远缘杂交中不育基因的位置和效应的最大似然估计

提出了一种统计方法,利用标记位点的异常分离,来估计远缘杂交中不育基因位点的位置和效应,在回交群体中,用最大似然法对不育基因与标记位点之间的生组值和配子存活率进行估计。将表现连续分布的育性指标转化为百连续变异的遗传标记的分离,可以避免对育性直接观测所带来的重组值估计结果的不稳定,还可以同时估计雌雄配子的存活率。     

A Beta-mixture model for assessing genetic population structure

Summary An important fraction of recently generated molecular data is dominant markers. They contain substantial information about genetic variation but dominance makes it impossible to apply standard techniques to calculate measures of genetic differentiation, such as F‐statistics. In this article, we propose a new Bayesian beta‐mixture model that more accurately describes the genetic structure from dominant markers and estimates multiple F_ST s from the sample. The model also has important application for codominant markers and single‐nucleotide polymorphism (SNP) data. The number of F_ST is assumed unknown beforehand and follows a random distribution. The reversible jump algorithm is used to estimate the unknown number of multiple F_ST s. We evaluate the performance of three split proposals and the overall performance of the proposed model based on simulated dominant marker data. The model could reliably identify and estimate a spectrum of degrees of genetic differentiation present in multiple loci. The estimates of F_ST s also incorporate uncertainty about the magnitude of within‐population inbreeding coefficient. We illustrate the method with two examples, one using dominant marker data from a rare orchid and the other using codominant marker data from human populations.     

Maximum likelihood techniques for the mapping and analysis of quantitative trait loci with the aid of genetic markers

A method is presented to estimate the biometric parameters of a quantitative trait locus linked to a genetic marker when both loci are segregating in the F-2 generation of a cross between two inbred lines. The method, which assumes underlying normal distributions, is a combination of maximum likelihood and moments methods and uses the statistics of the genetic marker genotype samples for the quantitative trait to estimate the recombination frequency between the two loci and the means and variances of the genotypes of the quantitative trait locus. With this method, the genetic parameters of a locus affecting plant height linked to an electrophoretic marker for esterase were accurately estimated from a sample of 1596 F-2 progeny of a cross between two species of Lycopersicon (tomato). Linkage distance between the two loci was 38 map units and the effect of the quantitative trait locus was 1.6 phenotypic standard deviation units. Accurate estimates of the genetic parameters and linkage distance for populations of 2000 individuals simulated with a segregating codominant locus with an effect of 1.63 standard deviations linked to a genetic marker with .2 recombination were also derived by this method. The method is not effective in distinguishing between complete and partial linkage in samples of only 500 individuals or for quantitative loci with effects less than a phenotypic standard deviation. The method is more effective for codominant than for dominant loci.     

Statistical confidence in parentage analysis with incomplete sampling: how many loci and offspring are needed?

We have recently presented models to estimate parentage in breeding systems with multiple mating and incomplete sampling of the candidate parents. Here we provide formulas to calculate the statistical confidence and the optimal trade-off between the number of loci and offspring. These calculations allow an understanding of the statistical significance of the parentage estimates as well as the appropriate sampling regime required to obtain a desired level of confidence. We show that the trade-off generally depends on the parentage of the putative parents. When parentage is low, sampling effort should concentrate on increasing the number of loci. Otherwise, there are similar benefits from increasing the number of loci or offspring. We demonstrate these methods using genetic data from a nest of the bluegill sunfish (Lepomis macrochirus).     

A saturated genetic linkage map of rubber tree (Hevea spp.) based on RFLP, AFLP, microsatellite, and isozyme markers

