{"paper_id":"097013e0-61a2-4e40-be0a-f0dc84d9c0da","body_text":"v.0.1.2 \n 1 \nGenome-wide characterization of upper Fraser River sockeye salmon 1 \nidentifies a region of major differentiation between run timing groups 2 \nin the Stuart River Watershed 3 \n 4 \nBen J. G. Sutherland1, Cory Williamson2, Brian Toth3, Gordon Sterritt3 5 \n 6 \n1 Sutherland Bioinformatics, Lantzville, BC, Canada V0R 2H0 7 \n2 Takla First Nation, Takla Landing, BC, Canada V0J 2T0 8 \n3 Upper Fraser Fisheries Conservation Alliance, Williams Lake, BC, Canada V2G 5K9  9 \n 10 \n* Author for correspondence: 11 \nBJGS: Sutherland Bioinformatics, Lantzville, BC, Canada V0R 2H0 12 \nSutherland.Bioinformatics@protonmail.com  13 \n 14 \n 15 \n 16 \n 17 \n 18 \n 19 \n 20 \n 21 \n 22 \n 23 \n 24 \nRunning title: Upper Fraser sockeye genomics  25 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 2 \nAbstract 26 \nEarly Stuart sockeye salmon Oncorhynchus nerka undergo one of the most intensive and far-reaching 27 \nmigrations in the Fraser River ( British Columbia, Canada) that has likely exerted selective pressure s 28 \nshaping their genetics and physiology. To support upper Fraser River sockeye management objectives, 29 \nthere is a need to further understand the unique genetics of these populations. Based on neutral genetic 30 \nmarkers, Early Stuart sockeye are considered a metapopulation with little to no genetic differentiation 31 \namong their approximately 50 spawning streams. In this study we make use of existing resources to 32 \nevaluate genome-wide genetic differentiation in this metapopulation and put it into the context of other 33 \nnearby populations. We confirm that genetic differentiation is low or negligible in the metapopulation 34 \nat a whole-genome level, although we identify a slight increase in differentiation at greater distances 35 \nwithin the watershed  compared to more proximal streams  (e.g., FST = 0.001-0.002 compared with 36 \nundifferentiated). Even the greatest differentiation detected is very low, being  nine times lower than 37 \nthat between run timing groups (Early Stuart vs. Stuart-Summer; e.g., FST = 0.0091). Notably, a region 38 \nof major differentiation was detected between the run timing groups on Chr18 between 56.3-58.0 Mbp 39 \n(average FST = 0.661). This genomic region appears to contain a unique haplotype specific to the Stuart-40 \nSummer, Nadina River, and Stellako River populations (i.e., upstream to the Nechako River).  By 41 \ncontrast, Early Stuart and other upper Fraser River sockeye outside of the Nechako Watershed do not 42 \npossess this haplotype. The genomic region is within ancestral chromosome 15.2, the homeolog to a 43 \nchromosome arm of Chr12 (i.e., 15.1); this arm of Chr12 is  known to contain a major differentiated 44 \nregion associated with run timing and life history variation in Alaska and the Okanagan. This finding 45 \nprovides additional evidence for the importance of this genomic region in both homeologous 46 \nchromosomes within different populations of the same species, and points to the uniqueness of upper 47 \nFraser River sockeye in this potential major effect locus.  48 \n 49 \nKeywords: Early Stuart; Fraser River; genomics; major effect locus; run timing; sockeye salmon  50 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 3 \nIntroduction 51 \nGenetic differentiation is a key metric to provide insight into population distinctiveness (Weir and 52 \nCockerham 1984)  and is the substrate for applications such as genetic stock identification  (GSI). 53 \nPopulation differentiation can be evaluated using 10s of neutral microsatellite markers (e.g., Beacham 54 \net al. 2004) or 100s of single nucleotide polymorphism (SNP) markers for example by amplicon panels 55 \n(Meek and Larson 2019) , 10,000s of SNPs through reduced representation sequencing (Baird et al. 56 \n2008; Peterson et al. 2012)  or 100,000s to millions of SNPs through whole-genome resequencing 57 \n(Christensen et al. 2024; Bemmels et al. 2025). These approaches can recover similar trends, although 58 \npower can be  influenced by population coverage and genomic coverage. Population coverage can 59 \ninclude collecting sufficient sample sizes to effectively represent the population, where more subtle 60 \npopulation structure can be identifiable at higher sample sizes (Araujo et al. 2014). Genomic coverage 61 \nis particularly critical when differentiation is specific to small regions of the genome, while the rest of 62 \nthe genome remains in an undifferentiated state (e.g., Barry et al. 2024). These relatively small regions 63 \nwith significantly increased differentiation relative to the rest of the genome may involve adaptive 64 \nvariation (Tigano and Russello 2022)  and/or structural variation such as inversions  (Akopyan et al. 65 \n2025), which can prevent local recombination, retaining haplotypes of adaptive alleles (Wellenreuther 66 \nand Bernatchez 2018).  67 \nThe Fraser River watershed is the largest sockeye salmon Oncorhynchus nerka complex in 68 \nBritish Columbia (BC), Canada, and has the greatest sockeye abundance in the world for any single 69 \nriver system (COSEWIC 2017) . Over the past century, there have been significant declines in all 70 \nspecies of salmon in the Fraser River; based on genetic evidence, sockeye salmon have had particularly 71 \ndrastic declines (Christensen et al. 2024). Multiple salmon species show similar trends in hierarchical 72 \npopulation genetic structure in the Fraser River , with the greatest differences observed among broad 73 \nregional groupings of lower, middle, and upper Fraser River (greatest between the lower and middle, 74 \nlikely due to the significant migration barrier of the Fraser Canyon; Christensen et al. 2024) . Th e 75 \noverall population structure of sockeye salmon in the Fraser  has been documented using multiple 76 \ndifferent marker types, includin g microsatellites and SNPs  (Beacham et al. 2004; Rondeau 2022) . 77 \nSubgroupings and structure among spawning locations is generally based on geographic proximity as 78 \nwell as ecotype and run  timing (Beacham et al. 2004; Beacham and Withler 2017) . The genetic 79 \ndiversity of Fraser River salmon collectively represents the standing genetic variation for the species 80 \nin the region, and holds adaptive traits and genetic diversity that is irreplaceable on timescales that are 81 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 4 \nrelevant to humans (Waples et al. 2001; COSEWIC 2017), critical for fisheries, culture, and resilience 82 \nto climate change.  