The effects of pollen and seed migration on nuclear-dicytoplasmic systems. I. Nonrandom associations and equilibrium structure with both maternal and paternal cytoplasmic inheritance

We determine the nuclear-dicytoplasmic effects of unidirectional gene flow via pollen and seeds upon a mixed-mating plant population, focusing on nuclear-mitochondrial-chloroplast systems where mitochondria are inherited maternally and chloroplasts paternally, as in many conifers. After first delineating the general effects of admixture (via seeds or individuals) on the nonrandom associations in such systems, we derive the full dicytonuclear equilibrium structure, including when disequilibria may be indicators of gene flow. Substantial levels of permanent two- and three-locus disequilibria can be generated in adults by (i) nonzero disequilibria in the migrant pools or (ii) intermigrant admixture effects via different chloroplast frequencies in migrant pollen and seeds. Additionally, three-locus disequilibria can be generated by higher-order intermigrant effects such as different chloroplast frequencies in migrant pollen and seeds coupled with nuclear-mitochondrial disequilibria in migrant seeds, or different nuclear frequencies in migrant pollen and seeds coupled with mitochondrial-chloroplast disequilibria in migrant seeds. Further insight is provided by considering special cases with seed or pollen migration alone, complete random mating or selfing, or migrant pollen and seeds lacking disequilibria or intermigrant admixture effects. The results complete the theoretical foundation for a new method for estimating pollen and seed migration using joint cytonuclear or dicytonuclear data.     

A new method for estimating joint parameters from motion data

Joint centers and axes of rotation (joint parameters) are central to all branches of movement analysis. In gait analysis, the standard protocol used to determine hip and knee joint parameters is prone to errors arising from palpation, anthropometric regression equations, and misplaced alignment devices. Several alternative methods have been proposed, but to date none have been shown to be accurate and reliable enough for use in the clinical setting. This article describes a new method for joint parameter estimation. The new method can be summarized as follows: (i) the motions of two adjacent segments spanning a single joint are tracked, (ii) the axis of rotation between every pair of observed segment configurations is computed, (iii) the most likely intersection of all axes (effective joint center) and most likely orientation of the axes (effective joint axis) is found. Initial validation of the method was conducted on a hinged mechanical analog and a single healthy adult subject. For the analog, the center was found to be within 3.8 mm of the geometric center and 2.0 degrees of the geometric axis (standard deviation). For the adult subject, hip centers varied on the order of 1-3 mm, knee centers by 3-9 mm, and knee axes by 2.0 degrees. The results suggest that the new method is an objective, precise, and practical alternative to the standard clinical approach.     

The effects of time,temperature and plant variety on pollen viability and its implications for gene flow risk

• Pollen viability affects the probability that a pollen grain deposited on a plant's stigma will produce a viable seed. Because a mature seed is needed before a gene flow event can occur, pollen viability will influence the risk of escape for genetically engineered (GE) crops.
• Pollen viability was measured at intervals for up to 2 h following removal of the pollen from the anthers. It was quantified at three temperatures and for different alfalfa varieties, including both conventional and Roundup Ready (RR) varieties. Pollen viability was assessed using in vitro germination.
• Time since removal from the anthers was the most prevalent factor affecting pollen viability in alfalfa. Pollen viability declined with increasing time at all three temperatures and for all varieties tested. Pollen viability was not affected by temperatures ranging between 25 and 37 °C and did not vary among plant varieties, including conventional and RR varieties.
• Bee foraging behaviour suggested pollen viability within the first 10 min following pollen removal from a flower to most affect seed production. Pollen longevity was predicted to have little impact on seed set and gene flow. Linking pollinator behaviour to pollen viability improved our understanding of its impact on gene flow risk.

     

Antagonistic effects of seed dispersal and herbivory on plant migration

The two factors that determine plant migration rates – seed dispersal and population growth – are generally treated independently, despite the fact that many animals simultaneously enhance plant migration rate via seed dispersal, and decrease it via negative effects of herbivory on population growth. Using extensive empirical data, we modelled the antagonistic effects of seed dispersal and herbivory by white-tailed deer on potential migration rates of Trillium grandiflorum , a forest herb in eastern North America. This novel antagonistic interaction is illustrated by maximum migration rates occurring at intermediate, but low herbivory (< 15%). Assuming herbivory < 20% and favourable conditions for population growth during post-glacial migration, seed dispersal by deer can explain rates of migration achieved in the past, in contrast to previous models of forest herb migration. However, relatively unfavourable conditions for population growth and increasingly intense herbivory by deer may compromise plant migration in the face of present and future climate change.     

