The Contribution of Quantitative Trait Loci and Neutral Marker Loci to the Genetic Variances and Covariances among Quantitative Traits in Random Mating Populations

Using Cockerham's approach of orthogonal scales, we develop genetic models for the effect of an arbitrary number of multiallelic quantitative trait loci (QTLs) or neutral marker loci (NMLs) upon any number of quantitative traits. These models allow the unbiased estimation of the contributions of a set of marker loci to the additive and dominance variances and covariances among traits in a random mating population. The method has been applied to an analysis of allozyme and quantitative data from the European oyster. The contribution of a set of marker loci may either be real, when the markers are actually QTLs, or apparent, when they are NMLs that are in linkage disequilibrium with hidden QTLs. Our results show that the additive and dominance variances contributed by a set of NMLs are always minimum estimates of the corresponding variances contributed by the associated QTLs. In contrast, the apparent contribution of the NMLs to the additive and dominance covariances between two traits may be larger than, equal to or lower than the actual contributions of the QTLs. We also derive an expression for the expected variance explained by the correlation between a quantitative trait and multilocus heterozygosity. This correlation explains only a part of the genetic variance contributed by the markers, i.e., in general, a combination of additive and dominance variances and, thus, provides only very limited information relative to the method supplied here.     

Neutral Genetic Patterns for Expanding Populations with Nonoverlapping Generations

We investigate the inside dynamics of solutions to integrodifference equations to understand the genetic consequences of a population with nonoverlapping generations undergoing range expansion. To obtain the inside dynamics, we decompose the solution into neutral genetic components. The inside dynamics are given by the spatiotemporal evolution of the neutral genetic components. We consider thin-tailed dispersal kernels and a variety of per capita growth rate functions to classify the traveling wave solutions as either pushed or pulled fronts. We find that pulled fronts are synonymous with the founder effect in population genetics. Adding overcompensation to the dynamics of these fronts has no impact on genetic diversity in the expanding population. However, growth functions with a strong Allee effect cause the traveling wave solution to be a pushed front preserving the genetic variation in the population. In this case, the contribution of each neutral fraction can be computed by a simple formula dependent on the initial distribution of the neutral fractions, the traveling wave solution, and the asymptotic spreading speed.     

Structure of Genetic Variation within and between Populations of Mycophagous Drosophila

Patterns of genetic variation within and between populations of five species of mycophagous Drosophila were examined by gel electrophoresis of several polymorphic loci. Populations of the five species could not be shown to be subdivided into sympatric host-adapted races. Statistically significant, but small, between-host differences in gene frequencies were observed at three of 15 loci. Mean gene frequencies at all loci were similar in New York and Tennessee, and, with one exception, relatively little genetic differentiation was observed among study sites within those two regions. Gene frequencies generally were stable over several years of collecting as well. The unpredictable nature of the fungal hosts may preclude the site fidelity and continuity of diversifying selection necessary for adaptive divergence of populations.     

Comparative Studies on the Estimation of Genetic Variances by Several Variance Components Estimation Method

Using a quantitative genetic model, this paper compares four different methods for estimating genetic variance components. Given various genetic parameters, data were generated and estimates computed. The number of negative estimates, the sample mean, the sample variance, and the sample mean squared error were computed for each method. It is shown that, if the genetic values are not very small, the traditional MATHER -JINKS method is at least as good as any other method. The ML method might be preferable only if the genetic values are very small and the number of loci large.     

胚乳性状的世代遗传方差

本文论述由两个纯系杂交而衍生的各种世代群体的胚乳性状的遗传方差分量。根据有关世代胚乳的遗传组成和加性-显性模型下的基因效应,导出了它们的总的、株间的和自交世代的遗传方差,并分别列于表1—3。     

Variances of the average numbers of nucleotide substitutions within and between populations

Statistical methods for computing the variances of nucleotide diversity within populations and of nucleotide divergence between populations are developed. Both variances are computed by finding the phylogenetic relationships of the DNA sequences studied through the unweighted pair-group method or some other tree-making method. The methods developed are applicable to both DNA sequence and restriction-site map data.     

