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Efficiency of allele frequency‐based bayesian programmes for detecting hybridization between farmed and wild salmon
Author(s) -
Vähä J.P. K.,
Primmer C. R.
Publication year - 2004
Publication title -
journal of fish biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.672
H-Index - 115
eISSN - 1095-8649
pISSN - 0022-1112
DOI - 10.1111/j.0022-1112.2004.0559y.x
Subject(s) - biology , introgression , hybrid , aquaculture , fishery , microsatellite , selection (genetic algorithm) , population , allele , allele frequency , evolutionary biology , zoology , fish <actinopterygii> , genetics , gene , demography , machine learning , sociology , computer science , botany
Large escapes of cultured salmon from net‐pens have become inevitable disasters linked to the growth of aquaculture in coastal areas. Hybridization between farmed and wild salmon has been witnessed; but the extent of eventual genetic introgression is controversial as selection against hybrids can maintain distinct gene pools. Individual assignment tests based on genetic data have been widely used in fisheries, due to the importance of accurate population assignment for a variety of purposes including distinction between individuals of native and stocked origin. However the ability of these Bayesian programs to detect hybrids and subsequent generations between closely related populations has been little investigated. Here we present results regarding the efficiency of two new computer programs, structure and New Hybrids in detecting hybridization between farmed and wild salmon from the river Teno (Northern Europe) based on genetic data obtained from 17 microsatellite loci.