The first genetic map for Hevea spp. (2n=36) is presented here. It is based on a F₁ progeny of 106 individuals allowing the construction of a female, a male, and a synthetic map according to the pseudo-testcross strategy. Progeny were derived from an interspecific cross between PB260, a H. brasiliensis cultivated clone, and RO38, a H. brasiliensis×H. benthamiana interspecific hybrid clone. The disomic inheritance observed for all the codominant markers scattered on the 2n=36 chromosomes revealed that Hevea behaves as diploids. Homologous linkage groups between the two parental maps were merged using bridge loci. A total of 717 loci constituted the synthetic map, including 301 RFLPs, 388 AFLPs, 18 microsatellites, and 10 isozymes. The markers were assembled into 18 linkage groups, thus reflecting the basic chromosome number, and covered a total distance of 2144 cM. Nine markers were found to be unlinked. Segregation distortion was rare (1.4%). Average marker density was 1 per 3 cM. Comparison of the distance between loci in the parental maps revealed significantly less meiotic recombination in the interspecific hybrid male parent than in the female parent. Hevea origin and genome organisation are discussed. Received: 2 February 1999 / Accepted: 11 March 1999     

Estimating pairwise relatedness from dominant genetic markers

Knowledge of the genetic relatedness between a pair of individuals is important in many research areas of quantitative genetics, conservation genetics, evolution and ecology. Many estimators have been developed to estimate such pairwise relatedness (r) using codominant markers, such as microsatellites and enzymes. In contrast, only two estimators are proposed to use dominant markers, such as random amplified polymorphic DNAs (RAPDs) and amplified fragment length polymorphisms (AFLPs), in relatedness inference. They are both biased estimators, and their statistical properties and robustness to the sampling errors in allele frequency have not been investigated. In this short paper, I propose two new pairwise relatedness estimators for dominant markers, and compare them in precision, accuracy and robustness to sampling with the two previous estimators using simulations. It was found that the new estimator based on the least squares approach is unbiased when allele frequencies are known or estimated from a sample without correcting for sampling effects. It has, however, a low precision and as a result, an intermediate overall performance among the four estimators in terms of the mean squared deviation (MSD) of estimates from actual values of r. The new estimator based on a similarity index is slightly biased but has generally the lowest MSD among the four estimators compared, regardless of the number of loci, type of actual relationships, allele frequencies known or estimated from samples. Simulations also show that the confidence intervals estimated by bootstrapping are appropriate for different estimators provided that the number of loci used in the estimation is not small.     

INFERENCE OF SPERM COMPETITION FROM BROODS OF FIELD-CAUGHT DROSOPHILA

In field studies of multiple mating and sperm competition there typically is no experimental control over the number of times that a female mates, the interval between matings, or the genetic identity of multiple fathers contributing to a brood. Irrespective of this complexity, high-resolution molecular markers can be used to assign paternity with considerable confidence. This study employed two highly heterozygous microsatellite loci to assess multiple paternity and sperm displacement in a sample of broods taken from a natural population of Drosophila melanogaster. The large number of alleles present at each of the loci makes it difficult to derive explicit maximum-likelihood estimates for multiple paternity and sperm displacement from brood samples. Monte Carlo simulations were used to estimate maximum-likelihood parameters for the distribution of female remating frequency and the proportion of offspring sired by the second or subsequent mating males. Estimates were made based on genotypes scored at two distinct marker loci because they were found to give statistically homogeneous results. Fitting a Poisson distribution of number of matings, the mean number of males mated by a female was 1.82. The sperm displacement parameter estimated from doubly mated females were 0.79 and 0.86 for the two loci (0.83 for the joint estimate). The overall probability that a multiply mated female will be misclassified as singly mated was only 0.006, which indicates that microsatellites can provide excellent resolution for identifying multiple mating. In addition, microsatellites can be used to generate relatively precise estimates of sperm precedence in brood-structured samples from a natural population.     

An estimator for pairwise relatedness using molecular markers

I propose a new estimator for jointly estimating two-gene and four-gene coefficients of relatedness between individuals from an outbreeding population with data on codominant genetic markers and compare it, by Monte Carlo simulations, to previous ones in precision and accuracy for different distributions of population allele frequencies, numbers of alleles per locus, actual relationships, sample sizes, and proportions of relatives included in samples. In contrast to several previous estimators, the new estimator is well behaved and applies to any number of alleles per locus and any allele frequency distribution. The estimates for two- and four-gene coefficients of relatedness from the new estimator are unbiased irrespective of the sample size and have sampling variances decreasing consistently with an increasing number of alleles per locus to the minimum asymptotic values determined by the variation in identity-by-descent among loci per se, regardless of the actual relationship. The new estimator is also robust for small sample sizes and for unknown relatives being included in samples for estimating allele frequencies. Compared to previous estimators, the new one is generally advantageous, especially for highly polymorphic loci and/or small sample sizes.     