Hidden Genetic Variability within Electromorphs in Finite Populations

The amount of hidden genetic variability within electromorphs in finite populations is studied by using the infinite site model and stepwise mutation model simultaneously. A formula is developed for the bivariate probability generating function for the number of codon differences and the number of electromorph state differences between two randomly chosen cistrons. Using this formula, the distribution as well as the mean and variance of the number of codon differences between two identical or nonidentical electromorphs are studied. The distribution of the number of codon differences between two randomly chosen identical electromorphs is similar to the geometric distribution but more leptokurtic. Studies are also made on the number of codon differences between two electromorphs chosen at random one from each of two populations which have been separated for an arbitrary number of generations. It is shown that the amount of hidden genetic variability is very large if the product of effective population size and mutation rate is large.     

Realized Sampling Variances of Estimates of Genetic Parameters and the Difference between Genetic and Phenotypic Correlations

A data set of 1572 heritability estimates and 1015 pairs of genetic and phenotypic correlation estimates, constructed from a survey of published beef cattle genetic parameter estimates, provided a rare opportunity to study realized sampling variances of genetic parameter estimates. The distribution of both heritability estimates and genetic correlation estimates, when plotted against estimated accuracy, was consistent with random error variance being some three times the sampling variance predicted from standard formulae. This result was consistent with the observation that the variance of estimates of heritabilities and genetic correlations between populations were about four times the predicted sampling variance, suggesting few real differences in genetic parameters between populations. Except where there was a strong biological or statistical expectation of a difference, there was little evidence for differences between genetic and phenotypic correlations for most trait combinations or for differences in genetic correlations between populations. These results suggest that, even for controlled populations, estimating genetic parameters specific to a given population is less useful than commonly believed. A serendipitous discovery was that, in the standard formula for theoretical standard error of a genetic correlation estimate, the heritabilities refer to the estimated values and not, as seems generally assumed, the true population values.     

Sampling Variances of Heterozygosity and Genetic Distance

Mathematical formulae for the sampling variances of average heterozygosity and Nei's genetic distance are developed. These sampling variances are decomposed into their two components, i.e. the inter-locus and intra-locus variances. The relationship between the number of loci and the number of individuals per locus to be examined for estimating average heterozygosity and genetic distance is also discussed. The utility of the inter-locus variance of heterozygosity for studying the mechanism of maintenance of genetic variability in populations is indicated.     

Neutral and Adaptive Drivers of Microgeographic Genetic Divergence within Continuous Populations: The Case of the Neotropical Tree Eperua falcata (Aubl.)

BackgroundIn wild plant populations, genetic divergence within continuous stands is common, sometimes at very short geographical scales. While restrictions to gene flow combined with local inbreeding and genetic drift may cause neutral differentiation among subpopulations, microgeographical variations in environmental conditions can drive adaptive divergence through natural selection at some targeted loci. Such phenomena have recurrently been observed in plant populations occurring across sharp environmental boundaries, but the interplay between selective processes and neutral genetic divergence has seldom been studied.MethodsWe assessed the extent of within-stand neutral and environmentally-driven divergence in the Neotropical tree Eperua falcate Aubl. (Fabaceae) through a genome-scan approach. Populations of this species grow in dense stands that cross the boundaries between starkly contrasting habitats. Within-stand phenotypic and candidate-gene divergence have already been proven, making this species a suitable model for the study of genome-wide microgeographic divergence. Thirty trees from each of two habitats (seasonally flooded swamps and well-drained plateaus) in two separate populations were genotyped using thousands of AFLPs markers. To avoid genotyping errors and increase marker reliability, each sample was genotyped twice and submitted to a rigorous procedure for data cleaning, which resulted in 1196 reliable and reproducible markers.ResultsDespite the short spatial distances, we detected within-populations genetic divergence, probably caused by neutral processes, such as restrictions in gene flow. Moreover, habitat-structured subpopulations belonging to otherwise continuous stands also diverge in relation to environmental variability and habitat patchiness: we detected convincing evidence of divergent selection at the genome-wide level and for a fraction of the analyzed loci (comprised between 0.25% and 1.6%). Simulations showed that the levels of differentiation for these outliers are compatible with scenarios of strong divergent selection.     