Using seed purity data to estimate an average pollen mediated gene flow from crops to wild relatives

Gene flow from crops to wild related species has been recently under focus in risk-assessment studies of the ecological consequences of growing transgenic crops. However, experimental studies addressing this question are usually temporally or spatially limited. Indirect population-structure approaches can provide more global estimates of gene flow, but their assumptions appear inappropriate in an agricultural context. In an attempt to help the committees providing advice on the release of transgenic crops, we present a new method to estimate the quantity of genes migrating from crops to populations of related wild plants by way of pollen dispersal. This method provides an average estimate at a landscape level. Its originality is based on the measure of the inverse gene flow, i.e. gene flow from the wild plants to the crop. Such gene flow results in an observed level of impurities from wild plants in crop seeds. This level of impurity is usually known by the seed producers and, in any case, its measure is easier than a direct screen of wild populations because crop seeds are abundant and their genetic profile is known. By assuming that wild and cultivated plants have a similar individual pollen dispersal function, we infer the level of pollen-mediated gene flow from a crop to the surrounding wild populations from this observed level of impurity. We present an example for sugar beet data. Results suggest that under conditions of seed production in France (isolation distance of 1,000 m) wild beets produce high numbers of seeds fathered by cultivated plants. Received: 5 February 2001 / Accepted: 26 March 2001     

A new method for estimating the size of small populations from genetic mark-recapture data

The use of non-invasive genetic sampling to estimate population size in elusive or rare species is increasing. The data generated from this sampling differ from traditional mark-recapture data in that individuals may be captured multiple times within a session or there may only be a single sampling event. To accommodate this type of data, we develop a method, named capwire, based on a simple urn model containing individuals of two capture probabilities. The method is evaluated using simulations of an urn and of a more biologically realistic system where individuals occupy space, and display heterogeneous movement and DNA deposition patterns. We also analyse a small number of real data sets. The results indicate that when the data contain capture heterogeneity the method provides estimates with small bias and good coverage, along with high accuracy and precision. Performance is not as consistent when capture rates are homogeneous and when dealing with populations substantially larger than 100. For the few real data sets where N is approximately known, capwire's estimates are very good. We compare capwire's performance to commonly used rarefaction methods and to two heterogeneity estimators in program capture: Mh-Chao and Mh-jackknife. No method works best in all situations. While less precise, the Chao estimator is very robust. We also examine how large samples should be to achieve a given level of accuracy using capwire. We conclude that capwire provides an improved way to estimate N for some DNA-based data sets.     

A new method of estimating the pollen dispersal curve independently of effective density

We introduce a novel indirect method of estimating the pollen dispersal curve from mother-offspring genotypic data. Unlike an earlier indirect approach (TwoGener), this method is based on a normalized measure of correlated paternity between female pairs whose expectation does not explicitly depend on the unknown effective male population density (d(e)). We investigate the statistical properties of the new method, by comparison with those of TwoGener, considering the sensitivity to reductions of d(e), relative to census density, resulting from unequal male fecundity and asynchronous flowering. Our main results are: (i) it is possible to obtain reliable estimates of the average distance of pollen dispersal, delta, from indirect methods, even under nonuniform male fecundity and variable flowering phenology; (ii) the new method yields more accurate and more precise delta-estimates than TwoGener under a wide range of sampling and flowering scenarios; and (iii) TwoGener can be used to obtain approximate d(e) estimates, if needed for other purposes. Our results also show that accurately estimating the shape of the tail of the pollen dispersal function by means of indirect methods remains a very difficult challenge.     

