Gene Flow and Genetic Differentiation

A brief analysis is presented for the effects of gene flow upon genetic differentiation within and between populations generated by mutation and drift. Previous results obtained with the "island" model are developed into a form that lends itself to biological interpretation. Attention is focused upon the effective local population size and the ratio of the genetic identity of two genes in different populations to that of two genes in the same population. The biological significance of this ratio, which is independent of population size, is discussed. Similarities between the results of this model and those of the "stepping-stone" model are noted.     

Hierarchical Nuclear and Cytoplasmic Genetic Architectures for Plant Growth and Defense within Arabidopsis

To understand how genetic architecture translates between phenotypic levels, we mapped the genetic architecture of growth and defense within the Arabidopsis thaliana Kas × Tsu recombinant inbred line population. We measured plant growth using traditional size measurements and size-corrected growth rates. This population contains genetic variation in both the nuclear and cytoplasmic genomes, allowing us to separate their contributions. The cytoplasmic genome regulated a significant variance in growth but not defense, which was due to cytonuclear epistasis. Furthermore, growth adhered to an infinitesimal model of genetic architecture, while defense metabolism was more of a moderate-effect model. We found a lack of concordance between quantitative trait loci (QTL) regulating defense and those regulating growth. Given the published evidence proving the link between glucosinolates and growth, this is likely a false negative result caused by the limited population size. This size limitation creates an inability to test the entire potential genetic landscape possible between these two parents. We uncovered a significant effect of glucosinolates on growth once we accounted for allelic differences in growth QTLs. Therefore, other growth QTLs can mask the effects of defense upon growth. Investigating direct links across phenotypic hierarchies is fraught with difficulty; we identify issues complicating this analysis.     

Cytoplasmically Inherited Reproductive Incompatibility in Tribolium Flour Beetles: The Rate of Spread and Effect on Population Size

This paper reports on the effects of a cytoplasmically inherited reproductive incompatibility in different genetic strains of the flour beetle, Tribolium confusum. We measured the rate of spread and the effect of host population size using different initial frequencies of infection with a cytoplasmic factor that mediates reproductive incompatibility. There were two experiments, in one the infected and uninfected lines were from the same genetic strain, b-Yugoslavia. In the other, the infected line was from the "high cannibalism" bIV strain and the uninfected line from the "low cannibalism" bI strain. We estimate that the fitness ratio of infected to uninfected in b-Yugoslavia is 0.63 and the observed rate of spread for this strain corresponds to a model of cytoplasmic inheritance that takes into account the productivity differences between the infected and cured lines. In the bI-bIV experiment, because the uninfected and infected lines are from different genetic strains, we cannot partition the effects of the cytoplasmic factor from other factors. The rate of spread in the bI-bIV experiment is faster in males and slower in females than predicted from a model of cytoplasmic inheritance. In both experiments, productivity varies with initial infection frequency; however, the relationship is not explained by a simple model that predicts lower population size at intermediate infection frequencies.     

Efficient Multiple-Trait Association and Estimation of Genetic Correlation Using the Matrix-Variate Linear Mixed Model

Multiple-trait association mapping, in which multiple traits are used simultaneously in the identification of genetic variants affecting those traits, has recently attracted interest. One class of approaches for this problem builds on classical variance component methodology, utilizing a multitrait version of a linear mixed model. These approaches both increase power and provide insights into the genetic architecture of multiple traits. In particular, it is possible to estimate the genetic correlation, which is a measure of the portion of the total correlation between traits that is due to additive genetic effects. Unfortunately, the practical utility of these methods is limited since they are computationally intractable for large sample sizes. In this article, we introduce a reformulation of the multiple-trait association mapping approach by defining the matrix-variate linear mixed model. Our approach reduces the computational time necessary to perform maximum-likelihood inference in a multiple-trait model by utilizing a data transformation. By utilizing a well-studied human cohort, we show that our approach provides more than a 10-fold speedup, making multiple-trait association feasible in a large population cohort on the genome-wide scale. We take advantage of the efficiency of our approach to analyze gene expression data. By decomposing gene coexpression into a genetic and environmental component, we show that our method provides fundamental insights into the nature of coexpressed genes. An implementation of this method is available at http://genetics.cs.ucla.edu/mvLMM.     

