Using genetic markers to directly estimate gene flow and reproductive success parameters in plants on the basis of naturally regenerated seedlings

Estimating seed and pollen gene flow in plants on the basis of samples of naturally regenerated seedlings can provide much needed information about "realized gene flow," but seems to be one of the greatest challenges in plant population biology. Traditional parentage methods, because of their inability to discriminate between male and female parentage of seedlings, unless supported by uniparentally inherited markers, are not capable of precisely describing seed and pollen aspects of gene flow realized in seedlings. Here, we describe a maximum-likelihood method for modeling female and male parentage in a local plant population on the basis of genotypic data from naturally established seedlings and when the location and genotypes of all potential parents within the population are known. The method models female and male reproductive success of individuals as a function of factors likely to influence reproductive success (e.g., distance of seed dispersal, distance between mates, and relative fecundity--i.e., female and male selection gradients). The method is designed to account for levels of seed and pollen gene flow into the local population from unsampled adults; therefore, it is well suited to isolated, but also wide-spread natural populations, where extensive seed and pollen dispersal complicates traditional parentage analyses. Computer simulations were performed to evaluate the utility and robustness of the model and estimation procedure and to assess how the exclusion power of genetic markers (isozymes or microsatellites) affects the accuracy of the parameter estimation. In addition, the method was applied to genotypic data collected in Scots pine (isozymes) and oak (microsatellites) populations to obtain preliminary estimates of long-distance seed and pollen gene flow and the patterns of local seed and pollen dispersal in these species.     

Tracking the motion of hidden segments using kinematic constraints and Kalman filtering

Motion capture for biomechanical applications involves in almost all cases sensors or markers that are applied to the skin of the body segments of interest. This paper deals with the problem of estimating the movement of connected skeletal segments from 3D position data of markers attached to the skin. The use of kinematic constraints has been shown previously to reduce the error in estimated segment movement that are due to skin and muscles moving with respect to the underlying segment. A kinematic constraint reduces the number of degrees of freedom between two articulating segments. Moreover, kinematic constraints can help reveal the movement of some segments when the 3D marker data otherwise are insufficient. Important cases include the human ankle complex and the phalangeal segments of the horse, where the movement of small segments is almost completely hidden from external observation by joint capsules and ligaments. This paper discusses the use of an extended Kalman filter for tracking a system of connected segments. The system is modeled using rigid segments connected by simplified joint models. The position and orientation of the mechanism are specified by a set of generalized coordinates corresponding to the mechanism's degrees of motion. The generalized coordinates together with their first time derivatives can be used as the state vector of a state space model governing the kinematics of the mechanism. The data collected are marker trajectories from skin-mounted markers, and the state vector is related to the position of the markers through a nonlinear function. The Jacobian of this function is derived. The practical use of the method is demonstrated on a model of the distal part of the limb of the horse. Monte Carlo simulations of marker data for a two-segment system connected by a joint with three degrees of freedom indicate that the proposed method gives significant improvement over a method, which does not make use of the joint constraint, but the method requires that the model is a good approximation of the true mechanism. Applying the method to data on the movement of the four distal-most segments of the horse's limb shows good between trial consistency and small differences between measured marker positions and marker positions predicted by the model.     

Vocal learning by greater spear-nosed bats.

Vocal learning is well known among passerine and psittacine birds, but most data on mammals are equivocal. Specific benefits of vocal learning are poorly understood for most species. One case where vocal learning should be favoured by selection is where calls indicate group membership and group mates are unrelated. Female greater spear-nosed bats, Phyllostomus hastatus, live in stable groups of unrelated bats and use loud, broadband calls to coordinate foraging movements of social group mates. Bats benefit from group foraging. Calls differ between female social groups and cave colonies, and playback experiments demonstrate that bats perceive these acoustic differences. Here I show that the group distinctive structure of calls arises through vocal learning. Females change call structure when group composition changes, resulting in increased similarity among new social group mates. Comparisons of transfers with age-matched half-sibs indicate that call changes are not simply due to maturation, the physical environment or heredity. These results suggest that studies testing vocal learning in mammals could profit by focusing on vocalizations that signify group membership.     

