Overview of research topics
Host-parasite coevolutionary dynamics
Plant-parasite interactions provide particularly suitable model systems for molecular ecology studies as there has been a substantial emphasis in recent years on dissecting the genetic and molecular architecture of host-parasite specificity (Jones and Dangl, Nature 2006). Coevolutionary models suggest that reciprocal changes of allele frequencies over time at genes involved in host and parasite interactions can follow two simple scenarios (Woolhouse et al., Nature Genet 2002; Holub, Nat Rev Genet 2001): the ‘arms-race’ scenario, which is a series of recurrent selective sweeps, and the ‘trench warfare’ (or balancing selection) scenario, which maintains alleles at intermediate frequencies due to frequency-dependent selection. Using as a case study the gene-for-gene interactions (GFG) between host (plant or animal) resistance genes and parasite effectors, we have shown (with James KM Brown) that a fundamental mathematical condition, direct frequency-dependence selection, is necessary for the occurrence of balancing selection and is promoted by various plant and parasite life-history traits and ecological characteristics (review in Brown and Tellier Annu Rev Phytopathol 2011): e.g. seed banks and perenniality or parasite polycyclicity. The occurrence of arms race or trench warfare dynamics thus depends on a few key coevolutionary parameters (ecological and genetic costs). Moreover, environmental variability also has a crucial influence on coevolution (the ‘Geographic Mosaic Theory of Coevolution’: Thompson J.N., The Geographic Mosaic of Coevolution 2005), specifically in GFG interactions (Laine and Tellier, Oikos 2008). These theoretical developments lay the foundations for a quantitative understanding of the major ecological mechanisms driving the molecular evolution of host defence genes in natural populations. The lab focuses on developing new models and statistical methods for host-parasite coevolution to 1) understand the genome evolution of both antagonistic species (Zivkovic et al. 2019), 2) draw inference of the coevolution history using polymorphism data (Märkle and Tellier 2020, Saubin et al. 2023), and 3) find the genes under coevolution or driving GxG interactions (Märkle et al. 2024, reviews in Märkle et al. 2021, Cornille et al. 2022).
Ecological significance of seed dormancy and genomic consequences
Many plant, invertebrate, fungal or bacterial species do present life-history traits which violate the assumptions of the classic evolutionary theoretical framework. A first specific life-history characteristic of most plant species is to produce seeds, which may remain in the soil for long period of time (Fenner and Thompson, The Ecology of Seeds 2004). In general terms, the reproductive mode (seed or egg dormancy) is described as a bet-hedging strategy in plants (Evans and Dennehy, Q Rev Biol 2005), invertebrates (Daphnia: Decaestecker et al. Nature 2007, mosquitoes) and micro-organisms (Lennon and Jones, Nat Rev Microbiol 2011) to buffer against environmental variability. Bet-hedging is a strategy in which adults release their offspring into several different environments to maximize the chance that some will survive, thus magnifying the evolutionary effect of good years and dampening the effect of bad years. It also counter-acts habitat fragmentation by buffering against the extinction of small and isolated populations, a phenomenon known as “temporal rescue effect” (Honnay et al., Oikos 2008). Improving our understanding of seed bank evolution and its genetic underpinnings is thus important for the conservation of endangered plant species. However, little is yet known about the evolutionary and ecological mechanisms governing the evolution of seed dormancy. Seed banks also promote the storage of genetic diversity, increasing thus the effective population size (Kaj et al., J Appl Proba 2001) and decreasing among population differentiation (Vitalis et al., Am Nat 2005). We investigate the consequences of seed banks on coalescent trees and expected patterns of neutral and selective polymorphism using mathematics (Koopmann et al. 2017, Heinrich et al. 2018, Sellinger et al. 2019, Müller and Tellier 2022), simulations (Korfmann et al. 2023) as well as inference methods based on the Sequential Markovian Coalescent (SMC, Sellinger et al. 2020). Other life-history traits of importance include selfing and sweepstake reproduction, which is the large variance in production of offspring typical of many marine organisms but also fungal or viral parasites (Tellier and Lemaire 2014, Korfmann et al. 2023). The lab develops SMC methods (eSMC, eSMC2, SMbetaC, teSMC) to infer the parameters of these life-history traits based on full genome data (Sellinger et al. 2020, 2021, Strütt et al. 2023, Korfmann et al. 2024). We also develop ad hoc Approximate Bayesian Computation (ABC) methods (Dittberner et al. 2019, 2022) and Deep Learning (Krofmann et al. 2024) methods to draw inference of past history under these peculiar ecological traits. We are also enhancing the power of these inference methods by integrating other types of markers such as methylation (
1) Wild tomato species (Solanum chilense)
Wild tomato species are excellent model organisms for ‘molecular ecology’ studies with a focus on the effect of the spatial structure of populations (metapopulation). These species exhibit numerous patches of small sizes subject to extinction/recolonization, with migration among demes. They are found in South America in a great variety of habitats ranging from coastal plains, to the Chilean desert and to high altitudes of the Andes (above 3000 m)(Peralta et al., Syst Bot Monogr 2008; Nakazyto et al., Evolution 2008). We focus on S. chilense which is found in Southern Peru and Northern Chile in arid habitats around the Atacama desert. I have already shown that coalescent theory and new Bayesian methods are appropriate to study rates of adaptation in such complex ecological set-ups (Tellier et al., PNAS 2011; Tellier et al., Heredity 2011). The lab has built a reference genome (Stam et al. 2019a, Silva-Arias et al. 2025) as key resource to study the evolution of resistance genes to pathogens across different habitats (Stam et al. 2016, 2017, 2019b, Bashir et al. 2022, Silva-Arias et al. 2025) as well as adaptation to abiotic stresses (Wei et al. 2023, 2024). We extend this work to study the speciation in progress between allopatric southern populations of S. chilense.
We study also the genome evolution of Barley pathogens, such as Blumeria graminis ssp. hordei, Fusarium sp. and Ramularia collo-cygni (Havis et al. 2015, Stam et al. 2019c). Our aim is to quantify the processes driving the neutral and selective processes driving genomic changes in barley pathogens.
3) Alpine soil crusts and human exploitation of natural resources in ancient times
We are developing two new study systems in the lab. First, we study the composition and genetic diversity of fungal and bacterial communities and species in soil crust in high alpine environments which are subjected to changing climate. Second, we investigate the effect of human exploitation of resources during ancient times (Roman empire) and the consequences on the genetic diversity. We use the marine snail species Hexaplex (Murex) and Rubia plant species as model systems. We are developing genomic resources for these different species and systems.
Funding
