Population Genetic Summary Statistics Research Articles

Using Runs of Homozygosity and Machine Learning to Disentangle Sources of Inbreeding and Infer Self-Fertilization Rates.

Runs of homozygosity (ROHs) are indicative of elevated homozygosity and inbreeding due to mating of closely related individuals. Self-fertilization can be a major source of inbreeding which elevates genome-wide homozygosity and thus should also create long ROHs. While ROHs are frequently used to understand inbreeding in the context of conservation and selective breeding, as well as for consanguinity of populations and their demographic history, it remains unclear how ROH characteristics are altered by selfing and if this confounds expected signatures of inbreeding due to demographic change. Using simulations, we study the impact of the mode of reproduction and demographic history on ROHs. We apply random forests to identify unique characteristics of ROHs, indicative of different sources of inbreeding. We pinpoint distinct features of ROHs that can be used to better characterize the type of inbreeding the population was subjected to and to predict outcrossing rates and complex demographic histories. Using additional simulations and four empirical datasets, two from highly selfing species and two from mixed-maters, we predict the selfing rate and validate our estimations. We find that self-fertilization rates are successfully identified even with complex demography. Population genetic summary statistics improve algorithm accuracy particularly in the presence of additional inbreeding, e.g. from population bottlenecks. Our findings highlight the importance of ROHs in disentangling confounding factors related to various sources of inbreeding and demonstrate situations where such sources cannot be differentiated. Additionally, our random forest models provide a novel tool to the community for inferring selfing rates using genomic data.

Genetic variation in Loudetia simplex supports the presence of ancient grasslands in Madagascar

Societal Impact StatementRecognizing Loudetia‐dominated grasslands were widespread prior to human colonization highlights that open ecosystems were and continue to be an important component of Madagascar's biodiversity. A better understanding of the plant species that form grassland ecosystems is necessary for effective land management strategies that support livelihoods, but substantial financial and logistical barriers exist to implementing conservation genetic studies using contemporary genomic tools. Some challenges for population genetic analyses of non‐model polyploids lacking reference genomes can be ameliorated by developing computational resources that leverage a cost‐effective data generation strategy that requires no prior genetic knowledge of the target species. This may benefit conservation programs with small operating budgets while reducing uncertainty compared to status quo microsatellite assays.Summary The extent of Madagascar's grasslands prior to human colonization is unresolved. We used population genetic analyses of a broadly dominant C4 fire‐adapted grass, Loudetia simplex, as a proxy for estimating grassland change through time. We carefully examined the utility of target‐enrichment data for population genetics to make recommendations for conservation genetics. We explored the potential of estimating individual ploidy levels from target‐enrichment data and how assumptions about ploidy could affect analyses. We developed a novel bioinformatic pipeline to estimate ploidy and genotypes from target‐enrichment data. We estimated standard population genetic summary statistics in addition to species trees and population structure. Extended Bayesian skyline plots provided estimates of population size through time for empirical and simulated data. All Malagasy L. simplex individuals sampled in this study formed a clade and possibly indicated an ancestral Central Highland distribution of 800 m in altitude and above. Demographic models suggested grassland expansions occurred prior to the Last Interglacial Period and supported extensive grasslands prior to human colonization. Though there are limitations to target‐enrichment data for population genetic studies, we find that analyses of population structure are reliable. Genetic variation in L. simplex supports widespread grasslands in Madagascar prior to the more recent periods of notable paleoclimatic change. However, the methods explored here could not differentiate between paleoclimatic change near the Last Glacial Maximum and anthropogenic effects. Target‐enrichment data can be a valuable tool for analyses of population structure in the absence a reference genome.

