Seascape analysis reveals regional gene flow patterns among populations of a marine planktonic diatom

We investigated the gene flow of the common marine diatom, Skeletonema marinoi, in Scandinavian waters and tested the null hypothesis of panmixia. Sediment samples were collected from the Danish Straits, Kattegat and Skagerrak. Individual strains were established from germinated resting stages. A total of 350 individuals were genotyped by eight microsatellite markers. Conventional F-statistics showed significant differentiation between the samples. We therefore investigated whether the genetic structure could be explained using genetic models based on isolation by distance (IBD) or by oceanographic connectivity. Patterns of oceanographic circulation are seasonally dependent and therefore we estimated how well local oceanographic connectivity explains gene flow month by month. We found no significant relationship between genetic differentiation and geographical distance. Instead, the genetic structure of this dominant marine primary producer is best explained by local oceanographic connectivity promoting gene flow in a primarily south to north direction throughout the year. Oceanographic data were consistent with the significant F_ST values between several pairs of samples. Because even a small amount of genetic exchange prevents the accumulation of genetic differences in F-statistics, we hypothesize that local retention at each sample site, possibly as resting stages, is an important component in explaining the observed genetic structure.     

Spatio-temporal patterns of gene flow and dispersal under temperature increase

Recent data show that the Earth climate is undergoing a change at a rate which is outstanding in geologic history. Temperature is one of the major driving forces of gene flow and dispersal. In this paper the spatial dynamics of genetic dispersal is studied under the auspices of temperature increase by means of a mathematical model. The main elements genetics, competition and dispersal are combined in a coherent approach by a system of coupled partial differential equations with non-linear reaction terms describing population dynamics, genetic exchange and competition. Temperature reaction norms are conferred by a two allele system. The non-linearities of the interaction terms give rise to a richness of spatio-temporal dynamic patterns. Here we show how invasion processes in form of travelling waves are initiated by a temperature rise.     

Detection of differential gene flow from patterns of quantitative variation

A major goal in anthropological genetics is the assessment of the effects of different microevolutionary forces. Harpending and Ward (1982) developed a model that aids in this effort by comparing observed and expected heterozygosity within populations in a local region. The expected heterozygosity within a population is a function of the total heterozygosity of the entire region and the distance of the population from the regional mean centroid of allele frequencies. Greater than average gene flow from an external source will result in a population having greater heterozygosity than expected. Less than average gene flow from an external source will result in a population having less heterozygosity than expected. We extend the Harpending-Ward model to quantitative traits using an equal and additive effects model of inheritance. Here the additive genetic variance within a population is directly proportional to heterozygosity, and its expectation is directly proportional to the genetic distance from the centroid. Under certain assumptions the expectations for phenotypic variances are similar. Observed and expected genetic or phenotypic variance can then be compared to assess the effects of differential external gene flow. When the additive genetic covariance matrix or heritabilities are not known, the phenotypic covariance matrix can be used to provide a conservative application of the model. In addition, we develop new methods for estimation of the genetic relationship matrix (R) from quantitative traits. We apply these models to two data sets: (1) six principal components derived from twenty dermatoglyphic ridge count measures for nine villages in Nepal and (2) ten anthropometric measurements for seven isolated populations in western Ireland. In both cases both the univariate and multivariate analyses provide results that can be directly interpreted in terms of historically known patterns of gene flow.     

Temporal recruitment patterns and gene flow in kelp rockfish (Sebastes atrovirens)

