Experimental verification of microsatellite null alleles in Norway spruce (Picea abies [L.] Karst.): Implications for population genetic studies

Three stands ofPicea abies [L.] Karst. with different density in the Harz Mountains (Lower Saxony, Germany) were characterized at 4 microsatellite loci. An excess of homozygotes was observed in all 3 stands at 1 simple sequence repeat (SSR) locus, suggesting the presence of null alleles. To test for the segregation of a null allele, 24 openpollinated seeds (haploid megagametophytes and embryos) from apparently homozygous mother trees were analyzed. For 1 of 3 trees that could be identified as heterozygous for a null allele, no significant deviation from the expected 1∶1 segregation into marker absence (null allele) and marker presence of the second maternal allele could be observed in the haploid megagametophyte. Concordantly, the numbers of embryos heterozygous for the null allele and for the other maternal allele were not significantly different from each other. Inheritance analyses in seedlings and corresponding megagametophytes of gymnosperms were used as a direct experimental verification of microsatellite null alleles in single-tree progeny. Microsatellites with an abundance of null alleles should be discarded from further analysis because inclusion of these loci results in incorrect estimation of allele frequencies.     

Estimation of mating system parameters in plant populations using the EM algorithm

Theoretical and Applied Genetics - An EM algorithm procedure is presented for the maximum-likelihood estimation of mating system parameters of mixed mating system models for both angiosperms and...     

Population estimators or progeny tests: what is the best method to assess null allele frequencies at SSR loci?

Nuclear SSRs are notorious for having relatively high frequencies of null alleles, i.e. alleles that fail to amplify and are thus recessive and undetected in heterozygotes. In this paper, we compare two kinds of approaches for estimating null allele frequencies at seven nuclear microsatellite markers in three French Fagus sylvatica populations: (1) maximum likelihood methods that compare observed and expected homozygote frequencies in the population under the assumption of Hardy-Weinberg equilibrium and (2) direct null allele frequency estimates from progeny where parent genotypes are known. We show that null allele frequencies are high in F. sylvatica (7.0% on average with the population method, 5.1% with the progeny method), and that estimates are consistent between the two approaches, especially when the number of sampled maternal half-sib progeny arrays is large. With null allele frequencies ranging between 5% and 8% on average across loci, population genetic parameters such as genetic differentiation (F _ST) may be mostly unbiased. However, using markers with such average prevalence of null alleles (up to 15% for some loci) can be seriously misleading in fine scale population studies and parentage analysis.     

The genetics of the sixth and seventh components of complement in the dog: Polymorphism,linkage, locus duplication,and silent alleles

The complement components C6 and C7 exhibit genetic polymorphism in the domestic dog. In the case of C6, there is a single locus with a null allele and two structural alleles; in the case of C7, there are two linked loci, each with three structural alleles. There is a null allele or locus deletion at one of these loci. In all cases, inheritance is autosomal and codominant. The C7 loci are closely linked to each other and to C6. This complex is not close to the dog major histocompatibility complex (MHC) locus.     

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.     

Deterministic paternity exclusion using RAPD markers

The Random Amplified Polymorphic DNA (RAPD) technique can potentially provide hundreds of polymorphic markers for use by ecologists studying mating systems in natural populations. We consider here the implications of the dominance displayed by RAPD markers for deterministic paternity assignment. Our goal was to provide a means for assessing the costs associated with such a study for ecologists who might be considering the use of RAPD markers for paternity analysis. The theoretical expected proportion of offspring for which all males except the true father can be exlucded (P(ET)) is calculated for both dominant and codominant marker systems. The ability to assign paternity unambiguously generally increases with the number of loci and the frequency of the recessive allele (but only up to a point), and decreases with increasing sample size (number of individuals surveyed). The gain in P(ET) with decreasing sample size is unexpectedly slight. Not surprisingly, the performance of dominant markers at paternity exclusion is, in general, greatly exceeded by codominant markers, with the exception of the case in which the frequency of the recessive allele is high at all loci. In this case, codominant markers perform only slightly better than do dominant markers. Thus, a researcher should expect to score more than 50 RAPD loci for each offspring for most applications of paternity exclusion analysis.(ABSTRACT TRUNCATED AT 250 WORDS)     

Comparing the van Oosterhout and Chybicki‐Burczyk methods of estimating null allele frequencies for inbred populations

