DetSel 1.0: A Computer Program to Detect Markers Responding to Selection

SNP4OrphanSpecies: A bioinformatics pipeline to isolate molecular markers for studying genetic diversity of orphan species

Background

For several decades, an increase in disease or pest emergences due to anthropogenic introduction or environmental changes has been recorded. This increase leads to serious threats to the genetic and species diversity of numerous ecosystems. Many of these events involve species with poor or no genomic resources (called here "orphan species"). This lack of resources is a serious limitation to our understanding of the origin of emergent populations, their ability to adapt to new environments and to predict future consequences to biodiversity. Analyses of genetic diversity are an efficient method to obtain this information rapidly, but require available polymorphic genetic markers.

New information

We developed a generic bioinformatics pipeline to rapidly isolate such markers with the goal for the pipeline to be applied in studies of invasive taxa from different taxonomic groups, with a special focus on forest fungal pathogens and insect pests. This pipeline is based on: 1) an automated de novo genome assembly obtained from shotgun whole genome sequencing using paired-end Illumina technology; 2) the isolation of single-copy genes conserved in species related to the studied emergent organisms; 3) primer development for multiplexed short sequences obtained from these conserved genes. Previous studies have shown that intronic regions of these conserved genes generally contain several single nucleotide polymorphisms within species. The pipeline's functionality was evaluated with sequenced genomes of five invasive or expanding pathogen and pest species in Europe (Armillariaostoyae (Romagn.) Herink 1973, Bursaphelenchusxylophilus Steiner & Buhrer 1934, Sphaeropsissapinea (fr.) Dicko & B. Sutton 1980, Erysiphealphitoides (Griffon & Maubl.) U. Braun & S. Takam. 2000, Thaumetopoeapityocampa Denis & Schiffermüller, 1775). We successfully isolated several pools of one hundred short gene regions for each assembled genome, which can be amplified in multiplex. The bioinformatics pipeline is user-friendly and requires little computational resources. This easy-to-set-up and run method for genetic marker identification will be useful for numerous laboratories studying biological invasions, but with limited resources and expertise in bioinformatics.

Genetic structure of wild rice Zizania latifolia in an expansive heterogeneous landscape along a latitudinal gradient

Global aquatic habitats are undergoing rapid degradation and fragmentation as a result of climate change and changes in land use. Understanding the genetic variability and adaptive potential of aquatic plant species is thus important for conservation purposes. In this study, we investigated the genetic diversity and structure of the extant natural populations of Zizania latifolia from five river basins in China based on 46 microsatellite markers. We tested isolation by environment (IBE), isolation by resistance (IBR), and isolation by distance (IBD) patterns using a reciprocal causal model (RCM). Furthermore, we elucidated the impact of the environment on Z. latifolia genetic diversity using generalized linear models (GLMs) and spatially explicit mixed models. Low genetic diversity (HE = 0.125–0.433) and high genetic differentiation (FST = 0.641, Øpt = 0.654) were found. Higher historical gene flow (MH = 0.212–2.354) than contemporary gene flow (MC = 0.0112–0.0247) and significant bottlenecks in almost all populations were identified, highlighting the negative impact of wetland fragmentation. The IBE model was exclusively supported for all populations and in three river basins. The IBD and IBR models were supported in one river basin each. The maximum temperature of the warmest month and precipitation seasonality were the plausible environmental parameters responsible for the observed pattern of genetic diversity. Local adaptation signatures were found, with nine loci identified as outliers, four of which were gene-linked and associated with environmental variables. Based on these findings, IBE is more important than IBD and IBR in shaping the genetic structure of Z. latifolia.

