Reliable selfing rate estimates from imperfect population genetic data

Abstract

Genotypic frequencies at codominant marker loci in population samples convey information on mating systems. A classical way to extract this information is to measure heterozygote deficiencies ( F IS ) and obtain the selfing rate s from F IS = = = = s /(2 − − − − s ), assuming inbreeding equilibrium. A major drawback is that heterozygote deficiencies are often present without selfing, owing largely to technical artefacts such as null alleles or partial dominance. We show here that, in the absence of gametic disequilibrium, the multilocus structure can be used to derive estimates of s independent of F IS and free of technical biases. Their statistical power and precision are comparable to those of F IS , although they are sensitive to certain types of gametic disequilibria, a bias shared with progeny-array methods but not F IS . We analyse four real data sets spanning a range of mating systems . In two examples, we obtain s = = = = 0 despite positive F IS , strongly suggesting that the latter are artefactual. In the remaining examples, all estimates are consistent. All the computations have been implemented in a open-access and userfriendly software called RMES (robust multilocus estimate of selfing) available at http:// ftp.cefe.cnrs.fr, and can be used on any multilocus data. Being able to extract the reliable information from imperfect data, our method opens the way to make use of the ever-growing number of published population genetic studies, in addition to the more demanding progenyarray approaches, to investigate selfing rates.

The strength of the association between heterozygosity and probability of interannual local recruitment increases with environmental harshness in blue tits

“…We neither found significant HFC when estimating heterozygosity from the subset of presumably functional loci, which is the group of markers most likely to show local or direct effects due to their location inside or flanking coding gene sequences that are being actively transcribed to RNA (Li et al., 2004; Olano‐Marin, Mueller, & Kempenaers, 2011a; Olano‐Marin, Mueller, & Kempenaers, 2011b). Thus, genomewide inbreeding seems to be the most plausible explanation for the observed HFC, a hypothesis that is also partially supported by the fact that we found evidence for ID (i.e., positive and significant g 2 values) in different study years (David et al., 2007; Szulkin et al., 2010; e.g., García‐Navas, Cáliz‐Campal et al., 2014). …”

“…We used the inverse of HL (i.e., 1‐HL) as an estimate of individual heterozygosity in subsequent analyses. To analyze the presence of identity disequilibrium in our population and determine whether heterozygosity measured at our set of microsatellite loci is representative of genomewide inbreeding, we calculated the parameter g 2 and tested whether it differed significantly from zero using 1,000 iterations in the software rmes (David, Pujol, Viard, Castella, & Goudet, 2007). …”

Population genomics of the introduced and cultivated Pacific kelp Undaria pinnatifida: Marinas—not farms—drive regional connectivity and establishment in natural rocky reefs

“…For each locality, the number of study individuals, the expected heterozygosity ( H E ), the estimate of fixation index F IS and the probability of the exact test for Hardy–Weinberg equilibrium (pHW) are provided. Selfing rates ( s ) estimated with the g 2 value (David et al., 2007) are also given. Similar information is provided in the Supplementary Material (Supporting Information Table S1) for the microsatellite panel.…”

Age‐dependent, negative heterozygosity–fitness correlations and local effects in an endangered Caribbean reptile, Iguana delicatissima

“…Identity disequilibrium (ID) is the covariance in marker heterozygosity or the nonrandom heterozygosity association among loci in an individual (Miller & Coltman, 2014; Weir & Cockerham, 1969). ID was calculated using the g 2 statistic in RMES (David, Pujol, Viard, Castella, & Goudet, 2007). The alternative hypothesis for HFCs in studies using microsatellites is the local effect hypothesis, in which the chosen markers are in linkage disequilibrium with loci that directly influence fitness.…”