1 Introduction
Many animals undertake long-distance migration from their natal sites to
capitalize on abundant resources that may increase survival, fecundity,
and fitness (Dingle & Drake, 2007). Migrations offer temporal and
spatial availability of resources, along with seasonal suitability of
migratory corridors and natal areas (Edwards & Richardson, 2004;
Forrest & Miller-Rushing, 2010). The migration of Oncorhynchusspp. (Pacific salmon and trout) is a critical cultural, economic,
and ecological resource throughout their native range.
Conservation of salmon and
steelhead is based upon maintaining phenotypic and genetic variation of
distinct populations and a principal focus involves conserving migration
timings across large drainages such as the Columbia River basin. Many
populations are managed according to degree of reproductive isolation
and life history variation. Evolutionarily significant units (ESU) of
Pacific salmon and trout are defined as a Distinct Population Segment
(DPS) under the US Endangered Species Act (ESA) (Ryder, 1986; Waples,
1991) and each DPS is determined by whether it is sufficiently
reproductively isolated and of evolutionary importance to the species
(Waples, 1991). Since the late 1800s, wild Pacific salmon and trout have
experienced a steady decline in abundance and range. The freshwater
range of Pacific salmon and trout has shrunk to about 60% of the
historical range (National Research Council, 1996; English et al.,
2006). The decline has been initially attributed to overharvest, habitat
degradation (logging, mining, agricultural practices), and other
anthropogenic development, but modern anthropogenic activity including
hydroelectric dams’ disruption of migratory routes, climate change, and
an ongoing decrease in suitable habitat have also contributed to decline
(Chapman, 1986; Meehan, 1991; Crozier et al., 2008).
Steelhead (O. mykiss ) may undertake long migrations (over a
thousand kilometers) in early life stages and return to natal sites to
spawn (Busby et al., 1996; Keefer et al., 2014). Migratory phenotypes in
the Columbia River basin vary by genetic lineage that have been
previously characterized as either coastal or inland (Utter et al.,
1980; Busby et al., 1996; Quinn, 2018). The two genetic lineages are
geographically separated; the coastal lineage inhabits streams west of
the Cascade Mountains and the inland lineage inhabits streams east of
the Cascades (Busby et al., 1996; Brannon et al., 2004). Out of 15
steelhead ESUs in the Columbia River basin, 11 are listed under the ESA
(Waples et al., 2001); one steelhead ESU is endangered and ten are
threatened (Quinn, 2018). According to the ESA, an estimated one-third
of Pacific salmon and trout populations and all five DPS of steelhead in
the Columbia River are listed as threatened or endangered (Gustafson et
al., 2007). Steelhead have also been extirpated from the upper Snake
River and Columbia River head-waters (Gustafson et al., 2007).
Populations of steelhead consist of individuals that spawn at similar
times and are genetically similar at neutral genetic markers, but
individuals within a population may display significant variation in
when they enter freshwater or arrive at spawning grounds (Quinn, 2018).
Steelhead spawn in the spring, but can begin migration as early as
summer of the previous year before spawning or as late as winter/spring
just before spawning (Quinn et al., 2015). Steelhead migration may be
characterized as bimodal in some rivers (Leider et al., 1986; Hess et
al., 2016), with migrations referred to as early migrating summer-run
(premature) or late migrating winter-run (mature; Quinn et al., 2015).
Steelhead that exhibit early migration enter freshwater before they are
sexually mature, and then hold in freshwater for several months
throughout the winter before maturing and spawning the following spring
(Quinn et al., 2015; Quinn, 2018). Steelhead that exhibit late
migrations become sexually mature in the ocean before migration into
freshwater only weeks to a few months before spawning at natal sites in
the spring (Quinn et al., 2015; Quinn, 2018). Significantly more
stream-maturing steelhead populations have been extirpated than
ocean-maturing steelhead populations (Gustafson et al., 2007).