Association Tests for a Censored Quantitative Trait and Candidate Genes in Structured Populations with Multilevel Genetic Relatedness

Summary Several statistical methods for detecting associations between quantitative traits and candidate genes in structured populations have been developed for fully observed phenotypes. However, many experiments are concerned with failure‐time phenotypes, which are usually subject to censoring. In this article, we propose statistical methods for detecting associations between a censored quantitative trait and candidate genes in structured populations with complex multiple levels of genetic relatedness among sampled individuals. The proposed methods correct for continuous population stratification using both population structure variables as covariates and the frailty terms attributable to kinship. The relationship between the time‐at‐onset data and genotypic scores at a candidate marker is modeled via a parametric Weibull frailty accelerated failure time (AFT) model as well as a semiparametric frailty AFT model, where the baseline survival function is flexibly modeled as a mixture of Polya trees centered around a family of Weibull distributions. For both parametric and semiparametric models, the frailties are modeled via an intrinsic Gaussian conditional autoregressive prior distribution with the kinship matrix being the adjacency matrix connecting subjects. Simulation studies and applications to the Arabidopsis thaliana line flowering time data sets demonstrated the advantage of the new proposals over existing approaches.     

Maximum Likelihood Estimation of Genetic Parameters for Quantitative traits from Autotetraploid Self-Fertilized Populations

Assuming equality of genotypic effects over different loci, this paper provides an ML procedure for estimating genetic parameters for quantitative traits from autotetraploid self-fertilized populations. The results are illustrated by computer generated data involving P₁, P₂, F₂, B₁ and B₂ populations.     

Using Molecular Markers to Estimate Quantitative Trait Locus Parameters: Power and Genetic Variances for Unreplicated and Replicated Progeny

Many of the progeny types used to estimate quantitative trait locus (QTL) parameters can be replicated, e.g., recombinant inbred, doubled haploid, and F3 lines. These parameters are estimated using molecular markers or QTL genotypes estimated from molecular markers as independent variables. Experiment designs for replicated progeny are functions of the number of replications per line (r) and the number of replications per QTL genotype (n). The value of n is determined by the size of the progeny population (N), the progeny type, and the number of simultaneously estimated QTL parameters (q - 1). Power for testing hypotheses about means of QTL genotypes is increased by increasing r and n, but the effects of these factors have not been quantified. In this paper, we describe how power is affected by r, n, and other factors. The genetic variance between lines nested in QTL genotypes (sigma 2n:q) is the fraction of the genetic variance between lines (sigma 2n) which is not explained by simultaneously estimated intralocus and interlocus QTL parameters (phi 2Q); thus, sigma 2n:q = sigma 2n - phi 2Q. If sigma 2n:q not equal to 0, then power is not efficiently increased by increasing r and is maximized by maximizing n and using r = 1; however, if sigma 2n:q = 0, then r and n affect power equally and power is efficiently increased by increasing r and is maximized by maximizing N.r. Increasing n efficiently increases power for a wide range of values of sigma 2n:q.sigma 2n:q = 0 when the genetic variance between lines is fully explained by QTL parameters (sigma 2n = phi 2Q).(ABSTRACT TRUNCATED AT 250 WORDS)     

Genetic Connectivity among and Self-Replenishment within Island Populations of a Restricted Range Subtropical Reef Fish