Genomic selection: prediction of accuracy and maximisation of long term response

Genomic selection refers to the use of dense markers covering the whole genome to estimate the breeding value of selection candidates for a quantitative trait. This paper considers prediction of breeding value based on a linear combination of the markers. In this case the best estimate of each marker’s effect is the expectation of the effect conditional on the data. To calculate this requires a prior distribution of marker effects. If the marker effects are normally distributed with constant variance, BLUP can be used to calculate the estimated effects of the markers and hence the estimated breeding value (EBV). In this case the model is equivalent to a conventional animal model in which the relationship matrix among the animals is estimated from the markers instead of the pedigree. The accuracy of the EBV can approach 1.0 but a very large amount of data is required. An alternative model was investigated in which only some markers have non-zero effects and these effects follow a reflected exponential distribution. In this case the expected effect of a marker is a non-linear function of the data such that apparently small effects are regressed back almost to zero and consequently these markers can be deleted from the model. The accuracy in this case is considerably higher than when marker effects are normally distributed. If genomic selection is practiced for several generations the response declines in a manner that can be predicted from the marker allele frequencies. Genomic selection is likely to lead to a more rapid decline in the selection response than phenotypic selection unless new markers are continually added to the prediction of breeding value. A method to find the optimum index to maximise long term selection response is derived. This index varies the weight given to a marker according to its frequency such that markers where the favourable allele has low frequency receive more weight in the index.     

A General Monte Carlo Method for Mapping Multiple Quantitative Trait Loci

In this paper we address the mapping of multiple quantitative trait loci (QTLs) in line crosses for which the genetic data are highly incomplete. Such complicated situations occur, for instance, when dominant markers are used or when unequally informative markers are used in experiments with outbred populations. We describe a general and flexible Monte Carlo expectation-maximization (Monte Carlo EM) algorithm for fitting multiple-QTL models to such data. Implementation of this algorithm is straightforward in standard statistical software, but computation may take much time. The method may be generalized to cope with more complex models for animal and human pedigrees. A practical example is presented, where a three-QTL model is adopted in an outbreeding situation with dominant markers. The example is concerned with the linkage between randomly amplified polymorphic DNA (RAPD) markers and QTLs for partial resistance to Fusarium oxysporum in lily.     

The evolution of sex differences in mate searching when females benefit: new theory and a comparative test

Sexual selection is thought to have led to searching as a profitable, but risky way of males obtaining mates. While there is great variation in which sex searches, previous theory has not considered search evolution when both males and females benefit from multiple mating. We present new theory and link it with data to bridge this gap. Two different search protocols exist between species in the bush-cricket genus Poecilimon (Orthoptera): females search for calling males, or males search for calling females. Poecilimon males also transfer a costly nuptial food gift to their mates during mating. We relate variations in searching protocols to variation in nuptial gift size among 32 Poecilimon taxa. As predicted, taxa where females search produce significantly larger nuptial gifts than those where males search. Our model and results show that search roles can reverse when multiple mating brings about sufficiently strong material benefits to females.     

A spatially explicit model for an Allee effect: why wolves recolonize so slowly in Greater Yellowstone

A reduced probability of finding mates at low densities is a frequently hypothesized mechanism for a component Allee effect. At low densities dispersers are less likely to find mates and establish new breeding units. However, many mathematical models for an Allee effect do not make a distinction between breeding group establishment and subsequent population growth. Our objective is to derive a spatially explicit mathematical model, where dispersers have a reduced probability of finding mates at low densities, and parameterize the model for wolf recolonization in the Greater Yellowstone Ecosystem (GYE). In this model, only the probability of establishing new breeding units is influenced by the reduced probability of finding mates at low densities. We analytically and numerically solve the model to determine the effect of a decreased probability in finding mates at low densities on population spread rate and density. Our results suggest that a reduced probability of finding mates at low densities may slow recolonization rate.     

Stochastic search variable selection for identifying multiple quantitative trait loci

In this article, we utilize stochastic search variable selection methodology to develop a Bayesian method for identifying multiple quantitative trait loci (QTL) for complex traits in experimental designs. The proposed procedure entails embedding multiple regression in a hierarchical normal mixture model, where latent indicators for all markers are used to identify the multiple markers. The markers with significant effects can be identified as those with higher posterior probability included in the model. A simple and easy-to-use Gibbs sampler is employed to generate samples from the joint posterior distribution of all unknowns including the latent indicators, genetic effects for all markers, and other model parameters. The proposed method was evaluated using simulated data and illustrated using a real data set. The results demonstrate that the proposed method works well under typical situations of most QTL studies in terms of number of markers and marker density.     

