Introduction
The repeated evolution of similar phenotypes across independent lineages
in response to shared environmental conditions (i.e., parallel
evolution) provides strong evidence for natural selection (Manceau,
Domingues, Linnen, Rosenblum, & Hoekstra, 2010; Rosenblum, Parent,
Diepeveen, Noss, & Bi, 2017; Torres-Dowdall et al., 2017). Cases of
parallel evolution have been described in a wide array of organisms
across the tree of life (Colosimo et al., 2005; Mahler, Ingram, Revell,
& Losos, 2013; Rosenblum et al., 2017; Sage, Christin, & Edwards,
2011). Parallel evolution was initially studied on the phenotypic level
but recently focus has shifted towards identifying examples on the
molecular level (Stern, 2013). Phenotypic parallelism can be the product
of mutations in the same gene (Chan et al., 2010; Rosenblum, Rompler,
Schoneberg, & Hoekstra, 2010; Steiner, Rompler, Boettger, Schoneberg,
& Hoekstra, 2009; Zhen, Aardema, Medina, Schumer, & Andolfatto, 2012)
or involve many changes across the genome (Jones, Grabherr, et al.,
2012; Ravinet et al., 2016; Rennison, Stuart, Bolnick, & Peichel, 2019)
which results in a broad signature of parallel genomic divergence.
Identifying examples of genetic and genomic parallelism improved our
general understanding of parallel evolution (Arendt & Reznick, 2008;
Manceau et al., 2010); repeated use of the same genes or genomic regions
can suggest a source of genetic bias or constraint (reviewed in Bolnick,
Barrett, Oke, Rennison, & Stuart, 2018) and the reuse of genes or
regions can also be leveraged to identify candidate loci important for
adaptation.
It is becoming clear that the magnitude of repeatability of genome-wide
parallelism varies considerably across study systems (Jones, Chan, et
al., 2012; Le Moan, Gagnaire, & Bonhomme, 2016; Ravinet et al., 2016).
For example, species pairs of sunflowers that diverged along latitudinal
gradients (Renaut, Owens, & Rieseberg, 2014) show high levels of
genomic parallelism whereas little evidence for genomic parallelism is
found in repeated adaptive radiations of Nicaraguan crater lake cichlid
fishes (Kautt, Elmer, & Meyer, 2012). Within a species, population pairs
can also vary in their magnitude of parallelism (e.g., Ravinet et al.,
2016; Rennison et al., 2019). Threespine stickleback (Gasterosteus
aculeatus ) population pairs from adjacent lake and stream habitats in
Canada show multiple highly divergent genomic regions. A substantial
portion of these divergent regions (37%) is shared among independently
evolved lake-stream pairs. In contrast, lake-stream pairs from Europe
share only 3% of divergent regions (Feulner et al., 2015; Rennison et
al., 2019). In the rough periwinkle (Littorina saxatilis ),
parallelism ranges from 8-34 % of outliers, depending on the
populations compared (Kess, Galindo, & Boulding, 2018; Ravinet et al.,
2016). Both spatial proximity and ecological similarity seem to be key
predictors of the overall magnitude of genome-wide parallelism (Morales
et al., 2019; Rennison, Delmore, Samuk, Owens, & Miller, 2020). A
recent study on threespine stickleback from different areas of their
global distribution further emphasized that the demographic history and
previous selection can affect levels of genomic repeatability (Fang,
Kemppainen, Momigliano, Feng, & Merila, 2020). Taken together, these
results suggest that parallelism in genomic differentiation can be
substantial but highly context dependent. Despite these research
efforts, we currently lack a good understanding of how the geographic
context (divergence in allopatry vs. sympatry) may affect patterns of
genomic parallelism for populations adapting to similar ecological
niches.
In sympatry, the lack of physical barriers allows for gene flow between
diverging populations, which can counteract the accumulation of
genome-wide differentiation (Coyne & Orr, 2004). Gene flow homogenizes
neutral regions of the genome, and only few regions harboring genes
under divergent selection are expected to be strongly differentiated
when divergence occurs with gene flow, as shown for crows andHeliconius butterflies (Nadeau et al., 2014; Poelstra et al.,
2014), although reinforcement could potentially mitigate this effect
(Garner, Goulet, Farnitano, Molina-Henao, & Hopkins, 2018). The
homogenizing effect of gene flow also reduces the fraction of the genome
able to respond to natural selection (Samuk et al., 2017); previous work
has shown that in the presence of gene flow, divergence is limited to
regions with low rates of recombination (Samuk et al., 2017). Such
constraints are not expected in allopatry and the stochastic effects of
genetic drift, differences in effective population size and variable
ecology may generate more inconsistent patterns of differentiation among
allopatric populations. Thus, we predict higher levels of genomic
parallelism across sympatric species due to the bias of divergence
towards a smaller fraction of the genome and fewer stochastic peaks due
to genetic drift.
Threespine stickleback represent an excellent system for studying the
genomic signatures of repeated evolution in natural populations across
different geographic settings. Stickleback have rapidly adapted to
freshwater habitats throughout the northern hemisphere (Bell & Foster,
1994). Newly formed freshwater lakes were independently colonized by
marine stickleback after the last ice age, around 10,000 - 12,000 years
ago (Bell & Foster, 1994). Within these young lakes, stickleback have
repeatedly and independently adapted to novel resources through parallel
phenotypic evolution in trophic morphology (Bell & Foster, 1994;
Bolnick & Ballare, 2020; Schluter & McPhail, 1992). Lakes vary in size
and depth, encompassing different proportions of benthic and limnetic
habitat, which affects dietary and habitat availability for stickleback
(Bolnick & Ballare, 2020). Accordingly, variation in diet and
morphology across allopatric populations is associated with lake size;
stickleback mostly feed on littoral invertebrates (benthic prey) in
small lakes and pelagic zooplankton (limnetic prey) in large lakes
(Bolnick & Ballare, 2020). In medium-sized lakes, stickleback generally
have intermediate phenotypes and broader dietary niches (Bolnick &
Ballare, 2020). While most lakes are inhabited by a solitary population
(morphologically unimodal for most traits and approximately panmictic),
in five lakes in British Columbia the colonizing stickleback
independently evolved into co-occurring pairs of sympatric benthic and
limnetic specialists (Taylor & McPhail, 1999). This repeated divergence
in trophic ecology along the benthic-limnetic axis across sympatric and
allopatric stickleback populations allows us to study parallelism of
genomic differentiation in different geographic settings.
Here, we employ two approaches to map the genomic signatures of
sticklebacks’ adaptation to benthic and limnetic habitats. We use
FST to detect adaptive divergence between benthic and
limnetic sympatric species pairs (Gow, Rogers, Jackson, & Schluter,
2008; Schluter & McPhail, 1992) and among allopatric populations from
small benthic and large limnetic lakes (Bolnick & Ballare, 2020).
Further, we use genome-wide association (GWA) mapping (Bolnick &
Ballare, 2020) for a larger dataset of allopatric lake populations to
detect alleles associated with lake size (the proxy for dietary niche).
By comparing benthic-limnetic adaptation in different geographic
contexts, we were able to quantify the magnitude of parallelism and ask
whether the geographic context affects patterns of shared genomic
architecture during adaptation to similar niches. Furthermore, it is
likely that regions identified to overlap between these datasets contain
loci important for adaptation to divergent benthic and limnetic niches,
such candidate regions provide opportunities for follow-up work.