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Oncorhynchus Mykiss) Growth Genes Are Implicated in The Evolutionary Divergence of Sympatric Piscivorous and Insectivorous Rainbow Trout (Oncorhynchus Mykiss) Jared A. Grummer ( [email protected] ) University of British Columbia Michael Whitlock University of British Columbia Patricia Schulte University of British Columbia Eric Taylor University of British Columbia Research Article Keywords: genome scan, small-effect loci, FST, GO analysis, rainbow trout, ecotype Posted Date: February 5th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-157772/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Version of Record: A version of this preprint was published at BMC Ecology and Evolution on April 22nd, 2021. See the published version at https://doi.org/10.1186/s12862-021-01795-9. RH: GENOMIC DIVERGENCE OF SYMPATRIC TROUT ECOTYPES Growth genes are implicated in the evolutionary divergence of sympatric piscivorous and insectivorous rainbow trout (Oncorhynchus mykiss) Jared A. Grummer1, Michael Whitlock1, Patricia M. Schulte1, and Eric B. Taylor1,2 1Department of Zoology and Biodiversity Research Centre, University of British Columbia, 6270 University Blvd., Vancouver, BC V6T 1Z4, Canada 2Beaty Biodiversity Museum, University of British Columbia, 6270 University Blvd., Vancouver, BC V6T 1Z4, Canada Corresponding author: Jared A. Grummer; E-mail: [email protected] 1 1 Abstract.— 2 Background: Identifying ecologically significant phenotypic traits and the genomic 3 mechanisms that underly them are crucial steps in understanding the traits associated with 4 population divergence. We used genome-wide data to identify genomic regions associated 5 with a key trait that distinguishes two ecotypes of rainbow trout (Oncorhynchus mykiss)– 6 insectivores and piscivores – that coexist in Kootenay Lake, southeastern British Columbia, 7 for the non-breeding portion of the year. “Gerrards” are large-bodied (breeding maturity at 8 >60cm) piscivores that spawn ∼50km north of Kootenay Lake in the Lardeau River, in 9 contrast to the insectivorous populations that are on average smaller in body size, mainly 10 forage on aquatic insects, and spawn in tributaries immediately surrounding Kootenay 11 Lake. We used pool-seq data covering ∼60% of the genome to assess the level of genomic 12 divergence between ecotypes, test for genotype-phenotype associations, and identify loci 13 that may play functional or selective roles in their divergence. 14 Results: Analysis of nearly seven million SNPs provided a genome-wide mean FST 15 estimate of 0.18, indicating a high level of reproductive isolation between populations. The 16 window-based FST analysis did not reveal “islands” of genomic differentiation; however, the 17 window with highest FST estimate did include a gene associated with insulin secretion. 18 Although we explored the use of the “Local score” approach to identify genomic outlier 19 regions, this method was ultimately not used because simulations revealed a high false 20 discovery rate (∼20%). Gene Ontology (GO) analysis identified several growth processes as 21 enriched in genes occurring in the ∼200 most divergent genomic windows, indicating the 22 importance of genetically-based growth and growth-related metabolic functions in the 23 divergence of these ecotypes. 24 Conclusions: In spite of their sympatric coexistence, a high degree of genomic 25 differentiation separates the populations of piscivores and insectivores, indicating little to 26 no contemporary genetic exchange between ecotypes. Our results further indicate that the 2 27 large body piscivorous phenotype is likely not due to one or a few loci of large effect, rather 28 it may be controlled by several loci of small effect, thus highlighting the power of 29 whole-genome low-coverage sequencing in phenotypic association studies. 30 (Keywords: genome scan, small-effect loci, FST , GO analysis, rainbow trout, ecotype) 3 31 Understanding the divergence of populations and the mechanisms responsible for it 32 are important for the fields of speciation, macroevolution, ecology, and conservation (Coyne 33 and Orr 2004). In many cases, population-level divergences are associated with character 34 displacement and phenotypic divergence of sympatric forms (e.g., Kitano et al. 2007). 35 Recent advancements in sequencing technologies have enabled investigations into the 36 genomics underlying traits associated with phenotypic divergences in non-model systems. 37 In some cases, few highly differentiated loci of large effect can be responsible for 38 population-level phenotypic or behavioural divergence in spite of the majority of genomic 39 differentiation being very low between populations as the result of either recent divergence 40 and/or ongoing gene flow (e.g., Heliconius butterflies; Supple et al. 2013, Morris et al. 41 2019). 