Hitchhiking effect of a beneficial mutation spreading in a subdivided population

A central problem in population genetics is to detect and analyze positive natural selection by which beneficial mutations are driven to fixation. The hitchhiking effect of a rapidly spreading beneficial mutation, which results in local removal of standing genetic variation, allows such an analysis using DNA sequence polymorphism. However, the current mathematical theory that predicts the pattern of genetic hitchhiking relies on the assumption that a beneficial mutation increases to a high frequency in a single random-mating population, which is certainly violated in reality. Individuals in natural populations are distributed over a geographic space. The spread of a beneficial allele can be delayed by limited migration of individuals over the space and its hitchhiking effect can also be affected. To study this effect of geographic structure on genetic hitchhiking, we analyze a simple model of directional selection in a subdivided population. In contrast to previous studies on hitchhiking in subdivided populations, we mainly investigate the range of sufficiently high migration rates that would homogenize genetic variation at neutral loci. We provide a heuristic mathematical analysis that describes how the genealogical structure at a neutral locus linked to the locus under selection is expected to change in a population divided into two demes. Our results indicate that the overall strength of genetic hitchhiking--the degree to which expected heterozygosity decreases--is diminished by population subdivision, mainly because opportunity for the breakdown of hitchhiking by recombination increases as the spread of the beneficial mutation across demes is delayed when migration rate is much smaller than the strength of selection. Furthermore, the amount of genetic variation after a selective sweep is expected to be unequal over demes: a greater reduction in expected heterozygosity occurs in the subpopulation from which the beneficial mutation originates than in its neighboring subpopulations. This raises a possibility of detecting a "hidden" geographic structure of population by carefully analyzing the pattern of a selective sweep.     

Assessing natural introgression in 2 biomedical model species, the rhesus macaque (Macaca mulatta) and the long-tailed macaque (Macaca fascicularis)

Rhesus macaque (Macaca mulatta) and long-tailed macaque (Macaca fascicularis) are the 2 most commonly used primate model species in biomedical sciences. Although morphological studies have revealed a weak hybridization at the interspecific contact zone, in the north of Indochina, a molecular study has suggested an ancient introgression from rhesus to long-tailed macaque into the Indo-Chinese peninsula. However, the gene flow between these 2 taxa has never been quantified using genetic data and theoretical models. In this study, we have examined genetic variation within and between the parapatric Chinese rhesus macaque and Indo-Chinese long-tailed macaque populations, using 13 autosomal, 5 sex-linked microsatellite loci and mitochondrial DNA sequence data. From these data, we assessed genetic structure and estimated gene flow using a Bayesian clustering approach and the "Isolation with Migration" model. Our results reveal a weak interspecific genetic differentiation at both autosomal and sex-linked loci, suggesting large population sizes and/or gene flow between populations. According to the Bayesian clustering, Chinese rhesus macaque is a highly homogeneous gene pool that contributes strongly to the current Indo-Chinese long-tailed macaque genetic makeup, whether or not current admixture is assumed. Coalescent simulations, which integrated the characteristics of the loci, pointed out 1) a higher effective population size in rhesus macaque, 2) no mitochondrial gene flow, and 3) unilateral and male-mediated nuclear gene flow of approximately 10 migrants per generation from rhesus to long-tailed macaque. These patterns of genetic structure and gene flow suggest extensive ancient introgression from Chinese rhesus macaque into the Indo-Chinese long-tailed macaque population.     

