The effect of a barrier to gene flow on patterns of geographic variation.

Explicit formulae are given for the effects of a barrier to gene flow on random fluctuations in allele frequency; these formulae can also be seen as generating functions for the distribution of coalescence times. The formulae are derived using a continuous diffusion approximation, which is accurate over all but very small spatial scales. The continuous approximation is confirmed by comparison with the exact solution to the stepping stone model. In both one and two spatial dimensions, the variance of fluctuations in allele frequencies increases near the barrier; when the barrier is very strong, the variance doubles. However, the effect on fluctuations close to the barrier is much greater when the population is spread over two spatial dimensions than when it occupies a linear, one-dimensional habitat: barriers of strength comparable with the dispersal range (B approximately equal to sigma) can have an appreciable effect in two dimensions, whereas only barriers with strength comparable with the characteristic scale (B approximately equal to L=sigma/sqrt{2mu}) are significant in one dimension (mu is the rate of mutation or long-range dispersal). Thus, in a two-dimensional population, barriers to gene flow can be detected through their effect on the spatial pattern of genetic marker alleles.     

Craniometric variation of the Ainu: an assessment of differential gene flow from northeast Asia into northern Japan, Hokkaido

In and after the latest Neolithic period in Japan (approximately B.P. 2,300 years), there were two distinct waves of migration from eastern Asia. One is well known as successive episodes in which indigenous inhabitants of main-island Japan were intruded on by new arrivals with advanced technology, and of a different genetic stock. Another migration of people and culture, identified as the Okhotsk culture, reached the northeastern part of Hokkaido. As opposed to main-island Japan, the morphological continuity from the Neolithic to recent inhabitants in Hokkaido (Ainu) is notable, so that the evidence of admixture easily could have escaped notice. In this study, the effects of gene flow from an outside source on the pattern of among-group variation of Hokkaido Ainu are examined by means of two models. One is the R-matrix model comparing observed and expected craniometric variation for estimating differential external gene flow into a region. The other is a simple simulation model that estimates admixture in a population with two parental populations. The two approaches give similar results. The results suggest the possibility of admixture between the migrants from Northeast Asia, the Okhotsk culture people, and the indigenous inhabitants in Hokkaido during the 5th to 12th centuries A.D., at least in northeastern Hokkaido. Such gene flow may have a certain degree of effect on the genetic structure of recent Ainu. The findings further suggest morphological heterogeneity in Northeast Asia during the Holocene that has relevance for understanding the morphological heterogeneity seen through time in the New World.     

Hydrodynamic mediation of predator-prey interactions: differential patterns of prey susceptibility and predator success explained by variation in water flow

In most shallow water marine systems, fluid movements vary on scales that may influence local community dynamics both directly, through changes in the abundance of species, and indirectly, by modifying important behaviors of organisms. We examined how differences in current speed affect the outcome of predator-prey interactions for two species of marine benthic predators (knobbed whelks, Busycon carica, and blue crabs, Callinectes sapidus) foraging on two common prey species (bay scallops, Argopecten irradians, and hard clams, Mercenaria mercenaria). The predators differ in their foraging strategies and prey in their potential escape responses. Predation by blue crabs, highly mobile predators/scavengers that rely upon chemical odors transported in the water column to locate prey, could be strongly affected by changes in current speed and turbulent mixing because their foraging strategy relies on a high degree of spatial integration of prey odor plumes. Whelks, slow moving, predatory gastropods that often forage with their bodies buried in the sediment, may be less susceptible to flow-induced distortion of prey odor plumes because their sluggish movements result in a high degree of temporal integration of prey odors. Bay scallops, relatively mobile bivalves capable of rapid short-distance swimming burst, and hard clams, sedentary bivalves, have been shown to respond to varying degrees to predator odors that are dispersed in the water column. Flow regime for the predator-prey experiments was manipulated in situ using large channels. Predation by blue crabs on both juvenile hard clams and bay scallops decreased with increases in water flow (0-12 vs. 0-30 cm s⁻¹). Whelk predation on bay scallops increased with increases in water flow, whereas predation by whelks on hard clams did not differ between flow regimes. For blue crabs movement decreased at periods of high water flow. Because blue crabs locate prey through chemolocation of water-borne cues, which are diluted rapidly at higher flows, decreases in foraging may result from the inability to successfully detect prey at enhanced flows. Differences in predation by whelks could not be explained by a similar mechanism. Visual observations of foraging whelks revealed no differences in whelk behavior between the two flow regimes. The pattern of higher whelk predation on scallops at enhanced flow is likely to be related to a flow-inhibiting ability of scallops to detect predator approach. Thus, flow enhancement interferes with three of the predator-prey systems but the effect on predator success depends on whether the predator or prey is most affected.     