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)     

Inferring relatedness and heritability using molecular markers in radiata pine

A set of eight unlinked microsatellite markers was used to estimate relatedness among 355 individuals of a Pinus radiata breeding population. The average performance of open-pollinated progeny of each individual, for wood density, was considered to represent the phenotype of all 355 individuals. Marker-based estimates of relationship were compared with the pedigree-based coefficients of relationships. The phenotypic similarity among all pairs of individuals was regressed on marker-estimated relatedness to estimate the inheritance of wood density. The marker-based estimate of heritability was compared with that obtained using classical quantitative genetic methods. Overall, a low correlation (0.13) was observed between marker-based and pedigree-based estimates of relatedness. After discarding negative estimates of relatedness, the average coefficient of relationship among known groups of maternal half-sibs, full-sibs and unrelated individuals, increased from 0.24 to 0.29 (0.25 expected), from 0.43 to 0.48 (0.50 expected) and from –0.04 to 0.15 (0 expected), respectively. Marker-based and conventional estimates of heritability of wood density were 0.79 and 0.38, respectively. However, by using only marker loci with expected Hardy–Weinberg frequencies, marker-based estimate of heritability was 0.33, which is very similar to that obtained from conventional approaches. The use of molecular markers to understand quantitative genetic variation is discussed.     

Mapping Mendelian Factors Underlying Quantitative Traits Using RFLP Linkage Maps

The advent of complete genetic linkage maps consisting of codominant DNA markers [typically restriction fragment length polymorphisms (RFLPs)] has stimulated interest in the systematic genetic dissection of discrete Mendelian factors underlying quantitative traits in experimental organisms. We describe here a set of analytical methods that modify and extend the classical theory for mapping such quantitative trait loci (QTLs). These include: (i) a method of identifying promising crosses for QTL mapping by exploiting a classical formula of SEWALL WRIGHT; (ii) a method (interval mapping) for exploiting the full power of RFLP linkage maps by adapting the approach of LOD score analysis used in human genetics, to obtain accurate estimates of the genetic location and phenotypic effect of QTLs; and (iii) a method (selective genotyping) that allows a substantial reduction in the number of progeny that need to be scored with the DNA markers. In addition to the exposition of the methods, explicit graphs are provided that allow experimental geneticists to estimate, in any particular case, the number of progeny required to map QTLs underlying a quantitative trait.     

First-generation linkage map of the warningly colored butterfly Heliconius erato

We report the first genetic linkage map of Heliconius erato, a species that shows remarkable variation in its warningly colored wing patterns. We use crosses between H. erato and its sister species, H. himera, to place two major color pattern genes, D and Cr, on a linkage map containing AFLP, allozyme, microsatellite and single-copy nuclear loci. We identified all 21 linkage groups in an initial genetic screen of 22 progeny from an F1 female x male H. himera family. Of the 229 markers, 87 used to identify linkage groups were also informative in 35 progeny from a sibling backcross (H. himera female x F1 male). With these, and an additional 33 markers informative in the second family, we constructed recombinational maps for 19 of the 21 linkage groups. These maps varied in length from 18.1 to 431.1 centimorgans (cM) and yielded an estimated total length of 2400 cM. The average distance between markers was 23 cM, and eight of the 19 linkage groups, including the sex chromosome (Z) and the chromosome containing the Cr locus, contained two or more codominant anchor loci. Of the three potential candidate genes mapped here, Cubitus interruptus (Ci), Decapentaplegic (Dpp) and Wingless (Wg), only Ci was linked, although loosely, to a known Heliconius color pattern locus. This work is an important first step for constructing a denser genetic map of the H. erato color pattern radiation and for a comparative genomic study of the architecture of mimicry in Heliconius butterflies.     

