Divergent life-history races do not represent Chinook salmon coast-wide: the importance of scale in Quaternary biogeography

The dynamic Quaternary geology of the Pacific Ring of Fire created substantial challenges for biogeography. Fish life history and population genetic variation were shaped by climate change, repeated formation and subsidence of ice sheets, sea-level change, volcanism and tectonics, isostatic rebound, and now human activities. It is widely recognized in Chinook salmon (Oncorhynchus tshawytscha) that parallel evolution and phenotypic plasticity have obscured range-wide patterns of life-history segregation with evolutionary lineage, yet the idea of the lineages themselves persists. We employed a large, internationally standardized, microsatellite data set to explore population structure at coast-wide scale and test for two divergent lineages, whether or not related to life history. We found at least 27 distinct lineages. However, relationships among groups were poorly resolved - essentially a star phylogeny. We found pervasive isolation by distance among groups, complicating cluster analysis. Only in the interior Columbia River (east of the Cascade Mountains) is there a deep genetic bifurcation that supports both the two-lineage hypothesis and the life-history segregation hypothesis. This broad-scale perspective helps reconcile different views of Chinook salmon phylogeography and life-history distribution.Keywords: Wire tag recoveries, North America, British Columbia, Reproductive isolation, Genetic popoulation structure, Columbia River Basin, Oncorhynchus Tshawytscha, Mitochondrial DNA variation, Pacific Salmon, Sockeye salmonThis is the publisher’s final pdf. The published article is copyrighted by NRC Research Press and can be found at: http://www.nrcresearchpress.com

The effect of tracheotomy on drug consumption in patients with acute aneurysmal subarachnoid hemorrhage: an observational study

Background Patients with aneurysmal subarachnoid hemorrhage (aSAH) are common in intensive care units (ICU). In patients with aSAH, sedation is used as a neuroprotective measure in order to secure adequate cerebral perfusion pressure (CPP). Compared with the use of an endotracheal tube, a tracheotomy has the advantage of securing the airway at a much lower level of distress, and aSAH patients can often be awakened more rapidly. Little is known about the impact of tracheotomy on the consumption of sedative/analgesic and vasoactive drugs and the maintenance of CPP within defined limits in aSAH patients. Methods We conducted an observational study of aSAH patients who underwent percutaneous tracheotomy. A prospective registry of patient data was supplemented with retrospective retrievals from medical records. Sedative, analgesic and vasoactive drug doses were registered for 3 days prior to and after percutaneous tracheotomy, respectively. Blood pressure, CPP, and the mode of mechanical ventilation were registered 24 h prior to and after tracheotomy. Results Between January 2001 and June 2009, 902 aSAH patients were admitted to our hospital; 74 (8%) were deeply comatose/dying upon arrival. The ruptured aneurysm was repaired in 828 patients (surgical repair 50%) and percutaneous tracheotomy was performed 182 times in 178 patients (59 men and 119 women). This subpopulation (178 of 828 patients) was significantly older (56 vs. 53 years) and presented with a more severe Hunt & Hess grade (p < 0.001). Percutaneous tracheotomy caused a marked decline in mean daily consumption of the analgesics/sedatives fentanyl, midazolam, and propofol, as well as the vasoactive drugs noradrenaline and dopamine. These declines were statistically and clinically significant. The mean CPP was 76 mmHg (SD 8.6) the day before and 79 mmHg (SD 9.6) 24 h after percutaneous tracheotomy. After percutaneous tracheotomy, mechanical ventilatory support could be reduced to a patient-controlled ventilatory support mode in a significant number of patients (p < 0.001). Conclusions Percutaneous tracheotomy in aSAH patients is a swift procedure with low risk that is associated with a significant decline in the consumption of sedative/analgesic and vasoactive drugs while clinical surveillance parameters remain stable or improve

Data from: Comparison of SNPs and microsatellites for fine-scale application of genetic stock identification of Chinook salmon in the Columbia River Basin

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Genetic variation associated with adult migration timing in lineages of Steelhead and Chinook Salmon in the Columbia River

Abstract With the discovery of a major effect region (GREB1L, ROCK1) for adult migration timing in genomes of both Chinook Salmon and Steelhead, several subsequent studies have investigated the effect size and distribution of early and late migration alleles among populations in the Columbia River. Here, we synthesize the results of these studies for the major lineages of Chinook Salmon and Steelhead that include highly distinct groups in the interior Columbia River that exhibit atypical life histories from most coastal lineage populations of these two species. Whole‐genome studies with high marker density have provided extensive insight into SNPs most associated with adult migration timing, and suites of markers for each species have been genotyped in large numbers of individuals to further validate phenotypic effects. For Steelhead, the largest phenotypic effect sizes have been observed in the coastal lineage (36% of variation for passage timing at Bonneville Dam; 43% of variation for tributary arrival timing) compared to the inland lineage (7.5% of variation for passage timing at Bonneville Dam; 8.4% of variation for tributary arrival timing) that overwinter in freshwater prior to spawning. For Chinook Salmon, large effect sizes have been observed in all three lineages for multiple adult migration phenotypes (Coastal lineage: percentage of variation of 27.9% for passage timing at Bonneville Dam, 28.7% for arrival timing for spawning; Interior ocean type: percentage of variation of 47.6% for passage timing at Bonneville Dam, 39.6% for tributary arrival timing, 77.9% for arrival timing for spawning; Interior stream type: percentage of variation of 35.3% for passage at Bonneville Dam, 9.8% for tributary arrival timing, 4.7% for arrival timing for spawning). Together, these results have extended our understanding of genetic variation associated with life history diversity in distinct populations of the Columbia River, however, much research remains necessary to determine the causal mechanism for this major effect region on migration timing in these species

