@article{12081, abstract = {Selection accumulates information in the genome—it guides stochastically evolving populations toward states (genotype frequencies) that would be unlikely under neutrality. This can be quantified as the Kullback–Leibler (KL) divergence between the actual distribution of genotype frequencies and the corresponding neutral distribution. First, we show that this population-level information sets an upper bound on the information at the level of genotype and phenotype, limiting how precisely they can be specified by selection. Next, we study how the accumulation and maintenance of information is limited by the cost of selection, measured as the genetic load or the relative fitness variance, both of which we connect to the control-theoretic KL cost of control. The information accumulation rate is upper bounded by the population size times the cost of selection. This bound is very general, and applies across models (Wright–Fisher, Moran, diffusion) and to arbitrary forms of selection, mutation, and recombination. Finally, the cost of maintaining information depends on how it is encoded: Specifying a single allele out of two is expensive, but one bit encoded among many weakly specified loci (as in a polygenic trait) is cheap.}, author = {Hledik, Michal and Barton, Nicholas H and Tkačik, Gašper}, issn = {1091-6490}, journal = {Proceedings of the National Academy of Sciences}, number = {36}, publisher = {Proceedings of the National Academy of Sciences}, title = {{Accumulation and maintenance of information in evolution}}, doi = {10.1073/pnas.2123152119}, volume = {119}, year = {2022}, } @phdthesis{11388, abstract = {In evolve and resequence experiments, a population is sequenced, subjected to selection and then sequenced again, so that genetic changes before and after selection can be observed at the genetic level. Here, I use these studies to better understand the genetic basis of complex traits - traits which depend on more than a few genes. In the first chapter, I discuss the first evolve and resequence experiment, in which a population of mice, the so-called "Longshanks" mice, were selected for tibia length while their body mass was kept constant. The full pedigree is known. We observed a selection response on all chromosomes and used the infinitesimal model with linkage, a model which assumes an infinite number of genes with infinitesimally small effect sizes, as a null model. Results implied a very polygenic basis with a few loci of major effect standing out and changing in parallel. There was large variability between the different chromosomes in this study, probably due to LD. In chapter two, I go on to discuss the impact of LD, on the variability in an allele-frequency based summary statistic, giving an equation based on the initial allele frequencies, average pairwise LD, and the first four moments of the haplotype block copy number distribution. I describe this distribution by referring back to the founder generation. I then demonstrate how to infer selection via a maximum likelihood scheme on the example of a single locus and discuss how to extend this to more realistic scenarios. In chapter three, I discuss the second evolve and resequence experiment, in which a small population of Drosophila melanogaster was selected for increased pupal case size over 6 generations. The experiment was highly replicated with 27 lines selected within family and a known pedigree. We observed a phenotypic selection response of over one standard deviation. I describe the patterns in allele frequency data, including allele frequency changes and patterns of heterozygosity, and give ideas for future work.}, author = {Belohlavy, Stefanie}, isbn = {978-3-99078-018-3}, pages = {98}, publisher = {Institute of Science and Technology Austria}, title = {{The genetic basis of complex traits studied via analysis of evolve and resequence experiments}}, doi = {10.15479/at:ista:11388}, year = {2022}, } @article{10535, abstract = {Realistic models of biological processes typically involve interacting components on multiple scales, driven by changing environment and inherent stochasticity. Such models are often analytically and numerically intractable. We revisit a dynamic maximum entropy method that combines a static maximum entropy with a quasi-stationary approximation. This allows us to reduce stochastic non-equilibrium dynamics expressed by the Fokker-Planck equation to a simpler low-dimensional deterministic dynamics, without the need to track microscopic details. Although the method has been previously applied to a few (rather complicated) applications in population genetics, our main goal here is to explain and to better understand how the method works. We demonstrate the usefulness of the method for two widely studied stochastic problems, highlighting its accuracy in capturing important macroscopic quantities even in rapidly changing non-stationary conditions. For the Ornstein-Uhlenbeck process, the method recovers the exact dynamics whilst for a stochastic island model with migration from other habitats, the approximation retains high macroscopic accuracy under a wide range of scenarios in a dynamic environment.}, author = {Bod'ová, Katarína and Szep, Eniko and Barton, Nicholas H}, issn = {1553-7358}, journal = {PLoS Computational Biology}, number = {12}, publisher = {Public Library of Science}, title = {{Dynamic maximum entropy provides accurate approximation of structured population dynamics}}, doi = {10.1371/journal.pcbi.1009661}, volume = {17}, year = {2021}, } @article{8708, abstract = {The Mytilus complex of marine mussel species forms a mosaic of hybrid zones, found across temperate regions of the globe. This allows us to study ‘replicated’ instances of secondary contact between closely related species. Previous work on this complex has shown that local introgression is both widespread and highly heterogeneous, and has identified SNPs that are outliers of differentiation between lineages. Here, we developed an ancestry‐informative panel of such SNPs. We then compared their frequencies in newly sampled populations, including samples from within the hybrid zones, and parental populations at different distances from the contact. Results show that close to the hybrid zones, some outlier loci are near to fixation for the heterospecific allele, suggesting enhanced local introgression, or the local sweep of a shared ancestral allele. Conversely, genomic cline analyses, treating local parental populations as the reference, reveal a globally high concordance among loci, albeit with a few signals of asymmetric introgression. Enhanced local introgression at specific loci is consistent with the early transfer of adaptive variants after contact, possibly including asymmetric bi‐stable variants (Dobzhansky‐Muller incompatibilities), or haplotypes loaded with fewer deleterious mutations. Having escaped one barrier, however, these variants can be trapped or delayed at the next barrier, confining the introgression locally. These results shed light on the decay of species barriers during phases of contact.}, author = {Simon, Alexis and Fraisse, Christelle and El Ayari, Tahani and Liautard‐Haag, Cathy and Strelkov, Petr and Welch, John J and Bierne, Nicolas}, issn = {14209101}, journal = {Journal of Evolutionary Biology}, number = {1}, pages = {208--223}, publisher = {Wiley}, title = {{How do species barriers decay? Concordance and local introgression in mosaic hybrid zones of mussels}}, doi = {10.1111/jeb.13709}, volume = {34}, year = {2021}, } @article{8743, abstract = {Montane cloud forests are areas of high endemism, and are one of the more vulnerable terrestrial ecosystems to climate change. Thus, understanding how they both contribute to the generation of biodiversity, and will respond to ongoing climate change, are important and related challenges. The widely accepted model for montane cloud forest dynamics involves upslope forcing of their range limits with global climate warming. However, limited climate data provides some support for an alternative model, where range limits are forced downslope with climate warming. Testing between these two models is challenging, due to the inherent limitations of climate and pollen records. We overcome this with an alternative source of historical information, testing between competing model predictions using genomic data and demographic analyses for a species of beetle tightly associated to an oceanic island cloud forest. Results unequivocally support the alternative model: populations that were isolated at higher elevation peaks during the Last Glacial Maximum are now in contact and hybridizing at lower elevations. Our results suggest that genomic data are a rich source of information to further understand how montane cloud forest biodiversity originates, and how it is likely to be impacted by ongoing climate change.}, author = {Salces-Castellano, Antonia and Stankowski, Sean and Arribas, Paula and Patino, Jairo and Karger, Dirk N. and Butlin, Roger and Emerson, Brent C.}, issn = {1558-5646}, journal = {Evolution}, number = {2}, pages = {231--244}, publisher = {Wiley}, title = {{Long-term cloud forest response to climate warming revealed by insect speciation history}}, doi = {10.1111/evo.14111}, volume = {75}, year = {2021}, }