Data from: Genetic architecture in a marine hybrid zone: comparing outlier detection and genomic clines analysis in the bivalve Macoma balthica

• Main Authors: Luttikhuizen, Pieternella C., Drent, Jan, Peijnenburg, Katja T. C. A., van der Veer, Henk W., Johannesson, Kerstin
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: 2012
• Subjects: Genomics/Proteomics; Hybridization; Population Genetics - Empirical; Speciation; Invertebrates; Arctic; Kattegat; North Atlantic
• Online Access: http://hdl.handle.net/10255/dryad.38467; https://doi.org/10.5061/dryad.70np2513

The role of natural selection in speciation has received increasing attention and support in recent years. Different types of approaches have been developed that can detect genomic regions influenced by selection. Here we address the question whether two highly different methods - Fst outlier analysis and admixture analysis - detect largely the same set of non-neutral genomic elements or, instead, complementary sets. We study genetic architecture in a natural secondary contact zone where extensive admixture occurs. The marine bivalves Macoma balthica rubra and M. b. balthica descend from two independent trans-Arctic invasions of the north Atlantic and hybridize extensively where they meet, for example in the Kattegat - Danish Straits - Baltic Sea region. The Kattegat - Danish Straits region forms a steep salinity cline and is the only entrance to the recently (ca 8000 years ago) established brackish water basin the Baltic Sea. Salinity along the contact zone drops from 30‰ (Skagerrak, M.b.rubra) to 3‰ (Baltic, M.b.balthica). Both outlier analysis and genomic clines analysis suggest that large parts of the genome are influenced by non-neutral effects. Contrasting samples from well outside the hybrid zone, outlier analysis detects 16 of 84 amplified fragment length polymorphism (AFLP) markers as significant Fst outliers. Genomic clines analysis detects 31 out of 84 markers as non-neutral inside the hybrid zone. Remarkably, only three markers are detected by both methods. We conclude that the two methods together identify a suite of markers that are under the influence of non-neutral effects.