Exclusion probabilities for pedigree testing farm animals

Pedigree testing, using genetic markers, may be undertaken for a variety of situations, of which the classical paternity testing is only one. This has not always been made clear in the literature. Exclusion probabilities associated with various testing situations, including the use of autosomal or X-linked codominant marker systems with any number of alleles, are presented. These formulae can be used to determine the appropriate exclusion probability for the situation being investigated. One such situation is where sire groups of progeny are to be verified without knowledge of the dams' genotypes, in which case the classical paternity exclusion probability is too high, and if used may result in an optimistic declaration about the progeny that have not been excluded. On the other hand, if mating pairs are known then incorrect progeny can be excluded at a higher rate than suggested by paternity exclusion calculations. The formulae also assist in determining the usefulness of X-linked markers, particularly if the pedigree checks involve progeny of only one sex. A system of notation that is useful for the algebraic manipulation of genetic probabilities, including exclusion probabilities as presented here, is also given.     

送春与多花兰种间杂交后代的ISSR分析

该文使用简单重复序列间( ISSR)分子标记,对送春与多花兰种间杂交后代进行了研究。结果表明：从80个ISSR引物中筛选出14个扩增效果稳定的ISSR引物,对两亲本和59个F1代个体进行了ISSR扩增,得到107个扩增位点,扩增的片段大小位于90~2100 bp之间,平均每个引物扩增7.64条条带,得到11种类型的带。 ISSR标记在送春×多花兰的F1代中表现出一定的多态性,分离频率为44.86％,分离位点有83.33％符合孟德尔1︰1或3︰1的分离规律,产生偏孟德尔分离的位点占12.50％,余下的4.17％属于特殊分离带型。可能导致后代变异的位点为偏孟德尔分离的6条带、缺失的8条带或新生成的2条带。聚类图中父本和母本与F1代个体间的遗传距离较远,59个杂交后代先聚集成一组,再同母本相聚为一组,最后才同父本聚在一起,59个杂种均偏母本型。送春与多花兰的杂交后代在植株形态、染色体、遗传物质方面都具备双亲特点,61个个体间的ISSR分子量标记结果和植株形态学特征都说明,59个F1代杂种包含送春和多花兰的遗传特性是真杂种;F1代杂种既有双亲的互补特征带,又有双亲的重组片断即产生新的特异带,这说明送春与多花兰的杂交后代具有遗传变异的特点。该研究结果可以有效地对杂交后代进行定向选择,为兰花的杂交育种提供了分子依据。     

On the Potential for Estimating the Effective Number of Breeders from Heterozygote-Excess in Progeny

The important parameter of effective population size is rarely estimable directly from demographic data. Indirect estimates of effective population size may be made from genetic data such as temporal variation of allelic frequencies or linkage disequilibrium in cohorts. We suggest here that an indirect estimate of the effective number of breeders might be based on the excess of heterozygosity expected in a cohort of progeny produced by a limited number of males and females. In computer simulations, heterozygote excesses for 30 unlinked loci having various numbers of alleles and allele-frequency profiles were obtained for cohorts produced by samples of breeders drawn from an age-structured population and having known variance in reproductive success and effective number. The 95% confidence limits around the estimate contained the true effective population size in 70 of 72 trials and the Spearman rank correlation of estimated and actual values was 0.991. An estimate based on heterozygote excess might have certain advantages over the previous estimates, requiring only single-locus and single-cohort data, but the sampling error among individuals and the effect of departures from random union of gametes still need to be explored.     

A recoding scheme for X-linked and pseudoautosomal loci to be used with computer programs for autosomal LOD-score analysis

We present a recoding scheme that allows for a parametric multipoint X-chromosomal linkage analysis of dichotomous traits in the context of a computer program for autosomes that can use trait models with imprinting. Furthermore, with this scheme, it is possible to perform a joint multipoint analysis of X-linked and pseudoautosomal loci. It is required that (1) the marker genotypes of all female nonfounders are available and that (2) there are no male nonfounders who have daughters in the pedigree. The second requirement does not apply if the trait locus is pseudoautosomal. The X-linked marker loci are recorded by adding a dummy allele to the males' hemizygous genotypes. For modelling an X-linked trait locus, five different liability classes are defined, in conjunction with a paternal imprinting model for male nonfounders. The formulation aims at the mapping of a diallelic trait locus relative to an arbitrary number of codominant markers with known genetic distances, in cases where a program for a genuine X-chromosomal analysis is not available.     

