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Futschik, A.

Publications and source records attributed to Futschik, A..

10 recordsLinked to original sources
bioRxiv2026

Causal analysis of rock-biodiversity relationships over the global Phanerozoic challenges rock record bias and common cause hypothesis

Sampled marine biodiversity covaries strongly with sedimentary rock quantity over the Phanerozoic, but the respective contributions of different potential causes remain unsettled. Although regional studies show that rock-record bias accounts for more variation in sampled marine biodiversity than common-cause mechanisms, evaluating this relationship across the global Phanerozoic record remains difficult because fossil databases are inherently biased toward fossiliferous strata. To address this limitation, we compiled literature-derived measures of global marine biodiversity and sedimentary strata, along with an existing sea-level curve. Using an information-theoretic causal framework, we then evaluated the relative contributions of rock-record bias and common-cause hypotheses to Phanerozoic-scale variation in sampled marine biodiversity. Our results show a strong contemporaneous causality of marine strata on sampled biodiversity, indicating that rock record bias detected at regional scales extends to the global scale. However, neither rock record bias nor common-cause mechanisms accounts for most Phanerozoic-scale patterns in sampled biodiversity, and additional unmeasured factors likely contribute. Finally, we find tentative evidence that synergistic causality between geologically mediated sampling biases and forces shaping the underlying biological signal contributes to global Phanerozoic patterns in sampled biodiversity.

paleontology↗
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↗
bioRxiv2022

Bayesian linear models with unknown design over finite alphabets

Our topic is the reconstruction of the unknown matrices S and{omega} for the multivariate linear model Y = S{omega} +{varepsilon} under the assumption that the entries of S are drawn from the finite alphabet [A] = 0, 1 and{omega} is a weight matrix. While a frequentist method has recently been proposed for this purpose, a Bayesian approach seems also desirable. We therefore provide a new hierarchical Bayesian method for this inferential task. Our approach provides estimates of the posterior that may be used to quantify uncertainty. Since matching permutations in both S and{omega} lead to the same reconstruction S{omega}, we introduce an order-preserving shrinkage prior to establish identifiability with respect to permutations.

genetics↗
bioRxiv2022

Joint likelihood-free inference of the number of selected SNPs and the selection coefficient in an evolving population

Given the often intractable exact likelihood, likelihood-free inference plays an important role in population genetics. Indeed, several methodological developments in approximate Bayesian Computation (ABC) were inspired by applications in population genetics. Here, we explore a novel combination of recently proposed ABC tools that can handle high-dimensional summary statistics and apply them to infer selection strength and the number of selected loci from experimental evolution data. While several methods infer selection strength at the single-nucleotide polymorphism (SNP) level, our approach provides additional information about the selective architecture, including the number of selected positions in a candidate window of interest. This is nontrivial, since the spatial correlation induced by genomic linkage can produce selection signals at neighboring SNPs. A further advantage of our approach is that we can readily quantify uncertainty using the ABC posterior. On both simulated and real data, we demonstrate promising performance. This suggests that our ABC variant could also be interesting in other applications.

evolutionary biology↗
bioRxiv2022

Haplotype based testing for a better understanding of the selective architecture

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. With this approach, less multiple testing correction is needed, which leads to tests with higher power, especially when the number of candidate haplotypes is small or moderate. Another advantage is that haplotype frequencies can often be recovered with less noise than SNP frequencies, especially under pool sequencing. For a larger number of haplotypes, we investigate methods to combine them to a moderate number of haplotype subsets. The use of haplotypes also permits a better understanding of selective signatures. For this purpose, we propose post hoc tests for the selected haplotypes and differences between their selection coefficients. Using both simulated and real data sets, we illustrate the performance and benefits of our proposed test statistics.

bioinformatics↗
bioRxiv2020

Waves out of the Korean Peninsula and inter- and intra-species replacements in freshwater fishes in Japan

The Japanese archipelago is located at the periphery of the continent of Asia. Rivers in the Japanese archipelago, separated from the continent of Asia about 17 Ma, have experienced an intermittent exchange of freshwater fish taxa through a narrow land bridge generated by lowered sea level. As the Korean Peninsula and Japanese archipelago were not covered by an ice sheet during glacial periods, phylogeographical analyses in this region can trace the history of biota for a long time beyond the last glacial maximum. In this study, we analyzed the phylogeography of four freshwater fish taxa, Hemibarbus longirostris, dark chub Nipponocypris temminckii, Tanakia ssp. and Carassius ssp., whose distributions include both the Korean Peninsula and western Japan. We found for each taxon that a small component of diverse Korean clades of freshwater fishes migrated in waves into the Japanese archipelago to form the current phylogeographic structure of biota. Indigenous populations were replaced by succeeding migrants. We refer to this phenomenon as "waves out of the Korean Peninsula," with parallels to "out of Africa" in humans.

zoology↗
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

Length asymmetry and heterozygosity strongly influences the evolution of poly-A microsatellites at meiotic recombination hotspots

Meiotic recombination has strong, but poorly understood, effects on short tandem repeat (STR) instability. Here, we screened thousands of single recombinant products to characterize the transmission and evolution of polymorphic poly-A repeats at a human recombination hotspot. We show that length asymmetry between heterozygous poly-As plays a key role in the recombination outcome and their transmission. A difference of 10 As (9A/19A) elevates the frequency of non-crossovers, complex recombination products, and long conversion tracts. Moreover, asymmetry also influences STR transmission: the shorter allele is transmitted more frequently (deletion bias) at the asymmetric STR (9A/19A), while the longer allele is favored (insertion bias) at the site with a small STR length difference (6A/7A). Finally, potentially due to this opposing insertion/deletion driven evolution, we find that poly-As are enriched at human recombination hotspots predominantly with short poly-As, possibly influencing open chromatin regions that in turn can activate hotspots.

evolutionary biology↗
bioRxiv2017

LDJump: Estimating Variable Recombination Rates from Population Genetic Data

As recombination plays an important role in evolution, its estimation, as well as, the identification of hotspot positions is of considerable interest. We propose a novel approach for estimating historical recombination along a chromosome that involves a sequential multiscale change point estimator. Our method also permits to take demography into account. It uses a composite likelihood estimate and other summary statistics within a regression model fitted on suitable scenarios. Our proposed method is accurate, computationally fast, and provides a parsimonious solution by ensuring a type I error control against too many changes in the recombination rate. An application to human genome data suggests a good congruence between our estimated and experimentally identified hotspots. Our method is implemented in the R-package LDJump, which is freely available from https://github.com/PhHermann/LDJump.

bioinformatics↗