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Biology subjects

Metzger, L.

Publications and source records attributed to Metzger, L..

3 recordsLinked to original sources

Evolutionary transitions to self-fertilization influence the inference of introgression history

The availability of polymorphism data and statistical inference methods allows documenting the widespread occurrence of introgression and hybridization across the tree of life. However, these methods are primarily optimized for outcrossing species without generation overlap or seed banking, thereby ignoring the consequences of life-history traits (and their evolution) on genome-wide polymorphism patterns. We investigate how a transition from outcrossing to selfing, a common feature of plant species, may affect the inference of introgression history. We simulate six demographic models with different histories of gene flow under two mating-system scenarios: a constant high selfing rate and a transition-to-selfing scenario. Using an Approximate Bayesian Computation framework with random forests, we compare model choice based on genotypic summary statistics alone and in combination with coalescent statistics derived from coalescent tree sequences. Including coalescent information substantially improves model classification, especially for distinguishing secondary contact and continuous gene flow. Cross-classification of pseudo-observed datasets shows that ignoring a transition to selfing can lead to false demographic inferences, with transition-to-selfing data often misclassified as ancient gene flow or secondary contact when analyzed under a constant selfing model. We then apply this inference framework to genomic data from Arabis nemorensis and Arabis sagittata, two predominantly selfing species with evidence for post-split hybridization. Our analyses reveal a likely transition to selfing roughly 470,000-890,000 years ago, and a likely continuous level of gene flow after the species split. The latter results lead us to revisit our previous scenario of gene flow due to secondary contact between species inferred under constant selfing. Changes in mating systems and, by extension, life-history traits can therefore bias inference about introgression if they are not explicitly modeled. Tree-sequence-based coalescent statistics provide useful information for inferring complex demographic histories that involve both gene flow and transitions to selfing.

evolutionary biology↗

Contemporary hybridization among Arabis floodplain species creates opportunities for adaptation

Hybridization between closely related species is increasingly recognized as a major source of biodiversity. Yet, whether it can create advantageous trait combinations while purging harmful alleles remains unknown. We studied Arabis nemorensis and A. sagittata, two endangered species that currently hybridize in a single hotspot. We measured 22 phenotypic traits and mapped their genetic basis in an F2 population, after generating high quality genome assemblies for both species. In total, 58 QTLs were identified for 20 traits, with additive and dominance effects best fitting Gaussian and logistic distributions, respectively. Six large-effect QTLs were linked to significant hybrid fitness loss. Two genomic regions showed strong transmission bias favoring A. sagittata alleles, potentially accelerating their introgression. However, 48% of QTLs were unlinked to reduced fitness or segregation distortion and may generate genotypes exceeding parental performance. Notably, a major QTL affecting flowering time explained 23% of phenotypic variation and implicated TFL1 as a candidate gene for life history adaptation. While most QTLs lacked overlap with past selective sweeps, indicating limited recent positive selection, 5 of 7 QTLs for rosette size overlapped with sweep signatures in the parental lineages. Overall, our findings offer unique insights into incipient stages of hybridization.

evolutionary biology↗

Inference of host-pathogen interaction matrices from genome-wide polymorphism data

Coevolution is defined as the evolutionary change in one antagonist (host) in response to changes in the other antagonist (pathogen). At the genetic level, these changes are determined by genotype x genotype (GxG) interactions. We build on a general theoretical model of a host-pathogen interaction to derive four indices to retrieve key features of GxG interactions. The four developed indices extract relevant information from polymorphism data of randomly sampled uninfected hosts as well as infected hosts and their respective pathogen strains. Using these indices as summary statistics in an Approximate Bayesian Computation method, we can show their power to discriminate between GxG interaction matrices. Second, we apply our ABC method to a SNP data set of 451 European humans and their infecting Hepatitis C Virus (HCV) strains supplemented by polymorphism data of 503 individuals from the 1,000 genomes project. As our indices encompass and extend previous natural co-GWAs we recover many of the associations previously reported for this dataset and infer their underlying interaction matrix. We reveal a new candidate gene for resistance to HCV in the human genome, and two groups of significant GxG associations exhibiting gene-for-gene interactions. We suggest that the inferred types of GxG interactions result from the recent expansion, adaptation and low prevalence of the HCV virus population in Europe. Significance statementWhy are some host individuals susceptible/resistant to infection by certain pathogen genotypes and others not? Understanding the genetic characteristics of genes driving host-pathogen interactions is crucial to predict epidemics. We develop four indices based on a mathematical model and build a Bayesian statistical method computing these indices on full genome data of infected hosts and their infecting pathogen strains and data of non-infected hosts. We can pinpoint the genes underlying host-pathogen interactions and infer their characteristics. Applying our framework to data from European humans and the Hepatitis C virus, we discover a new potential resistance gene in humans and reveal how the virus has adapted in the last 150 years to match the genetic diversity of the European human population.

evolutionary biology↗