Epidemiological inference for emerging viruses using segregating sites

Epidemiological models are commonly fit to case and pathogen sequence data to estimate parameters and to infer unobserved disease dynamics. Here, we present an inference approach based on sequence data that is well suited for model fitting early on during the expansion of a viral lineage. Our approach relies on a trajectory of segregating sites to infer epidemiological parameters within a Sequential Monte Carlo framework. Using simulated data, we first show that our approach accurately recovers key epidemiological quantities under a single-introduction scenario. We then apply our approach to SARS-CoV-2 sequence data from France, estimating a basic reproduction number of approximately 2.3-2.7 under an epidemiological model that allows for multiple introductions. Our approach presented here indicates that inference approaches that rely on simple population genetic summary statistics can be informative of epidemiological parameters and can be used for reconstructing infectious disease dynamics during the early expansion of a viral lineage.

Demographic history and patterns of molecular evolution from whole genome sequencing in the radiation of Galapagos giant tortoises.

Whole genome sequencing provides deep insights into the evolutionary history of a species, including patterns of diversity, signals of selection, and historical demography. When applied to closely related taxa with a wealth of background knowledge, population genomics provides a comparative context for interpreting population genetic summary statistics and comparing empirical results with the expectations of population genetic theory. The Galapagos giant tortoises (Chelonoidis spp.), an iconic rapid and recent radiation, offer such an opportunity. Here, we sequenced whole genomes from three individuals of the 12 extant lineages of Galapagos giant tortoise and estimate diversity measures and reconstruct changes in coalescent rate over time. We also compare the number of derived alleles in each lineage to infer how synonymous and nonsynonymous mutation accumulation rates correlate with population size and life history traits. Remarkably, we find that patterns of molecular evolution are similar within individuals of the same lineage, but can differ significantly among lineages, reinforcing the evolutionary distinctiveness of the Galapagos giant tortoise species. Notably, differences in mutation accumulation among lineages do not align with simple population genetic predictions, suggesting that the drivers of purifying selection are more complex than is currently appreciated. By integrating results from earlier population genetic and phylogeographic studies with new findings from the analysis of whole genomes, we provide the most in-depth insights to date on the evolution of Galapagos giant tortoises, and identify discrepancies between expectation from population genetic theory and empirical data that warrant further scrutiny.

Predictors of phylogeographic structure among codistributed taxa across the complex Australian monsoonal tropics.

Differences in the geographic scale and depth of phylogeographic structure across codistributed taxa can reveal how microevolutionary processes such as population isolation and persistence drive diversification. In turn, environmental heterogeneity, species' traits, and historical biogeographic barriers may influence the potential for isolation and persistence. Using extensive SNP data and a combination of population genetic summary statistics and landscape genomic analyses, we explored predictors of the scale and depth of phylogeographic structure in codistributed lizard taxa from the topographically and climatically complex monsoonal tropics (AMT) of Australia. We first resolved intraspecific lineages and then tested whether genetic divergence across space within lineages is related to isolation by distance, resistance and/or environment and whether these factors differ across genera or between rock-related versus habitat generalist taxa. We then tested whether microevolutionary processes within lineages explain differences in the geographic scale and depth of intraspecific phylogeographic lineages. The results indicated that landscape predictors of phylogeographic structure differ between taxa. Within lineages, there was prevalent isolation by distance, but the strength of isolation by distance is independent of the taxonomic family, habitat specialization, and climate. Isolation by environment is the strongest predictor of landscape-scale genetic divergence for all taxa, with both temperature and precipitation acting as limiting factors. The strength of isolation by distance does not predict the geographic scale of the phylogeographic structure. However, more localized lineages had higher mean individual heterozygosity and less negative Tajima's D. This result implies that finer-scale phylogeographic structuring within species is associated with larger and more stable populations and, hence, persistence.

Climatic Refugia and Geographical Isolation Contribute to the Speciation and Genetic Divergence in Himalayan-Hengduan Tree Peonies (Paeonia delavayi and Paeonia ludlowii).

