Simultaneous Estimation of Null Alleles and Inbreeding Coefficients

Abstract

Although microsatellites are a very efficient tool for many population genetics applications, they may occasionally produce "null" alleles, which, when present in high proportion, may affect estimates of key parameters such as inbreeding and relatedness coefficients or measures of genetic differentiation. In order to account for the presence of null alleles, it is first necessary to estimate their frequency within studied populations. However, the commonly used null allele frequency estimators are not of general applicability because they can produce upwardly biased estimates when a population under study experiences some inbreeding. In such a case, 2 formerly described approaches, population inbreeding model and individual inbreeding model, can be applied for simultaneous estimation of null allele frequencies and of the inbreeding coefficient. In this study, we demonstrate the properties and utility of these 2 methods and show that they outperform the commonly used approaches in the estimation of null allele frequencies based on genotypic data. The methods are applied to empirical data from a natural population of European beech (Fagus sylvatica L.), and results are briefly discussed. The methods presented in this paper are implemented in the Windows-based user-friendly INEST computer program (available free of charge at http://genetyka.ukw.edu.pl/INEst10_setup.exe).

Size advantage for male function and size‐dependent sex allocation in Ambrosia artemisiifolia, a wind‐pollinated plant

“…Before paternity analysis, we checked null allele frequency using INEST 2.1 (Chybicki & Burczyk, 2009), and we used six of 10 loci in which null allele frequency was <0.34 in seed samples. We selected sets of seeds and parents genotyped at least for five of the six loci.…”

Effect of geographic range discontinuity on species differentiation—East-Mediterranean Abies cilicica: a case study

“…Genetic diversity parameters, including average number of alleles (A), observed heterozygosity (H O ), expected heterozygosity (H E ), and frequency of the null alleles (N 0 ) were estimated using INEst v.1.0 (Chybicki and Burczyk 2009). Allelic richness (A R ) was calculated using FSTAT 2.9.3 (Goudet 2001).…”

“…The fulllikelihood-based analysis (medium likelihood precision and medium length of run) was done under the assumption of polygamy, monoecy, and inbreeding. Locus-specific estimates of null allele frequencies were used as the surrogates for allelic dropout rates, together with genotyping errors provided by INEST 1.0. software (Chybicki and Burczyk 2009).…”

Genetic evidence of reproductive isolation in a remote enclave of Quercus pubescens in the presence of cross-fertile species

“…P values were obtained based on 100,000 random permutations of alleles among genotypes, after correction for multiple tests using the Š idak procedure. The computations were conducted with the updated version of INEst software (Chybicki and Burczyk 2009).…”

“…The full-likelihood-based analysis (medium likelihood precision and medium length of run) was performed under the assumption of polygamy and monoecy with a possibility of self-fertilisation. Rates for allelic dropout were substituted with locus-specific estimates of null allele frequencies provided with INEst software (Chybicki and Burczyk 2009). Rates of other error types were arbitrarily fixed at 0.01.…”