83 \nEarly Stuart sockeye spawn in the upper Stuart River watershed, a major sub-basin of the Fraser 84 \nRiver watershed in central BC that is comprised of two large lakes, Takla Lake and Trembleur Lake, 85 \nthat are connected by the wide and shallow Middle River  (Bradford and Braun 2021) . Early Stuart 86 \nsockeye are the sole representative of the Early Stuart run timing group, one of the four run timing 87 \ndesignations in the Fraser River (COSEWIC 2017). Early Stuart sockeye have the earliest upstream 88 \nmigration of all Fraser River sockeye (Idler and Clemens 1959; Bradford and Braun 2021). Returning 89 \nadults enter the Fraser River in early July and quickly migrate to spawning streams in the Stuart system, 90 \nwhere peak spawning occurs in natal streams in mid -August (Bradford and Braun 2021) . 91 \nApproximately half of the Early Stuart run timing group passes Hell’s Gate by July 14 th, whereas the 92 \nearly summer, summer, and late run timing groups correspond to Aug. 6 th, Aug. 17th, and Sept. 21 st, 93 \nrespectively (COSEWIC 2017) . The Early Stuart sockeye and other neighbouring populations, 94 \nincluding the Stuart-Summer sockeye, must travel great distances and overcome significant river force 95 \n(Wright et al. 2025)  to reach the spawning grounds . This migration is thought to have shaped Early 96 \nStuart sockeye genetics and physiology  through long-exerted evolutionary forces based on energetic 97 \nrequirements and local environments of the route (Hinch and Rand 1998; Rand et al. 2006; Crossin et 98 \nal. 2004; Eliason et al. 2011). Early Stuart sockeye have smaller and more fusiform body shapes than 99 \nother deeper bodied morphologies that occur in sockeye populations with easier routes, higher somatic 100 \nenergy density, fewer carried eggs  and exhibit more efficient travel  (Gilhousen 1980; reviewed by 101 \nCrossin et al. 2004) , are capable of higher aerobic scope  and cardiac capacity (Crossin et al. 2004; 102 \nEliason et al. 2011).  103 \nEarly Stuart sockeye are considered to exist in a metapopulation, or a collection of streams that 104 \nall comprise one large population with some extent of gene flow expected between streams (Bradford 105 \nand Braun 2021). The sockeye populations that spawn most temporally and geographically proximal 106 \nto the Early Stuart sockeye are from the genetically distinct Stuart-summer run timing group (Beacham 107 \net al. 2004; Rondeau 2022) . Of the over 50 Early Stuart spawning sites within the Stuart River 108 \nwatershed (COSEWIC 2017), 36 streams have been characterized in detail  by Bradford and Braun 109 \n(2021), who report that 12 streams contain good and stable habitat, are occupied in more than 90% of 110 \nevaluated years, and contain at least 85% of the spawners of the metapopulation. The other 24 streams 111 \nexhibit poorer habitat, are not persistently abundant with spawners, and are periodically recolonized 112 \nby dispersers from the 12 strong streams, which are therefore considered to be the key to the resiliency 113 \nof the system (Bradford and Braun 2021). Genetic characterization with high numbers of samples and 114 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 5 \nmicrosatellite or SNP markers have not identified significant population structure in the 115 \nmetapopulation (Beacham et al. 2004; Rondeau 2022) , and so the current expectation  for the 116 \nmetapopulation is panmixia. However, this type of analysis has yet to be conducted at a genome-wide 117 \nlevel. Evaluating differentiation in the metapopulation at this scale will provide valuable information 118 \nto support management and conservation objectives.  119 \nThe primary purpose of this work is to determine whether any neutral or putatively functional 120 \ngenetic variation , including that within punctuated and relatively  small genomic regions,  are 121 \ndifferentiated between sockeye spawning in individual tributaries used by Early Stuart sockeye salmon. 122 \nA secondary objective is to determine whether unique characteristics exist in the genome of the Early 123 \nStuart sockeye relative to Stuart-Summer or other nearby populations that can aid in our understanding 124 \nof differences between these populations. By using the recently published genome-wide SNP data for 125 \nFraser River sockeye salmon (Christensen et al. 2024), we directly address these two objectives in the 126 \naim to guide conservation and management of these important populations.  127 \n 128 \nMethods 129 \nSamples and genotypes 130 \nMultilocus genotypes were obtained as a VCF file from a recent study on salmonids of the Fraser River 131 \n(see Data Availability; Christensen et al. 2024). The VCF file was subset with bcftools (Danecek et al. 132 \n2021) to retain sockeye collections from the mid- or upper-Fraser River (Table 1). Annotations were 133 \nadded to the VCF file and SNPs were filtered to only retain those with minor allele frequency (MAF) 134 \n> 0.01. An additional dataset was generated for use in population genetic analyses by filtering for MAF 135 \n> 0.05 and removing SNPs in high linkage (maximum r2 = 0.5 in 50 kb windows) using bcftools.  136 \n 137 \nPopulation genetics 138 \nThe population genetic dataset (MAF > 0.05 and LD -filtered) was used as an input to a principal 139 \ncomponents analysis (PCA) including all samples. Region-specific analyses were also conducted, with 140 \ndatasets filtered for (1) all waters that flow into the Nechako River (i.e., Early Stuart, Stuart-Summer, 141 \nNadina River, and Stellako River); (2) all waters that flow in to the Quesnel River (i.e., Quesnel and 142 \nHorsefly); and (3) all waters that flow into the Chilcotin River (i.e., Chilko Lake, Chilko River, Taseko 143 \nRiver). The region-specific analyses used PCA to identify general trends, and discriminant analysis of 144 \nprincipal components (DAPC) to identify loci contributing to the separation of the most differentiated 145 \ngroups in each dataset. Loading values for these loci were plotted on sockeye salmon chromosomes 146 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 6 \n(GCF_034236695.1; Christensen et al. 2020)  using fastman (Paria et al. 2022) . To investigate 147 \nsubstructure within the Early Stuart sockeye, a dataset was generated containing only the Early Stuart 148 \ncollections, and a DAPC was conducted and loading values plotted across the chromosomes. Genetic 149 \ndifferentiation was evaluated using FST (Weir and Cockerham 1984) calculated as the average of all 150 \nper-locus FST values between specific contrasts calculated by VCFtools (Danecek et al. 2011).  