Himalaya and Hengduan Mountains (HHM) is a biodiversity hotspot, and very rich in endemic species. Previous phylogeographical studies proposed different hypotheses (vicariance and climate-driven speciation) in explaining diversification and the observed pattern of extant biodiversity, but it is likely that taxa are forming in this area in species-specific ways. Here, we reexplored the phylogenetic relationship and tested the corresponding hypotheses within Paeonia subsect. Delavayanae composed of one widespread species (Paeonia delavayi) and the other geographically confined species (Paeonia ludlowii). We gathered genetic variation data at three chloroplast DNA fragments and one nuclear gene from 335 individuals of 34 populations sampled from HHM. We performed a combination of population genetic summary statistics, isolation-with-migration divergence models, isolation by environment, and demographic history analyses. We found evidence for the current taxonomic treatment that P. ludlowii and P. delavayi are two different species with significant genetic differentiation. The significant isolation by environment was revealed within all sampled populations but genetic distances only explained by geographical distances within P. delavayi populations. The results of population divergence models and demographic history analyses indicated a progenitor–derivative relationship and the Late Quaternary divergence without gene flow between them. The coalescence of all sampled cpDNA haplotypes could date to the Late Miocene, and P. delavayi populations probably underwent a severe bottleneck in population size during the last glacial period. Genetic variation in Paeonia subsect. Delavayanae is associated with geographical and environmental distances. These findings point to the importance of geological and climatic changes as causes of the speciation event and lineage diversification within Paeonia subsect. Delavayanae.

Population Genomic Analyses Confirm Male-Biased Mutation Rates in Snakes.

Male-biased mutation rates occur in a diverse array of organisms. The ratio of male-to-female mutation rate may have major ramifications for evolution across the genome, and for sex-linked genes in particular. In ZW species, the Z chromosome is carried by males two-thirds of the time, leading to the prediction that male-biased mutation rates will have a disproportionate effect on the evolution of Z-linked genes relative to autosomes and the W chromosome. Colubroid snakes (including colubrids, elapids, and viperids) have ZW sex determination, yet male-biased mutation rates have not been well studied in this group. Here we analyze a population genomic dataset from rattlesnakes to quantify genetic variation within and genetic divergence between species. We use a new method for unbiased estimation of population genetic summary statistics to compare variation between the Z chromosome and autosomes and to calculate net nucleotide differentiation between species. We find evidence for a 2.03-fold greater mutation rate in male rattlesnakes relative to females, corresponding to an average μZ/μA ratio of 1.1. Our results from snakes are quantitatively similar to birds, suggesting that male-biased mutation rates may be a common feature across vertebrate lineages with ZW sex determination.

Comparative evolutionary genetics of deleterious load in sorghum and maize.

Sorghum and maize share a close evolutionary history that can be explored through comparative genomics1,2. To perform a large-scale comparison of the genomic variation between these two species, we analysed ~13 million variants identified from whole-genome resequencing of 499 sorghum lines together with 25 million variants previously identified in 1,218 maize lines. Deleterious mutations in both species were prevalent in pericentromeric regions, enriched in non-syntenic genes and present at low allele frequencies. A comparison of deleterious burden between sorghum and maize revealed that sorghum, in contrast to maize, departed from the domestication-cost hypothesis that predicts a higher deleterious burden among domesticates compared with wild lines. Additionally, sorghum and maize population genetic summary statistics were used to predict a gene deleterious index with an accuracy greater than 0.5. This research represents a key step towards understanding the evolutionary dynamics of deleterious variants in sorghum and provides a comparative genomics framework to start prioritizing these variants for removal through genome editing and breeding.

Space is the Place: Effects of Continuous Spatial Structure on Analysis of Population Genetic Data.