A brief history and popularity of methods and tools used to estimate micro-evolutionary forces

Population genetics is a field of research that predates the current generations of sequencing technology. Those approaches, that were established before massively parallel sequencing methods, have been adapted to these new marker systems (in some cases involving the development of new methods) that allow genome-wide estimates of the four major micro-evolutionary forces-mutation, gene flow, genetic drift, and selection. Nevertheless, classic population genetic markers are still commonly used and a plethora of analysis methods and programs is available for these and high-throughput sequencing (HTS) data. These methods employ various and diverse theoretical and statistical frameworks, to varying degrees of success, to estimate similar evolutionary parameters making it difficult to get a concise overview across the available approaches. Presently, reviews on this topic generally focus on a particular class of methods to estimate one or two evolutionary parameters. Here, we provide a brief history of methods and a comprehensive list of available programs for estimating micro-evolutionary forces. We furthermore analyzed their usage within the research community based on popularity (citation bias) and discuss the implications of this bias for the software community. We found that a few programs received the majority of citations, with program success being independent of both the parameters estimated and the computing platform. The only deviation from a model of exponential growth in the number of citations was found for the presence of a graphical user interface (GUI). Interestingly, no relationship was found for the impact factor of the journals, when the tools were published, suggesting accessibility might be more important than visibility.

Navigating the currents of seascape genomics: how spatial analyses can augment population genomic studies

Population genomic approaches are making rapid inroads in the study of non-model organisms, including marine taxa. To date, these marine studies have predominantly focused on rudimentary metrics describing the spatial and environmental context of their study region (e.g., geographical distance, average sea surface temperature, average salinity). We contend that a more nuanced and considered approach to quantifying seascape dynamics and patterns can strengthen population genomic investigations and help identify spatial, temporal, and environmental factors associated with differing selective regimes or demographic histories. Nevertheless, approaches for quantifying marine landscapes are complicated. Characteristic features of the marine environment, including pelagic living in flowing water (experienced by most marine taxa at some point in their life cycle), require a well-designed spatial-temporal sampling strategy and analysis. Many genetic summary statistics used to describe populations may be inappropriate for marine species with large population sizes, large species ranges, stochastic recruitment, and asymmetrical gene flow. Finally, statistical approaches for testing associations between seascapes and population genomic patterns are still maturing with no single approach able to capture all relevant considerations. None of these issues are completely unique to marine systems and therefore similar issues and solutions will be shared for many organisms regardless of habitat. Here, we outline goals and spatial approaches for landscape genomics with an emphasis on marine systems and review the growing empirical literature on seascape genomics. We review established tools and approaches and highlight promising new strategies to overcome select issues including a strategy to spatially optimize sampling. Despite the many challenges, we argue that marine systems may be especially well suited for identifying candidate genomic regions under environmentally mediated selection and that seascape genomic approaches are especially useful for identifying robust locus-by-environment associations.

High performance computation of landscape genomic models including local indicators of spatial association

With the increasing availability of both molecular and topo-climatic data, the main challenges facing landscape genomics - that is the combination of landscape ecology with population genomics - include processing large numbers of models and distinguishing between selection and demographic processes (e.g. population structure). Several methods address the latter, either by estimating a null model of population history or by simultaneously inferring environmental and demographic effects. Here we present samβada, an approach designed to study signatures of local adaptation, with special emphasis on high performance computing of large-scale genetic and environmental data sets. samβada identifies candidate loci using genotype-environment associations while also incorporating multivariate analyses to assess the effect of many environmental predictor variables. This enables the inclusion of explanatory variables representing population structure into the models to lower the occurrences of spurious genotype-environment associations. In addition, samβada calculates local indicators of spatial association for candidate loci to provide information on whether similar genotypes tend to cluster in space, which constitutes a useful indication of the possible kinship between individuals. To test the usefulness of this approach, we carried out a simulation study and analysed a data set from Ugandan cattle to detect signatures of local adaptation with samβada, bayenv, lfmm and an F_ST outlier method (FDIST approach in arlequin) and compare their results. samβada - an open source software for Windows, Linux and Mac OS X available at http://lasig.epfl.ch/sambada - outperforms other approaches and better suits whole-genome sequence data processing.

