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Investigating the morphological and genetic divergence of arctic char (Salvelinus alpinus) populations in lakes of arctic Alaska

Citation

Klobucar, Stephen L. et al. (2021), Investigating the morphological and genetic divergence of arctic char (Salvelinus alpinus) populations in lakes of arctic Alaska, Dryad, Dataset, https://doi.org/10.5061/dryad.1vhhmgqrs

Abstract

Polymorphism facilitates coexistence of divergent morphs (e.g., phenotypes) of the same species by minimizing intraspecific competition, especially when resources are limiting. Arctic char (Salvelinus sp.) are a Holarctic fish often forming morphologically, and sometimes genetically, divergent morphs. In this study, we assessed the morphological and genetic diversity and divergence of 263 individuals from seven populations of arctic char with varying length-frequency distributions across two distinct groups of lakes in northern Alaska. Despite close geographic proximity, each lake group occurs on landscapes with different glacial ages and surface water connectivity, and thus were likely colonized by fishes at different times. Across lakes, a continuum of physical (e.g., lake area, maximum depth) and biological characteristics (e.g., primary productivity, fish density) exists, likely contributing to characteristics of present-day char populations. Although some lakes exhibit bimodal size distributions, using model-based clustering of morphometric traits corrected for allometry, we did not detect morphological differences within and across char populations. Genomic analyses using 15,934 SNPs obtained from genotyping-by-sequencing demonstrated differences among lake groups related to historical biogeography, but within lake groups and within individual lakes, genetic differentiation was not related to total body length. We used PERMANOVA to identify environmental and biological factors related to observed char size structure. Significant predictors included water transparency (i.e., a primary productivity proxy), char density (fish·ha-1), and lake group. Larger char occurred in lakes with greater primary production and lower char densities, suggesting less intraspecific competition and resource limitation. Thus, char populations in more productive and connected lakes may prove more stable to environmental changes, relative to food-limited and closed lakes, if lake productivity increases concomitantly. Our findings provide some of the first descriptions of genomic characteristics of char populations in arctic Alaska, and offer important consideration for the persistence of these populations for subsistence and conservation.

Methods

Arctic char were collected from lakes in northern Alaska, DNA was extracted, genotyping-by-sequencing libraries were prepared, and libraries were sequenced as explained in Klobucar et al. 2021, Ecology & Evolution. Raw fastq reads (archived in NCBI BioProject PRJNA687211, https://www.ncbi.nlm.nih.gov/bioproject/?term=prjna687211) were aligned to the Atlantic salmon genome (NCBI BioProject PRJNA287919; Lien et al., 2016) using bwa, and variants were called using samtools and bcftools. These variants were then filtered to retain sites with < 50% missing data, minor allele frequency > 0.01, and only one site per locus using vcftools, resulting in the file variants_nolowcov10k_miss0.5_maf0.01.vcf.gz. The R script for analyzing this VCF is char_PCA_from_covariance.R. Additionally, variants were called on (1) only individuals from the LTER lakes, and (2) only individuals from the FOG lakes, and filtered as described. In addition, scaffolds containing significant sex-associated loci were removed, resulting in the files variants_LTER_nolowcov10k_miss0.5_maf0.01_noSex.vcf.gz and variants_FOG_nolowcov10k_miss0.5_maf0.01_noSex.vcf.gz. These two files were analyzed in R using the scripts char_PCA_from_covariance_LTER_clean.R and char_PCA_from_covariance_FOG_clean.R, respectively.

Usage Notes

The metadata corresponding to the individuals in these VCFs can be found in AC_GBSdata_Master_Clean.csv.

Funding

National Science Foundation, Award: DEB-1026843

National Science Foundation, Award: DEB-1637459

National Science Foundation, Award: DEB-1556963