Thank you for finding me! I am a biologist intrigued by EVOLUTION, and fascinated by its outcomes. I am currently working as a Postdoc at the University of Bern in Switzerland.

Why are living organisms so incredibly diverse? – This overarching question is driving my research. Defined broadly, my approach is to apply population genomics within a clear ecological framework to shed light on the processes influencing adaptive (population) diversification. However, my research is not contingent upon a specific type of approach, but rather follows my instinct for interesting questions, whereby I’m open to take whatever route is needed to address a question appropriately. Many ideas emerge as I observe the living world around me, and as I stumble across inexplicable patterns during biological data analysis. My main empirical study system is the threespine stickleback fish that has adapted rapidly to distinct environments. However, I have also been working with other organisms (cichlid fish, Daphnia, icefish, and lampreys). You can find my published work here.

Current projects involve the study of stickleback populations inhabiting distinct environments, such as lakes differing mainly in abiotic factors (e.g., Haenel et al. 2019), or lakes differing in a single biotic factor – that is, the presence vs. absence of a competing fish species. I am describing how the genome (e.g., Miller, Roesti, Schluter 2019), as well as traits (forthcoming), diverge due to this species interaction. It happens to be that most of my current empirical work uses allopatric populations, which stands in contrast to the majority of my previous work, where the emphasis was on population divergence in the presence of gene flow (e.g., Roesti et al. 2012, Roesti et al. 2014, Roesti et al. 2015). I plan to again focus on the latter in the near future.

More recently, I’ve really started valuing – and enjoy conducting – large field experiments to test specific predictions prompted by observations in wild populations. Threespine stickleback make it possible to conduct such experiments, which is one of many reasons why I like working with this organism. One of the questions I am currently answering experimentally is whether a simple biotic change to the environment of an organism has resulted in substantial reproductive isolation (speciation) as a by-product.

Results from my empirical research stimulate and inform my theoretical work. I’m using simulations to better understand the genomic footprints of selection (e.g., Roesti et al. 2014). I have longstanding interest in gaining an evolutionary understanding of intra-genomic variation in the rate of crossover (recombination), and how this variation influences the genome during adaptive diversification (e.g., Roesti et al. 2012, Roesti et al. 2013, Haenel et al. 2018, Roesti 2018). Simulations further help me explore how crossover rate variation in context of polygenic adaptation influences evolutionary genomic methodologies and inferences, such as the search for targets of selection through genome scans (Roesti et al. 2012, Berner & Roesti 2017, Roesti 2018). I have also done theory work exploring the genetic signature of selection during parallel adaptation involving pre-existing genetic variation, such as standing or introgressed variation (Roesti et al. 2014).

If you like to get further information on my past or ongoing work, do not hesitate to contact me!

SNIPPETS OF MY RESEARCH (non-chronological)

Do adaptive loci cluster within a genome to better resist gene flow?  In this paper, I summarize  ideas of why, how and where in a genome adaptive loci should become clustered  when local adaptation occurs in the presence of maladaptive gene flow. I argue that although there are many convincing theoretical arguments, we have a poor empirical understanding about where in a genome the adaptive loci are actually located. Even though genome regions of low recombination appear as promising hotspots for adaptive loci to cluster, observed patterns of ‘clustered loci’ are often likely to be explained by  detection biases of popular empirical approaches  (e.g.,  population genome scans  and  QTL mapping) . I use hundreds of previously published QTLs from threespine stickleback fish to demonstrate this bias, and then suggest promising future avenues of how to get around these problems  (   Roesti 2018   )

Do adaptive loci cluster within a genome to better resist gene flow? In this paper, I summarize ideas of why, how and where in a genome adaptive loci should become clustered when local adaptation occurs in the presence of maladaptive gene flow. I argue that although there are many convincing theoretical arguments, we have a poor empirical understanding about where in a genome the adaptive loci are actually located. Even though genome regions of low recombination appear as promising hotspots for adaptive loci to cluster, observed patterns of ‘clustered loci’ are often likely to be explained by detection biases of popular empirical approaches (e.g., population genome scans and QTL mapping). I use hundreds of previously published QTLs from threespine stickleback fish to demonstrate this bias, and then suggest promising future avenues of how to get around these problems (Roesti 2018)

Ancestral  inversion polymorphisms  differentiate young lake and stream stickleback fish. We demonstrate experimentally the absence of recombination between the two inversion variants. Yet, genomic differentiation between individuals carrying different inversion variants suggests that  rare recombination is happening between the inversion variants in the center of the inversion  in nature (  Roesti et al. 2015   ).

Ancestral inversion polymorphisms differentiate young lake and stream stickleback fish. We demonstrate experimentally the absence of recombination between the two inversion variants. Yet, genomic differentiation between individuals carrying different inversion variants suggests that rare recombination is happening between the inversion variants in the center of the inversion in nature (Roesti et al. 2015).

Broad-scale patterns of genomic differentiation is similar in many organisms  and is explained by the interaction of polygenic adaptive divergence, gene flow, and recombination rate variation. Tailored to empirical observations, we use  simulations  to quantify different  genetic mechanisms leading to elevated population divergence in regions of low recombination , including  genetic hitchhiking  and  gene flow barriers . We then test the predictions from these models by comparing allopatric and parapatric populations of stickleback residing in different, or similar, environments  (   Berner & Roesti 2017   ).

Broad-scale patterns of genomic differentiation is similar in many organisms and is explained by the interaction of polygenic adaptive divergence, gene flow, and recombination rate variation. Tailored to empirical observations, we use simulations to quantify different genetic mechanisms leading to elevated population divergence in regions of low recombination, including genetic hitchhiking and gene flow barriers. We then test the predictions from these models by comparing allopatric and parapatric populations of stickleback residing in different, or similar, environments (Berner & Roesti 2017).