Controlling false discoveries in genome scans for selection

Population differentiation (PD) and ecological association (EA) tests have recently emerged as prominent statistical methods to investigate signatures of local adaptation using population genomic data. Based on statistical models, these genomewide testing procedures have attracted considerable attention as tools to identify loci potentially targeted by natural selection. An important issue with PD and EA tests is that incorrect model specification can generate large numbers of false-positive associations. Spurious association may indeed arise when shared demographic history, patterns of isolation by distance, cryptic relatedness or genetic background are ignored. Recent works on PD and EA tests have widely focused on improvements of test corrections for those confounding effects. Despite significant algorithmic improvements, there is still a number of open questions on how to check that false discoveries are under control and implement test corrections, or how to combine statistical tests from multiple genome scan methods. This tutorial study provides a detailed answer to these questions. It clarifies the relationships between traditional methods based on allele frequency differentiation and EA methods and provides a unified framework for their underlying statistical tests. We demonstrate how techniques developed in the area of genomewide association studies, such as inflation factors and linear mixed models, benefit genome scan methods and provide guidelines for good practice while conducting statistical tests in landscape and population genomic applications. Finally, we highlight how the combination of several well-calibrated statistical tests can increase the power to reject neutrality, improving our ability to infer patterns of local adaptation in large population genomic data sets.

Towards the identification of the loci of adaptive evolution

1. Establishing the genetic and molecular basis underlying adaptive traits is one of the major goals of evolutionary geneticists in order to understand the connection between genotype and phenotype and elucidate the mechanisms of evolutionary change. Despite considerable effort to address this question, there remain relatively few systems in which the genes shaping adaptations have been identified. 2. Here, we review the experimental tools that have been applied to document the molecular basis underlying evolution in several natural systems, in order to highlight their benefits, limitations and suitability. In most cases, a combination of DNA, RNA and functional methodologies with field experiments will be needed to uncover the genes and mechanisms shaping adaptation in nature.

Continental-scale footprint of balancing and positive selection in a small rodent (Microtus arvalis)

Genetic adaptation to different environmental conditions is expected to lead to large differences between populations at selected loci, thus providing a signature of positive selection. Whereas balancing selection can maintain polymorphisms over long evolutionary periods and even geographic scale, thus leads to low levels of divergence between populations at selected loci. However, little is known about the relative importance of these two selective forces in shaping genomic diversity, partly due to difficulties in recognizing balancing selection in species showing low levels of differentiation. Here we address this problem by studying genomic diversity in the European common vole (Microtus arvalis) presenting high levels of differentiation between populations (average F_ST = 0.31). We studied 3,839 Amplified Fragment Length Polymorphism (AFLP) markers genotyped in 444 individuals from 21 populations distributed across the European continent and hence over different environmental conditions. Our statistical approach to detect markers under selection is based on a Bayesian method specifically developed for AFLP markers, which treats AFLPs as a nearly codominant marker system, and therefore has increased power to detect selection. The high number of screened populations allowed us to detect the signature of balancing selection across a large geographic area. We detected 33 markers potentially under balancing selection, hence strong evidence of stabilizing selection in 21 populations across Europe. However, our analyses identified four-times more markers (138) being under positive selection, and geographical patterns suggest that some of these markers are probably associated with alpine regions, which seem to have environmental conditions that favour adaptation. We conclude that despite favourable conditions in this study for the detection of balancing selection, this evolutionary force seems to play a relatively minor role in shaping the genomic diversity of the common vole, which is more influenced by positive selection and neutral processes like drift and demographic history.

Genetic differentiation revealed by selective loci of drought-responding EST-SSRs between upland and lowland rice in China

Upland and lowland rice (Oryza sativa L.) represent two of the most important rice ecotypes adapted to ago-ecosystems with contrasting soil-water conditions. Upland rice, domesticated in the water-limited environment, contains valuable drought-resistant characters that can be used in water-saving breeding. Knowledge about the divergence between upland and lowland rice will provide valuable cues for the evolution of drought-resistance in rice. Genetic differentiation between upland and lowland rice was explored by 47 Simple Sequence Repeats (SSRs) located in drought responding expressed sequence tags (ESTs) among 377 rice landraces. The morphological traits of drought-resistance were evaluated in the field experiments. Different outlier loci were detected in the japonica and indica subspecies, respectively. Considerable genetic differentiation between upland and lowland rice on these outlier loci was estimated in japonica (Fst = 0.258) and indica (Fst = 0.127). Furthermore, populations of the upland and lowland ecotypes were clustered separately on these outlier loci. A significant correlation between genetic distance matrices and the dissimilarity matrices of drought-resistant traits was determined, indicating a certain relationship between the upland-lowland rice differentiation and the drought-resistance. Divergent selections occur between upland and lowland rice on the drought-resistance as the Qsts of some drought-resistant traits are significantly higher than the neutral Fst. In addition, the upland- and lowland-preferable alleles responded differently among ecotypes or allelic types under osmotic stress. This shows the evolutionary signature of drought resistance at the gene expression level. The findings of this study can strengthen our understanding of the evolution of drought-resistance in rice with significant implications in the improvement of rice drought-resistance.