Gene variation and gene flow inOrchis morio (Orchidaceae) from Italy

Data are presented on genetic variation at 27 enzyme loci of the Green-Winged orchid,Orchis morio, in 18 population samples from Italy. The existence in Italy of two subspecies, i.e. subspp.morio andpicta, is not supported by allozyme data. No genetic heterogeneity was found betweenmorio-like andpicta-like samples and specimens. Moreover, morphological transition between the two forms was observed in different Italian populations. The parameters of genetic variability estimated forO. morio populations are consistent with those found among monocotyledon plants, and among those outcrossing, animal-pollinated and with wind-dispersed seeds. Genetic diversity of ItalianO. morio is mostly within populations. Correspondingly, low values of interpopulational genetic distance were found. This appears to be due to high levels of gene flow, which were estimated with different methods. The lack ofO. longicornu from Italian samples, as well as of any hybrid withO. morio (F₁, backcrossed or recombinant individuals) is demonstrated on the basis of genetic data. It is concluded that recurrent reports ofO. longicornu from Italy are due to confusion withO. morio or with otherOrchis species.     

Detection of coregulation in differential gene expression profiles

Genomics and proteomics approaches generate distinct gene expression and protein profiles, listing individual genes embedded in broad functional terms as gene ontologies. However, interpretation of gene profiles in a regulatory and functional context remains a major issue. Elucidation of regulatory mechanisms at the gene expression level via analysis of promoter regions is a prominent procedure to decipher such gene regulatory networks. We propose a novel genetic algorithm (GA) to extract joint promoter modules in a set of coexpressed genes as resulting from differential gene expression experiments. Algorithm design has focused on the following constraints: (I) identification of the major promoter modules, which are (II) characterized by a maximum number of joint motifs and (III) are found in a maximum number of coexpressed genes. The capability of the GA in detecting multiple modules was evaluated on various test data sets, analyzing the impact of the number of motifs per promoter module, the number of genes associated with a module, as well as the total number of distinct promoter modules encoded in a sequence set. In addition to the test data sets, the GA was evaluated on two biological examples, namely a muscle-specific data set and the upstream sequences of the beta-actin gene (ACTB) derived from different species, complemented by a comparison to alternative promoter module identification routines.     

Detection and quantification of phnE gene from oil-contaminated soil samples by competitive quantitative PCR

The phnE gene encoding catechol 2,3-dioxygenase belonging to the meta-cleavage pathway was selected as the marker gene and was detected and quantified from soil samples by competitive quantitative PCR. A PCR primer pair was designed based on the phnE gene to amplify the target DNA bands and competitor DNA bands. The phnE gene was detected in two samples of three. In samples S1 and S2, the phnE gene copy number was 6.2×10⁷/g soil and 5.8×10⁷/g soil, respectively. But no phnE gene was detected in sample S3. The target DNA bands were extracted and expressed. The results confirmed that the target DNA bands were the native phnE genes.     

Exploring patterns of interspecific variation in quantitative traits using sequential phylogenetic eigenvector regressions

A number of metrics have been developed for estimating phylogenetic signal in data and to evaluate correlated evolution, inferring broad-scale evolutionary and ecological processes. Here, we proposed an approach called phylogenetic signal-representation (PSR) curve, built upon phylogenetic eigenvector regression (PVR). In PVR, selected eigenvectors extracted from a phylogenetic distance matrix are used to model interspecific variation. In the PSR curve, sequential PVR models are fitted after successively increasing the number of eigenvectors and plotting their R(2) against the accumulated eigenvalues. We used simulations to show that a linear PSR curve is expected under Brownian motion and that its shape changes under alternative evolutionary models. The PSR area, expressing deviations from Brownian motion, is strongly correlated (r= 0.873; P < 0.01) with Blomberg's K-statistics, so nonlinear PSR curves reveal if traits are evolving at a slower or higher rate than expected by Brownian motion. The PSR area is also correlated with phylogenetic half-life under an Ornstein-Uhlenbeck process, suggesting how both methods describe the shape of the relationship between interspecific variation and time since divergence among species. The PSR curve provides an elegant exploratory method to understand deviations from Brownian motion, in terms of acceleration or deceleration of evolutionary rates occurring at large or small phylogenetic distances.     