Pelagic dispersal of marine organisms provides abundant opportunity for gene flow and presumably inhibits population genetic divergence. However, ephemeral, fine-scale, temporal and spatial genetic heterogeneity is frequently observed in settled propagules of marine species that otherwise exhibit broad-scale genetic homogeneity. A large variance in reproductive success is one explanation for this phenomenon. Here, genetic analyses of 16 microsatellite loci are used to examine temporal patterns of variation in young-of-year kelp rockfish (Sebastes atrovirens) recruiting to nearshore habitat in Monterey Bay, California, USA. Population structure of adults from central California is also evaluated to determine if spatial structure exists and might potentially contribute to recruitment patterns. Genetic homogeneity was found among 414 young-of-year sampled throughout the entire 1998 recruitment season. No substantial adult population structure was found among seven populations spanning 800 km of coastline that includes the Point Conception marine biogeographic boundary. Comparison of young-of-year and adult samples revealed no genetic differentiation and no measurable reduction in genetic variation of offspring, indicating little variance in reproductive success and no reduction in effective population size for this year class. Simulation analyses determined that the data set was sufficiently powerful to detect both slight population structure among adults and a small reduction in effective number of breeders contributing to this year class. The findings of high gene flow and low genetic drift have important implications for fisheries management and conservation efforts.     

Inference of population structure and patterns of gene flow in canine heartworm (Dirofilaria immitis)

Understanding the genetic variation within a parasitic species is crucial to implementing successful control programs and preventing the dispersal of drug resistance alleles. We examined the population genetics and structure of canine heartworm (Dirofilaria immitis) by developing a panel of 11 polymorphic microsatellite loci for this abundant parasite. In total, 192 individual nematodes were opportunistically sampled from 9 geographic regions in the United States and Mexico and genotyped. Population genetic analyses indicate the presence of 4 genetic clusters. The canine heartworm samples used in this study were characterized by low heterozygosity, with eastern and central North America experiencing high levels of reciprocal gene flow. Geographic barriers impede the movement of vectors and infected hosts west of the Rocky Mountains and south of the Central Mexican Plateau. This, combined with corridors of contiguous habitat, could influence the spread of drug resistance alleles.     

Expression patterns and association analysis of the porcine DHX58 gene

RIG-1 signalling is responsible for the detection of cytoplasmic viral RNA molecules. DEXH (Asp-Glu-X-His) box polypeptide 58 (encoded by DHX58) is a negative regulator of the RIG-1 signalling pathway. In human, the DHX58 gene can be upregulated and can inhibit the RIG-1 signalling pathway during viral infection. In this study, porcine DHX58 gene expression patterns were studied. According to our results, the porcine DHX58 gene was upregulated not only by the stimulation of Poly I:C but also by the stimulation of 1ipopolysaccharides (LPS). One polymorphism (g.4919G>C), detected in the ninth intron, was significantly associated with some blood parameters including the red cell distribution width of 1-day-old pigs and white blood cell counts, lymphocyte absolute counts, and platelet distribution width of 17-day-old pigs (P < 0.05). Moreover, the individuals with the genotype GG have a significantly higher mean white blood cell count than individuals with genotype CC or GC (P < 0.05). Our study indicates that DHX58 is an important gene that is associated with the immune response in swine.     

Forest corridors maintain historical gene flow in a tiger metapopulation in the highlands of central India

Understanding the patterns of gene flow of an endangered species metapopulation occupying a fragmented habitat is crucial for landscape-level conservation planning and devising effective conservation strategies. Tigers (Panthera tigris) are globally endangered and their populations are highly fragmented and exist in a few isolated metapopulations across their range. We used multi-locus genotypic data from 273 individual tigers (Panthera tigris tigris) from four tiger populations of the Satpura–Maikal landscape of central India to determine whether the corridors in this landscape are functional. This 45 000 km² landscape contains 17% of India''s tiger population and 12% of its tiger habitat. We applied Bayesian and coalescent-based analyses to estimate contemporary and historical gene flow among these populations and to infer their evolutionary history. We found that the tiger metapopulation in central India has high rates of historical and contemporary gene flow. The tests for population history reveal that tigers populated central India about 10 000 years ago. Their population subdivision began about 1000 years ago and accelerated about 200 years ago owing to habitat fragmentation, leading to four spatially separated populations. These four populations have been in migration–drift equilibrium maintained by high gene flow. We found the highest rates of contemporary gene flow in populations that are connected by forest corridors. This information is highly relevant to conservation practitioners and policy makers, because deforestation, road widening and mining are imminent threats to these corridors.     