Computationally efficient sibship and parentage assignment from multilocus marker data

Quite a few methods have been proposed to infer sibship and parentage among individuals from their multilocus marker genotypes. They are all based on Mendelian laws either qualitatively (exclusion methods) or quantitatively (likelihood methods), have different optimization criteria, and use different algorithms in searching for the optimal solution. The full-likelihood method assigns sibship and parentage relationships among all sampled individuals jointly. It is by far the most accurate method, but is computationally prohibitive for large data sets with many individuals and many loci. In this article I propose a new likelihood-based method that is computationally efficient enough to handle large data sets. The method uses the sum of the log likelihoods of pairwise relationships in a configuration as the score to measure its plausibility, where log likelihoods of pairwise relationships are calculated only once and stored for repeated use. By analyzing several empirical and many simulated data sets, I show that the new method is more accurate than pairwise likelihood and exclusion-based methods, but is slightly less accurate than the full-likelihood method. However, the new method is computationally much more efficient than the full-likelihood method, and for the cases of both sexes polygamous and markers with genotyping errors, it can be several orders faster. The new method can handle a large sample with thousands of individuals and the number of markers limited only by the computer memory.     

Paternal Care by Genetic Fathers and Stepfathers I: Reports from Albuquerque Men

We present a biosocial model of human male parental care that allows male parental allocations to be influenced not only by changes in the fitness (welfare) of the recipient offspring, but also by their effects on the man's relationship with the child's mother. The model recognizes four classes of relationships between males and the children they parent: genetic offspring of current mates (combined relationship and parental effort), genetic offspring of previous mates (parental effort solely), step offspring of current mates (relationship effort solely), and stepchildren of previous mates (essentially no expected investment). We test the model using data on parental investments collected from adult males living in Albuquerque, New Mexico, U.S.A. Four measures of paternal investment are examined: the probability that a child attends college (2,191 offspring), the probability that a child who attends college receives money for it (N = 1,212), current financial expenditures on children (N = 635), and the amount of time per week that men spend with children ages 5 to 12 years (N = 2,589). The tests are consistent with a role for relationship effort in parental care: men invest more in the children of their current mates, even when coresidence with offspring is not a confounder.     

Detection of genetically divergent clone mates in apomictic dandelions

This study aims to identify genetically diverged clone mates in apomictic dandelions. Clone mates are defined as individuals that may have diverged as a result of mutation accumulation and that have undergone only clonal reproduction since their most recent common ancestor. Based on distinctive morphology and an aberrant and rare chloroplast haplotype, northwest European individuals of Taraxacum section Naevosa are well suited for the detection of clonal lineages in which mutation has occurred. In the case of strictly clonal reproduction, nuclear genetic variability was expected to be hierarchically organized. Nucleotide polymorphisms in internal transcribed spacer (ITS) sequences, however, were incompatible with a clonal structure of the Norwegian individuals, probably due to persistent ancestral polymorphisms that pre-date the origin of the Naevosa clone. This interpretation is supported by the presence of ITS variants in section Naevosa that were also found in distantly related dandelions. In contrast to the ITS sequence data, amplified fragment length polymorphisms (AFLPs), isozymes and microsatellites strongly supported the contention of prolonged clonal reproduction and mutation accumulation in Norwegian Naevosa. Because these markers are generally considered to be more variable and more rapidly evolving than ITS sequences, mutations in these markers probably evolved after the origin of the clone. Within the Norwegian clone, a surprising number of markers distinguished the clone mates. As a consequence, incorporation of mutation in the detection of clone mates is anticipated to have a big impact on estimates of size, geographical range and age of clones as well as on experimental designs of studies of clonal plants.     