In spite of the usefulness of codominant markers in population genetics, the existence of null alleles raises challenging estimation issues in natural populations that are characterized by positive inbreeding coefficients (F > 0). Disregarding the possibility of F > 0 in a population will generally lead to overestimates of null allele frequencies. Conversely, estimates of inbreeding coefficients (F) may be strongly biased upwards (excess homozygotes), in the presence of nontrivial frequencies of null alleles. An algorithm has been presented for the estimation of null allele frequencies in inbred populations (van Oosterhout method), using external estimates of the F‐statistics. The goal of this study is to introduce a modification of this method and to provide a formal comparison with an alternative likelihood‐based method (Chybicki‐Burczyk). Using simulated data, we illustrate the strengths and limitations of these competing methods. Under most circumstances, the likelihood method is preferable, but for highly inbred organisms, a modified van Oosterhout method offers some advantages.     

Resolving microsatellite genotype ambiguity in populations of allopolyploid and diploidized autopolyploid organisms using negative correlations between allelic variables

A major limitation in the analysis of genetic marker data from polyploid organisms is non‐Mendelian segregation, particularly when a single marker yields allelic signals from multiple, independently segregating loci (isoloci). However, with markers such as microsatellites that detect more than two alleles, it is sometimes possible to deduce which alleles belong to which isoloci. Here, we describe a novel mathematical property of codominant marker data when it is recoded as binary (presence/absence) allelic variables: under random mating in an infinite population, two allelic variables will be negatively correlated if they belong to the same locus, but uncorrelated if they belong to different loci. We present an algorithm to take advantage of this mathematical property, sorting alleles into isoloci based on correlations, then refining the allele assignments after checking for consistency with individual genotypes. We demonstrate the utility of our method on simulated data, as well as a real microsatellite data set from a natural population of octoploid white sturgeon (Acipenser transmontanus). Our methodology is implemented in the R package polysat version 1.6.     

The loss of statistical power to distinguish populations when certain samples are ambiguous

Case-control studies are used to map loci associated with a genetic disease. The usual case-control study tests for significant differences in frequencies of alleles at marker loci. In this paper, we consider the problem of comparing two or more marker loci simultaneously and testing for significant differences in haplotype rather than allele frequencies. We consider two situations. In the first, genotypes at marker loci are resolved into haplotypes by making use of biochemical methods or by genotyping family members. In the second, genotypes at marker loci are not resolved into haplotypes, but, by assuming random mating, haplotypes can be inferred using a likelihood method such as the expectation-maximization (EM) algorithm. We assume that a causative locus has two alleles with a multiplicative effect on the penetrance of a disease, with one allele increasing the penetrance by a factor pi. We find, for small values of pi-1 and large sample sizes, asymptotic results that predict the statistical power of a test for significant differences in haplotype frequencies between cases and a random sample of the population, both when haplotypes can be resolved and when haplotypes have to be inferred. The increase in power when haplotypes can be resolved can be expressed as a ratio R, which is the increase in sample size needed to achieve the same power when haplotypes are resolved over when they are not resolved. In general, R depends on the pattern of linkage disequilibrium between the causative allele and the marker haplotypes but is independent of the frequency of the causative allele and, to a first approximation, is independent of pi. For the special situation of two di-allelic marker loci, we obtain a simple expression for R and its upper bound.     

Genes Controlling Mating-Type Specificity in PARAMECIUM CAUDATUM: Three Loci Revealed by Intersyngenic Crosses

In mating interactions in Paramecium caudatum, initial mating agglutination is strictly mating-type specific, but subsequent conjugating pair formation is not mating-type specific. Using this nonspecificity of pair formation, intersyngenic (intersibling species) pairs were induced by mixing four mating types of two different syngens. To distinguish intersyngenic pairs from intrasyngenic ones, the behavioral marker CNR (Takahashi 1979) was mainly used. Clones of intersyngenic hybrids showed high fertility and thus made feasible a genetic analysis of syngenic specificity of mating type. The syngenic specificities of E (even) mating types were found to be controlled by co-dominant multiple alleles at the Mt locus, and those of O (odd) mating types by interactions of co-dominant multiple alleles at two loci, MA and MB. Clones of heterozygotes express dual mating types. Mt is epistatic to MA and MB, and thus O mating types can be expressed only in the recessive homozygote (mt/mt) at the Mt locus. In addition, at least one allele each at the MA and MB loci must have a common syngen specificity for the expression of O types. Thus, when MA is homozygous for one syngen and MB is homozygous for another syngen, no mating type is expressed.     

