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Monday, 06 May 2024
Time Speaker Title Resources
09:30 to 11:00 Michael Lynch (Arizona State University, USA) Drift and the Concept Effective Population Size (Lecture 1)
11:30 to 13:00 Luis-Miguel Chevin (CNRS, France) Adaptation at the Levels of Fitness and Traits

In this lecture, I will cover theories of adaptation that do and do not explicitly account for phenotypes, in particular regarding distribution of fitness effects of mutations across genotypes and environment.

14:00 to 15:30 -- Poster Teasers
16:00 to 17:30 Jacqueline Sztepanacz [ONLINE] (University of Toronto, Canada) Introduction to quantitative genetics
Tuesday, 07 May 2024
Time Speaker Title Resources
09:30 to 11:00 Bruce Walsh (University of Arizona, USA) Detecting QTLs

an overview of QTL mapping

11:30 to 13:00 Nick Barton (IST Austria) Polygenic Adaptation (Lecture 1)
14:00 to 15:30 Bratati Kahali (IISc, India) Population scale genome sequencing to gain insights into genetic underpinnings of complex diseases
16:00 to 17:30 Shweta Ramdas (IISc, India) Tutorial on Genomewide Association Studies

This tutorial will cover a basic genome-wide association study.

Wednesday, 08 May 2024
Time Speaker Title Resources
09:30 to 11:00 Michael Lynch (Arizona State University, USA) Drift and the Concept Effective Population Size (Lecture 2)
11:30 to 13:00 Bruce Walsh (University of Arizona, USA) GWAS and Quantitative Genomics

An overview of GWAS

14:00 to 15:30 Daniel Fisher (Stanford University, USA) Ecology and Perpetual Evolution in High Dimensions

In a simple, constant environment does evolution continue forever? Does extensive diversification via small genetic and ecological differences? What are general evolutionary consequences of organismic complexity? Hints from long term laboratory evolution experiments and from genomic data of within-species bacterial diversity motivate considering these questions. Several simple models of evolution with small ecological feedback will be introduced, with the high dimensionality of phenotype space enabling mathematical analysis.

Thursday, 09 May 2024
Time Speaker Title Resources
09:30 to 11:00 Jacqueline Sztepanacz [ONLINE] (University of Toronto, Canada) Introduction to multivariate quantitative genetics
11:30 to 13:00 -- Poster session
14:00 to 15:30 Himani Sachdeva (University of Vienna, Austria) Modeling polygenic barriers to gene flow between species

Populations often adapt to spatially heterogeneous environments via substitutions or allele frequency changes at many loci spread across the genome. Subsequent contact between diverged populations can produce unfit hybrids, which inhibits genetic exchange across the genome, thus setting the stage for further divergence and speciation. How such polygenic divergence builds up or is maintained depends on the coupled dynamics of multiple loci under selection, making it challenging to predict. In this talk, I will outline simple theoretical approximations based on effective migration rates that capture how coupling or linkage disequilibria (LD) between loci influences the maintenance of polygenic adaptive divergence. This analysis allow us to clarify how genetic architecture (i.e., the numbers, selective and dominance effects and linkage relationships of selected variants) influences divergence in the face of gene flow and genetic drift. I will conclude my talk with a broader perspective on the unreasonable effectiveness of effective parameters in population genetics.

16:00 to 17:30 Nick Barton (IST Austria) Tutorials
Friday, 10 May 2024
Time Speaker Title Resources
09:30 to 11:00 Luisa Pallares (MPI for Biology, Tübingen) The Environment-dependent Nature of Genotype-Phenotype Maps
11:30 to 13:00 Christian Schlötterer (Univ. of Veterinary Medicine, Austria) Understanding Polygenic Adaptation with Experimental Evolution

Using replicate populations evolved under the same environmental conditions, experimental evolution provides the unique opportunity to study polygenic adaptation. I will discuss how genetic redundancy, pleiotropy, epistasis and linkage disequilibrium influence the selection response of polygenic traits.

14:00 to 15:00 Michael Lynch (Arizona State University, USA) Principles of Evolutionary Overdesign and Underperformance

For over a century, most biologists have been convinced that all aspects of biodiversity have been driven entirely by natural selection, with stochastic forces and mutation bias playing a minimal role. However, this is not the case at the molecular and cellular levels, where diverse traits scale with cell/organism size in ways that cannot be explained by optimization and/or speed vs. efficiency arguments. These include aspects of gene/genome architecture, intracellular error rates, the multimeric nature of proteins, swimming efficiencies, and maximum growth rates.