Data from: Genetic basis of adult migration timing in anadromous steelhead discovered through multivariate association testing

Migration traits are presumed to be complex and to involve interaction among multiple genes, thus we employed both univariate analyses and multivariate Random Forest (RF) machine learning algorithm to conduct association mapping of 15,239 single nucleotide polymorphisms (SNPs) for adult migration-timing phenotype in steelhead (Oncorhynchus mykiss). Our study focused on a model natural population of steelhead that exhibits two distinct migration-timing life histories with high levels of admixture in nature. Neutral divergence was limited between fish exhibiting summer- and winter-run migration owing to high levels of interbreeding, but a univariate mixed linear model found three SNPs from a major effect gene to be significantly associated with migration-timing (p < 0.000005) that explained 46% of trait variation. Alignment to the annotated S. salar genome provided evidence that all three SNPs localize within a 46 kb region overlapping GREB1-like (an estrogen target gene) on chromosome Ssa03. Additionally, multivariate analyses with RF identified that these 3 SNPs plus 15 additional SNPs explained up to 60% of trait variation. These candidate SNPs may provide the ability to predict adult migration-timing of steelhead to facilitate conservation management of this species and this study demonstrates the benefit of multivariate analyses for association studies

Data from: Environmental adaptation in Chinook salmon (Oncorhynchus tshawytscha) throughout their North American range

Landscape genomics is a rapidly growing field with recent advances in both genotyping efficiency and statistical analyses that provide insight towards local adaptation of populations under varying environmental and selective pressure. Chinook salmon (Oncorhynchus tshawytscha) are a broadly distributed Pacific salmon species, occupying a diversity of habitats throughout the northeastern Pacific with pronounced variation in environmental and climate features but little is understood regarding local adaptation in this species. We used a multivariate method, redundancy analysis (RDA), to identify polygenic correlations between 19 703 SNP loci and a suite of environmental variables in 46 collections of Chinook salmon (1956 total individuals) distributed throughout much of its North American range. Models in RDA were conducted on both rangewide and regional scales by hierarchical partitioning of the populations into three distinct genetic lineages. Our results indicate that between 5.8 and 21.8% of genomic variation can be accounted for by environmental features, and 566 putatively adaptive loci were identified as targets of environmental adaptation. The most influential drivers of adaptive divergence included precipitation in the driest quarter of the year (Rangewide and North Coastal Lineage, anova P = 0.002 and 0.01, respectively), precipitation in the wettest quarter of the year (Interior Columbia River Stream-Type Lineage, anova P = 0.03), variation in mean diurnal range in temperature (South Coastal Lineage, anova P = 0.005), and migration distance (Rangewide, anova P = 0.001). Our results indicate that environmental features are strong drivers of adaptive genomic divergence in this species, and provide a foundation to investigate how Chinook salmon might respond to global environmental change

Data from: Population genomics of Pacific lamprey: adaptive variation in a highly dispersive species

Unlike most anadromous fishes that have evolved strict homing behaviour, Pacific lamprey (Entosphenus tridentatus) seem to lack philopatry as evidenced by minimal population structure across the species range. Yet unexplained findings of within-region population genetic heterogeneity coupled with the morphological and behavioural diversity described for the species suggest that adaptive genetic variation underlying fitness traits may be responsible. We employed restriction site–associated DNA sequencing to genotype 4439 quality filtered single nucleotide polymorphism (SNP) loci for 518 individuals collected across a broad geographical area including British Columbia, Washington, Oregon and California. A subset of putatively neutral markers (N = 4068) identified a significant amount of variation among three broad populations: northern British Columbia, Columbia River/southern coast and ‘dwarf’ adults (FCT = 0.02, P ≪ 0.001). Additionally, 162 SNPs were identified as adaptive through outlier tests, and inclusion of these markers revealed a signal of adaptive variation related to geography and life history. The majority of the 162 adaptive SNPs were not independent and formed four groups of linked loci. Analyses with matsam software found that 42 of these outlier SNPs were significantly associated with geography, run timing and dwarf life history, and 27 of these 42 SNPs aligned with known genes or highly conserved genomic regions using the genome browser available for sea lamprey. This study provides both neutral and adaptive context for observed genetic divergence among collections and thus reconciles previous findings of population genetic heterogeneity within a species that displays extensive gene flow

Quality filtered genotypes of Pacific lamprey in GENEPOP format

GENEPOP file: 518 Pacific lamprey individuals from 21 collections, genotyped with a set of 4,439 quality filtered SNPs from a larger dataset of 8,772 unique SNP loci identified using methods described by Hess et al. 2013. "POP" headings delineate collections of individuals and include collections names listed in Table 1, Hess et al. 2013