Real geography is continuous, but standard models in population genetics are based on discrete, well-mixed populations. As a result, many methods of analyzing genetic data assume that samples are a random draw from a well-mixed population, but are applied to clustered samples from populations that are structured clinally over space. Here, we use simulations of populations living in continuous geography to study the impacts of dispersal and sampling strategy on population genetic summary statistics, demographic inference, and genome-wide association studies (GWAS). We find that most common summary statistics have distributions that differ substantially from those seen in well-mixed populations, especially when Wright’s neighborhood size is < 100 and sampling is spatially clustered. “Stepping-stone” models reproduce some of these effects, but discretizing the landscape introduces artifacts that in some cases are exacerbated at higher resolutions. The combination of low dispersal and clustered sampling causes demographic inference from the site frequency spectrum to infer more turbulent demographic histories, but averaged results across multiple simulations revealed surprisingly little systematic bias. We also show that the combination of spatially autocorrelated environments and limited dispersal causes GWAS to identify spurious signals of genetic association with purely environmentally determined phenotypes, and that this bias is only partially corrected by regressing out principal components of ancestry. Last, we discuss the relevance of our simulation results for inference from genetic variation in real organisms.

Population genomic SNPs from epigenetic RADs: Gaining genetic and epigenetic data from a single established next‐generation sequencing approach

Abstract Epigenetics is increasingly recognized as an important molecular mechanism underlying phenotypic variation. To study DNA methylation in ecological and evolutionary contexts, epiRADseq is a cost‐effective next‐generation sequencing (NGS) technique based on reduced representation sequencing of genomic regions surrounding non‐/methylated sites. EpiRADseq for genome‐wide methylation abundance and ddRADseq for genome‐wide single‐nucleotide polymorphism (SNP) genotyping follow very similar library and sequencing protocols, but to date these two types of dataset have been handled separately. Here we test the performance of using epiRADseq data to generate SNPs for population genomic analyses. We tested the robustness of using epiRADseq data for population genomics with two independent datasets: a newly generated single‐end dataset for the European whitefish Coregonus lavaretus, and a re‐analysis of publicly available, previously published paired‐end data on corals. Using standard bioinformatic pipelines with a reference genome and without (i.e. de novo catalogue loci), we compared the number of SNPs retained, population genetic summary statistics and population genetic structure between data drawn from ddRADseq and epiRADseq library preparations. We found that SNPs drawn from epiRADseq are similar in number to those drawn from ddRADseq, with 55%–83% of SNPs being identified by both methods. Genotyping error rate was &lt;5% in both approaches. EpiRADseq‐specific allele dropout was low (~1%). For summary statistics, such as heterozygosity and nucleotide diversity, there is a strong correlation between methods (Spearman's rho &gt; 0.88). Furthermore, identical patterns of population genetic structure were recovered using SNPs from epiRADseq and ddRADseq approaches. We show that SNPs obtained from epiRADseq are highly similar to those from ddRADseq and are equivalent for estimating genetic diversity and population structure. This finding is particularly relevant to researchers interested in genetics and epigenetics on the same individuals because using a single epigenomic approach to generate two datasets greatly reduces the time and financial costs compared to using these techniques separately. It also efficiently enables correction of epigenetic estimates with population genetic data. Many studies will benefit from a combinatorial approach with genetic and epigenetic markers and this demonstrates a single, efficient method to do so.

A statistical model for reference-free inference of archaic local ancestry.

Statistical analyses of genomic data from diverse human populations have demonstrated that archaic hominins, such as Neanderthals and Denisovans, interbred or admixed with the ancestors of present-day humans. Central to these analyses are methods for inferring archaic ancestry along the genomes of present-day individuals (archaic local ancestry). Methods for archaic local ancestry inference rely on the availability of reference genomes from the ancestral archaic populations for accurate inference. However, several instances of archaic admixture lack reference archaic genomes, making it difficult to characterize these events. We present a statistical method that combines diverse population genetic summary statistics to infer archaic local ancestry without access to an archaic reference genome. We validate the accuracy and robustness of our method in simulations. When applied to genomes of European individuals, our method recovers segments that are substantially enriched for Neanderthal ancestry, even though our method did not have access to any Neanderthal reference genomes.

