|Título||Genomic scans detect signatures of selection along a salinity gradient in populations of the intertidal seaweed Fucus serratus on a 12 km scale.|
|Publication Type||Journal Article|
|Authors||Coyer, JA, Hoarau, G, Pearson, GA, Mota, C, Jüterbock, A, Alpermann, T, John, U, Olsen, JL|
|Year of Publication||2011|
|Date Published||2011 Mar|
|Palavras-chave||Fucus, Genome, Plant, Genomics, Microsatellite Repeats, Oceans and Seas, Salinity, Seawater, Selection, Genetic|
Detecting natural selection in wild populations is a central challenge in evolutionary biology and genomic scans are an important means of detecting allele frequencies that deviate from neutral expectations among marker loci. We used nine anonymous and 15 EST-linked microsatellites, 362 AFLP loci, and several neutrality tests, to identify outlier loci when comparing four populations of the seaweed Fucus serratus spaced along a 12km intertidal shore with a steep salinity gradient. Under criteria of at least two significant tests in at least two population pairs, three EST-derived and three anonymous loci revealed putative signatures of selection. Anonymous locus FsB113 was a consistent outlier when comparing least saline to fully marine sites. Locus F37 was an outlier when comparing the least saline to more saline areas, and was annotated as a polyol transporter/putative mannitol transporter - an important sugar-alcohol associated with osmoregulation by brown algae. The remaining loci could not be annotated using six different data bases. Exclusion of microsatellite outlier loci did not change either the degree or direction of differentiation among populations. In one outlier test, the number of AFLP outlier loci increased as the salinity differences between population pairs increased (up to 14); only four outliers were detected with the second test and only one was consistent with both tests. Consistency may be improved with a much more rigorous approach to replication and/or may be dependent upon the class of marker used.
|Alternate Journal||Mar Genomics|