Mating patterns of dermatophytes of diverse origin in India

The mating patterns of Trichophyton mentagrophytes var. interdigitale (74 isolates) and the Microsporum gypseum complex (17 isolates) of diverse origin and T. rubrum (25 isolates) and T. tonsurans (10 isolates) of clinical origin were studied. The results of the study showed that the teleomorph of the Indian isolates of T. mentagrophytes belong to Arthroderma vanbreuseghemii, undetermined teleomorphs of T. mentagrophytes var. interdigitale (+) mating types, and undetermined teleomorphs of T. mentagrophytes var. interdigitale indeterminate mating types. All the isolates of T. rubrum and T. tonsurans were found to be of the (-) mating type.     

Geographical patterns of adaptation within a species' range: interactions between drift and gene flow

We use individual-based stochastic simulations and analytical deterministic predictions to investigate the interaction between drift, natural selection and gene flow on the patterns of local adaptation across a fragmented species' range under clinally varying selection. Migration between populations follows a stepping-stone pattern and density decreases from the centre to the periphery of the range. Increased migration worsens gene swamping in small marginal populations but mitigates the effect of drift by replenishing genetic variance and helping purge deleterious mutations. Contrary to the deterministic prediction that increased connectivity within the range always inhibits local adaptation, simulations show that low intermediate migration rates improve fitness in marginal populations and attenuate fitness heterogeneity across the range. Such migration rates are optimal in that they maximize the total mean fitness at the scale of the range. Optimal migration rates increase with shallower environmental gradients, smaller marginal populations and higher mutation rates affecting fitness.     

Gene flow and life history patterns

Dispersal distances overestimate the gene-flow scale l (the square-root of the mean squared distance travelled from birth to reproduction) when egg laying is concentrated early in dispersal and when there is mortality during dispersal. If egg laying follows a square-root normal distribution in time, as it does in several Drosophila species, then l is reduced to about 0.6 of that estimated from dispersal alone, unless egg laying is concentrated in a very brief period. If mortality is such that the half-life is earlier than the mean fecundity day, then l will be reduced still more relative to the dispersal estimate, and will be very sensitive to small changes in mortality. Overestimating l yields overestimates of the amount of selection needed to maintain geographic differences in gene frequencies. If mortality increases in suboptimal habitats, then the neighborhood size will be smaller in those areas, because increased mortality decreases l. This means that l is smallest, allowing the greatest differentiation and genetic innovation, precisely where it is most needed. This lends support to Wright's shifting balance hypothesis. If l is adjusted to local conditions, then we do not necessarily expect a positive relationship between environmental and genetic heterogeneity. Data from Drosophila pseudoobscura are used to make the models realistic, and it is shown that l depends on the distances among traps or breeding sites. It is therefore essential to know the geometry of breeding sites and the life history parameters to estimate l.     

Sensitivity to corners in flow patterns

Flow patterns are two-dimensional orientation structures that arise from the projection of certain kinds of surface coverings (such as fur) onto images. Detecting orientation changes within them is an important task, since the changes often correspond to significant events such as corners, occluding edges, or surface creases. We model such patterns as random-dot Moiré patterns, and examine sensitivity to change in orientation within them. We show that the amount of structure available from which orientation and curvature can be estimated is critical, and introduce a path-length parameter to model it. For short path lengths many discontinuities are smoothed over, which has further implications for computational modeling of orientation selectivity.     

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.     

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/.     

Microfluidic single-cell real-time PCR for comparative analysis of gene expression patterns

Single-cell quantitative real-time PCR (qRT-PCR) combined with high-throughput arrays allows the analysis of gene expression profiles at a molecular level in approximately 11 h after cell sample collection. We present here a high-content microfluidic real-time platform as a powerful tool for comparatively investigating the regulation of developmental processes in single cells. This approach overcomes the limitations involving heterogeneous cell populations and sample amounts, and may shed light on differential regulation of gene expression in normal versus disease-related contexts. Furthermore, high-throughput single-cell qRT-PCR provides a standardized, comparative assay for in-depth analysis of the mechanisms underlying human pluripotent stem cell self-renewal and differentiation.