Genetic patterns within each species
The patterns of genetic diversity along the threespine genome have previously been described in studies of divergence between marine and freshwater threespine population pairs (Hohenlohe et al. 2010, Chan et al. 2010, Jones et al. 2013, Roesti et al. 2015). FSTscores typically cluster in several broad peaks in comparisons among freshwater and marine environments, with pronounced peaks around theEda locus (chr4; Hohenlohe et al. 2010) and the Pitx1locus (chr7; Chan et al. 2010), which are involved in freshwater adaptation. Additionally, broad peaks found at three inversions (chr1, 11 & 21) have also been associated with freshwater adaptation (Jones et al. 2012; Roesti et al. 2015). Unexpectedly, as we compared two marine populations, we identified some of these characteristic patterns of marine-freshwater divergence in this study (Fig. S3). A possible explanation is that the northern and southern populations differ in the degree to which they receive gene flow from freshwater populations. In the south, threespines were sampled from an isolated stream that drained directly into the ocean, while the northern threespines were sampled from a lake connected to an estuary (Tables S1). Counterintuitively, the patterns we found probably came from freshwater alleles in the southern population, as a previous study of the lake in the north found no evidence of hybridization between ‘anadromous’ and freshwater populations (Drevecky, Falco and Aguirre, 2013), and a study of marine populations in the North-West Pacific found a higher frequency of freshwater associated alleles at the EDA locus in Oregon than Alaska (Morris et al. , 2018). However, to test such hypotheses about introgression, we would have to look at the frequency of the low-plate EDA allele and the frequencies of inversions in Oregon and Alaska and contrast this with nearby freshwater populations. An alternative explanation is that the some of the patterns of marine-freshwater adaptation may also be pleiotropically connected to thermal regulation, as has been suggested for the EDA locus (Morris et al. , 2018). Whether it is differential gene-flow or pleiotropic adaption, we have found that the genomic landscape of geographically diverse marine threespines is strikingly similar to the marine-freshwater landscape.
In contrast to the patterns found in threespines, no large peaks of FST were present along the tubesnout genome (Fig. 2). Instead, there were several small and narrow FST peaks suggesting that the tubesnout genome has been shaped by processes that do not leave strong genetic signals, such as genetic drift or polygenic adaptation (Rockman 2012, Stinchcombe and Hoekstra 2008, Yeaman 2015). As the Null-W test is designed to detect linked clusters of F­ST outliers, this also explains the lack of any signatures of convergent evolution. Since the patterns of FST were not strongly heterogeneous in tubesnout, it is unsurprising that no significant matches to threespine were found.
The genetic patterns present in the ninespine stickleback were likely the result of a strong genetic bottleneck and isolation between the northern and southern populations, as on average, genetic divergence was high and genetic diversity was low in all four populations (Table 1, Fig. 2). Southern populations were sampled from two prairie lakes, which were formed when a larger post-glacial lake dried up, isolating these ninespine populations and presumably causing a genetic bottleneck (Tufts, 2018), similar to the founder-effect observed in Nordic populations (Shikano et al. , 2010). In contrast, the northern populations were sampled from lakes close to the sea, which potentially has provided several opportunities for gene flow from the marine populations. A phylogeographic study separated ninespine populations from the Atlantic coast and Great Lakes regions into two post-glacial lineages, with evidence suggesting that the divergence time among these lineages may be much older than the last glacial maximum (Aldenhovenet al. , 2010). Presumably, the prairie lake populations are part of this Great Lakes lineage (Tufts, 2018) and therefore should be highly diverged from the Northern populations. The extreme genetic divergence among these populations is likely to be the result of long-term genetic isolation combined with a strong genetic bottleneck in the southern populations, not adaptation to latitude.
Comparing the genome scans of all species reveals three distinct patterns, suggesting that the balance between the evolutionary processes has differed among these species. The FST Manhattan plots (Fig. 2A) show different patterns, which can be interpreted as the result of three distinct evolutionary scenarios: local adaptation (threespine), genetic bottlenecks (ninespine) and a weak or polygenic selection and/or drift (tubesnout). This does not imply that the ninespine has not experienced selection or that the threespine has not been affected by drift, just that the patterns of diversity in the genome have been more strongly affected by different processes in each species.
A major caveat to these results is that very few populations were sampled per species. Pool-seq mixes alleles across a population, which means that the basic sampling unit is a population, in effect each species had only 2-4 data points. The comparisons made in this study may have been underpowered to detect any shared genetic patterns. However, the presence of threespine peaks in previously identified regions undergoing adaptation (Fig. S3) shows that strong genetic patterns were detectable, thus only subtle patterns of genetic diversity were lost. The lack of this pattern in tubesnout may be due to the lack of an evolutionary history of repeated colonization followed by gene-flow from freshwater populations, which can lead to complex genomic architecture for adaptive traits (Tigano and Friesen, 2016; Faria et al. , 2019). All things considered; this study demonstrates the diversity of genetic patterns that can be identified from genome scans of wild species, even with a limited number of populations.