A coalescent-based method for detecting and estimating recombination from gene sequences

Determining the amount of recombination in the genealogical history of a sample of genes is important to both evolutionary biology and medical population genetics. However, recurrent mutation can produce patterns of genetic diversity similar to those generated by recombination and can bias estimates of the population recombination rate. Hudson 2001 has suggested an approximate-likelihood method based on coalescent theory to estimate the population recombination rate, 4N(e)r, under an infinite-sites model of sequence evolution. Here we extend the method to the estimation of the recombination rate in genomes, such as those of many viruses and bacteria, where the rate of recurrent mutation is high. In addition, we develop a powerful permutation-based method for detecting recombination that is both more powerful than other permutation-based methods and robust to misspecification of the model of sequence evolution. We apply the method to sequence data from viruses, bacteria, and human mitochondrial DNA. The extremely high level of recombination detected in both HIV1 and HIV2 sequences demonstrates that recombination cannot be ignored in the analysis of viral population genetic data.     

A new method for estimating age-at-death from the first rib

A new method for estimating adult age-at-death from the first rib was developed as a modification of the Kunos et al. (Am J Phys Anthropol 110 (1999) 303-323) method. Data were collected on three aspects of the first rib (costal face, rib head, and tubercle facet) for 470 known-age males of Balkan ancestry collected as evidence during investigations conducted by the International Criminal Tribunal for the former Yugoslavia (ICTY). Ages-at-death range from 12 to 90 years (mean of 47.7 years). Several variables were extracted from the original study utilizing all three skeletal aspects of the first rib. This list was modified to 11 variables as preliminary tests on seriations of the samples were undertaken. A cumulative probit model with age measured on a log scale was used to calculate the mean and standard deviation of the ages-of-transition for each component. Multivariate analysis of the three components was also performed. The lowest correlation (r = 0.079, controlling for age) was between the geometric shape of the costal face and the surface texture of the tubercle facet. Assuming a correlation of zero, these two traits were used to calculate the highest posterior density regions for estimating individual ages-at-death. Age-at-death estimates generated from 50 and 95% posterior density regions indicate that this method captures age-related change reaching the ninth decade. The Bayesian statistical approach used here produced a valuable and promising new method for estimating age-at-death. Additional research is necessary to determine if these highest posterior density regions produce results highly correlated with age in other samples and its applicability to females.     

Semiparametric method for estimating paleodemographic profiles from age indicator data.

This paper addresses the problem of estimating an age-at-death distribution or paleodemographic profile from osteological data. It is demonstrated that the classical two-stage procedure whereby one first constructs estimates of age-at-death of individual skeletons and then uses these age estimates to obtain a paleodemographic profile is not a correct approach. This is a consequence of Bayes' theorem. Instead, we demonstrate a valid approach that proceeds from the opposite starting point: given skeletal age-at-death, one first estimates the probability of assigning the skeleton into a specific osteological age-indicator stage. We show that this leads to a statistically valid method for obtaining a paleodemographic profile, and moreover, that valid individual age estimation itself requires a demographic profile and therefore is done subsequent to its construction. Individual age estimation thus becomes the last rather than the first step in the estimation procedure. A central concept of our statistical approach is that of a weight function. A weight function is associated with each osteological age-indicator stage or category, and provides the probability that a specific age indicator stage is observed, given age-at-death of the individual. We recommend that weight functions be estimated nonparametrically from a reference data set. In their entirety, the weight functions characterize the relevant stochastic properties of a chosen age indicator. For actual estimation of the paleodemographic profile, a parametric age distribution in the target sample is assumed. The maximum likelihood method is used to identify the unknown parameters of this distribution. As some components are estimated nonparametrically, one then has a semiparametric model. We show how to obtain valid estimates of individual age-at-death, confidence regions, and goodness-of-fit tests. The methods are illustrated with both real and simulated data.     

The effects of pollen diversity on plant reproduction: insights from apple

For many plants, the number of pollen genotypes deposited on a flower’s stigma is positively related to fruit maturation and seed number; however, the mechanisms underlying this effect are less understood. Here we examined whether diversity of pollen (1, 3, or 5 donors) affects reproductive success in self-incompatible apple (Malus × domestica). Using paternity analysis, we then assessed the siring rate of individual donors to test whether diversity effects are related to the presence of a superior pollen donor or to donor × donor interactions. Increasing the diversity of compatible pollen enhanced seed number and reduced seed abortion in some but not all recipient genotypes. This effect was associated with an increased number of sires per fruit and non-random siring success among pollen donors. Two donors had consistently high siring rates, regardless of recipient genotype; however, the siring success of pollen donors was not correlated with their siring success in single-donor pollinations. Rather, siring success was affected by the identity of other pollen genotypes present on the stigma. Our results therefore suggest that the effects of pollen diversity are variable but may enhance fecundity by fostering interactions between pollen donors.     