Cichlid fish  species in the East African Lake Tankanyika  differ in how they care for their eggs and juvenile offspring : either only one parental sex or both sexes use mouthbrooding during parental care, or parental care involves no mouthbrooding at all. We predicted that due to a likely  functional involvement of gill rakers in mouthbrooding besides in foraging , only uni-parental mouthbrooding species should be sexually dimorphic in gill raker morphology. Indeed, this is what we found! This study provides a largely unrecognized explanation for sexual dimorphism in nature because  neither sexual selection nor initial niche divergence between the sexes seem to explain this sexual dimorphism   (Ronco*, Roesti*, Salzburger* 2019, in press) .

Cichlid fish species in the East African Lake Tankanyika differ in how they care for their eggs and juvenile offspring: either only one parental sex or both sexes use mouthbrooding during parental care, or parental care involves no mouthbrooding at all. We predicted that due to a likely functional involvement of gill rakers in mouthbrooding besides in foraging, only uni-parental mouthbrooding species should be sexually dimorphic in gill raker morphology. Indeed, this is what we found! This study provides a largely unrecognized explanation for sexual dimorphism in nature because neither sexual selection nor initial niche divergence between the sexes seem to explain this sexual dimorphism (Ronco*, Roesti*, Salzburger* 2019, in press).

Evidence for  genome-wide adaptation  to a seemingly  simple biotic change  to the environment of an organism: In many postglacial lakes in Western Canada, threespine stickleback and prickly sculpin co-occur and interact (food competition and opportunistic predation). In some lakes, however, there are only stickleback, but no sculpin. We find evidence for strong, parallel selection in the genome of stickleback as a consequence of sculpin presence/absence. The  extent of phenotypic and genomic adaptive divergence are positively associated   (   Miller, Roesti, Schluter 2019   ) . More work on this species interaction is forthcoming.

Evidence for genome-wide adaptation to a seemingly simple biotic change to the environment of an organism: In many postglacial lakes in Western Canada, threespine stickleback and prickly sculpin co-occur and interact (food competition and opportunistic predation). In some lakes, however, there are only stickleback, but no sculpin. We find evidence for strong, parallel selection in the genome of stickleback as a consequence of sculpin presence/absence. The extent of phenotypic and genomic adaptive divergence are positively associated (Miller, Roesti, Schluter 2019). More work on this species interaction is forthcoming.

Left:  Parallel adaptation from shared genetic variation , such as from  pre-existing or introgressed variation , produces a distinct  genetic signature  within a genome. We predict this signature using simulation models, and then confirm the prediction by genome-wide and targeted sequencing of natural stickleback populations  (   Roesti et al. 2014   ).   Right:  Chromosome-wide variation in recombination rate  shapes differentiation and diversity within the stickleback genome.  Recombination rate is consistently elevated towards the tips of chromosomes, and reduced in the center of chromosomes – a pattern that appears to be unrelated to the position of the centromeres , but instead, is related to functional constraints during meiosis. We further find that recombination rate variation influences nucleotide composition within a genome  (   Roesti et al. 2013   ).

Left: Parallel adaptation from shared genetic variation, such as from pre-existing or introgressed variation, produces a distinct genetic signature within a genome. We predict this signature using simulation models, and then confirm the prediction by genome-wide and targeted sequencing of natural stickleback populations (Roesti et al. 2014).

Right: Chromosome-wide variation in recombination rate shapes differentiation and diversity within the stickleback genome. Recombination rate is consistently elevated towards the tips of chromosomes, and reduced in the center of chromosomes – a pattern that appears to be unrelated to the position of the centromeres, but instead, is related to functional constraints during meiosis. We further find that recombination rate variation influences nucleotide composition within a genome (Roesti et al. 2013).

Lake-stream divergence of stickleback in lateral plating and the associated  molecular signatures   (   Roesti et al. 2015   ) .

Lake-stream divergence of stickleback in lateral plating and the associated molecular signatures (Roesti et al. 2015).

Phenotypic adaptation  of stickleback into lake and stream habitats, and associated  genetic and genome-wide signatures of selection . We detect the  constraint of gene flow  to genome-wide differentiation between diversifying populations, and find that the degree of  phenotypic and genome-wide differentiation correlate  positively. This study provided one of the first genome-wide demonstrations of how recombination rate variation shapes genomic differentiation during diversification  (   Roesti et al. 2012   ).

Phenotypic adaptation of stickleback into lake and stream habitats, and associated genetic and genome-wide signatures of selection. We detect the constraint of gene flow to genome-wide differentiation between diversifying populations, and find that the degree of phenotypic and genome-wide differentiation correlate positively. This study provided one of the first genome-wide demonstrations of how recombination rate variation shapes genomic differentiation during diversification (Roesti et al. 2012).

Left: Evidence for  strong genome-wide differentiation between distinct lamprey ecotypes  that were previously thought to be the product of phenotypic plasticity  (   Mateus et al. 2013   ) .  Right:  Phylogenomics  applied to Patagonotothen icefish species reveals  incomplete species boundaries  in this adaptive radiation  (   Ceballos 2019   ).

Left: Evidence for strong genome-wide differentiation between distinct lamprey ecotypes that were previously thought to be the product of phenotypic plasticity (Mateus et al. 2013).

Right: Phylogenomics applied to Patagonotothen icefish species reveals incomplete species boundaries in this adaptive radiation (Ceballos 2019).