title: More precisely biased: increasing the number of markers is not a silver bullet in genetic bottleneck testing.
abstract: In response to our review of the use of genetic bottleneck tests in the conservation literature (Peery et al. 2012,Molecular Ecology, 21, 3403–3418), Hoban et al. (2013, Molecular Ecology, in press) conducted population genetic simulations to show that the statistical power of genetic bottleneck tests can be increased substantially by sampling large numbers of microsatellite loci, as they suggest is now possible in the age of genomics. While we agree with Hoban and co-workers in principle, sampling large numbers of microsatellite loci can dramatically increase the probability of committing type 1 errors(i.e. detecting a bottleneck in a stable population) when the mutation model is incorrectly assumed. Using conservative values for mutation model parameters can reduce the probability of committing type 1 errors, but doing so can result in significant losses in statistical power. Moreover, we believe that practical limitations associated with developing large numbers of high-quality microsatellite loci continue to constrain sample sizes, a belief supported by a literature review of recent studies using next generation sequencing methods to develop microsatellite libraries. conclusion, we maintain that researchers employing genetic bottleneck tests should proceed with caution and carefully assess both statistical power and type 1 error rates associated with their study design.
authors: M Zachariah
authors: MZ
authors: Peery
authors: Brendan N
authors: BN
authors: Reid
authors: Rebecca
authors: R
authors: Kirby
authors: Ricka
authors: R
authors: Stoelting
authors: Elena
authors: E
authors: Doucet-Bëer
authors: Stacie
authors: S
authors: Robinson
authors: Catalina
authors: C
authors: Vásquez-Carrillo
authors: Jonathan N
authors: JN
authors: Pauli
authors: Per J
authors: PJ
authors: Palsbø LL
mesh_terms: D003198:Computer Simulation; D019143:Evolution, Molecular; D023281:Genomics; D008957:Models, Genetic