Influence of mutational and sampling factors on the estimation of demographic parameters in a "continuous" population under isolation by distance

In numerous species, individual dispersal is restricted in space so that "continuous" populations evolve under isolation by distance. A method based on individual genotypes assuming a lattice population model was recently developed to estimate the product Dsigma2, where D is the population density and sigma2 is the average squared parent-offspring distance. We evaluated the influence on this method of both mutation rate and mutation model, with a particular reference to microsatellite markers, as well as that of the spatial scale of sampling. Moreover, we developed and tested a nonparametric bootstrap procedure allowing the construction of confidence intervals for the estimation of Dsigma2. These two objectives prompted us to develop a computer simulation algorithm based on the coalescent theory giving individual genotypes for a continuous population under isolation by distance. Our results show that the characteristics of mutational processes at microsatellite loci, namely the allele size homoplasy generated by stepwise mutations, constraints on allele size, and change of slippage rate with repeat number, have little influence on the estimation of Dsigma2. In contrast, a high genetic diversity (approximately 0.7-0.8), as is commonly observed for microsatellite markers, substantially increases the precision of the estimation. However, very high levels of genetic diversity (>0.85) were found to bias the estimation. We also show that statistics taking into account allele size differences give unreliable estimations (i.e., high variance of Dsigma2 estimation) even under a strict stepwise mutation model. Finally, although we show that this method is reasonably robust with respect to the sampling scale, sampling individuals at a local geographical scale gives more precise estimations of Dsigma2.     

Phylogeography of <Emphasis Type="Italic">Achyranthes bidentata</Emphasis> (Amaranthaceae) in China’s Warm-Temperate Zone Inferred from Chloroplast and Nuclear DNA: Insights into Population Dynamics in Response to Climate Change During the Pleistocene

Previous phylogeographic studies of the warm-temperate zone in China focused on woody plants, but little attention was given to the climate-sensitive herbaceous plants. In this work, we implemented a phylogeographic survey on the perennial herb Achyranthes bidentata in China’s warm-temperate zone. The sequence variation of cpDNA and nDNA was examined across 209 individuals from 21 populations. A total of 11 chlorotypes and 26 ribotypes were identified. The cpDNA data showed weak population genetic differentiation and could not divide the 21 populations into different genetic groups. By contrast, the nDNA data revealed stronger genetic differentiation than cpDNA and could divide these populations into two genetic groups. The cpDNA and nDNA data both gave unambiguous signs of recent sudden population expansion. Based on the cpDNA and nDNA data, the estimated time of population expansion occurred at interglacial Marine Isotope Stage (MIS) 9 of the Penultimate Glaciation in China. The cpDNA and nDNA data suggested that the glaciation during this period deeply influenced the current distribution patterns and intraspecific divergence of A. bidentata. Our survey showed that A. bidentata tracked climatic oscillations by a large range of southward retreat into three main refugia during MIS 8, followed by the sudden northward expansion from these refugia during MIS 9.     

Comparative population genetics of mimetic Heliconius butterflies in an endangered habitat; Brazil's Atlantic Forest

Background

The islands of North Maluku, Indonesia occupy a central position in the major prehistoric dispersal streams that shaped the peoples of Island Southeast Asia and the Pacific. Within this region a linguistic contact zone exists where speakers of Papuan and Austronesian languages reside in close proximity. Here we use population genetic data to assess the extent to which North Maluku populations experienced admixture of Asian genetic material, and whether linguistic boundaries reflect genetic differentiation today.

Results

Autosomal and X-linked markers reveal overall Asian admixture of 67% in North Maluku, demonstrating a substantial contribution of genetic material into the region from Asia. We observe no evidence of population structure associated with ethnicity or language affiliation.

Conclusions

Our data support a model of widespread Asian admixture in North Maluku, likely mediated by the expansion of Austronesian-speaking peoples into the region during the mid Holocene. In North Maluku there is no genetic differentiation in terms of Austronesian- versus Papuan-speakers, suggesting extensive gene flow across linguistic boundaries. In a regional context, our results illuminate a major genetic divide at the Molucca Sea, between the islands of Sulawesi and North Maluku. West of this divide, populations exhibit predominantly Asian ancestry, with very little contribution of Papuan genetic material. East of the Molucca Sea, populations show diminished rates of Asian admixture and substantial persistence of Papuan genetic diversity.     

