Abstract
Adaptive genetic divergence occurs when selection imposed by the
environment causes the genomic component of the phenotype to
differentiate. However, genomic signatures of natural selection are
usually identified without information on which trait is responding to
selection by which selective agent(s). Here we integrate
whole-genome-sequencing with phenomics and measures of putative
selective agents to assess the extent of adaptive divergence in
threespine stickleback occupying the highly heterogeneous lake Mývatn,
NE Iceland. We find negligible genome wide divergence, yet multiple
traits (body size, gill raker structure and defence traits) were
divergent along known ecological gradients (temperature, predatory bird
densities and water depth). SNP based heritability of all measured
traits was high (h2 = 0.42 – 0.65), indicating
adaptive potential for all traits. Whilst environment-association
analyses identified thousands of loci putatively involved in selection,
related to genes linked to neuron development and protein
phosphorylation, only allelic variation linked to pelvic spine length
was concurrently linked to environmental variation (water depth) -
supporting the conclusion that divergence in pelvic spine length
occurred in face of gene flow. Our results suggest that whilst there is
substantial genetic variation in the traits measured, phenotypic
divergence of Mývatn stickleback is mostly weakly associated with
environmental gradients, potentially as a result of substantial gene
flow. Our study illustrates the value of integrative studies that
combine genomic assays of multivariate trait variation with landscape
genomics.
Keywords: adaptive divergence, gene flow, environmental gradients,
genome scans, landscape genomics, Gasterosteus aculeatus
Introduction
Elucidating the genetic basis of adaptive divergence in natural
populations is an enduring goal of evolutionary biology . Doing so can
provide insight into evolutionary processes occurring in the wild,
including the mechanisms associated with adaptive divergence, and the
extent to which divergence takes place in the face of gene flow .
Genetically, adaptive divergence is expected to manifest as blocks of
differentiation across the genome, at regions containing genes that
contribute to adaptation to divergent local environments . Genome scan
studies that test these expectations have identified genomic regions
associated with adaptation to divergent ecological niches in numerous
species (e.g., ). This has been termed a “reverse ecology” approach,
whereby loci associated with adaptation may be identified without
measuring the traits themselves . However, genome scan studies on wild
populations are seldom able to provide precise information on which
aspects of the phenotype selection is acting on, or which environmental
factors are imposing selection .
A comprehensive view on the genomic mechanisms associated with adaptive
divergence requires studies that combine phenotypic, environmental and
genomic data. Accordingly, integrative approaches that combine
association mapping with landscape genomics or selection scans to map
gene-phenotype-environment associations could be a powerful means to
infer the genomic basis of adaptation . Association mapping studies
(e.g., genome-wide-associations, GWA ) identify specific loci that
underlie divergent traits, whereas landscape genomic studies can aid in
determining loci associated with adaptive divergence, under the
assumption that loci should be correlated with environmental variation
that is directly or indirectly causing selection . Combining association
mapping with landscape genomics can strengthen the identification of
genomic signatures of selection by allowing inference on whether causal
variants of phenotypic variation are concurrently associated with
environmental variation. This would be especially true in cases where
correlations between phenotype and environment are mirrored in genetic
polymorphisms, where at some quantitative trait loci, allele frequencies
differ between groups that inhabit different environments.
In the absence of dispersal barriers, many populations remain connected
by gene flow during the process of adaptive divergence, often along
environmental clines . Gene flow is expected to constrain divergence,
swamping locally adapted alleles and breaking up favourable allele
combinations through recombination . Whilst in cases of substantial gene
flow there may be little genome-wide divergence, responses to natural
selection may be present at specific genomic regions (islands of
divergence; ). Identifying genomic divergence in the presence of gene
flow is a major challenge because most genome scan approaches require
grouping individuals, which is not usually possible when individuals
remain connected . Our perspective on adaptive divergence may therefore
be biased towards studies where physical barriers to gene flow have
facilitated divergence. Although such studies have provided great
insight into evolutionary processes, studying processes of divergence in
populations connected by gene flow can greatly improve our understanding
of the relative roles of natural selection and gene flow in adaptive
divergence .
Here, we employ GWA and landscape genomic approaches to map
gene-phenotype-environment associations in threespine stickleback that
inhabit Mývatn, a highly environmentally heterogeneous lake in NE
Iceland. Threespine stickleback is a well-established model system in
evolutionary biology . Within freshwater systems, there is evidence for
repeated adaptive divergence at both phenotypic and genomic levels ,
most commonly across the benthic-limnetic axis (e.g. ) but also across a
range of other selective agents (e.g., predation ). However, most of the
studies focus on simple environmental contrasts (e.g., benthic vs
limnetic or lake vs stream), and only few studies have aimed to test
intralacustrine divergence across environmental gradients.
Mývatn is a large (37 km2) lake, where temperature,
water depth, invertebrate, and vertebrate (including stickleback)
densities vary over space and time . Stickleback habitats in this lake
can crudely be divided to five main types, across which stickleback vary
phenotypically . Previous work found that male stickleback had
relatively larger brains in a ´lava´ (warm) than a ´mud´ (colder)
habitat , relatively longer spines in the north basin than the south
basin , and divergence in gill raker morphology and diet among some of
the habitats . Evidence for population genetic divergence of stickleback
across the lake is mixed. Using samples collected between 1999 and 2002,
found evidence for genetic divergence using a suite of nuclear and
mitochondrial markers between stickleback inhabiting the ´lava´ and
´mud´ habitats (microsatellites: FST = 0.08;
mtDNA: FST = 0.223), suggesting the presence of
two contrasting morphs. In contrast, using samples collected in 2009 and
12 nuclear microsatellite loci (seven of which were the same as in
Ólafsdóttir et al. 2007), found little evidence for neutral
genetic divergence of stickleback across five habitat types (average
pairwise FST = 0.004), suggesting extensive gene
flow.
Given the known phenotypic divergence in traits typically under
selection in stickleback, coupled with spatial variation in possible
selective agents, our main goal here was to identify genomic signatures
of selection in Mývatn stickleback occupying different environments.
Genomic signatures of selection are typically defined as genomic regions
which are disproportionately divergent between groups compared to the
rest of the genome . We extended this definition to strengthen our
identification of signatures of selection: we expected that genomic
regions that bear a signature of selection should be both divergent
across ecological axes, and contain loci associated with variation in
divergent traits. We further measured SNP-based additive genetic
variation of divergent traits to gain insight into the evolutionary
potential of traits that are spatially divergent.