Tabula rasa in the Patagonian Channels II: The cushion peat bog species Astelia pumila (Asteliaceae) and Donatia fascicularis (Stylidiaceae) survived the last glacial in south‐central Chile

AbstractAimPlant phylogeographic data from the Patagonian Channels are scant and it is largely unknown how the extensive Quaternary glaciations affected the population dynamics of the region's major vegetation component, that is cushion peat bogs (Magellanic moorland). Whether ice‐age glaciers wiped out all terrestrial plant life or whether some populations persisted in situ remains unclear. We reconstructed the phylogeography of two dominant Patagonian cushion peat bog species, Astelia pumila (G.Forst.) Gaudich. (Asteliaceae) and Donatia fascicularis J.R.Forst. &amp; G.Forst. (Stylidiaceae), to test (a) the hypothesis of a glacial refugium for moorland plants in south‐central Chile and (b) the tabula rasa scenario for the Patagonian Channels. The retrieved phylogeographic patterns were compared with those reported previously for a further cushion peat bog species (Pfanzelt et al., Molecular Ecology 26, 4027–4044), with the objective to provide a broader picture of how West Patagonian moorland plants responded to the Quaternary ice‐ages.LocationWest and Fuegian Patagonia, and the Falkland Islands (Islas Malvinas), southern South America.MethodsDNA sequence data from seven and fourteen, respectively, nuclear loci containing Simple Sequence Repeats of 371 and 328 individuals of the two study species were analysed using population genetic summary statistics, phylogenetic networks and Bayesian and multivariate methods to determine genetic structure. Ecological niche modelling was used to reconstruct the spatial distribution of suitable habitat at the Last Glacial Maximum.ResultsAll A. pumila populations belong to a single population genetic cluster. In the case of D. fascicularis, only the northernmost sampled population from Nahuelbuta (Chile) is genetically distinct, whereas the remainder forms a cluster without much further substructure. According to palaeodistribution models, south‐central Chile offered suitable habitat during the last glacial.Main conclusionBoth ecological niche modelling and the very low genetic subdifferentiation are congruent with a tabula rasa scenario for the Patagonian Channels. Populations survived the last glacial in south‐central Chile, in an area to the northwest of the ice sheet. From there, southern regions were recolonized through highly bottlenecked source populations. Other, non‐mutually exclusive factors may have further shaped the population genetic patterns, among them high gene flow mediated by the strong westerly winds.

Supervised machine learning reveals introgressed loci in the genomes of Drosophila simulans and D. sechellia.

Hybridization and gene flow between species appears to be common. Even though it is clear that hybridization is widespread across all surveyed taxonomic groups, the magnitude and consequences of introgression are still largely unknown. Thus it is crucial to develop the statistical machinery required to uncover which genomic regions have recently acquired haplotypes via introgression from a sister population. We developed a novel machine learning framework, called FILET (Finding Introgressed Loci via Extra-Trees) capable of revealing genomic introgression with far greater power than competing methods. FILET works by combining information from a number of population genetic summary statistics, including several new statistics that we introduce, that capture patterns of variation across two populations. We show that FILET is able to identify loci that have experienced gene flow between related species with high accuracy, and in most situations can correctly infer which population was the donor and which was the recipient. Here we describe a data set of outbred diploid Drosophila sechellia genomes, and combine them with data from D. simulans to examine recent introgression between these species using FILET. Although we find that these populations may have split more recently than previously appreciated, FILET confirms that there has indeed been appreciable recent introgression (some of which might have been adaptive) between these species, and reveals that this gene flow is primarily in the direction of D. simulans to D. sechellia.