42 In fishes, this is the case for the phenotypic divergence of two forms of brown trout 43 (Salmo trutta) – piscivores and insectivores – where Jacobs et al. (2018) identified ∼10 44 genomic outlier regions containing several genes involved in development, growth, and gene 45 expression and regulation. In Atlantic cod (Gadus morhua), a ∼17 MB (megabase) region 46 containing two chromosomal inversions is associated with population divergence based on 47 migration phenotype (Kirubakaran et al. 2016). Additionally, in Pacific salmon (genus 48 Oncorhynchus), one small genomic region has been shown to control a vital phenotype for 49 the natural history of two species – adult migration timing (Prince et al. 2017). 50 Theory predicts that the distribution of allelic effects on quantitative traits should 51 be nearly exponential, where few loci have large effects and explain most of the variance in 52 traits, but many loci with smaller effects explain the remaining variation in the trait 53 (Robertson 1967; Mackay 2001). Across taxa, several phenotypes are explained by many 54 loci of small effect. For instance, hundreds of genetic variants explain only ∼10% of the 55 phenotypic variation in human height (Allen et al. 2010). And a genome-wide analysis of 56 50,000 SNPs (single nucleotide polymorphism) in the collared flycatcher (Ficedula 4 57 albicollis) revealed that no SNPs were significantly associated with forehead patch size, a 58 sexually selected trait (Kardos et al. 2016). Furthermore, Kardos et al. (2016) report that 59 thousands of individuals and near-complete genome sequencing are necessary to reliably 60 detect large-effect loci. 61 Identifying the genomic regions underlying ecological forms can provide insights into 62 population divergence, especially with regards to the insectivorous–piscivorous divergence 63 that has been seen in many systems. Arctic charr (Salvelinus alpinus) have repeatedly 64 evolved sympatric forms of zooplanktivores and piscivores on multiple continents (Skúlason 65 1999; Jonsson and Jonsson 2001), including Iceland’s Lake Thingvallavatn (e.g., Skúlason 66 et al. 1993). Additionally, a large and piscivorous form of brown trout (“Ferox” trout; 67 Salmo trutta) exists in Loch Rannoch, Scotland (Thorne et al. 2016). Although individuals 68 usually breed with others of the same morph (assortative mating; Jonsson and Jonsson 69 2001) thereby leading to reproductive isolation between populations, evidence from Lake 70 Thingvallavatn suggests that the piscivorous morph may not be genetically distinguishable 71 from the other morphs (Guðbrandsson et al. 2019). It remains to be seen whether these 72 morphs a) have a genetic basis, b) share a genetic basis in independent waterbodies, and c) 73 are controlled by few loci of large-effect or many loci of small-effect. 74 We assessed whether particular genomic regions, and their putative functions, were 75 associated with the phenotypic differentiation of two sympatric populations of rainbow 76 trout in Kootenay Lake of southeastern British Columbia (Taylor et al. 2019). Phylogenetic 77 analyses suggest that O. mykiss diverged from other Oncorhynchus species (e.g., cutthroat 78 trout and Pacific salmon) in the early Miocene, ∼20 million years ago (Lecaudey et al. 79 2018). Oncorhynchus mykiss spans a broad latitudinal range in western North America 80 from central Mexico to Alaska and likely originated in the south and expanded northward 81 over time (Hendrickson et al. 2002; Penaluna et al. 2016). Fish populations in most of 82 Canada were displaced by Pleistocene glaciations and current populations are therefore 5 83 assumed to be the results of postglacial range expansions in the past ∼15,000 years 84 (Schluter 1996; Taylor 1999). A variety of divergent life-history patterns can be found in 85 populations across the native range of O. mykiss, including migration patterns (resident vs. 86 anadromous), habitat type (lake vs. stream), and diet (piscivory vs. insectivory) (Keeley 87 et al. 2007). While genomic regions have been found that are associated with migration and 88 habitat type (Hess et al. 2016; Prince et al. 2017), little is known about the evolutionary 89 mechanisms promoting divergence of piscivorous and insectivorous O. mykiss populations. 90 In Kootenay Lake, a large piscivorous form (often > 60cm and 5kg, but up to 12kg), 91 locally known as “Gerrards”, has an adult dietary specialization on Kokanee salmon – 92 small, land-locked sockeye salmon (O. nerka) – and spawns near the abandoned town site 93 Gerrard (thus the name “Gerrards”) on the Lardeau River that drains into the north arm of 94 Kootenay Lake (Northcote 1973; Irvine 1978); the size of this population
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