Impacts of seed and pollen flow on population genetic structure for plant genomes with three contrasting modes of inheritance

The classical island and one-dimensional stepping-stone models of population genetic structure developed for animal populations are extended to hermaphrodite plant populations to study the behavior of biparentally inherited nuclear genes and organelle genes with paternal and maternal inheritance. By substituting appropriate values for effective population sizes and migration rates of the genes concerned into the classical models, expressions for genetic differentiation and correlation in gene frequency between populations can be derived. For both models, differentiation for maternally inherited genes at migration-drift equilibrium is greater than that for paternally inherited genes, which in turn is greater than that for biparentally inherited nuclear genes. In the stepping-stone model, the change of genetic correlation with distance is influenced by the mode of inheritance of the gene and the relative values of long- and short-distance migration by seed and pollen. In situations where it is possible to measure simultaneously Fst for genes with all three types of inheritance, estimates of the relative rates of pollen to seed flow can be made for both the short- and long-distance components of migration in the stepping-stone model.     

A robust method for estimating gene expression states using Affymetrix microarray probe level data

Background  

Microarray technology is a high-throughput method for measuring the expression levels of thousand of genes simultaneously. The observed intensities combine a non-specific binding, which is a major disadvantage with microarray data. The Affymetrix GeneChip assigned a mismatch (MM) probe with the intention of measuring non-specific binding, but various opinions exist regarding usefulness of MM measures. It should be noted that not all observed intensities are associated with expressed genes and many of those are associated with unexpressed genes, of which measured values express mere noise due to non-specific binding, cross-hybridization, or stray signals. The implicit assumption that all genes are expressed leads to poor performance of microarray data analyses. We assume two functional states of a gene - expressed or unexpressed - and propose a robust method to estimate gene expression states using an order relationship between PM and MM measures.     

A comparison of two indirect methods for estimating average levels of gene flow using microsatellite data

We compare the performance of Nm estimates based on FST and RST obtained from microsatellite data using simulations of the stepwise mutation model with range constraints in allele size classes. The results of the simulations suggest that the use of microsatellite loci can lead to serious overestimations of Nm, particularly when population sizes are large (N > 5000) and range constraints are high (K < 20). The simulations also indicate that, when population sizes are small (N /= 50) and many loci (nl >/= 20), RST performs better than FST for most of the parameter space. However, FST-based estimates are always better than RST when sample sizes are moderate or small (ns 相似文献   

A new method for gene discovery in large-scale microarray data

Microarrays are an effective tool for monitoring genome-wide gene expression levels. In current microarray analyses, the majority of genes on arrays are frequently eliminated for further analysis because the changes in their expression levels (ratios) are considered to be not significant. This strategy risks failure to discover whole sets of genes related to a quantitative trait of interest, which is generally controlled by several loci that make various contributions. Here, we describe a high-throughput gene discovery method based on correspondence analysis with a new index for expression ratios [arctan (1/ratio)] and three artificial marker genes. This method allows us to quickly analyze the whole microarray dataset and discover up-/down-regulated genes related to a trait of interest. We employed an example dataset to show the theoretical advantage of this method. We then used the method to identify 88 cancer-related genes from a published microarray data from patients with breast cancer. This method also allows us to predict the phenotype of a given sample from the gene expression profile. This method can be easily performed and the result is also visible in 3D viewing software that we have developed.     

A new spreadsheet method for the analysis of bivariate flow cytometric data

Background  

A useful application of flow cytometry is the investigation of cell receptor-ligand interactions. However such analyses are often compromised due to problems interpreting changes in ligand binding where the receptor expression is not constant. Commonly, problems are encountered due to cell treatments resulting in altered receptor expression levels, or when cell lines expressing a transfected receptor with variable expression are being compared. To overcome this limitation we have developed a Microsoft Excel spreadsheet that aims to automatically and effectively simplify flow cytometric data and perform statistical tests in order to provide a clearer graphical representation of results.