Estimating pollen flow using SSR markers and paternity exclusion: accounting for mistyping

Highly informative genetic markers, such as simple sequence repeats (SSRs), can be used to directly measure pollen flow by parentage analysis. However, mistyping (i.e. false inference of genotypes caused by the occurrence of null alleles, mutations, and detection errors) can lead to substantial biases in the estimates obtained. Using computer simulations, we evaluated a direct method for estimating pollen immigration using SSR markers and a paternity exclusion approach. This method accounts for mistyping and does not rely on assumptions about the distribution of male reproductive success. If ignored, even minor rates of mistyping (1.5%) resulted in overestimating pollen immigration by up to 150%. When we required at least two mismatching loci before excluding candidate fathers from paternity, the resulting pollen immigration estimates had small biases for rates of mistyping up to 4.5%. Requiring at least three mismatches for exclusion was needed to minimize the upward biases of pollen immigration caused by rates of mistyping up to 10.5%. The minimum number of highly variable SSR loci needed to minimize cryptic gene flow and obtain reliable estimates of pollen immigration varied from five to seven for a sampling scheme applicable to most conifers (i.e. when paternal haplotypes can be unambiguously determined). Between five and nine highly variable SSR loci were needed for a more general sampling scheme that is applicable to all diploid seed plants. With moderately variable SSR markers, consistently accurate estimates of pollen immigration could be obtained only for rates of mistyping up to 4.5%. We developed the POLLEN FLOW (PFL) computer program which can be used to obtain unbiased and precise estimates of pollen immigration under a wide range of conditions, including population sizes as large as 600 parents and mistyping rates as high as 10.5%.     

Unbiased estimation of relative reproductive success of different groups: evaluation and correction of bias caused by parentage assignment errors

Parentage assignment is widely applied to studies on mating systems, population dynamics and natural selection. However, little is known about the consequence of assignment errors, especially when some parents are not sampled. We investigated the effects of two types of error in parentage assignment, failing to assign a true parent (type A) and assigning an untrue parent (type B), on an estimate of the relative reproductive success (RRS) of two groups of parents. Employing a mathematical approach, we found that (i) when all parents are sampled, minimizing either type A or type B error insures the minimum bias on RRS, and (ii) when a large number of parents is not sampled, type B error substantially biases the estimated RRS towards one. Interestingly, however, (iii) when all parents were sampled and both error rates were moderately high, type A error biased the estimated RRS even more than type B error. We propose new methods to obtain an unbiased estimate of RRS and the number of offspring whose parents are not sampled (zW(z)), by correcting the error effects. Applying them to genotypic data from steelhead trout (Oncorhynchus mykiss), we illustrated how to estimate and control the assignment errors. In the data, we observed up to a 30% assignment error and a strong trade-off between the two types of error, depending on the stringency of the assignment decision criterion. We show that our methods can efficiently estimate an unbiased RRS and zW(z) regardless of assignment method, and how to maximize the statistical power to detect a difference in reproductive success between groups.     

The potential costs of accounting for genotypic errors in molecular parentage analyses

Genotypic errors, whether due to mutation or laboratory error, can cause the genotypes of parents and their offspring to appear inconsistent with Mendelian inheritance. As a result, molecular parentage analyses are expected to benefit when allowances are made for the presence of genotypic errors. However, a cost of allowing for genotypic errors might also be expected under some analytical conditions, primarily because parentage analyses that assume nonzero genotypic error rates can neither assign nor exclude parentage with certainty. The goal of this work was therefore to determine whether or not such costs might be important under conditions relevant to parentage analyses, particularly in natural populations. Simulation results indicate that the costs may often outweigh the benefits of accounting for nonzero error rates, except in situations where data are available for many marker loci. Consequently, the most powerful approach to handling genotypic errors in parentage analyses might be to apply likelihood equations with error rates set to values substantially lower than the rates at which genotypic errors occur. When applying molecular parentage analyses to natural populations, we advocate an increased consideration of optimal strategies for handling genotypic errors. Currently available software packages contain procedures that can be used for this purpose.     

Multiple paternity in a philopatric rodent: the interaction of competition and choice

Paternity confusion is often suggested as the benefit that femalemammals accrue by mating with multiple males, but genetic advantagesare also possible. Microsatellite-based parentage analyses demonstratethat female banner-tailed kangaroo rats (Dipodomys spectabilis)commonly mate with more than one male; we asked how male andfemale behaviors interact to influence the characteristics ofmales that sire offspring. Specifically, we compared attributes(age, weight, mobility, relatedness, proximity) of the fathersof 229 known-maternity offspring with those of the other malesaccessible to the mothers. Adult males living adjacent to eachfemale attempt to monopolize access to her, and the nearestmale sires a plurality of offspring, but most mothers' youngare fathered by more than one male and littermates are usuallyhalf-sibs. Male proximity and mobility, but not size, influencethe probability of paternity, suggesting a role for competitivemate searching. Females significantly reduce the inbreedingcoefficient of their offspring by mating with males other than(or in addition to) the nearest male. Fathers are less closelyrelated to the mother in years of high density when unrelatedmales are more accessible to the female. Our results favor thegenetic "bet-hedging" hypothesis, whereby females actively butunselectively seek matings with additional males when the malemost likely to win in mate competition is costly to her (inthis case, genetically less compatible). We anticipate thatgenetic bet hedging will be common in species whose femalesare defendable, especially if they are also philopatric.     