Polymorphic signals of harassed female odonates and the males that learn them support a novel frequency-dependent model

For mate-searching species, the learned mate recognition (LMR) hypothesis assumes that sexual harassment favours signal variation among females, which exploits the receiver ability of males. The model predicts that coevolving males have responded to the female sexual foil by learning to recognize female variants as potential mates. I translate the LMR hypothesis into the language of signal detection theory to explain its novelty as a dynamic, coevolutionary, negative frequency-dependent selection model. Due to gene-environment interactions, males cueing to the morph detected most often should generate positive but often asymmetrical, detection-dependent harassment towards females. Females are expected to sort to an ideal free distribution where harassment costs are equal. At equilibrium, morph fitness, but not necessarily morph frequency, is predicted to be equal. The LMR hypothesis is consistent with recent experimental data and the distribution of colour polymorphisms in the Odonata, predicts general conditions favouring variation in sexual signals, and provides a novel mechanism for speciation via sexual signalling.     

MEASURING THE EFFECTS OF PAIRING SUCCESS,EXTRA-PAIR COPULATIONS AND MATE QUALITY ON THE OPPORTUNITY FOR SEXUAL SELECTION

Sexual selection can act through variation in the number of social mates obtained, variation in mate quality, or variation in success at obtaining extra-pair fertilizations. Because within-pair fertilizations (WPF) and extra-pair fertilizations (EPF) are alternate routes of reproduction, they are additive, rather than multiplicative, components of fitness. We present a method for partitioning total variance in reproductive success (a measure of the opportunity for selection) when fitness components are both additive and multiplicative and use it to partition the variance into components that correspond to each mechanism of sexual selection. Computer simulations show that extra-pair fertilizations can either increase or decrease total variance, depending on the covariance between within-pair and extra-pair success. Simulations also suggest that for socially monogamous species, extra-pair fertilizations have a greater effect than variation in mate quality or pairing status on the opportunity for selection. Application of our model to data gathered for a population of red-winged blackbirds (Agelaius phoeniceus) indicates that most of the variance in male reproductive success was attributable to within-pair sources of variance. Nevertheless, extra-pair copulations increased the opportunity for selection because males varied both in the proportion of their social young that they sired and in the number of extra-pair mates that they obtained. Furthermore, large and positive covariances existed between the number of extra-pair mates a male obtained and both social pairing success and within-pair paternity, indicating that, in this population, males preferred as social mates also were preferred as extra-pair mates.     

Social living mitigates the costs of a chronic illness in a cooperative carnivore

Infection risk is assumed to increase with social group size, and thus be a cost of group living. We assess infection risk and costs with respect to group size using data from an epidemic of sarcoptic mange (Sarcoptes scabiei) among grey wolves (Canis lupus). We demonstrate that group size does not predict infection risk and that individual costs of infection, in terms of reduced survival, can be entirely offset by having sufficient numbers of pack‐mates. Infected individuals experience increased mortality hazards with increasing proportions of infected pack‐mates, but healthy individuals remain unaffected. The social support of group hunting and territory defence are two possible mechanisms mediating infection costs. This is likely a common phenomenon among other social species and chronic infections, but difficult to detect in systems where infection status cannot be measured continuously over time.     

Mate choice and uncertainty in the decision process

The behavior of females in search of a mate determines the likelihood that a high quality male is encountered in the search process and alternative search strategies provide different fitness returns to searchers. Models of search behavior are typically formulated on an assumption that the quality of prospective mates is revealed to searchers without error, either directly or by inspection of a perfectly informative phenotypic character. But recent theoretical developments suggest that the relative performance of a search strategy may be sensitive to any uncertainty associated with the to-be-realized fitness benefit of mate choice decisions. Indeed, uncertainty in the decision process is inevitable whenever unobserved male attributes influence the fitness of searchers. In this paper, we derive solutions to the sequential search strategy and the fixed sample search strategy for the general situation in which observed and unobserved male attributes affect the fitness consequences of female mate choice decisions and we determine how the magnitude of various parameters that are influential in the standard models alter these more general solutions. The distribution of unobserved attributes amongst prospective mates determines the uncertainty of mate choice decisions-the reliability of an observed male character as a predictor of male quality-and the realized functional relationship between an observed male character and the fitness return to searchers. The uncertainty of mate choice decisions induced by unobserved male attributes has no influence on the generalized model solutions. Thus, the results of earlier studies of these search models that rely on the use of a perfectly informative male character apply even if an observed male trait does not reveal the quality of prospective mates with certainty. But the solutions are sensitive to any changes of the distribution of unobserved male attributes that alter the realized functional relationship between an observed character and the fitness return to searchers. For example, the standard sequential search model exhibits a reservation property--the acceptability of prospective mates is delimited by a unique threshold criterion--and the existence of this model property under generalized conditions depends critically on the association between the observed and unobserved male characters. In our formulations of the models we assumed that females use a single male character to evaluate the quality of prospective mates, but the model properties generalize to situations in which male quality is evaluated by a direct inspection of multiple male characters.     