Analysis of heterosis by a direct method using the concept of heritability

The presence of heterosis has been observed in many species at both phenotypic and gene levels. Strangely, the genetic basis of heterosis was and still is largely unknown. In this study, we extended and simplified some formulas that we reported previously. The foundation of our model was based on partitioning the F ₁ phenotypic variance of the cross between two pure lines into additive, dominance and epistasis components, which lead to the estimation of effective factors, crossheritability in the broad and narrow sense and heterotic power. In the model, we assume that all polygenes controlling a quantitative trait have an equal genetic effect and are independent of each other. By extension of the heritability to a cross population, new features appear. The word crossheritability acquires the status of a new genetic parameter that suffices to deal with the problem of crossbreeding and clarifies the picture of heterosis. Lastly, an example of employing the proposed method in analyzing the crossing data from Drosophila melanogaster is given to illustrate its application.     

EVOLUTION AT THE MOUSE t COMPLEX: WHY IS THE t HAPLOTYPE PRESERVED AS AN INTEGRAL UNIT?

Abstract Segregation distorters are selfish genetic elements that bias Mendelian segregation in their favor. All well-known segregation distortion systems consist of one or more "distorter" loci that act upon a "responder" locus. At the t complex of the house mouse, segregation distortion is brought about by the harmful effect of t alleles at a number of distorter loci on the wild-type variant of the responder locus. The responder and distorter alleles are closely linked by a number of inversions, thus forming a coherent t haplotype. It has been conjectured that the close integration of the various components into a "complete" t haplotype has been crucial for the evolutionary success of these selfish genetic elements. By means of a population genetical metapopulation model, we show that this intuition may be unfounded. In fact, under most circumstances an "insensitive" t haplotype retaining only the responder did invade and reach a high frequency, despite the fact that this haplotype has a strong segregation disadvantage. For certain population structures, the complete t haplotype was even competitively excluded by partial t haplotypes with lower segregation ratios. Moreover, t haplotypes carrying one or more recessive lethals only prevailed over their nonlethal counterparts if the product of local population size and migration rate ( Nm ) was not much smaller or larger than one. These phenomena occurred for rather realistic fitness, segregation, and recombination values. It is therefore quite puzzling that partial t haplotypes are absent from natural house mousepopulations, and that t haplotypes carrying recessive lethals prevail over nonlethal t haplotypes.     

Genetic diversity of native and introduced populations of the invasive house crow (<Emphasis Type="Italic">Corvus splendens</Emphasis>) in Asia and Africa

The common house crow (Corvus splendens) is one of the best known and most wide spread species of the family Corvidae. It is a successful invasive species able to exploit urban environments, well removed from its natural distribution. It is considered a pest as it attains high population densities, can cause serious economic losses and has many adverse effects on native fauna and flora, including predation, competitive displacement and disease transmission. Little genetic research on the house crow has been undertaken so we have only a limited understanding of its natural genetic population structure and invasion history. In this study, we employ microsatellite and mitochondrial DNA markers to assess genetic diversity, phylogeography and population structure of C. splendens within its native range represented by Sri Lanka and Bangladesh and introduced range represented by Malaysia, Singapore, Kenya and South Africa. We found high levels of genetic diversity in some of the invasive populations for which multiple invasions are proposed. The lowest genetic diversity was found for the intentionally introduced population in Selangor, Malaysia. Sri Lanka is a possible source population for Malaysia Selangor consistent with a documented introduction over 100 years ago, with port cities within the introduced range revealing possible presence of migrants from other unsampled locations. We demonstrate the power of the approach of using multiple molecular markers to untangle patterns of invasion, provide insights into population structure and phylogeographic relationships and illustrate how historical processes may have contributed to making this species such a successful invader.     

On the origin and spread of the Scab disease of apple: out of central Asia

Background

Venturia inaequalis is an ascomycete fungus responsible for apple scab, a disease that has invaded almost all apple growing regions worldwide, with the corresponding adverse effects on apple production. Monitoring and predicting the effectiveness of intervention strategies require knowledge of the origin, introduction pathways, and population biology of pathogen populations. Analysis of the variation of genetic markers using the inferential framework of population genetics offers the potential to retrieve this information.