The use of the expectation-maximization (EM) algorithm for maximum likelihood estimation of gametic frequencies of multilocus polymorphic codominant systems based on sampled population data

Estimation of gametic frequencies in multilocus polymorphic systems based on the numerical distribution of multilocus genotypes in a population sample ("analysis without pedigrees") is difficult because some gametes are not recognized in the data obtained. Even in the case of codominant systems, where all alleles can be recognized by genotypes, so that direct estimation of the frequencies of genes (alleles) is possible ("complete data"), estimation of the frequencies of multilocus gametes based on the data on multilocus genotypes is sometimes impossible, whether population data or even family data are used for studying genotypic segregation or analysis of linkage ("incomplete data"). Such "incomplete data" are analyzed based on the corresponding genetic models using the expectation-maximization (EM) algorithm. In this study, the EM algorithm based on the random-marriage model for a nonsubdivided population was used to estimate gametic frequencies. The EM algorithm used in the study does not set any limitations on the number of loci and the number of alleles of each locus. Locus and alleles are identified by numeration making possible to arrange loops. In each combination of alleles for a given combination of m out of L loci (L is the total number of loci studied), all alleles are assigned value 1, and the remaining alleles are assigned value 0. The sum of zeros and unities for each gamete is its gametic value (h), and the sum of the gametic values of the gametes that form a given genotype is the genotypic value (g) of this genotype. Then, gametes with the same h are united into a single class, which reduces the number of the estimated parameters. In a general case of m loci, this procedure yields m + 1 classes of gametes and 2m + 1 classes of genotypes with genotypic values g = 0, 1, 2, ..., 2m. The unknown frequencies of the m + 1 classes of gametes can be represented as functions of the gametic frequencies whose maximum likelihood estimations (MLEs) have been obtained in all previous EM procedures and the only unknown frequency (Pm(m)) that is to be estimated in the given EM procedure. At the expectation step, the expected frequencies (Fm(g) of the genotypes with genotypic values g are expressed in terms of the products of the frequencies of m + 1 classes of gametes. The data on genotypes are the numbers (ng) of individuals with genotypic values g = 0, 1, 2, 3, ..., 2m. The maximization step is the maximization of the logarithm of the likelihood function (LLF) for ng values. Thus, the EM algorithm is reduced, in each case, to solution of only one equation with one unknown parameter with the use of the ng values, i.e., the numbers of individuals after the corresponding regrouping of the data on the individuals' genotypes. Treatment of the data obtained by Kurbatova on the MNSs and Rhesus systems with alleles C, Cw, c, D, d, E, e with the use of Weir's EM algorithm and the EM algorithm suggested in this study yielded similar results. However, the MLEs of the parameters obtained with the use of either algorithm often converged to a wrong solution: the sum of the frequencies of all gametes (4 and 12 gametes for MNSs and Rhesus, respectively) was not equal to 1.0 even if the global maximum of LLF was reached for each of them (as it was for MNSs with the use of Weir's EM algorithm), with each parameter falling within admissible limits (e.g., [0, min(PN,Ps)] for PNs). The chi 2 function is suggested to be used as a goodness-of-fit function for the distribution of genotypes in a sample in order to select acceptable solutions. However, the minimum of this function only guarantee the acceptability of solutions if all limitations on the parameters are met: the sum of estimations of gametic frequencies is 1.0, each frequency falls within the admissible limits, and the "gametic algebra" is complied with (none of the frequencies is negative).     

Primers for nine microsatellite loci in the hermaphroditic snail Lymnaea stagnalis

Variation in and amplification conditions for nine polymorphic microsatellite loci identified from Lymnaea stagnalis, a hermaphroditic pulmonate snail, are described. Eight populations from central Finland were studied, which varied in terms of both observed polymorphism and heterozygosity. The number of alleles at each locus is moderate (two to seven), except for one exceptional locus having 16 alleles, and for which null alleles are possible. There is no evidence for genotypic disequilibrium in the populations for all pairs of loci. Heterozygosity levels are indicative of outcrossing in L. stagnalis, whose mating system will be characterized further using these markers.     