R-matrix analysis and patterns of gene flow in India

An appraisal on the usefulness of R-matrix analysis and the model of Harpending and Ward (1982) to study the population structure of Indian populations is made in the light of prevalent marriage patterns, caste structure, and cultural specificity of the region. With the help of available data on the migration histories and geographical backgrounds of marine fishermen on the east coast of India, and through the historical analysis of marriage patterns, it is demonstrated that the routine inferences based on the regression plots of average heterozygosity versus genetic distance from the centroid may not generally be apt for the Indian situation. Increased heterozygosity among migrant fishermen seems to have resulted from mating patterns within this community rather than from external gene flow. In either case, the genetic implications are supposedly identical. Nevertheless, when making inferences regarding local population structure it is important to have detailed knowledge of mating patterns and the cultural context of the region under study.     

PADGE: analysis of heterogeneous patterns of differential gene expression.

We have devised a novel analysis approach, percentile analysis for differential gene expression (PADGE), for identifying genes differentially expressed between two groups of heterogeneous samples. PADGE was designed to compare expression profiles of sample subgroups at a series of percentile cutoffs and to examine the trend of relative expression between sample groups as expression level increases. Simulation studies showed that PADGE has more statistical power than t-statistics, cancer outlier profile analysis (COPA) (Tomlins SA, Rhodes DR, Perner S, Dhanasekaran SM, Mehra R, Sun XW, Varambally S, Cao X, Tchinda J, Kuefer R, Lee C, Montie JE, Shah RB, Pienta KJ, Rubin MA, Chinnaiyan AM. Science 310: 644-648, 2005), and kurtosis (Teschendorff AE, Naderi A, Barbosa-Morais NL, Caldas C. Bioinformatics 22: 2269-2275, 2006). Application of PADGE to microarray data sets in tumor tissues demonstrated its utility in prioritizing cancer genes encoding potential therapeutic targets or diagnostic markers. A web application was developed for researchers to analyze a large gene expression data set from heterogeneous biological samples and identify differentially expressed genes between subsets of sample classes using PADGE and other available approaches. Availability: http://www.cgl.ucsf.edu/Research/genentech/padge/.     

Normalization and analysis of residual variation in two-dimensional gel electrophoresis for quantitative differential proteomics

Although two-dimensional gel electrophoresis (2-DE) has long been a favorite experimental method to screen proteomes, its reproducibility is seldom analyzed with the assistance of quantitative error models. The lack of models of residual distributions that can be used to assign likelihood to differential expression reflects the difficulty in tackling the combined effect of variability in spot intensity and uncertain recognition of the same spot in different gels. In this report we have analyzed a series of four triplicate two-dimensional gels of chicken embryo heart samples at two distinct development stages to produce such a model of residual distribution. In order to achieve this reference error model, a nonparametric procedure for consistent spot intensity normalization had to be established, and is also reported here. In addition to variability in normalized intensity due to various sources, the residual variation between replicates was observed to be compounded by failure to identify the spot itself (gel alignment). The mixed effect is reflected by variably skewed bimodal density distributions of residuals. The extraction of a global error model that accommodated such distribution was achieved empirically by machine learning, specifically by bootstrapped artificial neural networks. The model described is being used to assign confidence values to observed variations in arbitrary 2-DE gels in order to quantify the degree of over-expression and under-expression of protein spots.     