Although natural selection may be the most powerful force in the biological world, it is not all powerful, and the power of random genetic drift ultimately dictates what selection can and cannot accomplish. Many prokaryotes may reside in population-genetic environments where the limits to selection are indeed dictated only by the constraints of cell biology. However, in the eukaryotic domain, larger organism size is typically associated with a reduction in effective population size (Ne), enabling the accumulation of very mildly deleterious mutations, which in turn induces coevolutionary side effects leading to more complex and less efficient phenotypes.

This general conclusion is embodied in the drift-barrier hypothesis, which postulates that traits under persistent directional selection become stalled when further increments in improvement are thwarted by the power of random genetic drift. Integration of biology’s three engines of quantitative theory – population genetics, biophysics, and biochemistry, combined with observations from cellular bioenergetics, is providing a platform for the emergence of a formal field of evolutionary cell biology.

Monday, 13 May 2024
Time Speaker Title Resources
09:30 to 11:00 Sam Yeaman [ONLINE] (University of Calgary, Canada) The genetic architecture of repeated local vs. global adaptation in plants: surprisingly consistent with theoretical predictions

The interplay between natural selection and migration is predicted to shape the architecture of adaptation in different ways, depending on whether the direction of selection is spatially homogenous or heterogeneous. When different populations experience selection towards a similar phenotypic optimum, there is no tension with migration and "global adaptation" proceeds in manner similar to that predicted for a single population. By contrast, when populations are selected towards different optima, "local adaptation" occurs, which tends to favour architectures driven by fewer, larger, and more tightly clustered alleles than global adaptation. Despite this clear theoretical prediction, there have been few, if any, comprehensive tests in natural populations. Here, we bring together genome sequence data from thousands of individuals from 25 species of plants to compare signatures of repeated selective sweeps (global adaptation) with those of genotype-environment association (local adaptation). We deploy a common bioinformatic pipeline to call variants in all datasets, reconstruct orthology relationships, and test for repeated signatures across species. In both the local and global adaptation analyses, we find a large number of genes with evidence for repeated signatures across multiple species, including many genes with previously established functions in response to biotic and abiotic stress. We then use RNAseq datasets to build gene co-expression networks, which provide an estimation of the pleiotropy of each gene (more connections/centrality == more pleiotropy). As pleiotropy is generally positively related to allele effect size, we would expect more pleiotropy for local adaptation and less pleiotropy for global adaptation due to the interplay between migration and selection. Our results are remarkably consistent with this prediction, with significant enrichment for high pleiotropy among the genes driving local adaptation, and low pleiotropy among the genes driving global adaptation.

11:30 to 13:00 Henrique Teotonio (ENS Paris, France) Empirical approaches to understand polygenic adaptation

In this two-part lecture, I will review the design principles of observational and experimental studies to detect polygenic adaptation. The first part of the lecture will cover modeling of genetic drift and selection the DNA sequence level, while the second part of the lecture will focus on multivariate trait models under infinitesimal assumptions. Several case studies will be discussed, particularly experimental evolution studies in the nematode Caenorhabditis elegans.

14:00 to 15:30 Michael Lynch (Arizona State University, USA) Mutation and Drift (Lecture 3)
16:00 to 17:30 Nick Barton (IST Austria) Polygenic Adaptation (Lecture 2)
Tuesday, 14 May 2024
Time Speaker Title Resources
09:30 to 11:00 Nick Barton (IST Austria) Polygenic Adaptation (Lecture 3)
11:30 to 13:00 Luis-Miguel Chevin (CNRS, France) Adaptation to changing environments

In this lecture, I will cover theory of adaptation to changing environments based on moving optimum models.

14:00 to 15:30 Neda Barghi (Univ. of Veterinary Medicine, Austria) Adaptation of Complex Traits: Insights from Evolution Experiments in Drosophila

Most adaptive traits are polygenic with many underlying loci. The genetic architecture of these traits specifies how the phenotypes can be changed by mutations, but many factors determine which of these loci will be used during adaptation. Additionally, adaptation of complex traits in replicate populations with phenotypic convergence can occur through selection of different sets of loci. The analysis of time-series phenotypic and genomic data in replicates of evolving populations is crucial for understanding the adaptive architecture of a trait. I will demonstrate how experimental evolution emerges as an exceptional approach for generating precisely this type of data. Drawing on empirical evidence, I will show that temporal phenotypic data enable the identification of adaptive patterns, even when the selected trait(s) are unidentified, as is often the case in natural and experimental populations. Finally, I will discuss the next generation of evolution experiments, designed to mimic the assumptions of theoretical models of polygenic adaptation. These experiments help in testing the predictions of theoretical models and exploring the effect of factors such as selection strength on adaptive responses.