Genome scans for detecting footprints of local adaptation using a Bayesian factor model

There is a considerable impetus in population genomics to pinpoint loci involved in local adaptation. A powerful approach to find genomic regions subject to local adaptation is to genotype numerous molecular markers and look for outlier loci. One of the most common approaches for selection scans is based on statistics that measure population differentiation such as FST. However, there are important caveats with approaches related to FST because they require grouping individuals into populations and they additionally assume a particular model of population structure. Here, we implement a more flexible individual-based approach based on Bayesian factor models. Factor models capture population structure with latent variables called factors, which can describe clustering of individuals into populations or isolation-by-distance patterns. Using hierarchical Bayesian modeling, we both infer population structure and identify outlier loci that are candidates for local adaptation. In order to identify outlier loci, the hierarchical factor model searches for loci that are atypically related to population structure as measured by the latent factors. In a model of population divergence, we show that it can achieve a 2-fold or more reduction of false discovery rate compared with the software BayeScan or with an FST approach. We show that our software can handle large data sets by analyzing the single nucleotide polymorphisms of the Human Genome Diversity Project. The Bayesian factor model is implemented in the open-source PCAdapt software.

Identification of selection signatures in livestock species

The identification of regions that have undergone selection is one of the principal goals of theoretical and applied evolutionary genetics. Such studies can also provide information about the evolutionary processes involved in shaping genomes, as well as physical and functional information about genes/genomic regions. Domestication followed by breed formation and selection schemes has allowed the formation of very diverse livestock breeds adapted to a wide variety of environments and with special characteristics. The advances in genomics in the last five years have enabled the development of several methods to detect selection signatures and have resulted in the publication of a considerable number of studies involving livestock species. The aims of this review are to describe the principal effects of natural/artificial selection on livestock genomes, to present the main methods used to detect selection signatures and to discuss some recent results in this area. This review should be useful also to research scientists working with wild animals/non-domesticated species and plant biologists working with breeding and evolutionary biology.

Gene-flow in a mosaic hybrid zone: is local introgression adaptive?

Genome-wide scans of genetic differentiation between hybridizing taxa can identify genome regions with unusual rates of introgression. Regions of high differentiation might represent barriers to gene flow, while regions of low differentiation might indicate adaptive introgression-the spread of selectively beneficial alleles between reproductively isolated genetic backgrounds. Here we conduct a scan for unusual patterns of differentiation in a mosaic hybrid zone between two mussel species, Mytilus edulis and M. galloprovincialis. One outlying locus, mac-1, showed a characteristic footprint of local introgression, with abnormally high frequency of edulis-derived alleles in a patch of M. galloprovincialis enclosed within the mosaic zone, but low frequencies outside of the zone. Further analysis of DNA sequences showed that almost all of the edulis allelic diversity had introgressed into the M. galloprovincialis background in this patch. We then used a variety of approaches to test the hypothesis that there had been adaptive introgression at mac-1. Simulations and model fitting with maximum-likelihood and approximate Bayesian computation approaches suggested that adaptive introgression could generate a "soft sweep," which was qualitatively consistent with our data. Although the migration rate required was high, it was compatible with the functioning of an effective barrier to gene flow as revealed by demographic inferences. As such, adaptive introgression could explain both the reduced intraspecific differentiation around mac-1 and the high diversity of introgressed alleles, although a localized change in barrier strength may also be invoked. Together, our results emphasize the need to account for the complex history of secondary contacts in interpreting outlier loci.

