%0 Journal Article %1 fourcade2013local %A Fourcade, Yoan %A Chaput-Bardy, Audrey %A Secondi, Jean %A Fleurant, Cyril %A Lemaire, Christophe %D 2013 %J Molecular Ecology %K GWAS fractal_landscape local_adaptation spatial_structure %N 8 %P 2065--2073 %R 10.1111/mec.12158 %T Is local selection so widespread in river organisms? Fractal geometry of river networks leads to high bias in outlier detection %U http://dx.doi.org/10.1111/mec.12158 %V 22 %X Identifying local adaptation is crucial in conservation biology to define ecotypes and establish management guidelines. Local adaptation is often inferred from the detection of loci showing a high differentiation between populations, the so-called FST outliers. Methods of detection of loci under selection are reputed to be robust in most spatial population models. However, using simulations we showed that FST outlier tests provided a high rate of false-positives (up to 60%) in fractal environments such as river networks. Surprisingly, the number of sampled demes was correlated with parameters of population genetic structure, such as the variance of FSTs, and hence strongly influenced the rate of outliers. This unappreciated property of river networks therefore needs to be accounted for in genetic studies on adaptation and conservation of river organisms.

@article{fourcade2013local, abstract = {Identifying local adaptation is crucial in conservation biology to define ecotypes and establish management guidelines. Local adaptation is often inferred from the detection of loci showing a high differentiation between populations, the so-called FST outliers. Methods of detection of loci under selection are reputed to be robust in most spatial population models. However, using simulations we showed that FST outlier tests provided a high rate of false-positives (up to 60%) in fractal environments such as river networks. Surprisingly, the number of sampled demes was correlated with parameters of population genetic structure, such as the variance of FSTs, and hence strongly influenced the rate of outliers. This unappreciated property of river networks therefore needs to be accounted for in genetic studies on adaptation and conservation of river organisms.}, added-at = {2013-08-06T00:30:01.000+0200}, author = {Fourcade, Yoan and Chaput-Bardy, Audrey and Secondi, Jean and Fleurant, Cyril and Lemaire, Christophe}, biburl = {https://www.bibsonomy.org/bibtex/21443c9943f06d634a663f49d18bd51e8/peter.ralph}, doi = {10.1111/mec.12158}, interhash = {6ef7bb4c55ecfea7228301015a9d996e}, intrahash = {1443c9943f06d634a663f49d18bd51e8}, issn = {1365-294X}, journal = {Molecular Ecology}, keywords = {GWAS fractal_landscape local_adaptation spatial_structure}, number = 8, pages = {2065--2073}, timestamp = {2013-08-06T00:30:01.000+0200}, title = {Is local selection so widespread in river organisms? Fractal geometry of river networks leads to high bias in outlier detection}, url = {http://dx.doi.org/10.1111/mec.12158}, volume = 22, year = 2013 }