Migration timing in Pacific salmon and trout has been demonstrated to be
heritable (Quinn et al., 2000; Thériault et al., 2007; Carlson &
Seamons, 2008; Quinn et al., 2015). Further, migration timing is
associated with a genomic region of major effect in both steelhead and
Chinook salmon (O. tshawytscha ) (Hess et al., 2016; Prince et
al., 2017; Micheletti et al., 2018a; Narum et al., 2018; Thompson et
al., 2019). Restriction site associated DNA sequencing (RAD-seq) studies
have revealed single-nucleotide polymorphisms (SNPs) within thegreb1L gene region that are associated with steelhead migration
timing (Hess et al., 2016; Prince et al., 2017). Additional candidate
genes associated with migration timing have been identified using a
genome resequencing technique (Pool-seq; Micheletti and Narum, 2018)
that generates allele frequencies at the population level spanning
nearly half the genome. Pooled-sequencing (Pool-seq) methods and
PoolParty analysis pipeline (Micheletti & Narum, 2018) revealed further
SNPs associated with migration timing and expanded the genomic region of
discovered SNPs to three more candidate genes (rock1, mib1,
abhd3 , and intergenic region between greb1L and rock1 )
(Micheletti et al., 2018a). While this genomic region of major effect
may have direct conservation applications such as refining conservation
units and fisheries harvest (Waples & Lindley, 2018), further
understanding is needed including inheritance patterns and linkage
relationships among candidate markers, and the influence of landscape
characters on the distribution and frequency of candidate markers.
The greb1L gene is broadly present and conserved in vertebrates
and the function is believed to be similar to greb1 , which has
been shown to modulate estrogen receptors and augment the role of
estrogen in transcription in humans (Mohammed et al., 2013). Markers
shown to have non-conservative and non-synonymous mutations by
Micheletti et al. (2018a) indicate that this genetic region is under
selection and the markers in the intergenic region, upstream ofgreb1L , associated with migration timing could be promoters or
enhancers and regulate expression of greb1L (Kilpinen et al.,
2013). Recent studies suggest that greb1L plays a role in early
and late migration phenotypes in steelhead and Chinook salmon (Hess et
al., 2016; Prince et al., 2017; Micheletti et al., 2018a; Narum et al.,
2018; Thompson et al., 2019). Migration to spawning grounds is
intrinsically linked to sexual development and maturation in Pacific
salmon and trout and these processes have been attributed togreb1L in chum salmon (Oncorhynchus keta ) and other
species (Ghosh et al., 2000; Rae et al., 2006; Pellegrini et al., 2012;
Choi et al., 2014).
In this study, we examined the
distribution of genetic variation for the candidate genomic region in
steelhead and were able to expand upon the number of candidate markers
associated with migration timing, the number of individuals sampled, and
improved sampling coverage across the Columbia River basin compared to
previous studies (Hess et al., 2016; Prince et al., 2017; Micheletti et
al., 2018a). We used 13 candidate markers spanning greb1L ,rock1 , and the intergenic region to test combinations of markers
that resulted in haplotypes representative of migration timing
phenotypes. Four of the candidate markers were previously identified
with RADseq and pooled sequencing methods (Hess et al., 2016; Micheletti
et al., 2018a), and nine additional candidate markers were developed
with pooled sequencing methods (Table 1). Sample collections were
distributed across the Columbia River basin, allowing for comparisons of
candidate allelic and haplotypic frequencies for migration timing in a
variety of steelhead habitats to better understand the spatial
distribution of genetic variation underlying steelhead migration timing.
Finally, we use landscape genetic analyses to expand upon the evaluation
of environmental drivers of genetic variation identified by Micheletti
et al. (2018b) for these candidate markers and for an expansion of
collection sites. To distinguish between migration timing phenotypes and
associated genetic variation, we use the terminology of ‘early’ and
‘late’ to refer to migration phenotypes and ‘premature’ and ‘mature’ to
refer to genetic variation (alleles, genotypes, or haplotypes).