Genomic regions repeatedly involved in divergence among plant-specialized pea aphid biotypes

Understanding the genetic bases of biological diversification is a long-standing goal in evolutionary biology. Here, we investigate whether replicated cases of adaptive divergence involve the same genomic regions in the pea aphid, Acyrthosiphon pisum, a large complex of genetically differentiated biotypes, each specialized on different species of legumes. A previous study identified genomic regions putatively involved in host-plant adaptation and/or reproductive isolation by performing a hierarchical genome scan in three biotypes. This led to the identification of 11 F(ST) outliers among 390 polymorphic microsatellite markers. In this study, the outlier status of these 11 loci was assessed in eight biotypes specialized on other host plants. Four of the 11 previously identified outliers showed greater genetic differentiation among these additional biotypes than expected under the null hypothesis of neutral evolution (α < 0.01). Whether these hotspots of genomic divergence result from adaptive events, intrinsic barriers or reduced recombination is discussed.

Population structure of barley landrace populations and gene-flow with modern varieties

Landraces are heterogeneous plant varieties that are reproduced by farmers as populations that are subject to both artificial and natural selection. Landraces are distinguished by farmers due to their specific traits, and different farmers often grow different populations of the same landrace. We used simple sequence repeats (SSRs) to analyse 12 barley landrace populations from Sardinia from two collections spanning 10 years. We analysed the population structure, and compared the population diversity of the landraces that were collected at field level (population). We used a representative pool of barley varieties for diversity comparisons and to analyse the effects of gene flow from modern varieties. We found that the Sardinian landraces are a distinct gene pool from those of both two-row and six-row barley varieties. There is also a low, but significant, mean level and population-dependent level of introgression from the modern varieties into the Sardinian landraces. Moreover, we show that the Sardinian landraces have the same level of gene diversity as the representative sample of modern commercial varieties grown in Italy in the last decades, even within population level. Thus, these populations represent crucial sources of germplasm that will be useful for crop improvement and for population genomics studies and association mapping, to identify genes, loci and genome regions responsible for adaptive variations. Our data also suggest that landraces are a source of valuable germplasm for sustainable agriculture in the context of future climate change, and that in-situ conservation strategies based on farmer use can preserve the genetic identity of landraces while allowing adaptation to local environments.

When history repeats itself: exploring the genetic architecture of host-plant adaptation in two closely related lepidopteran species

The genus Ostrinia includes two allopatric maize pests across Eurasia, namely the European corn borer (ECB, O. nubilalis) and the Asian corn borer (ACB, O. furnacalis). A third species, the Adzuki bean borer (ABB, O. scapulalis), occurs in sympatry with both the ECB and the ACB. The ABB mostly feeds on native dicots, which probably correspond to the ancestral host plant type for the genus Ostrinia. This situation offers the opportunity to characterize the two presumably independent adaptations or preadaptations to maize that occurred in the ECB and ACB. In the present study, we aimed at deciphering the genetic architecture of these two adaptations to maize, a monocot host plant recently introduced into Eurasia. To this end, we performed a genome scan analysis based on 684 AFLP markers in 12 populations of ECB, ACB and ABB. We detected 2 outlier AFLP loci when comparing French populations of the ECB and ABB, and 9 outliers when comparing Chinese populations of the ACB and ABB. These outliers were different in both countries, and we found no evidence of linkage disequilibrium between any two of them. These results suggest that adaptation or preadaptation to maize relies on a different genetic architecture in the ECB and ACB. However, this conclusion must be considered in light of the constraints inherent to genome scan approaches and of the intricate evolution of adaptation and reproductive isolation in the Ostrinia spp. complex.