Mating strategies in dominant meerkats: evidence for extra‐pair paternity in relation to genetic relatedness between pair mates

Rates of extra‐pair paternity (EPP) have frequently been associated with genetic relatedness between social mates in socially monogamous birds. However, evidence is limited in mammals. Here, we investigate whether dominant females use divorce or extra‐pair paternity as a strategy to avoid the negative effects of inbreeding when paired with a related male in meerkats Suricata suricatta, a species where inbreeding depression is evident for several traits. We show that dominant breeding pairs seldom divorce, but that rates of EPP are associated with genetic similarity between mates. Although extra‐pair males are no more distantly related to the female than social males, they are more heterozygous. Nevertheless, extra‐pair pups are not more heterozygous than within‐pair pups. Whether females benefit from EPP in terms of increased fitness of the offspring, such as enhanced survival or growth, requires further investigations.     

Runs of homozygosity implicate autozygosity as a schizophrenia risk factor

Autozygosity occurs when two chromosomal segments that are identical from a common ancestor are inherited from each parent. This occurs at high rates in the offspring of mates who are closely related (inbreeding), but also occurs at lower levels among the offspring of distantly related mates. Here, we use runs of homozygosity in genome-wide SNP data to estimate the proportion of the autosome that exists in autozygous tracts in 9,388 cases with schizophrenia and 12,456 controls. We estimate that the odds of schizophrenia increase by ~17% for every 1% increase in genome-wide autozygosity. This association is not due to one or a few regions, but results from many autozygous segments spread throughout the genome, and is consistent with a role for multiple recessive or partially recessive alleles in the etiology of schizophrenia. Such a bias towards recessivity suggests that alleles that increase the risk of schizophrenia have been selected against over evolutionary time.     

偏分离分子标记的作图方法

对取自MAPMAKER软件小鼠F_2群体(含333个体)的5个RFLP连锁标记数据作了共显性分子标记偏分离的分析。先确定选择类型的方程组(配子或合子),随后采用Newton-Raphson迭代法估算标记间的重组值。在构建分子标记遗传图谱时,如果两个相邻标记均存在偏分离,最好采用纳入偏分离因子的估算方法。在估计F_2群体标记间偏分离重组距离上,用连续x~2检测方法比传统x~2检测更为准确。     

Quality Control of Genotypes Using Heritability Estimates of Gene Content at the Marker

Quality control filtering of single-nucleotide polymorphisms (SNPs) is a key step when analyzing genomic data. Here we present a practical method to identify low-quality SNPs, meaning markers whose genotypes are wrongly assigned for a large proportion of individuals, by estimating the heritability of gene content at each marker, where gene content is the number of copies of a particular reference allele in a genotype of an animal (0, 1, or 2). If there is no mutation at the marker, gene content has an additive heritability of 1 by construction. The method uses restricted maximum likelihood (REML) to estimate heritability of gene content at each SNP and also builds a likelihood-ratio test statistic to test for zero error variance in genotyping. As a by-product, estimates of the allele frequencies of markers at the base population are obtained. Using simulated data with 10% permutation error (4% actual error) in genotyping, the method had a specificity of 0.96 (4% of correct markers are rejected) and a sensitivity of 0.99 (1% of wrong markers are accepted) if markers with heritability lower than 0.975 are discarded. Checking of Mendelian errors resulted in a lower sensitivity (0.84) for the same simulation. The proposed method is further illustrated with a real data set with genotypes from 3534 animals genotyped for 50,433 markers from the Illumina PorcineSNP60 chip and a pedigree of 6473 individuals; those markers underwent very little quality control. A total of 4099 markers with P-values lower than 0.01 were discarded based on our method, with associated estimates of heritability as low as 0.12. Contrary to other techniques, our method uses all information in the population simultaneously, can be used in any population with markers and pedigree recordings, and is simple to implement using standard software for REML estimation. Scripts for its use are provided.