A comparison of biallelic markers and microsatellites for the estimation of population and conservation genetic parameters in Atlantic salmon (Salmo salar)

Biallelic markers such as single nucleotide polymorphisms (SNPs) and insertion/deletion polymorphisms have become increasingly popular markers for various population genetics applications. However, the effort required to develop biallelic markers in nonmodel organisms is still substantial. In this study, we compared the estimation of various population genetic parameters (genetic divergence and structuring, isolation-by-distance, genetic diversity) using a limited number of biallelic markers (in total 7 loci) to those estimated with 14 microsatellite loci in 21 Atlantic salmon (Salmo salar) populations from northern Europe. Pairwise F-ST values were significantly correlated between biallelic loci and microsatellite datasets, as was overall heterozygosity when both anadromous and nonanadromous populations were analyzed together. However, when the anadromous and nonanadromous samples were analyzed separately, only genetic divergence correlations remained significant. Biallelic markers alone were not sufficient for reliable neighbor-joining clustering of populations but gave highly similar isolation-by-distance signals when compared with microsatellites. Finally, although several population prioritization measures for conservation exhibited significant correlation between different marker types, the specific populations highlighted as being most valuable for conservation purposes varied depending on the marker type and conservation criteria applied. This study demonstrates that a relatively small set of biallelic markers can be sufficient for obtaining concordant results in most of the analyses compared with microsatellites, although estimates of genetic distance are generally more concordant than estimates of genetic diversity. This suggests that a relatively small number of biallelic markers can provide useful information for various population genetic applications. However, we emphasize that the use of much higher number of loci is preferable, especially when the genetic differences between populations are subtle or individual multilocus genotype-based analyses are to be performed.