151 \n 152 \nOutlier region characterization 153 \nTo explore a detected region of increased differentiation, the full dataset with all SNPs (MAF > 0.01) 154 \nwas limited to only Chr18 and only Early Stuart and Stuart-Summer samples (i.e., the two genetically 155 \nmost proximal populations that exhibited the elevated differentiation on Chr18. Monomorphic and low 156 \nMAF loci (MAF ≤ 0.01) in the subset dataset were removed and per-locus FST was calculated for all 157 \nloci on Chr18 using pegas (Paradis 2010) in R (R Core Team 2025) . To understand the geographic 158 \ncontext of the differentiated region, the section of the chromosome with FST > 0.5 was identified and 159 \nSNPs from this region for all individuals in the study were selected using bcftools and read into R 160 \nusing vcfR (Knaus and Grünwald 2017). Genotypes were converted to allele dosage and  plotted in a 161 \nheatmap in R, allowing dendrogram clustering of samples , but not SNPs,  using heatmap function 162 \ndefaults.  163 \n To inspect the genomic context of the differentiated region, the identified region and its 164 \nflanking sections were inspected for annotated genes in NCBI and for indications of inversions based 165 \non manual inspections of short read alignments, respectively. The SNP positions from the genome used 166 \nby Christensen et al. (2024) were converted to the latest genome available in NCBI (i.e., 167 \nGCF_034236695.1; Christensen et al. 2020)  using SNPlift (Normandeau et al. 2023) . The region of 168 \ninterest was confirmed to be in a similar position based on the positions of the SNPs delimiting the 169 \nregion, as well as re -running an FST analysis for the Stuart River system samples only with the 170 \nconverted dataset. Inspections for structural variation was explored using two representative samples 171 \nfrom each haplotype group  (i.e., unique haplotype to upstream to Nechako represented by Kuzkwa 172 \nRiver, and the haplotype more typical of the rest of the Fraser River from the Driftwood River). These 173 \nsamples were obtained as fastq data from NCBI using SRA -toolkit. The samples were  trimmed for 174 \nquality using cutadapt (Martin 2011), and aligned against Chr18 of the reference genome using bwa 175 \nmem (Li 2013). All alignments or discordant alignments were inspected using the Integrated Genomics 176 \nViewer (IGV; Robinson et al. 2011) with a focus on the delimiters of the elevated differentiation region 177 \nfor indications of inversions.  178 \n 179 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 7 \nResults 180 \nPopulation genetic structure in upper Fraser River sockeye salmon 181 \nUpper Fraser River sockeye salmon samples sourced from Christensen et al. (2024) that are included 182 \nin the present analysis are presented in Table 1 and include the following regions: Stuart (Early Stuart, 183 \nStuart-Summer), Nadina/Francois, Francois/Fraser, Bowron, Quesnel and Horsefly, and Chil ko. For 184 \neach collection included, year of sampling was obtained from Christensen et al. (2024), and run timing 185 \ndesignations were sourced from Rondeau (2022).  186 \n Population genetic trends were explored using linkage filtered SNPs (n = 627,769 ; MAF > 187 \n0.05). A PCA clustering all samples by SNPs shows four main clusters in PC1 and PC2 (Figure 1A; 188 \nPVE = 3.6% and 1.8%, respectively) . These clusters include the  populations using tributaries to the 189 \nNechako River as natal habitat (i.e., both run timing groups from the Stuart River watershed, Nadina, 190 \nand Stellako), the Bowron River, Quesnel/Horsefly, and the Chilcotin Watershed (Figure 1A). 191 \nPopulations from Quesnel, Horsefly, and Chilcotin regions have a similar position on PC1 but are 192 \nseparated across PC2. A genetic dendrogram shows similar groupings, with the largest difference in 193 \nthe data being  between the populations upstream to the Nechako from the other collections (Figure 194 \nS1). The second grouping contains Bowron as the most external population to the grouping, followed 195 \nby Chilcotin region populations, and a grouping containing Quesnel and Horsefly populations, which 196 \nare grouped together but in separate branches (Figure S1). Some indication of unexpected clustering 197 \ndue to low sample size is suggested by the dendrogram, with Felix (n = 5) and Takla (n = 4) collections 198 \ngrouping closely and separately from other collections , as well as poor clustering of Middle River (n 199 \n= 7) and Pinchi (n = 4). Notably, Driftwood (n = 7) also clusters on the outside of the other Early Stuart 200 \ncollections.  201 \nWithin-region variation was inspected for populations upstream to the Nechako River (n = 96 202 \nsamples, 12 collection sites, and 620,725 SNPs). A PCA groups all Early Stuart collections separately 203 \nfrom Stuart-Summer, Nadina, and Stellako  on PC1 (PVE = 2.7% ; Figure 1B) . Nadina and Stellako 204 \ncollections grouped generally with the Stuart -Summer for some samples  along PC1, but other 205 \nindividual samples within these collections cluster distantly on both PC1 and PC2. Applying a DAPC 206 \nseparates three groups: (1) Early Stuart; (2) Stuart-Summer and Stellako; and (3) Nadina (Figure 2A). 207 \nLoci contributing the most to this separation were clustered in a region on Chr18, showing a peak that 208 \nis significantly elevated relative to the rest of the genome (Figure 2B; see Major differentiating region 209 \non Chr18 below).  210 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 8 \n Populations upstream to the Chilcotin River (n = 45 samples, 611,274 SNPs) evaluated by PCA 211 \nfound that all Chilko Lake and Chilko River samples (run timing: Summer) grouped together and 212 \nseparately from the Taseko River collection (run timing: Early Summer ; Figure S2A ; PC1 PVE = 213 \n5.3%). These two groups were strongly separated by DAPC (Figure S2B) and the loci separating the 214 \ngroups came from throughout the genome without any clear outlier regions (Figure S2C).  215 \n Populations upstream to the Quesnel River (n = 59 samples, 612,528 SNPs) evaluated by PCA 216 \nfound overlap in groupings within some Quesnel collections, and separate clustering of the Horsefly 217 \ncollections (i.e., Horsefly and McKinley; Figure S3A; PC1 PVE = 5.4%). A DAPC recovered similar 218 \ntrends (Figure S3B) , and  loci contributing to the separation o f Quesnel and Horsefly came from 219 \nthroughout the genome, with no clear indication of outlier genomic regions (Figure S3C).  220 \n 221 \nMajor differentiating region on Chr18 222 \nThe major differentiating region on Chr18 observed between the Early Stuart and Stuart -Summer, 223 \nNadina and Stellako populations (Figure 2B) was explored  further. The approximate genomic 224 \ncoordinate boundaries of the outlier region , based on these populations,  were identified as being 1.7 225 \nMbp in size and spanning from 56,293,719 - 57,982,347 bp, a region with average (± s.d.) FST of 0.661 226 \n± 0.133 (Figure 3A).  