Predicted activity of UGT2B7, ABCB1, OPRM1, and COMT using full-gene haplotypes and their association with the CYP2D6-inferred metabolizer phenotype

The pharmacogene, CYP2D6, is commonly used to infer metabolizer phenotype of many marketed drugs and endogenous toxins in ante- and post-mortem patients but only represents the efficiency of phase 1 metabolism. Downstream metabolic enzymes encoded by UGT2B7, ABCB1, OPRM1, and COMT also have been implicated in variable individual response to drugs due to their activity at different stages of the tramadol ADME (absorption, distribution, metabolism, and excretion) process. While commonly studied as single genes using targeted genotyping approaches, a more comprehensive tramadol metabolism profile has not been evaluated. 1000 Genomes Project data for UGT2B7, ABCB1, OPRM1, and COMT were used to characterize full-gene haplotypes and their effect on protein function using in-house excel-based workbooks, PopART, and TreeView. Population genetic summary statistics and intergenic analyses associated these haplotypes with full-gene CYP2D6-inferred metabolizer phenotype. The findings suggest that UGT2B7, ABCB1, OPRM1, and COMT may contribute to predicted metabolizer phenotype as opposed to relying solely on CYP2D6.

Genomewide patterns of variation in genetic diversity are shared among populations, species and higher-order taxa.

Genomewide screens of genetic variation within and between populations can reveal signatures of selection implicated in adaptation and speciation. Genomic regions with low genetic diversity and elevated differentiation reflective of locally reduced effective population sizes (Ne ) are candidates for barrier loci contributing to population divergence. Yet, such candidate genomic regions need not arise as a result of selection promoting adaptation or advancing reproductive isolation. Linked selection unrelated to lineage-specific adaptation or population divergence can generate comparable signatures. It is challenging to distinguish between these processes, particularly when diverging populations share ancestral genetic variation. In this study, we took a comparative approach using population assemblages from distant clades assessing genomic parallelism of variation in Ne . Utilizing population-level polymorphism data from 444 resequenced genomes of three avian clades spanning 50 million years of evolution, we tested whether population genetic summary statistics reflecting genomewide variation in Ne would covary among populations within clades, and importantly, also among clades where lineage sorting has been completed. All statistics including population-scaled recombination rate (ρ), nucleotide diversity (π) and measures of genetic differentiation between populations (FST , PBS, dxy ) were significantly correlated across all phylogenetic distances. Moreover, genomic regions with elevated levels of genetic differentiation were associated with inferred pericentromeric and subtelomeric regions. The phylogenetic stability of diversity landscapes and stable association with genomic features support a role of linked selection not necessarily associated with adaptation and speciation in shaping patterns of genomewide heterogeneity in genetic diversity.

Identifying Genetic Signatures of Natural Selection Using Pooled Population Sequencing in Picea abies.

The joint inference of selection and past demography remain a costly and demanding task. We used next generation sequencing of two pools of 48 Norway spruce mother trees, one corresponding to the Fennoscandian domain, and the other to the Alpine domain, to assess nucleotide polymorphism at 88 nuclear genes. These genes are candidate genes for phenological traits, and most belong to the photoperiod pathway. Estimates of population genetic summary statistics from the pooled data are similar to previous estimates, suggesting that pooled sequencing is reliable. The nonsynonymous SNPs tended to have both lower frequency differences and lower FST values between the two domains than silent ones. These results suggest the presence of purifying selection. The divergence between the two domains based on synonymous changes was around 5 million yr, a time similar to a recent phylogenetic estimate of 6 million yr, but much larger than earlier estimates based on isozymes. Two approaches, one of them novel and that considers both FST and difference in allele frequencies between the two domains, were used to identify SNPs potentially under diversifying selection. SNPs from around 20 genes were detected, including genes previously identified as main target for selection, such as PaPRR3 and PaGI.

