Literature DB >> 10583833

Potential of microsatellites for individual assignment: the North Atlantic redfish (genus Sebastes) species complex as a case study.

S Roques1, P Duchesne, L Bernatchez.   

Abstract

We used the four redfish taxa (genus Sebastes) from the North Atlantic to evaluate the potential of multilocus genotype information obtained from microsatellites in assigning individuals at two different levels of group divergence. We first tested the hypothesis that microsatellites can diagnostically discriminate individual redfish from different groups. Second, we compared two different methods to quantify the effect of number of loci and likelihood stringency levels on the power of microsatellites for redfish group membership. The potential of microsatellites to discriminate individuals from different taxa was illustrated by a shared allele distance tree in which four major clusters corresponding to each taxa were defined. Concomitant with this strong discrimination, microsatellites also proved to be powerful in reclassifying specimens to the taxon of origin, using either an empirical or simulated method of estimating assignment success. By testing for the effect of both the number of loci and the level of stringency on the assignment success, we found that 95% of all specimens were still correctly reclassified with only four loci at the most commonly used criterion of log0. In contrast, the results obtained at the population level within taxa highlighted several problems of assignment that may occur at low levels of divergence. Namely, a drastic decrease of success with increasing stringency illustrated the lack of power of our set of loci. Strong discrepancy was observed between results obtained from the empirical and simulated methods. Finally, the highest assignment success was obtained when reducing the number of loci used, an observation previously reported in studies of human populations.

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Year:  1999        PMID: 10583833     DOI: 10.1046/j.1365-294x.1999.00759.x

Source DB:  PubMed          Journal:  Mol Ecol        ISSN: 0962-1083            Impact factor:   6.185


  7 in total

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Authors:  Laura M Benestan; Quentin Rougemont; Caroline Senay; Eric Normandeau; Eric Parent; Rick Rideout; Louis Bernatchez; Yvan Lambert; Céline Audet; Geneviève J Parent
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  7 in total

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