227 \n To understand the geographic context of the differentiated region, a heatmap was constructed 228 \nincluding the 10,563 SNPs within the genomic region (MAF > 0.01) from all samples in the study (n 229 \n= 210; Figure 3B). The heatmap shows a distinct haplotype with low heterozygosity  specific to the 230 \ngrouping of  Stuart-Summer, Nadina, and Stellako, whereas the rest of the upper Fraser River 231 \ncollections (including Early Stuart) do not have this haplotype. The top differentiated SNPs had FST 232 \nvalues of 0.975 and were at positions 57,673,269 bp, 57,712,980 bp, and 57,982,347 bp. These three 233 \nSNPs show near fixation between the more derived grouping ( i.e., Stuart-Summer, Nadina, Stellako) 234 \nand the rest of the samples (Additional File S1). For example, SNP Chr18:57,712,980 is a homozygous 235 \nalternate genotype (A/A) in 49 of 50 samples and a heterozygote in one sample  (from Tachie) in the 236 \nStuart-Summer/Stellako/Nadina grouping, and is homozygous reference (G/G) in 158 of 160 samples 237 \nand heterozygous in two samples (both from Horsefly River)  in the rest of the upper Fraser River 238 \npopulations analyzed. The other two SNPs show the same pattern, or exhibit three heterozygotes in the 239 \nHorsefly River (for SNP Chr18:57,712,980). Visualizing read alignments from representatives of each 240 \ngrouping of the major differentiation region with a focus on discordant alignments in flanking genomic 241 \nregions did not provide any clear evidence of an inversion (data not shown).  242 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 9 \nThe annotated gene content in the outlier region was inspected, finding 48 annotated putative 243 \ngenes (RefSeq annotation; Additional File S2). Putative genes within this region included leucine-rich 244 \nrepeat-containing protein 9-like (lrrc9-like; 56.33-56.36 Mbp), fibroblast growth factor receptor-like 245 \n1 (56.48-56.56 Mbp), and homeobox protein OTX2 (57.88-57.89), among others.  246 \n 247 \nMetapopulation differentiation in Early Stuart sockeye 248 \nTo determine whether the whole-genome data indicates genetic distinctiveness or separation between 249 \ntributaries within the Early Stuart metapopulation, a limited dataset with the four populations with the 250 \ngreatest sample sizes was analyzed (i.e., between 7-10 samples per site; total n = 37 samples, 611,155 251 \nSNPs). The four collections were sourced from throughout the two-lake system, including Driftwood 252 \nRiver from the northern end of Takla Lake (n = 7), Dust Creek from the western arm of Takla Lake (n 253 \n= 10), Bivouac Creek from the southern end of Takla Lake (n = 10), and Paula Creek from the western 254 \nend of Trembleur Lake (n = 10). All of these samples were collected in 2005 (Table 1).  255 \nMany of the contrasts within this system showed 95% confidence intervals (CI) for FST that 256 \noverlapped zero, suggesting no discernable differentiation at a genome -wide scale between the 257 \ntributaries (Table 2). Two of the contrasts had very low, non-zero FST values: Driftwood River-Bivouac 258 \nCreek and Driftwood River-Paula Creek 95% CI FST of 0.0017-0.0021 (mean = 0.0019) and 0.0008-259 \n0.0012 (mean = 0.0010) , respectively. A PCA shows a general overlap of all ellipses  around each 260 \ncollection (Figure S4A), suggesting low to negligible FST. A DAPC recovers similar trends to the FST 261 \ncontrasts, where Driftwood is projected furthest from Bivouac Creek and Paula Creek, although some 262 \noverlap exists between Bivouac Creek and Driftwood River  (Figure 4). Therefore, the most distant 263 \nlocations geographically ( i.e., Paula Creek or Bivouac Creek with  Driftwood River) were the most 264 \ndistant genetically, albeit with very low genetic difference. Notably, there were no genomic regions  265 \nshowing elevated contributions to the separation of the Early Stuart collections by DAPC (Figure S4B), 266 \nsuggesting equal differentiation or lack thereof throughout the genome.  267 \nTo put the slight non-zero genetic distance observed between the Driftwood River and Paula 268 \nCreek into context, contrasts between an Early Stuart collection (Paula Creek) and populations from 269 \noutside the Early Stuart group were conducted. Paula Creek compared with Kuzkwa River (Stuart -270 \nSummer) shows an average genome-wide FST of 0.0091 (95% CI: 0.0089-0.0093) based on this dataset, 271 \nwhich is 9.1x higher than Driftwood River vs. Paula Creek. Paula Creek compared with Bowron River 272 \nshows an average genome -wide FST of 0.0355 (95% CI: 0.0353 -0.0358), or 35.5x higher than  273 \nDriftwood vs. Paula.  274 \n 275 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 10 \nDiscussion 276 \nThe present study took an in -depth and region -specific investigation into  genome-wide genetic 277 \nvariation within the upper Fraser River  sockeye salmon through the re -use of existing genomic 278 \nresources generated as part of a three-species analysis of the Fraser River salmonids (Christensen et al. 279 \n2024). General population genetic  trends were similar to those observed using other resources 280 \nincluding microsatellites (Beacham et al. 2004)  or SNPs  (Rondeau 2022) , with some notable 281 \nexceptions, as described below.  282 \n 283 \nMajor region of differentiation on Chr18 in sockeye from the Nechako Watershed 284 \nA main finding of this work was the identification of a major differentiating region between the Early 285 \nStuart sockeye and the Stuart-Summer/Nadina/Stellako sockeye. This genomic region may be involved 286 \nin phenotypic variation in run-timing between these groupings. The Nadina and Stellako populations 287 \nare considered to be Early Summer and Summer run timing groups , respectively (COSEWIC 2017). 288 \nThe unique haplotype identified here appears to be in  a derived form with low heterozygosity in the 289 \nStuart-Summer/Nadina/Stellako samples, as the Early Stuart samples share alleles with samples from 290 \nother populations within the upper Fraser River. Interestingly, some variants within this haplotype are 291 \nnearly fixed between the Stuart-Summer/Nadina/Stellako grouping and the rest of the upper Fraser 292 \nRiver. At the most differentiated loci, there are very few heterozygous genotypes in either grouping . 293 \nThis suggests that these populations have very low gene flow between the haplotype  groups. There 294 \nwas no clear evidence of an inversion in the area, but this remains inconclusive as the current available 295 \ndata was comprised of short reads, whereas a long -read analysis could provide a more definitive 296 \nconclusion regarding structural variation.  