A MARKER-BASED METHOD FOR INFERENCES ABOUT QUANTITATIVE INHERITANCE IN NATURAL POPULATIONS

A marker-based method for studying quantitative genetic characters in natural populations is presented and evaluated. The method involves regressing quantitative trait similarity on marker-estimated relatedness between individuals. A procedure is first given for estimating the narrow sense heritability and additive genetic correlations among traits, incorporating shared environments. Estimation of the actual variance of relatedness is required for heritability, but not for genetic correlations. The approach is then extended to include isolation by distance of environments, dominance, and shared levels of inbreeding. Investigations of statistical properties show that good estimates do not require great marker polymorphism, but rather require significant variation of actual relatedness; optimal allocation generally favors sampling many individuals at the expense of assaying fewer marker loci; when relatedness declines with physical distance, it is optimal to restrict comparisons to within a certain distance; the power to estimate shared environments and inbreeding effects is reasonable, but estimates of dominance variance may be difficult under certain patterns of relationship; and any linkage of markers to quantitative trait loci does not cause significant problems. This marker-based method makes possible studies with long-lived organisms or with organisms difficult to culture, and opens the possibility that quantitative trait expression in natural environments can be analyzed in an unmanipulative way.     

Spurious linkage between markers in QTL mapping

Selective genotyping of extreme progeny is a powerful method to increase the information content per individual when looking for quantitative trait loci (QTLs) using molecular markers for which a map is known. However, if marker information from the selected individuals is used to construct the map of the markers, this can lead to distorted segregation of the markers that in turn can lead to the estimation of a spurious linkage between independently inherited markers. The mistaken estimation of linkage between independently inherited markers will occur when there are two (or more) independently inherited QTLs linked to two (or more) markers and the same individuals are used to estimate the map of the markers and to do the QTL estimation. The incorrect linkage occurs because in selecting individuals from the tails of the phenotypic distribution we will also be selecting certain combinations of the markers instead of obtaining a random sample of the true distribution of the marker genotypes. Analytical results are outlined and the analyses of a simulated data set illustrate the problems that could arise when data from individuals chosen by selective genotyping are incorrectly employed to construct a marker map. A strategy is proposed to remedy this problem.     

Understanding the population genetic structure of Gleditsia triacanthos L.: seed dispersal and variation in female reproductive success

Fine-scale genetic structuring is influenced by a variety of ecological factors and can directly affect the evolutionary dynamics of plant populations by influencing effective population size and patterns of viability selection. In many plant species, genetic structuring within populations may result from highly localized patterns of seed dispersal around maternal plants or by the correlated dispersal and recruitment of siblings from the same fruit. This fine-scale genetic structuring may be enhanced if female parents vary significantly in their reproductive success. To test these hypotheses, we used genetic data from 17 allozyme loci and a maximum-likelihood, ‘maternity-analysis’ model to estimate individual female fertilities for maternal trees across a large number of naturally established seedlings and saplings in two populations of Gleditsia triacanthos L. (Leguminosae). Maximum-likelihood fertility estimates showed that the three highest fertility females accounted for 58% of the 313 progeny at the first site and 46% of the 651 progeny at the second site, whereas 18 of 35 and 16 of 34 females, respectively, had fertility estimates that did not exceed 1%. Additional analyses of the second site found individual female fertility to vary significantly both within and among juvenile age classes. Female fertility at the first site was weakly correlated with maternal tree size and spatial location relative to the open, old-field portions of the population, where the great majority of seedlings and saplings were growing, but no such correlations were found at the second site. Estimates of realized seed dispersal distances indicated that dispersal was highly localized at the first site, but was nearly random at the second site, possibly reflecting differences between the two sites in the behaviour of animal dispersers. The combined estimates of seed dispersal patterns and fertility variation are sufficient to explain previously described patterns of significant fine-scale spatial genetic structure in these two populations. In general, our results demonstrate that effective seed dispersal distributions may vary significantly from population to population of a species due to the unpredictable behaviour of secondary dispersers. Consequently, the effects of seed dispersal on realized fine-scale genetic structure may also be relatively unpredictable.     

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.