Estimating Relatedness in the Presence of Null Alleles

Studies of genetics and ecology often require estimates of relatedness coefficients based on genetic marker data. However, with the presence of null alleles, an observed genotype can represent one of several possible true genotypes. This results in biased estimates of relatedness. As the numbers of marker loci are often limited, loci with null alleles cannot be abandoned without substantial loss of statistical power. Here, we show how loci with null alleles can be incorporated into six estimators of relatedness (two novel). We evaluate the performance of various estimators before and after correction for null alleles. If the frequency of a null allele is <0.1, some estimators can be used directly without adjustment; if it is >0.5, the potency of estimation is too low and such a locus should be excluded. We make available a software package entitled PolyRelatedness v1.6, which enables researchers to optimize these estimators to best fit a particular data set.     

Analysis of population genetic structure with RAPD markers

Recent advances in the application of the polymerase chain reaction make it possible to score individuals at a large number of loci. The RAPD (random amplified polymorphic DNA) method is one such technique that has attracted widespread interest. The analysis of population structure with RAPD data is hampered by the lack of complete genotypic information resulting from dominance, since this enhances the sampling variance associated with single loci as well as induces bias in parameter estimation. We present estimators for several population-genetic parameters (gene and genotype frequencies, within- and between-population heterozygosities, degree of inbreeding and population subdivision, and degree of individual relatedness) along with expressions for their sampling variances. Although completely unbiased estimators do not appear to be possible with RAPDs, several steps are suggested that will insure that the bias in parameter estimates is negligible. To achieve the same degree of statistical power, on the order of 2 to 10 times more individuals need to be sampled per locus when dominant markers are relied upon, as compared to codominant (RFLP, isozyme) markers. Moreover, to avoid bias in parameter estimation, the marker alleles for most of these loci should be in relatively low frequency. Due to the need for pruning loci with low-frequency null alleles, more loci also need to be sampled with RAPDs than with more conventional markers, and some problems of bias cannot be completely eliminated.     

The genetics of colour-patterns in the grasshopper Chorthippus brunneus

Several alleles were found to determine the colour of the dorsal pronotum in Chorthippus brunneus; there was evidence for at least two loci ( C and V ). Brown ( C^B )was the universal recessive and green ( C^C ) was dominant to all other colours. The white allele ( C^W )was codominant with green( C^G )and purple ( C^P ). Wing-patterns were determined by a separate, probably linked locus ( W ). A dominant plain wing-pattern ( W^P ) was associated with colours other than brown. Striped( W^S )and mottled( W^mo ) were codominant and a plain recessive allele ( W^P ) was also found. All three alleles were associated with the brown phenotype. A purple-sided allele ( S^Pu ) was sometimes obmd with C^pu.. S ^Pu was dominant to brown sides ( S^B ), A series of markings on the dorsal and lateral pronotum ( linea intermedia, fascia postocularis, linea media, carina media and zona lateralis ) were investigated and found to be controlled at separate loci which may be linked to W . These characters were expressed by dominant alleles.
Epistatic effects by modifier loci were shown to have an important effect on the determination of wing phenotype. Allele Wo⁺ , for example, suppressed the stripe-wing pattern, linea media, carina media and zona lateralis .
It was concluded that colour patterns appear to be under genetic control and that dominant alleles were rare in the wild. Changes in shades of colours were shown to be age-dependent and minor.     

Null alleles at two lactate dehydrogenase loci in rainbow trout are associated with decreased developmental stability

Previous studies with rainbow trout (Oncorhynchus mykiss) have shown that allozymic heterozygotes have increased developmental stability, as measured by reduced fluctuating bilateral asymmetry. In this paper, we examine the phenotypic effects of null alleles at two lactate dehydrogenase (LDH) loci. If the association between allozymic heterozygosity and developmental stability is due largely to linked chromosomal segments, then we would expect null allele heterozygotes to have increased developmental stability. In contrast, heterozygotes for LDH null alleles in three populations have reduced developmental stability. This suggests that the reduction in enzyme activity at these loci is having a deleterious effect on development that is strong enough to mask any beneficial effects that may be associated with heterozygosity for these chromosomal segments. The LDH loci examined in this study are members of two different paralogous pairs of duplicate genes produced by the polyploidization of the ancestral salmonid genome. The apparent deleterious effects of these null alleles in heterozygotes could retard the possible loss of duplicate gene expression.     