297 \nThe putatively derived state of the haplotype in the Stuart-Summer/Nadina/Stellako groupings 298 \nposes interesting questions around the emergence of this haplotype, as the putatively ancestral form is 299 \npresent in the group with the unique run timing designation, i.e., the Early Stuart sockeye. If the unique 300 \nhaplotype is related to phenotypic run timing variation, it therefore follows that the derived phenotype 301 \nwould be that of the Stuart-Summer/Nadina/Stellako grouping. If this genomic region underlies run 302 \ntiming variation, this may indicate that the early run for Early Stuart sockeye is the ancestral run timing 303 \nform, and the later runs to the region (e.g., Stuart -Summer) would be an adaptation allowing for 304 \nexpanded timing of spawning resource access (as discussed by Barry et al. 2024). However, it is also 305 \npossible that the unique region of differentiation is not related to run timing but is rather only coincident 306 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 11 \nto the run timing difference between the analyzed groups. However, other details around the  major 307 \ndifferentiated region on Chr18 suggest involvement in run timing or other life history variation.  308 \n The region of major differentiation on Chr18 at 56.3 – 58.0 Mbp falls within the sockeye 309 \nsalmon chromosome arm that corresponds to the ancestral chromosome 15. 2 (see Sutherland et al. 310 \n2016). The ancestral designation is related to the post -whole-genome duplication chromosome 311 \ncorrespondence where each of 25 ancestral chromosomes has two copies in the present-day salmonid 312 \ngenome, and where the 25 chromosomes roughly correspond to the present -day northern pike Esox 313 \nlucius genome (Rondeau et al. 2014). Importantly, a major differentiated section on the chromosome 314 \narm of Chr12 of sockeye salmon and Chr10 of pink salmon has been identified as being involved in 315 \nrun timing in Alaska (Barry et al. 2024). These two chromosomes both contain 15.1, the homeolog (or 316 \nohnolog) to 15.2 (Sutherland et al. 2016; Christensen et al. 2020; Barry et al. 2024) . Furthermore, a 317 \nmajor differentiating region of Chr12 is associated with life history variation in Okanagan O. nerka 318 \n(Tigano and Russello 2022). Recently, this region has been proposed as a master regulatory region in 319 \nmultiple salmonid species including pink salmon O. gorbuscha, chum salmon O. keta, and sockeye 320 \nsalmon in Alaska (Barry et al. 2024; Barry et al. 2025). Secondary regions of high differentiation have 321 \nbeen identified on the homeolog 15.2 in chum salmon and coho salmon O. kisutch related to run timing 322 \n(ancestral 15.2 or chum Chr29; Barry et al. 2025), but not yet in sockeye salmon until the present work.  323 \n A gene of interest in the genomic region of differentiation previously identified and highlighted 324 \nis leucine-rich repeat -containing protein 9 (lrrc9) (Barry et al. 2024) . The region of major 325 \ndifferentiation in the Stuart sockeye identified here contains a gene annotated as lrrc9-like, the 326 \nhomeologous gene to lrrc9 highlighted previously. However, in the sockeye salmon genome, this gene 327 \nis annotated as a putative pseudogene by the NCBI RefSeq annotation. Interestingly, Barry et al. (2025) 328 \npropose that the region of differentiation is likely driving phenotypic effects through transcription 329 \nregulation activity rather than changes in protein coding sequences due to the lack of non-synonymous 330 \nmutations identified and the prevalence of transcription factors in the region. If lrrc9-like is a 331 \npseudogene, this would support the lack of direct involvement of this gene in any downstream 332 \nphenotype. There are other genes in the major differentiated region identified here in sockeye salmon 333 \nthat may be of interest regarding a migratory timing phenotype, most notably homeobox protein OTX2 334 \n(orthodenticle homeobox 2), a transcription factor involved in brain and sensory organ development  335 \n(Beby and Lamonerie 2013) . OTX2 is involved in the formation of the pituitary gland  in zebrafish 336 \n(Bando et al. 2020) , and the pituitary -gonadal axis activity  in salmonids is connected to season and 337 \ndirectly related to homing adults, return migration and spawning preparation (Onuma et al. 2009; Ueda 338 \n2011). Furthermore, the role of OTX2 in the development of olfactory system, including imprinting 339 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 12 \nand homing has been demonstrated in the anemonefish Amphiprion percula (Veilleux et al. 2013), of 340 \ninterest given the important role of the olfactory system in homing migration in sockeye salmon (Bett 341 \net al. 2018).   342 \n The present study therefore identifies new evidence that points to potential involvement of the 343 \nproposed master control region  on ancestral chromosome 15  in a completely different population to 344 \nthat originally identified, and that has taken an alternate homeologous chromosome path to that which 345 \nwas previously identified in sockeye salmon  (Tigano and Russello 2022; Barry et al. 2024) . This 346 \nsupports the conclusions of Barry et al. (2025), and points to unique genetics and evolutionarily 347 \nsignificant adaptation route of the upper Fraser River  sockeye salmon. As functional analysis of the 348 \nmajor differentiated region here has not been conducted, the role of this region in run timing remains 349 \nputative. Although other run timing differences are reported in the populations analyzed in this study, 350 \nmost notably the two run timings of the Chilcotin Watershed sockeye (i.e., Chilko as Summer and 351 \nTaseko as Early Summer), there were no similar regions of major differentiation observed in these 352 \nother populations using the available samples.  353 \nConsidering the important role of ancestral chromosome 15.1 and 15.2, it is worth briefly 354 \nnoting other features of these chromosomes in the evolution of salmonids. First,  these chromosomes 355 \nare part of ancestral and conserved fusion events; ancestral 15.1 is proposed to have been fused to 4.1 356 \nprior to the divergence of genera Salmo and Oncorhynchus, although lineage -specific fissions and 357 \nfusions occurred in the lineage leading to the pink, chum, sockeye branch (Sutherland et al. 2016) . 358 \nAncestral 15.2 was part of a conserved fusion to 25.2 that occurred prior to the diversification of 359 \nOncorhynchus; this fusion remains in all Oncorhynchus species. Second, the ancestral chromosome 360 \n15.1 is within the chromosome that holds the master sex determining gene in Arctic charr Salvelinus 361 \nalpinus and brook charr S. fontinalis (Sutherland et al. 2017) . Although these features may not be 362 \nrelated to the specific life history and run timing variation  described here, given the proposed role of 363 \nthis genomic region as a master control region for multiple salmonid species, continued understanding 364 \nof these chromosomes may yield valuable insights in the evolution of phenotypic variation in the 365 \nsalmonids.  