16:00 to 17:30 Frédéric Guillaume [ONLINE] (University of Helsinki, Finland) Selection, genetic covariances, and network position predict gene expression evolution during adaptation

Understanding how selection acts on standing genetic variation is key to predict evolutionary changes leading to adaptation in new environments. Taking advantage of individual-level transcriptome and fitness data from two time points within replicated experimental evolution lines of Tribolium castaneum (red flour beetle), we could show that estimates of total genetic selection on transcript variation (Robertson-Price equation) were predictive of evolutionary changes in gene expression after 20 generations of adaptation to a hot-dry stressful environment (HD). Moreover, with estimates of transcriptome-wide genetic co-variances, we found that the majority of total selection is indirect, stemming from selection on correlated gene expression levels. A co-expression network analysis showed a weakened trait-fitness relationship in HD within the first generation, relative to a mild control environment caused by stress-related plastic responses of gene expression in HD. It also showed that selection had rewired the co-expression network in HD after 20 generations of adaptation. More importantly, we found that gene network position was predictive of the strength of total selection on gene expression, of evolutionary changes in gene expression and sequence variation, and of the presence of eQTL (genetic variants associated with expression at other genes). Our results thus suggest that selection for adaptation to a new environment targeted genes that occupy more central positions in gene co-expression networks (hub genes). They also show that by applying a classical quantitative genetics approach we could predict gene expression changes over relatively short-term adaptation. In addition, we could link parallelism of allele frequency changes among replicated lines with the strength of selection acting on gene expression levels, showing that genes under stronger total selection were carrying more parallel SNPs. Overall, our approach allowed us to gain a comprehensive view of how selection acts on gene expression variation during adaptation to a stressful environment.

Wednesday, 15 May 2024
Time Speaker Title Resources
09:30 to 11:00 Juliette de Meaux (University of Cologne, Germany) Polygenic adaptation and the evolution of gene expression in Arabidopsis lyrata ssp. petraea

Ecosystems are threatened worldwide by anthropogenic degradation, fragmentation and rapid climate change. Plants are critical for nearly all food webs and thus for the functioning of ecosystems. Many plant species are going extinct, at least on some part of their range. So in the future, to restore complex ecosystem and protect biodiversity, we must understand the genetic resources of endangered plant species. Arabidopsis lyrata ssp. petraea is a close relative of the model species Arabidopsis thaliana. In some part of its range, populations are becoming increasingly scarce. I will report work in my lab that examines three crucial aspects of genomic resources: the amount of deleterious variation, the fraction of additive genetic variance in populations and the optimization of complex polygenic traits. In doing so, I will illustrate how useful the study of gene expression variation is.

11:30 to 13:00 Henrique Teotonio (ENS Paris, France) Polygenic adaptation and the evolution of recombination

Genetic modifiers of local and genome-wide crossover placement have been described, but whether recombination rate heritabilities are maintained by natural selection is unclear. Using experimental evolution with the nematode Caenorhabditis elegans, we show that indirect selection at a modifier of crossover distribution occurs because of the nearby genomic associations it establishes with beneficial genotypes. However, the consequences of indirect selection to adaptation should be minimal until the modifier is fixed, when adaptation depends on many and small-effect beneficial alleles across the genome. With fixed recombination rate landscapes, polygenic adaptation is facilitated by the modifier allele that, on average, increases recombination rates in genomic regions containing adaptive variation. We further show that increased recombination rates in these regions break the negative linkage disequilibrium created by epistatic and interference interaction effects among beneficial and deleterious alleles. These findings suggest that conflicting indirect selection among several segregating modifiers might explain recombination rate heritabilities independently of adaptation.

14:00 to 15:30 Joachim Hermisson [ONLINE] (University of Vienna, Austria) Oligogenic Adaptation: between “SWEEPS" and “SHIFTS"

I present shared work with Benjamin Wölfl and Ilse Höllinger on the adaptive architecture of a quantitative trait that with a genetic basis of moderate size (oligogenic adaptation).

16:00 to 17:30 Kavita Jain (JNCASR, India) Polygenic adaptation
Thursday, 16 May 2024
Time Speaker Title Resources
11:30 to 13:00 Henrique Teotonio (ENS Paris, France) TBA
14:00 to 15:30 Subhash Rajpurohit [ONLINE] (Ahmedabad University, India) TBA
16:00 to 17:30 Bruce Walsh (University of Arizona, USA) Tools of high dimensional data ( lecture-3)

Multiple comparisons, combining p values, meta-analysis, model selection

Friday, 17 May 2024
Time Speaker Title Resources
09:30 to 11:00 Nick Barton (IST Austria) Understanding a Flower Colour Hybrid Zone - From a Polygenic Perspective (Lecture 4)
11:30 to 13:00 Luis-Miguel Chevin (CNRS, France) Phenotypic Plasticity and Adaptation to Variable or Novel Environments

In this talk, I will present theoretical and experimetnal results on the evolution of plasticity, and how this contributes to adaptation in temporally variable environments

14:00 to 15:30 -- Wrap-up discussion