polypatex: an r package for paternity exclusion in autopolyploids

Microsatellite markers have demonstrated their value for performing paternity exclusion and hence exploring mating patterns in plants and animals. Methodology is well established for diploid species, and several software packages exist for elucidating paternity in diploids; however, these issues are not so readily addressed in polyploids due to the increased complexity of the exclusion problem and a lack of available software. We introduce polypatex , an r package for paternity exclusion analysis using microsatellite data in autopolyploid, monoecious or dioecious/bisexual species with a ploidy of 4n, 6n or 8n. Given marker data for a set of offspring, their mothers and a set of candidate fathers, polypatex uses allele matching to exclude candidates whose marker alleles are incompatible with the alleles in each offspring–mother pair. polypatex can analyse marker data sets in which allele copy numbers are known (genotype data) or unknown (allelic phenotype data) – for data sets in which allele copy numbers are unknown, comparisons are made taking into account all possible genotypes that could arise from the compared allele sets. polypatex is a software tool that provides population geneticists with the ability to investigate the mating patterns of autopolyploids using paternity exclusion analysis on data from codominant markers having multiple alleles per locus.     

Genetic studies of water buffalo blood markers. I. Red cell acid phosphatase,albumin, catalase,red cell α-esterase-3, group-specific component,and protease inhibitor

We have developed the methodologies for typing and family studies to establish the modes of inheritance of water buffalo red cell acid phosphatase (Acp), protease inhibitor (Pi), and group-specific component (Gc) on isoelectric focusing and albumin (Alb), red cell -esterase-3 (Est-3), and catalase (Cat) on polyacrylamide gel electrophoresis. Family studies showed that Pi, Gc, Alb, and Cat are coded by autosomal genes with two codominant alleles, while Est-3 is autosomal with two codominant alleles and a recessive null allele and Acp exhibits three codominant alleles.This project was funded by the Australian Centre for International Agricultural Research through Grant PN 8364 and the Malaysian programme for Intensification of Research in Priority Areas through Grant IRPA 1-07-05-057.     

Marker selection for the transmission/disequilibrium test, in recently admixed populations.

Recent admixture between genetically differentiated populations can result in high levels of association between alleles at loci that are <=10 cM apart. The transmission/disequilibrium test (TDT) proposed by Spielman et al. (1993) can be a powerful test of linkage between disease and marker loci in the presence of association and therefore could be a useful test of linkage in admixed populations. The degree of association between alleles at two loci depends on the differences in allele frequencies, at the two loci, in the founding populations; therefore, the choice of marker is important. For a multiallelic marker, one strategy that may improve the power of the TDT is to group marker alleles within a locus, on the basis of information about the founding populations and the admixed population, thereby collapsing the marker into one with fewer alleles. We have examined the consequences of collapsing a microsatellite into a two-allele marker, when two founding populations are assumed for the admixed population, and have found that if there is random mating in the admixed population, then typically there is a collapsing for which the power of the TDT is greater than that for the original microsatellite marker. A method is presented for finding the optimal collapsing that has minimal dependence on the disease and that uses estimates either of marker allele frequencies in the two founding populations or of marker allele frequencies in the current, admixed population and in one of the founding populations. Furthermore, this optimal collapsing is not always the collapsing with the largest difference in allele frequencies in the founding populations. To demonstrate this strategy, we considered a recent data set, published previously, that provides frequency estimates for 30 microsatellites in 13 populations.     

KINALYZER, a computer program for reconstructing sibling groups

A software suite KINALYZER reconstructs full-sibling groups without parental information using data from codominant marker loci such as microsatellites. KINALYZER utilizes a new algorithm for sibling reconstruction in diploid organisms based on combinatorial optimization. KINALYZER makes use of a Minimum 2-Allele Set Cover approach based on Mendelian inheritance rules and finds the smallest number of sibling groups that contain all the individuals in the sample. Also available is a 'Greedy Consensus' approach that reconstructs sibgroups using subsets of loci and finds the consensus of the partial solutions. Unlike likelihood methods for sibling reconstruction, KINALYZER does not require information about population allele frequencies and it makes no assumptions regarding the mating system of the species. KINALYZER is freely available as a web-based service.