Development and characterization of eight new microsatellite markers for the haremic sandperch,Parapercis cylindrica (family Pinguipedidae)

Eight di‐, tri‐ and tetranucleotide microsatellite markers were developed for the haremic sandperch Parapercis cylindrica using a linker‐ligated, magnetic bead enrichment protocol. Screening of at least 17 individuals showed these markers to be polymorphic with observed heterozygosity ranging from 0.381 to 1.000 (mean = 0.742) and the numbers of alleles ranging from three to 18. The average polymorphic information content for these eight loci was 0.723. These markers may be used for parentage studies aimed at exploring the complex mating strategies employed by this haremic coral reef fish and will be valuable for population genetic studies.     

Estimation of the number of SNP genetic markers required for parentage verification

Formulae were developed to compute exclusion probabilities for parentage confirmation for any number of diallelic markers under the assumption that the minor allele frequency (MAF) varied among markers, but has a uniform distribution. Three scenarios were analysed: a progeny with (1) a single putative parent; (2) two putative parents; and (3) one actual parent and one putative parent. Exclusion probabilities were computed for minimum values for the MAFs of 0.1, 0.2 and 0.3, and required either one or at least two conflicts for exclusion. The numbers of markers required to obtain 99% exclusion probabilities based on a single conflict for the three minimum MAFs were 54, 45 and 39 for scenario 1; 17, 16 and 15 for scenario 2; and 28, 25 and 24 for scenario 3. The requirement of at least two conflicts for exclusion increased the number of markers required by approximately 45% for all three scenarios and all three minimum MAFs. The results obtained by the analytical formulae were very close to results obtained by simulation and to values in the literature for specific marker sets.     

p-loci: a computer program for choosing the most efficient set of loci for parentage assignment

Determining how many and which codominant marker loci are required for accurate parentage assignment is not straightforward because levels of marker polymorphism, linkage, allelic distributions among potential parents and other factors produce differences in the discriminatory power of individual markers and sets of markers. p-loci software identifies the most efficient set of codominant markers for assigning parentage at a user-defined level of success, using either simulated or actual offspring genotypes of known parentage. Simulations can incorporate linkage among markers, mating design and frequencies of null alleles and/or genotyping errors. p-loci is available for windows systems at http://marineresearch.oregonstate.edu/genetics/ploci.htm.     

Development and polymorphism of simple sequence repeat DNA markers for the evergreen shrub Ilex leucoclada M.

We have developed 13 microsatellite loci from an enrichment library of genomic DNA in the evergreen shrub Ilex leucoclada. One hundred and eighty‐nine out of 432 clones were found to contain microsatellite repeats. Primer pairs were designed for 92 of these clones according to their sequence data. Thirteen of these primer pairs revealed polymorphism among 36 individuals sampled from 12 populations. Three to 27 alleles per locus were detected, and the expected heterozygosity ranged from 0.133 to 0.971. Because these 13 microsatellite markers showed high degrees of genetic variation, they should be useful tools for studying population and ecological genetics of I. leucoclada.     

matesoft: a program for deducing parental genotypes and estimating mating system statistics in haplodiploid species

With the advent of sophisticated genetic markers, studies on mating systems and reproductive apportionment have become increasingly feasible. In particular, paternity analyses in haplodiploid species have gained in power as hemizygous paternal genotypes allow maternal and paternal genotypes to be directly inferred from offspring genotypes. The computer program matesoft offers both newly developed algorithms for inferring maternal and paternal genotypes, and integrated estimation and correction procedures for calculating mating frequency statistics. Standard data are offspring genotypes of male‐haplodiploid organisms, including social Hymenoptera.     

Polymorphic microsatellite loci from the red urchin,Strongylocentrotus franciscanus,with comments on heterozygote deficit

Strongylocentrotus sea urchins are common subjects for studies in developmental and cell biology, reproductive biology, ecology, and evolution. We report 14 microsatellite loci from the red urchin, S. franciscanus, isolated for the purpose of estimating paternal success of males in experimental group spawns. Most of these loci were found to be highly polymorphic in a population from British Columbia. A high frequency of null alleles appears responsible for heterozygote deficit at a majority of these loci, but if used with appropriate caution, these microsatellites should be effective markers for studies of Strongylocentrotus populations.