Methodology/Principal Findings

Here, we present a population genetic analysis of microsatellite variation in 1,273 strains of V. inaequalis representing 28 orchard samples from seven regions in five continents. Analysis of molecular variance revealed that most of the variation (88%) was distributed within localities, which is consistent with extensive historical migrations of the fungus among and within regions. Despite this shallow population structure, clustering analyses partitioned the data set into separate groups corresponding roughly to geography, indicating that each region hosts a distinct population of the fungus. Comparison of the levels of variability among populations, along with coalescent analyses of migration models and estimates of genetic distances, was consistent with a scenario in which the fungus emerged in Central Asia, where apple was domesticated, before its introduction into Europe and, more recently, into other continents with the expansion of apple growing. Across the novel range, levels of variability pointed to multiple introductions and all populations displayed signatures of significant post-introduction increases in population size. Most populations exhibited high genotypic diversity and random association of alleles across loci, indicating recombination both in native and introduced areas.

Conclusions/Significance

Venturia inaequalis is a model of invasive phytopathogenic fungus that has now reached the ultimate stage of the invasion process with a broad geographic distribution and well-established populations displaying high genetic variability, regular sexual reproduction, and demographic expansion.     

The standard genetic code enhances adaptive evolution of proteins

The standard genetic code, by which most organisms translate genetic material into protein metabolism, is non-randomly organized. The Error Minimization hypothesis interprets this non-randomness as an adaptation, proposing that natural selection produced a pattern of codon assignments that buffers genomes against the impact of mutations. Indeed, on the average any given point mutation has a lesser effect on the chemical properties of the utilized amino acid than expected by chance. Might it also, however, be the case that the non-random nature of the code effects the rate of adaptive evolution? To investigate this, here we develop population genetic simulations to test the rate of adaptive gene evolution under different genetic codes. We identify two independent properties of a genetic code that profoundly influence the speed of adaptive evolution. Noting that the standard genetic code exhibits both, we offer a new insight into the effects of the "error minimizing" code: such a code enhances the efficacy of adaptive sequence evolution.     

Founder effect in an island population of bighorn sheep

The Tiburon Island population of desert bighorn sheep has increased in size from 20 founders in 1975 to approximately 650 in 1999. This population is now the only population being used as the source stock for transplantations throughout northern Mexico. To evaluate the genetic variation in this population, we examined 10 microsatellite loci and a major histocompatibility complex (MHC) locus. The genetic variation was significantly less than found in other populations of the same subspecies in Arizona. Using a model that takes into account the effects of genetic drift on genetic distance, most of the genetic distance observed between the Tiburon population and Arizona samples could be explained. Because of the low genetic variation found in the Tiburon population, it is suggested that the Tiburon population should be supplemented with additional unrelated animals or that the transplant populations should be supplemented with unrelated animals.     

A hierarchical Bayesian model for next-generation population genomics

The demography of populations and natural selection shape genetic variation across the genome and understanding the genomic consequences of these evolutionary processes is a fundamental aim of population genetics. We have developed a hierarchical Bayesian model to quantify genome-wide population structure and identify candidate genetic regions affected by selection. This model improves on existing methods by accounting for stochastic sampling of sequences inherent in next-generation sequencing (with pooled or indexed individual samples) and by incorporating genetic distances among haplotypes in measures of genetic differentiation. Using simulations we demonstrate that this model has a low false-positive rate for classifying neutral genetic regions as selected genes (i.e., Φ(ST) outliers), but can detect recent selective sweeps, particularly when genetic regions in multiple populations are affected by selection. Nonetheless, selection affecting just a single population was difficult to detect and resulted in a high false-negative rate under certain conditions. We applied the Bayesian model to two large sets of human population genetic data. We found evidence of widespread positive and balancing selection among worldwide human populations, including many genetic regions previously thought to be under selection. Additionally, we identified novel candidate genes for selection, several of which have been linked to human diseases. This model will facilitate the population genetic analysis of a wide range of organisms on the basis of next-generation sequence data.     

