Premium
More precisely biased: increasing the number of markers is not a silver bullet in genetic bottleneck testing
Author(s) -
Peery M. Zachariah,
Reid Brendan N.,
Kirby Rebecca,
Stoelting Ricka,
DoucetBëer Elena,
Robinson Stacie,
VásquezCarrillo Catalina,
Pauli Jonathan N.,
Palsbøll Per J.
Publication year - 2013
Publication title -
molecular ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.619
H-Index - 225
eISSN - 1365-294X
pISSN - 0962-1083
DOI - 10.1111/mec.12394
Subject(s) - bottleneck , microsatellite , population bottleneck , biology , statistical power , population , type i and type ii errors , population genetics , sampling bias , sampling (signal processing) , evolutionary biology , genetic diversity , sample size determination , genetics , statistics , computer science , allele , mathematics , demography , gene , filter (signal processing) , sociology , computer vision , embedded system
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.