Gene flow at major transitional areas in sea bass (Dicentrarchus labrax) and the possible emergence of a hybrid swarm

The population genetic structure of sea bass (Dicentrarchus labrax) along a transect from the Atlantic Ocean (AO) to the Eastern Mediterranean (EM) Sea differs from that of most other marine taxa in this area. Three populations (AO, Western Mediterranean [WM], EM) are recognized today, which were originally two allopatric populations. How two ancestral genetic units have evolved into three distinct units has not been addressed yet. Therefore, to investigate mechanisms that lead to the emergence of the central WM population, its current status, and its connectivity with the two parental populations, we applied 20 nuclear loci that were either gene associated or gene independent. Results confirmed the existence of three distinct gene pools, with higher differentiation at two transitional areas, the Almeria-Oran Front (AOF) and of the Siculo-Tunisian Strait (STS), than within any population. Significant linkage disequilibrium and heterozygote excess indicated that the STS is probably another tension zone, as already described for the AOF. Neutrality tests fail to reveal marker loci that could be driven by selection within or among metapopulations, except for locus DLA0068. Collectively, results support that the central WM population arose by trapping two tensions zones at distinct geographic locations of limited connectivity. Population assignment further revealed that WM individuals were more introgressed than individuals from the other two metapopulations. This suggests that this population might result from hybrid swarming, and was or is still seeded by genes received through the filter of each tension zone.

Genome scanning for detecting adaptive genes along environmental gradients in the Japanese conifer, Cryptomeria japonica

Local adaptation is important in evolutionary processes and speciation. We used multiple tests to identify several candidate genes that may be involved in local adaptation from 1026 loci in 14 natural populations of Cryptomeria japonica, the most economically important forestry tree in Japan. We also studied the relationships between genotypes and environmental variables to obtain information on the selective pressures acting on individual populations. Outlier loci were mapped onto a linkage map, and the positions of loci associated with specific environmental variables are considered. The outlier loci were not randomly distributed on the linkage map; linkage group 11 was identified as a genomic island of divergence. Three loci in this region were also associated with environmental variables such as mean annual temperature, daily maximum temperature, maximum snow depth, and so on. Outlier loci identified with high significance levels will be essential for conservation purposes and for future work on molecular breeding.

Genetic variation in the acorn barnacle from allozymes to population genomics

Understanding the patterns of genetic variation within and among populations is a central problem in population and evolutionary genetics. We examine this question in the acorn barnacle, Semibalanus balanoides, in which the allozyme loci Mpi and Gpi have been implicated in balancing selection due to varying selective pressures at different spatial scales. We review the patterns of genetic variation at the Mpi locus, compare this to levels of population differentiation at mtDNA and microsatellites, and place these data in the context of genome-wide variation from high-throughput sequencing of population samples spanning the North Atlantic. Despite considerable geographic variation in the patterns of selection at the Mpi allozyme, this locus shows rather low levels of population differentiation at ecological and trans-oceanic scales (F(ST) ~ 5%). Pooled population sequencing was performed on samples from Rhode Island (RI), Maine (ME), and Southwold, England (UK). Analysis of more than 650 million reads identified approximately 335,000 high-quality SNPs in 19 million base pairs of the S. balanoides genome. Much variation is shared across the Atlantic, but there are significant examples of strong population differentiation among samples from RI, ME, and UK. An F(ST) outlier screen of more than 22,000 contigs provided a genome-wide context for interpretation of earlier studies on allozymes, mtDNA, and microsatellites. F(ST) values for allozymes, mtDNA and microsatellites are close to the genome-wide average for random SNPs, with the exception of the trans-Atlantic F(ST) for mtDNA. The majority of F(ST) outliers were unique between individual pairs of populations, but some genes show shared patterns of excess differentiation. These data indicate that gene flow is high, that selection is strong on a subset of genes, and that a variety of genes are experiencing diversifying selection at large spatial scales. This survey of polymorphism in S. balanoides provides a number of genomic tools that promise to make this a powerful model for ecological genomics of the rocky intertidal.

Divergence hitchhiking and the spread of genomic isolation during ecological speciation-with-gene-flow

In allopatric populations, geographical separation simultaneously isolates the entire genome, allowing genetic divergence to accumulate virtually anywhere in the genome. In sympatric populations, however, the strong divergent selection required to overcome migration produces a genetic mosaic of divergent and non-divergent genomic regions. In some recent genome scans, each divergent genomic region has been interpreted as an independent incidence of migration/selection balance, such that the reduction of gene exchange is restricted to a few kilobases around each divergently selected gene. I propose an alternative mechanism, 'divergence hitchhiking' (DH), in which divergent selection can reduce gene exchange for several megabases around a gene under strong divergent selection. Not all genes/markers within a DH region are divergently selected, yet the entire region is protected to some degree from gene exchange, permitting genetic divergence from mechanisms other than divergent selection to accumulate secondarily. After contrasting DH and multilocus migration/selection balance (MM/SB), I outline a model in which genomic isolation at a given genomic location is jointly determined by DH and genome-wide effects of the progressive reduction in realized migration, then illustrate DH using data from several pairs of incipient species in the wild.

