Genetic diversity insights from population genomics and machine learning tools for Nordic Arctic charr (Salvelinus alpinus) populations

Arctic charr ( Salvelinus alpinus ) is a salmonid species of high ecological and commercial value in the Holarctic region. Nevertheless, more information is needed about its underlying genetic diversity and population structure in the Nordics, especially regarding farmed populations. High-throughput sequencing was applied in three Arctic charr populations of anadromous or landlocked origin from Finland, Norway and Sweden. More specifically, the animals from the Swedish and Norwegian populations originated from a major egg supplier and producer, respectively. Furthermore, in the case of the Finnish population, the sampled animals originated from the only active conservation program for Arctic charr in the country with a potential interest in farming. Using double-digest restriction site-associated DNA sequencing (ddRAD-seq) on more than 500 fish, over 2000 single nucleotide polymorphisms (SNPs), both in the form of individual SNPs and as read haplotypes, were used to study the genetic diversity and structure of those populations. Genetic diversity metrics were similar between the Norwegian and the Swedish populations. However, substantially lower (40–50 %) genetic diversity was found in the Finnish population. Moreover, considerable genetic differentiation was implied between the studied populations as the mean fixation index (F ST ) was above 0.1 in all pairwise comparisons. All populations were easily discernible through either principal component analysis (PCA) or discriminant analysis of principal components (DAPC). In addition, unsupervised machine learning models such as K-means, Gaussian and Bayesian Gaussian mixtures were assessed for their ability to detect genetic clusters. A preceding dimensionality reduction step by PCA resulted in all three models, suggesting that the most probable number of clusters was three. Overall, our study affirmed the utility of the developed ddRAD-seq genotyping method and unveiled the genetic structure of the studied populations, both of which could contribute to their more efficient management by captive breeding. • First comparative high throughput genotyping study on the genetic diversity status of Nordic farmed Arctic charr • The three populations had a distinct genomic profile. • Limited genetic diversity was found in the case of the Finnish population. • Genetic diversity insights using SNP read-haplotypes. • Assessment of machine learning models in identifying genetic clusters using genomic information.

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Publication Details

Journal
Aquaculture Reports
Published
2024-11-07
DOI
https://doi.org/10.1016/j.aqrep.2024.102495
Citations
1
Primary Topic
Genetic and phenotypic traits in livestock
Type
article
Field-Weighted Citation Impact
0.55

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article

Genetic diversity insights from population genomics and machine learning tools for Nordic Arctic charr (Salvelinus alpinus) populations

Matti Janhunen, Fotis Pappas, Christos Palaiokostas, J. Beirão et al.
1 citations
Aquaculture Reports
Genetic and phenotypic traits in livestock
0.55
article

Genetic diversity insights from population genomics and machine learning tools for Nordic Arctic charr (Salvelinus alpinus) populations

Matti Janhunen, Fotis Pappas, Christos Palaiokostas, J. Beirão, Ørjan Hagen, Henrik Jeuthe, Khrystyna Kurta, Antti Kause
article en
1 citations

Abstract

Arctic charr ( Salvelinus alpinus ) is a salmonid species of high ecological and commercial value in the Holarctic region. Nevertheless, more information is needed about its underlying genetic diversity and population structure in the Nordics, especially regarding farmed populations. High-throughput sequencing was applied in three Arctic charr populations of anadromous or landlocked origin from Finland, Norway and Sweden. More specifically, the animals from the Swedish and Norwegian populations originated from a major egg supplier and producer, respectively. Furthermore, in the case of the Finnish population, the sampled animals originated from the only active conservation program for Arctic charr in the country with a potential interest in farming. Using double-digest restriction site-associated DNA sequencing (ddRAD-seq) on more than 500 fish, over 2000 single nucleotide polymorphisms (SNPs), both in the form of individual SNPs and as read haplotypes, were used to study the genetic diversity and structure of those populations. Genetic diversity metrics were similar between the Norwegian and the Swedish populations. However, substantially lower (40–50 %) genetic diversity was found in the Finnish population. Moreover, considerable genetic differentiation was implied between the studied populations as the mean fixation index (F ST ) was above 0.1 in all pairwise comparisons. All populations were easily discernible through either principal component analysis (PCA) or discriminant analysis of principal components (DAPC). In addition, unsupervised machine learning models such as K-means, Gaussian and Bayesian Gaussian mixtures were assessed for their ability to detect genetic clusters. A preceding dimensionality reduction step by PCA resulted in all three models, suggesting that the most probable number of clusters was three. Overall, our study affirmed the utility of the developed ddRAD-seq genotyping method and unveiled the genetic structure of the studied populations, both of which could contribute to their more efficient management by captive breeding. • First comparative high throughput genotyping study on the genetic diversity status of Nordic farmed Arctic charr • The three populations had a distinct genomic profile. • Limited genetic diversity was found in the case of the Finnish population. • Genetic diversity insights using SNP read-haplotypes. • Assessment of machine learning models in identifying genetic clusters using genomic information.

Aquaculture ReportsVol. 39
Nord University (NO), Swedish University of Agricultural Sciences (SE), Natural Resources Institute Finland (FI)
Knut och Alice Wallenbergs Stiftelse, Vetenskapsrådet, Science for Life Laboratory
Openalex Percentile: Top 25%
Genetic and phenotypic traits in livestock
0.55
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