Detection of gene flow from GM to non-GM watermelon in a field trial

Gene flow from genetically modified (GM) crops to conventional non-GM crops is a serious concern for protection of conventional and organic farming. Gene flow from GM watermelon developed for rootstock use, containing cucumber green mottle mosaic virus (CGMMV)-coat protein (CP) gene, to a non-GM isogenic control variety “Clhalteok” and grafted watermelon “Keumcheon” was investigated in a small scale field trial as a pilot study. Hybrids between GM and non-GM watermelons were screened from 1304 “Chalteok” seeds and 856 “Keumcheon” seeds using the duplex PCR method targeting theCGMMV- CP gene as a marker. Hybrids were found in all pollen recipient plots. The gene flow frequencies were greater for “Chaiteok” than for “KeumcheonD; with 75% outcrossing in the “Chaiteok” plot at the closest distance (0.8 m) to the GM plot. A much larger scale field trial is necessary to identify the isolation distance between GM and non-GM watermelon, as the behaviors of insect pollinators needs to be clarified in Korea.     

Genetic variation in restriction patterns among mouse amylase gene complexes

The expression of pancreatic amylase in the mouse exhibits pronounced genetic variation. Congenic lines with various amylase complexes on a common C3H/As background have different numbers and forms of isoenzymes. The relative ratio of these isoenzymes may vary, as does the overall production of pancreatic amylase, which in some lines is three- to fourfold higher than in others. DNA from a number of lines was digested with endonucleases and hybridized to an amylase cDNA probe. The restriction patterns from inbred stocks and the corresponding congenic lines are identical, demonstrating that the majority of (if not all) amylase-like DNA sequences is found within the amylase complex. Congenic lines with specific amylase expression, for instance, in enzyme production, show different restriction patterns, whereas three lines with the same amylase phenotype have a uniform pattern. Most of the variation in amylase expression is represented among congenic lines derived from Danish mice. A comparison of such lines with others of remote geographic origin reveals that the restriction patterns of the Danish lines have by far the highest degree of resemblance. This observation seems to exclude major rearrangements within the amylase complex as the cause of the differences in enzyme expression, which instead are likely to be due to variation in regulatory elements associated with the active structural amylase genes in the complex.This work was supported by Grant 11-2290 from the Danish Natural Science Research Council.     

Proteomic analysis from haploid and diploid embryos of Quercus suber L. identifies qualitative and quantitative differential expression patterns

Quercus suber L. is a Mediterranean forest species with ecological, social and economic value. Clonal propagation of Q. suber elite trees has been successfully obtained from in vitro‐derived somatic and gametic embryos. These clonal lines play a main role in breeding and genetic studies of Q. suber. To aid in unravelling diverse genetic and biological unknowns, a proteomic approach is proposed. The proteomic analysis of Q. suber somatic and gametic in vitro culture‐derived embryos, based on DIGE and MALDI‐MS, has produced for the first time proteomic data on this species. Seventeen differentially expressed proteins have been identified which display significantly altered levels between gametic and somatic embryos. These proteins are involved in a variety of cellular processes, most of which had been neither previously associated with embryo development nor identified in the genus Quercus. Some of these proteins are involved in stress and pollen development and others play a role in the metabolism of tannins and phenylpropanoids, which represent two of the major pathways for the synthesis of cork chemical components. Furthermore, the augmented expression levels found for specific proteins are probably related to the homozygous state of a doubled‐haploid sample. Proteins involved in synthesis of cork components can be detected at such early stages of development, showing the potential of the method to be useful in searching for biomarkers related to cork quality.     

Detection of an early cytomegalovirus antigen with two-color quantitative flow cytometry

An early cytomegalovirus (CMV) antigen was detected with a monoclonal antibody by two-color fluorescent flow cytometry. With the aid of a human diploid fibroblast cell strain, FLOW 2000, infected with the AD169 strain of CMV, the viral antigen and the DNA content of infected or uninfected cells were measured. There was no evidence of change in the cell-cycle distribution of the infected cells. The viral antigen was detected within 30 minutes following virus adsorption at 0.1 and 1.0 plaque-forming units/cells; and the percentage of positive cells increased with time and viral dosage. All stages of the cell cycle were susceptible to viral infection and the average fluorescence was greater than the background fluorescence. Flow cytometry detected the viral antigen earlier than conventional immunofluorescent microscopy and cell culture for CMV cytopathological effect (CPE). Ten bronchoalveolar lavages assayed by flow cytometry and conventional diagnostic procedures demonstrated that flow cytometry might be useful in early diagnosis for CMV infection.