Novel microsatellite loci reveal high genetic diversity yet low population structure for alfalfa leafcutting bees in North America

The alfalfa leafcutting bee, Megachile rotundata (ALCB) is an economically important pollinator necessary for seed production of the critical forage crop alfalfa, Medicago sativa. The pollinator was accidentally introduced to North America from Europe approximately 70 years ago, and it is primarily produced in Canada and shipped to the United States annually en masse for seed field pollination. We investigate how the large-scale commercial movement of this bee affects the genetic structure of populations in the North American seed growing system and compare the genetic diversity and structure of introduced North American bees with two native European populations. Using 16 newly developed microsatellite loci, we describe the North American population structure of this bee. ALCBs collected from alfalfa seed farms have a degree of genetic variability similar to one native European population, but lower than the second. Considering that the species was accidentally introduced into North America, we anticipated more signature of a founder effect. Despite the level of genetic variability, we found little, if any, genetic structuring across North America, other than that the North American populations were distinct from the European populations sampled. While we detected some sub-structure in North American populations using Bayesian methods, the structuring was without geographic pattern, and we propose it is the result of the intense human management and movement of these bees. The trade and movement of these bees by humans has created a nearly panmictic M. rotundata population across the continent, which has implications relevant to the preservation and conservation of other bee pollinators.     

Predicting diabetic nephropathy using a multifactorial genetic model

Aims

The tendency to develop diabetic nephropathy is, in part, genetically determined, however this genetic risk is largely undefined. In this proof-of-concept study, we tested the hypothesis that combined analysis of multiple genetic variants can improve prediction.

Methods

Based on previous reports, we selected 27 SNPs in 15 genes from metabolic pathways involved in the pathogenesis of diabetic nephropathy and genotyped them in 1274 Ashkenazi or Sephardic Jewish patients with Type 1 or Type 2 diabetes of >10 years duration. A logistic regression model was built using a backward selection algorithm and SNPs nominally associated with nephropathy in our population. The model was validated by using random “training” (75%) and “test” (25%) subgroups of the original population and by applying the model to an independent dataset of 848 Ashkenazi patients.

Results

The logistic model based on 5 SNPs in 5 genes (HSPG2, NOS3, ADIPOR2, AGER, and CCL5) and 5 conventional variables (age, sex, ethnicity, diabetes type and duration), and allowing for all possible two-way interactions, predicted nephropathy in our initial population (C-statistic = 0.672) better than a model based on conventional variables only (C = 0.569). In the independent replication dataset, although the C-statistic of the genetic model decreased (0.576), it remained highly associated with diabetic nephropathy (χ² = 17.79, p<0.0001). In the replication dataset, the model based on conventional variables only was not associated with nephropathy (χ² = 3.2673, p = 0.07).

Conclusion

In this proof-of-concept study, we developed and validated a genetic model in the Ashkenazi/Sephardic population predicting nephropathy more effectively than a similarly constructed non-genetic model. Further testing is required to determine if this modeling approach, using an optimally selected panel of genetic markers, can provide clinically useful prediction and if generic models can be developed for use across multiple ethnic groups or if population-specific models are required.     

Genotype and sex-based host variation in behaviour and susceptibility drives population disease dynamics

Host heterogeneity in pathogen transmission is widespread and presents a major hurdle to predicting and minimizing disease outbreaks. Using Drosophila melanogaster infected with Drosophila C virus as a model system, we integrated experimental measurements of social aggregation, virus shedding, and disease-induced mortality from different genetic lines and sexes into a disease modelling framework. The experimentally measured host heterogeneity produced substantial differences in simulated disease outbreaks, providing evidence for genetic and sex-specific effects on disease dynamics at a population level. While this was true for homogeneous populations of single sex/genetic line, the genetic background or sex of the index case did not alter outbreak dynamics in simulated, heterogeneous populations. Finally, to explore the relative effects of social aggregation, viral shedding and mortality, we compared simulations where we allowed these traits to vary, as measured experimentally, to simulations where we constrained variation in these traits to the population mean. In this context, variation in infectiousness, followed by social aggregation, was the most influential component of transmission. Overall, we show that host heterogeneity in three host traits dramatically affects population-level transmission, but the relative impact of this variation depends on both the susceptible population diversity and the distribution of population-level variation.