366 \n 367 \nMetapopulation genetics in Early Stuart sockeye 368 \nUsing genome-wide data we found some evidence of increased genetic differentiation with distance 369 \nwithin the Early Stuart spawning tributaries, specifically that only the spawning sockeye from the most 370 \ndistant tributaries showed non-zero FST. However, this level of differentiation was still very low, being 371 \n9-times lower than that which occurs between run timing groups. Further, in this genome -wide 372 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 13 \nanalysis, we did not identify any regions with elevated differentiation relative to the rest of the genome, 373 \nsuggesting that the results from panels of neutral markers should be similar to that obtained with 374 \ngenome-wide data. In the absence of large genetic differences among spawning tributaries of Early 375 \nStuart sockeye, i t is possible that any phenotypic variation observed between streams could be 376 \nassociated with plasticity, environmental effects, or epigenetic differences between populations  377 \n(Lamka et al. 2022). The greatest differentiation identified was still much lower than the FST 0.01 cutoff 378 \nproposed as the lower limit of what is possible for genetic stock identification (GSI) (Araujo et al. 379 \n2014). Therefore, these results support previous work indicating an inability to discriminate between 380 \npopulations using GSI  (Beacham et al. 2004; Rondeau 2022) , and support the connectivity and 381 \ncharacteristics of a metapopulation (Bradford and Braun 2021), but do provide some evidence for slight 382 \nspatial differentiation that is worthwhile considering as not completely panmictic. Although low 383 \nsample size appears to have resulted in misplaced populations in the genetic dendrogram (most 384 \nnoticeable with sample size under n = 5), and therefore raises the potential concern that this could drive 385 \nthe non-zero FST observed between Driftwood and other more distant streams, the observation that  386 \nDriftwood (n = 7 ) compared to Dust Creek  (n = 10) , the more proximal sampling location,  had an 387 \nestimated zero differentiation indicates that the conclusion of no differentiation could be determined at 388 \nthis sample size. It should also be noted that the samples used to represent the Early Stuart sockeye in 389 \nthis study were from 2005 , and if large scale genetic changes occurred for salmon spawning in these 390 \ntributaries since 2005, these results may not reflect current day genetic signatures.  391 \n Further investigation of the extent of gene flow in this metapopulation could be conducted by 392 \nparentage-based tagging (i.e., PBT) or other tagging methods that track returning adults to determine 393 \nthe extent of flow between tributaries. Furthermore, epigenetic analyses could be conducted to 394 \ndetermine the level of differentiation epigenetically between streams with different environmental 395 \nparameters (Venney et al. 2021; Lamka et al. 2022).  396 \n 397 \nConclusions 398 \nIn the present study we made use of existing genomic resources to characterize upper Fraser River 399 \nsockeye salmon populations from waterbodies that flow into the Nechako (including Nadina, Stellako, 400 \nand Stuart River systems), the Bowron River, Quesnel and Horsefly, and the Chilcotin Watershed. This 401 \nanalysis would not have been possible without the generation and publication of large -scale, open-402 \nsource genomic resources and metadata. The finding of a major differentiating region on Chr18 403 \n(ancestral 15.2) between two conservation units (Early Stuart and Stuart-Summer) with differing run 404 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 14 \ntimings points to the potential for this region to contain adaptive variation underlying the run timing 405 \nphenotype, although interestingly the more unique run timing (i.e., Early Stuart)  was in the grouping 406 \nwith the putatively more ancestral form of the haplotype on Chr18. Convergence upon the Chr18 (15.2) 407 \nchromosome near the lrrc9-like gene fits with other work that has proposed that this region, in both 408 \nduplicate chromosomes, is a major control region of run timing, evolving independently in multiple 409 \nspecies. This region and the genes within it, including otx2, merit further investigation. The genome-410 \nwide data on the Early Stuart metapopulation supports previous work indicating differentiation being 411 \ntoo low for GSI, but  does identify a very minor increase in differentiation with increased geographic 412 \ndistance within the Early Stuart spawning tributaries . These results collectively provide new insights 413 \non upper Fraser River sockeye salmon that will be useful for conservation and management.  414 \n 415 \nAcknowledgements 416 \nThanks to Drs. Ben Koop , Eric Rondeau , and Kris Christensen  for discussion on the major 417 \ndifferentiation region, and to Linda Stevens of UFFCA for technical support on the project. Thanks to 418 \nthe UFFCA for supporting this work in the interests of Upper Fraser First Nations.  419 \n 420 \nFunding 421 \nFunding for this work was made available via the Pacific Salmon Strategy Initiative in support of the 422 \nTuzist'ol T'ah process. Tuzist'ol T'ah is a collaboration between the Upper Fraser Fisheries 423 \nConservation Alliance, Binche Whut’en, Nak’azdli Whut’en, Takla Nation, Tl’azt’en Nation, 424 \nYekooche Nation, Province of British Columbia, and Fisheries and Oceans Canada tasked with 425 \ndeveloping a recovery strategy for Early Stuart Sockeye.  426 \n 427 \nCompeting Interests 428 \nBJGS is affiliated with Sutherland Bioinformatics. The authors have no competing financial interests to 429 \ndeclare.  430 \n  431 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 15 \nData Availability 432 \nSNP data were downloaded from FigShare: https://doi.org/10.25387/g3.25705428.v1  433 \nThe following analytic repositories supported this analysis:  434 \nCode and README for project: https://github.com/bensutherland/ms_oner_estu  435 \nPopulation genetic functions: https://github.com/bensutherland/simple_pop_stats  436 \n  437 \nAdditional Materials 438 \nA Supplemental Results section is provided with supplemental figures and tables.  439 \nAdditional File S1. Genotypes of top differentiated loci in major differentiation region.  440 \nAdditional File S2. Annotated gene content in major differentiation region.   441 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 16 \nReferences 442 \n 443 \nAkopyan, M., A. Tigano, A. Jacobs, A.P. Wilder, and N.O. Therkildsen, 2025 Genetic differentiation is 444 \nconstrained to chromosomal inversions and putative centromeres in locally adapted populations 445 \nwith higher gene flow. Molecular Biology and Evolution. 446 \nAraujo, H.A., J.R. Candy, T.D. Beacham, B. White, and C. Wallace, 2014 Advantages and challenges of 447 \ngenetic stock identification in fish stocks with low genetic resolution. Transactions of the 448 \nAmerican Fisheries Society 143 (2):479-488. 