Patterns of extensive genetic differentiation and variation among European harbor seals (Phoca vitulina vitulina) revealed using microsatellite DNA polymorphisms - PubMed (original) (raw)

Comparative Study

Patterns of extensive genetic differentiation and variation among European harbor seals (Phoca vitulina vitulina) revealed using microsatellite DNA polymorphisms

S J Goodman. Mol Biol Evol. 1998 Feb.

Abstract

The harbor seal (Phoca vitulina) has the most extensive distribution of any phocid seal species. An analysis of population structure in this species across its European range was made using 7 phocid derived microsatellites in a sample of 1,029 individuals from 12 separate geographic areas. Despite the species potential for long-distance movement, significant genetic differentiation between areas was observed using an unbiased estimator of RST. Six distinct population units were identified: Ireland-Scotland, English east coast, Waddensea, western Scandinavia (Norway-Kattegat-Skagerrak-west Baltic), east Baltic, and Iceland. Little local substructuring is present along coastlines with a continuous distribution of breeding animals, but differentiation does increase with geographic distance. The degree of differentiation is greater over equivalent distances where the distribution is discontinuous, such as along coasts where breeding colonies are separated by large distances or by stretches of open sea. Patterns of population differentiation derived from microsatellites are very similar to those obtained from previous mitochondrial DNA analysis and suggest that philopatry in harbor seals operates over 300-500 km. In Europe, harbor seals have experienced a complex demographic history and patterns of population structure are likely to have been affected by natural environmental influences such as Pleistocene glaciations and epizootics. Comparison of Nm values from an unbiased estimator of RST, GST, and theta are consistent and, in some cases, may indicate populations where conditions deviate from the expectations of the RST model.

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