Phylogeography and trans‐Pacific divergence of the rocky shore gastropod Nucella lima

AbstractAimWe have used phylogeographical and multilocus coalescent population genetic methods to reconstruct the Pleistocene biogeographical history of a broadly distributed north Pacific rocky shore gastropod, Nucella lima.LocationNorthern Pacific rim, from south‐eastern Alaska to Hokkaido Island.MethodsWe gathered DNA sequence data from three loci from N. lima, whose current distribution spans the entire North Pacific rim. We used a combination of population genetic summary statistics (Tajima's D, Fu's FS and ΦST), isolation‐with‐migration divergence models, and extended Bayesian skyline plots to reconstruct the recent biogeographical history of this species.ResultsThe largest values of ΦST across all loci were always between eastern and western samples. Population divergence models indicated no gene flow and mid‐Pleistocene divergence times (&gt; 600 ka) between eastern and western populations. Mitochondrial DNA diversity in the east was low, and coalescent‐based estimates of effective population size were significantly smaller in the east 20,000 years ago, at the end of the last glacial period.Main conclusionsThe results are consistent with a hypothesis in which north Pacific populations were separated into eastern and western refugia by 317 ka with no gene flow since the split. Eastern populations probably underwent a severe bottleneck in population size during the last glacial period. The contrasting demographic histories of eastern and western populations are consistent with the general palaeobiogeographical pattern of greater climate‐related extinction of marine taxa in the eastern Pacific.

Utilizing whole genome sequences to study population genomics of gene networks: a case study of the Arabidopsis thalianaimmune-signaling network

Arabidopsis thaliana is a member of the mustard (Brassicaceae) family that is widely used as a model organism in plant biology. The 1001 Genomes Project [1] has been sequencing the genomes of Arabidopsis strains (accessions) and has made these sequences available. We selected the genomes of 30 Arabidopsis accessions with diverse geographical and environmental origins for our analysis. Using the TAIR8 annotation of the Arabidopsis reference genome, for the accession Col-0, we generated a dataset of approximately 27,000 protein-coding genes for all of the 30 genomes. With such population genomic data, it is feasible to ask whether a group of genes is under a different type of selection from the rest of the genome. The plant immune-signaling network is robust to network perturbations. We hypothesized that genes that constitute a robust network tend to be under neutral selection because deleterious mutations in such genes do not strongly affect the immune phenotype owing to the robustness of the network. We identified the component genes of the plant immune-signaling network in a relatively unbiased manner by mining AraNet [2], which is a functional gene network built without using phenotype information. We compared population genetic summary statistics for the network component genes and those for all of the genes in the genome. For example, Tajima’s D is such a summary statistic, and positive, negative and zero values of Tajima’s D suggest diversifying, purifying and neutral selection, respectively, when the effective population size does not change. The Tajima’s D value distribution for all of the genes in the genome has a single clear peak with a negative value, suggesting that purifying selection is the genomic norm. Our preliminary results showed that the plant immune-signaling network genes are significantly enriched with genes whose Tajima’s D values are near zero compared with all of the genes in the genome. This finding suggests that there is a lower level of purifying selection among the network component genes than other genes.

Population Graphs: the graph theoretic shape of genetic structure

Patterns of intraspecific genetic variation result from interactions among both historical and contemporary evolutionary processes. Traditionally, population geneticists have used methods such as F-statistics, pairwise isolation by distance models, spatial autocorrelation and coalescent models to analyse this variation and to gain insight about causal evolutionary processes. Here we introduce a novel approach (Population Graphs) that focuses on the analysis of marker-based population genetic data within a graph theoretic framework. This method can be used to estimate traditional population genetic summary statistics, but its primary focus is on characterizing the complex topology resulting from historical and contemporary genetic interactions among populations. We introduce the application of Population Graphs by examining the range-wide population genetic structure of a Sonoran Desert cactus (Lophocereus schottii). With this data set, we evaluate hypotheses regarding historical vicariance, isolation by distance, population-level assignment and the importance of specific populations to species-wide genetic connectivity. We close by discussing the applicability of Population Graphs for addressing a wide range of population genetic and phylogeographical problems.