449 \nBaird, N.A., P.D. Etter, T.S. Atwood, M.C. Currey, A.L. Shiver et al., 2008 Rapid SNP discovery and 450 \ngenetic mapping using sequenced RAD markers. PLOS ONE 3 (10):e3376. 451 \nBando, H., P. Gergics, B.L. Bohnsack, K.P. Toolan, C.E. Richter et al., 2020 Otx2b mutant zebrafish have 452 \npituitary, eye and mandible defects that model mammalian disease. Human Molecular Genetics 453 \n29 (10):1648-1657. 454 \nBarry, P., N. Howe, G.L. Owens, D. Baetscher, K. D’Amelio et al., 2025 Diversification of large-effect 455 \nloci in a duplicated genomic region leads to complex phenotypes. 456 \nbioRxiv:2024.2003.2030.587279. 457 \nBarry, P.D., D.A. Tallmon, N.S. Howe, D.S. Baetscher, K.L. D’Amelio et al., 2024 A major effect locus 458 \ninvolved in migration timing is shared by pink and sockeye salmon. 459 \nbioRxiv:2024.2003.2030.587279. 460 \nBeacham, T.D., M. Lapointe, J.R. Candy, B. McIntosh, C. MacConnachie et al., 2004 Stock identification 461 \nof Fraser River sockeye salmon using microsatellites and major histocompatibility complex 462 \nvariation. Transactions of the American Fisheries Society 133 (5):1117-1137. 463 \nBeacham, T.D., and R.E. Withler, 2017 Population structure of sea-type and lake-type sockeye salmon 464 \nand kokanee in the Fraser River and Columbia River drainages. PLOS ONE 12 (9):e0183713. 465 \nBeby, F., and T. Lamonerie, 2013 The homeobox gene Otx2 in development and disease. Experimental 466 \nEye Research 111:9-16. 467 \nBemmels, J.B., S. Starko, B.L. Weigel, K. Hirabayashi, A. Pinch et al., 2025 Population genomics reveals 468 \nstrong impacts of genetic drift without purging and guides conservation of bull and giant kelp. 469 \nCurrent Biology 35 (3):688-698.e688. 470 \nBett, N.N., S.G. Hinch, K.H. Kaukinen, S. Li, and K.M. Miller, 2018 Olfactory gene expression in 471 \nmigrating adult sockeye salmon Oncorhynchus nerka. Journal of Fish Biology 92 (6):2029-2038. 472 \nBradford, M.J., and D.C. Braun, 2021 Regional and local effects drive changes in spawning stream 473 \noccupancy in a sockeye salmon metapopulation. Canadian Journal of Fisheries and Aquatic 474 \nSciences 78 (8):1084-1095. 475 \nChristensen, K.A., A.-M. Flores, D. Sakhrani, C.A. Biagi, R.H. Devlin et al., 2024 Revealing the 476 \nevolutionary history and contemporary population structure of Pacific salmon in the Fraser River 477 \nthrough genome resequencing. G3 Genes|Genomes|Genetics 14 (10). 478 \nChristensen, K.A., E.B. Rondeau, D.R. Minkley, D. Sakhrani, C.A. Biagi et al., 2020 The sockeye salmon 479 \ngenome, transcriptome, and analyses identifying population defining regions of the genome. 480 \nPLOS ONE 15 (10):e0240935. 481 \nCOSEWIC, 2017 COSEWIC assessment and status report on the sockeye salmon Oncorhynchus nerka, 482 \n24 Designatable Units in the Fraser River Drainage Basin, in Canada, pp. xli + 179, edited by 483 \nCommittee on the Status of Endangered Wildlife in Canada. 484 \nCrossin, G.T., S.G. Hinch, A.P. Farrell, D.A. Higgs, A.G. Lotto et al., 2004 Energetics and morphology of 485 \nsockeye salmon: effects of upriver migratory distance and elevation. Journal of Fish Biology 65 486 \n(3):788-810. 487 \nDanecek, P., A. Auton, G. Abecasis, C.A. Albers, E. Banks et al., 2011 The variant call format and 488 \nVCFtools. Bioinformatics 27 (15):2156-2158. 489 \nDanecek, P., J.K. Bonfield, J. Liddle, J. Marshall, V . Ohan et al., 2021 Twelve years of SAMtools and 490 \nBCFtools. GigaScience 10 (2). 491 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 17 \nEliason, E.J., T.D. Clark, M.J. Hague, L.M. Hanson, Z.S. Gallagher et al., 2011 Differences in thermal 492 \ntolerance among sockeye salmon populations. Science 332 (6025):109-112. 493 \nGilhousen, P., 1980 Energy sources and expenditures in Fraser River sockeye salmon during their 494 \nspawning migration. Int. Pac. Salmon Fish. Comm. Bull. 22:1-80. 495 \nHinch, S.G., and P.S. Rand, 1998 Swim speeds and energy use of upriver-migrating sockeye salmon 496 \n(Oncorhynchus nerka): role of local environment and fish characteristics. Canadian Journal of 497 \nFisheries and Aquatic Sciences 55 (8):1821-1831. 498 \nIdler, D., and W. Clemens, 1959 The energy expenditures of Fraser River sockeye salmon during the 499 \nspawning migration to Chilko and Stuart Lakes in International Pacific Salmon Fisheries 500 \nCommission Progress Report. International Pacific Salmon Fisheries Commission, New 501 \nWestminster, BC, Canada. 502 \nKnaus, B.J., and N.J. Grünwald, 2017 vcfr: a package to manipulate and visualize variant call format data 503 \nin R. Molecular Ecology Resources 17 (1):44-53. 504 \nLamka, G.F., A.M. Harder, M. Sundaram, T.S. Schwartz, M.R. Christie et al., 2022 Epigenetics in 505 \necology, evolution, and conservation. Frontiers in Ecology and Evolution Vo l u m e  1 0  - 2022. 506 \nLi, H., 2013 Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM, pp. 507 \narXiv:1303.3997. 508 \nMartin, M., 2011 Cutadapt removes adapter sequences from high-throughput sequencing reads. 509 \nEMBnet.journal 17 (1):3. 510 \nMeek, M.H., and W.A. Larson, 2019 The future is now: Amplicon sequencing and sequence capture usher 511 \nin the conservation genomics era. Molecular Ecology Resources 19 (4):795-803. 512 \nNormandeau, E., M. de Ronne, and D. Torkamaneh, 2023 SNPLift: Fast and accurate conversion of 513 \ngenetic variant coordinates across genome assemblies. bioRxiv:2023.2006.2013.544861. 514 \nOnuma, T.A., S. Sato, H. Katsumata, K. Makino, W. Hu et al., 2009 Activity of the pituitary–gonadal axis 515 \nis increased prior to the onset of spawning migration of chum salmon. Journal of Experimental 516 \nBiology 212 (1):56-70. 517 \nParadis, E., 2010 pegas: an R package for population genetics with an integrated–modular approach. 518 \nBioinformatics 26 (3):419-420. 519 \nParia, S.S., S.R. Rahman, and K. Adhikari, 2022 fastman: A fast algorithm for visualizing GWAS results 520 \nusing Manhattan and Q-Q plots. bioRxiv:2022.2004.2019.488738. 521 \nPeterson, B.K., J.N. Weber, E.H. Kay, H.S. Fisher, and H.E. Hoekstra, 2012 Double digest RADseq: an 522 \ninexpensive method for de novo SNP discovery and genotyping in model and non-model species. 523 \nPLOS ONE 7 (5):e37135. 524 \nR Core Team, 2025 R: A Language and Environment for Statistical Computing. R Foundation for 525 \nStatistical Computing, Vienna, Austria. 526 \nRand, P.S., H.S. G., M. J., F.M.G. G., M.M. J. et al., 2006 Effects of river discharge, temperature, and 527 \nfuture climates on energetics and mortality of adult migrating Fraser River sockeye salmon. 528 \nTransactions of the American Fisheries Society 135 (3):655-667. 529 \nRobinson, J.T., H. Thorvaldsdóttir, W. Winckler, M. Guttman, E.S. Lander et al., 2011 Integrative 530 \ngenomics viewer. Nature Biotechnology 29 (1):24-26. 531 \nRondeau, E.B., 2022 Sockeye salmon SNP panel genetic baseline for the Fraser River, Year 2 in Southern 532 \nEndowment Fund Annual Reports, edited by Pacific Salmon Commission. 