Marine protected areas (MPAs) are increasingly being advocated and implemented to protect biodiversity on coral reefs. Networks of appropriately sized and spaced reserves can capture a high proportion of species diversity, with gene flow among reserves presumed to promote long term resilience of populations to spatially variable threats. However, numerically rare small range species distributed among isolated locations appear to be at particular risk of extinction and the likely benefits of MPA networks are uncertain. Here we use mitochondrial and microsatellite data to infer evolutionary and contemporary gene flow among isolated locations as well as levels of self-replenishment within locations of the endemic anemonefish Amphiprion mccullochi, restricted to three MPA offshore reefs in subtropical East Australia. We infer high levels of gene flow and genetic diversity among locations over evolutionary time, but limited contemporary gene flow amongst locations and high levels of self-replenishment (68 to 84%) within locations over contemporary time. While long distance dispersal explained the species’ integrity in the past, high levels of self-replenishment suggest locations are predominantly maintained by local replenishment. Should local extinction occur, contemporary rescue effects through large scale connectivity are unlikely. For isolated islands with large numbers of endemic species, and high local replenishment, there is a high premium on local species-specific management actions.     

Estimation of Additive Genetic Variance Components in Aquaculture Populations Selectively Pedigreed by DNA Fingerprinting

A method to estimate genetic variance components in populations partially pedigreed by DNA fingerprinting is presented. The focus is on aquaculture, where breeding procedures may produce thousands of individuals. In aquaculture populations the individuals available for measurement will often be selected, i.e. will come from the upper tail of a size‐at‐age distribution, or the lower tail of an age‐at‐maturity distribution etc. Selection typically occurs by size grading during grow‐out and/or choice of superior fish as broodstock. The method presented in this paper enables us to estimate genetic variance components when only a small proportion of individuals, those with extreme phenotypes, have been identified by DNA fingerprinting. We replace the usual normal density by appropriate robust least favourable densities to ensure the robustness of our estimates. Standard analysis of variance or maximum likelihood estimation cannot be used when only the extreme progeny have been pedigreed because of the biased nature of the estimates. In our model‐based procedure a full robust likelihood function is defined, in which the missing information about non‐extreme progeny has been taken into account. This robust likelihood function is transformed into a computable function which is maximized to get the estimates. The estimates of sire and dam additive variance components are significantly and uniformly more accurate than those obtained by any of the standard methods when tested on simulated population data and have desirable robustness properties.     

遗传标记与数量性状基因间连锁关系的分析

本文讨论标记基因与数量性状主基因连锁关系的一般分析方法,包括重组值的估计和有关遗传假设的测验。并以我们水稻遗传试验中两个具有互补和重叠作用的卷叶基因和一个矮秆基因试验结果的分析为例作了较详细的示范。     

The Significance of Genetic Polymorphisms within and between Founder Populations of Ceratitis capitata (Wied.) from Argentina

Background

The Mediterranean fruit fly Ceratitis Capitata (DIPTERA: Tephritidae) is a major agricultural pest in Argentina. One main cause for the success of non-contaminant control programs based on genetic strategies is compatibility between natural and laboratory germplasms.A comprehensive characterization of the fruit fly based on genetic studies and compatibility analysis was undertaken on two founder populations from the provinces of Buenos Aires and Mendoza, used in pioneering sterile male technique control programmes in our country. The locations are 1,000 km apart from each other.

Methodology/Principal Findings

We compared the genetic composition of both populations based on cytological, physiological and morphological characterization. Compatibility studies were performed in order to determine the presence of isolation barriers. Results indicate that the Buenos Aires germplasm described previously is partially different from that of the Mendoza population. Both laboratory colonies are a reservoir of mutational and cytological polymorphisms. Some sexual chromosome variants such as the XL and the YL resulting from attachment of a B-chromosome to the X-chromosome or Y-chromosome behave as a lethal sex-linked factor. Our results also show incompatibility between both germplasms and pre-zygotic isolation barriers between them. Our evidence is consistent with the fact that polymorphisms are responsible for the lack of compatibility.

Conclusions

The genetic control mechanism should be directly produced in the germplasm of the target population in order to favour mating conditions. This is an additional requirement for the biological as well as economic success of control programs based on genetic strategies such as the sterile insect technique. The analysis of representative samples also revealed natural auto-control mechanisms which could be used in modifying pest population dynamics.