs maintains high drive conversion efficiency and avoids functional resistance alleles

Gene drives are engineered alleles that can bias inheritance in their favor, allowing them to spread throughout a population. They could potentially be used to modify or suppress pest populations, such as mosquitoes that spread diseases. CRISPR/Cas9 homing drives, which copy themselves by homology-directed repair in drive/wild-type heterozygotes, are a powerful form of gene drive, but they are vulnerable to resistance alleles that preserve the function of their target gene. Such resistance alleles can prevent successful population suppression. Here, we constructed a homing suppression drive in Drosophila melanogaster that utilized multiplexed gRNAs to inhibit the formation of functional resistance alleles in its female fertility target gene. The selected gRNA target sites were close together, preventing reduction in drive conversion efficiency. The construct reached a moderate equilibrium frequency in cage populations without apparent formation of resistance alleles. However, a moderate fitness cost prevented elimination of the cage population, showing the importance of using highly efficient drives in a suppression strategy, even if resistance can be addressed. Nevertheless, our results experimentally demonstrate the viability of the multiplexed gRNAs strategy in homing suppression gene drives.

genetics↗

bioRxiv2021

Fine mapping without phenotyping: Identification of selection targets in secondary Evolve and Resequence experiments

Evolve and Resequence (E&R) studies investigate the genomic selection response of populations in an Experimental Evolution setup. Despite the popularity of E&R, empirical studies in sexually reproducing organisms typically suffer from an excess of candidate loci due to linkage disequilibrium, and single gene or SNP resolution is the exception rather than the rule. Recently, so-called "secondary E&R" has been suggested as promising experimental follow-up procedure to confirm putatively selected regions from a primary E&R study. Secondary E&R provides also the opportunity to increase mapping resolution by allowing for additional recombination events, which separate the selection target from neutral hitchhikers. Here, we use computer simulations to assess the effect of different crossing schemes, population size, experimental duration, and number of replicates on the power and resolution of secondary E&R. We find that the crossing scheme and population size are crucial factors determining power and resolution of secondary E&R: a simple crossing scheme with few founder lines consistently outcompetes crossing schemes where evolved populations from a primary E&R experiment are mixed with a complex ancestral founder population. Regardless of the experimental design tested, a population size of at least 4,800 individuals, which is roughly 5 times larger than population sizes in typical E&R studies, is required to achieve a power of at least 75%. Our study provides an important step towards improved experimental designs aiming to characterize causative SNPs in Experimental Evolution studies. SignificanceDespite the popularity of Evolve and Resequence (E&R) to investigate genomic selection responses, most studies that use sexually reproducing organisms have broad selection signatures and an excess of candidate loci due to linkage disequilibrium. In this study, we use computer simulations and statistical modelling to evaluate the effects of different experimental and population genetic parameters on the success of potential follow-up experiments (=secondary E&R) aiming to validate and fine-map selection signatures of primary studies. We found that a large population size in combination with a simple crossing scheme is key to the success of secondary E&R in Drosophila.

evolutionary biology↗

bioRxiv2019

Low concordance of short-term and long-term selection responses in experimental Drosophila populations

AO_SCPLOWBSTRACTC_SCPLOWExperimental evolution is becoming a popular approach to study the genomic selection response of evolving populations. Computer simulation studies suggest that the accuracy of the signature increases with the duration of the experiment. Since some assumptions of the computer simulations may be violated, it is important to scrutinize the influence of the experimental duration with real data. Here, we use a highly replicated Evolve and Resequence study in Drosophila simulans to compare the selection targets inferred at different time points. At each time point, approximately the same number of SNPs deviates from neutral expectations, but only 10 % of the selected haplotype blocks identified from the full data set can be detected after 20 generations. Those haplotype blocks that emerge already after 20 generations differ from the others by being strongly selected at the beginning of the experiment and display a more parallel selection response. Consistent with previous computer simulations, our results demonstrate that only Evolve and Resequence experiments with a sufficient number of generations can characterize complex adaptive architectures.

molecular biology↗