533 \nRondeau, E.B., D.R. Minkley, J.S. Leong, A.M. Messmer, J.R. Jantzen et al., 2014 The genome and 534 \nlinkage map of the northern pike (Esox lucius): conserved synteny revealed between the salmonid 535 \nsister group and the Neoteleostei. PLoS One 9 (7):e102089. 536 \nSutherland, B.J.G., T. Gosselin, E. Normandeau, M. Lamothe, N. Isabel et al., 2016 Salmonid 537 \nchromosome evolution as revealed by a novel method for comparing RADseq linkage maps. 538 \nGenome Biology and Evolution 8 (12):3600-3617. 539 \nSutherland, B.J.G., C. Rico, C. Audet, and L. Bernatchez, 2017 Sex chromosome evolution, 540 \nheterochiasmy, and physiological QTL in the salmonid brook charr Salvelinus fontinalis. G3-541 \nGenes Genomes Genetics 7 (8):2749-2762. 542 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 18 \nTigano, A., and M.A. Russello, 2022 The genomic basis of reproductive and migratory behaviour in a 543 \npolymorphic salmonid. Molecular Ecology 31 (24):6588-6604. 544 \nUeda, H., 2011 Physiological mechanism of homing migration in Pacific salmon from behavioral to 545 \nmolecular biological approaches. General and Comparative Endocrinology 170 (2):222-232. 546 \nVeilleux, H.D., L. Van Herwerden, N.J. Cole, E.K. Don, C. De Santis et al., 2013 Otx2 expression and 547 \nimplications for olfactory imprinting in the anemonefish, Amphiprion percula. Biology Open 2 548 \n(9):907-915. 549 \nVenney, C.J., B.J.G. Sutherland, T.D. Beacham, and D.D. Heath, 2021 Population differences in Chinook 550 \nsalmon (Oncorhynchus tshawytscha) DNA methylation: Genetic drift and environmental factors. 551 \nEcology and Evolution 11 (11):6846-6861. 552 \nWaples, R.S., R.G. Gustafson, L.A. Weitkamp, J.M. Myers, O.W. Jjohnson et al., 2001 Characterizing 553 \ndiversity in salmon from the Pacific Northwest. Journal of Fish Biology 59 (sA):1-41. 554 \nWeir, B.S., and C.C. Cockerham, 1984 Estimating F-statistics for the analysis of population structure. 555 \nEvolution 38 (6):1358-1370. 556 \nWellenreuther, M., and L. Bernatchez, 2018 Eco-evolutionary genomics of chromosomal inversions. 557 \nTrends in Ecology & Evolution 33 (6):427-440. 558 \nWright, M.J., M. Hurson, K.A. Robinson, D.A. Patterson, and J.G. Venditti, 2025 A typology of potential 559 \nhydraulic barriers to adult salmon migration in a bedrock river. Canadian Journal of Fisheries 560 \nand Aquatic Sciences 82:1-19. 561 \n  562 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 19 \nFigures 563 \n 564 \n 565 \nFigure 1. (A) All upper Fraser River samples clustered by principal components analysis (PCA) using 566 \nMAF and LD -filtered SNPs (n = 627,769) shows main groupings of study, including the Nechako 567 \nWatershed (negative PC1), the Bowron River (positive PC1), the Chilcotin Watershed (negative PC2), 568 \nand Horsefly and Quesnel regions (positive PC1 and PC2). (B) PCA with only the populations from 569 \nthe Nechako Watershed shows Early Stuart grouping separately from Stuart-Summer, which were more 570 \ngenetically proximal to populations from the Nadina River and Stellako River.  571 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 20 \n 572 \n 573 \nFigure 2. (A) Discriminant analysis of principal components (DAPC) analysis of populations from the 574 \nNechako Watershed including Early Stuart, Stuart -Summer, Nadina River, and Stellako River  shows 575 \nseparation across discriminant function 1 ( DF1) from the Early Stuart and Stuart -Summer (and 576 \nStellako), and Nadina River grouping separately. (B) The loadings of SNP loci contributing to  the 577 \nseparation on DF1 indicate a major contributing genomic region on Chr18.   578 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 21 \n 579 \nFigure 3. (A) Genetic differentiation by FST within the Nechako Watershed for Chr18 between the 580 \nEarly Stuart and Stuart summer populations. (B) Heatmap of the differentiated genomic region based 581 \non allelic dosage of alternate alleles (0, 1, 2) coloured as grey, yellow, and blue, respectively. All 582 \nsamples from the study (n = 210) were included and allowed to cluster based on genotypes. Samples 583 \nare coloured on the vertical axis based on the source collection site as indicated in the legend.    584 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 22 \n 585 \nFigure 4. Disciminant analysis of principal components (DAPC) of collections from Early Stuart 586 \nspawning tributaries that contained at least seven samples each.   587 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 23 \nTables 588 \nTable 1. Samples available for the analysis from Christensen et al. (2024) genotyped by whole-genome 589 \nresequencing. Collection names and dates were provided in sample metadata from the original study, 590 \nfull names were determined from BC Geographical Names  (Government of BC ), and run -timing 591 \ndesignations were obtained from Rondeau (2022).   592 \n 593 \nRegion Run-Timing Collection Full Name Sample \nsize \nYear(s) \nsampled \nStuart Early-Stuart Bivouac Bivouac Cr. 10 2005 \n  Driftwood Driftwood R. 7  2005 \n  Dust Dust Cr. 10 2005 \n  Felix Sidney (Felix) Cr. 5 2005 \n  Paula Paula Cr. 10 2005 \n  Takla Takla Lk. 4 unkn. \n Summer Kuzkwa Kuzkwa R. 9 2001 \n  Middle Middle R. 7 2001 \n  Pinchi Pinchi Cr. 4 2005 \n  Tachie Tachie R. 11 2012, unkn. \nNadina/Francois Early summer Nadina Nadina R. 9 2000 \nFrancois/Fraser Summer Stellako Stellako R. 10 2011 \nBowron Early summer Bowron Bowron R. 10 2001 \nQuesnel Summer BlueLead Blue Lead Cr. 5 2001 \n  McKinley McKinley Cr. 9 2001 \n  Mitchell Mitchell Bay 8 2001 \n  Wasko Wasko Cr. 5 2001 \n  Horsefly* Horsefly R. and \nLk. \n24 2001, unkn \n  Quesnel Quesnel R. and \nLk. \n8 2013 \nChilcotin Summer Chilko* Chilko R. and Lk. 35 2001, 2008, \nunkn \n Early Summer Taseko Taseko R. 10 2011 \n  TOTAL  210  \n*includes various sub-naming  594 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint \n\nv.0.1.2 \n 24 \nTable 2. (A) Average FST between Early Stuart collections showing non -weighted estimate in the 595 \nbottom and weighted estimate in the top section; or (B) 95% confidence interval of FST showing the 596 \nupper limit in the top and lower limit in the bottom.  597 \n 598 \n(A)  599 \n \nBivouac Driftwood Dust Paula \nBivouac NA 0.0056 0.0010 0.0008 \nDriftwood 0.0019 NA 0.0022 0.0046 \nDust -0.0011 -0.0009 NA 0.0016 \nPaula -0.0011 0.0010 -0.0006 NA \n 600 \n(B)  601 \n \nBivouac Driftwood Dust Paula \nBivouac NA 0.0021 -0.0009 -0.0010 \nDriftwood 0.0017 NA -0.0007 0.0012 \nDust -0.0013 -0.0011 NA -0.0004 \nPaula -0.0013 0.0008 -0.0007 NA \n 602 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted June 7, 2025. ; https://doi.org/10.1101/2025.06.04.657877doi: bioRxiv preprint","source_license":"CC-BY-4.0","license_restricted":false}