DETSEL: an R-package to detect marker loci responding to selection

In the new era of population genomics, surveys of genetic polymorphism ("genome scans") offer the opportunity to distinguish locus-specific from genome-wide effects at many loci. Identifying presumably neutral regions of the genome that are assumed to be influenced by genome-wide effects only, and excluding presumably selected regions, is therefore critical to infer population demography and phylogenetic history reliably. Conversely, detecting locus-specific effects may help identify those genes that have been, or still are, targeted by natural selection. The software package DETSEL has been developed to identify markers that show deviation from neutral expectation in pairwise comparisons of diverging populations. Recently, two major improvements have been made: the analysis of dominant markers is now supported, and the estimation of empirical P-values has been implemented. These features, which are described below, have been incorporated into an R package, which replaces the stand-alone DETSEL software package.

Detection of outlier loci and their utility for fisheries management

Genetics-based approaches have informed fisheries management for decades, yet remain challenging to implement within systems involving recently diverged stocks or where gene flow persists. In such cases, genetic markers exhibiting locus-specific (‘outlier’) effects associated with divergent selection may provide promising alternatives to loci that reflect genome-wide (‘neutral’) effects for guiding fisheries management. Okanagan Lake kokanee (Oncorhynchus nerka), a fishery of conservation concern, exhibits two sympatric ecotypes adapted to different reproductive environments; however, previous research demonstrated the limited utility of neutral microsatellites for assigning individuals. Here, we investigated the efficacy of an outlier-based approach to fisheries management by screening >11 000 expressed sequence tags for linked microsatellites and conducting genomic scans for kokanee sampled across seven spawning sites. We identified eight outliers among 52 polymorphic loci that detected ecotype-level divergence, whereas there was no evidence of divergence at neutral loci. Outlier loci exhibited the highest self-assignment accuracy to ecotype (92.1%), substantially outperforming 44 neutral loci (71.8%). Results were robust among-sampling years, with assignment and mixed composition estimates for individuals sampled in 2010 mirroring baseline results. Overall, outlier loci constitute promising alternatives for informing fisheries management involving recently diverged stocks, with potential applications for designating management units across a broad range of taxa.

Scanning the European corn borer (Ostrinia spp.) genome for adaptive divergence between host-affiliated sibling species

It has recently been shown that the European corn borer, a major pest of maize crops, is actually composed of two genetically differentiated and reproductively isolated taxa, which are found in sympatry over a wide geographical range in Eurasia. Each taxon is adapted to specific host plants: Ostrinia nubilalis feeds mainly on maize, while O. scapulalis feeds mainly on hop or mugwort. Here, we present a genome scan approach as a first step towards an integrated molecular analysis of the adaptive genomic divergence between O. nubilalis and O. scapulalis. We analysed 609 AFLP marker loci in replicate samples of sympatric populations of Ostrinia spp. collected on maize, hop and mugwort, in France. Using two genome scan methods based on the analysis of population differentiation, we found a set of 28 outlier loci that departed from the neutral expectation in one or the other method (of which a subset of 14 loci were common to both methods), which showed a significantly increased differentiation between O. nubilalis and O. scapulalis, when compared to the rest of the genome. A subset of 12 outlier loci were sequenced, of which 7 were successfully re-amplified as target candidate loci. Three of these showed homology with annotated lepidopteran sequences from public nucleotide databases.

USING POPULATION GENOMICS TO DETECT SELECTION IN NATURAL POPULATIONS: KEY CONCEPTS AND METHODOLOGICAL CONSIDERATIONS

Natural selection shapes patterns of genetic variation among individuals, populations, and species, and it does so differentially across genomes. The field of population genomics provides a comprehensive genome-scale view of the action of selection, even beyond traditional model organisms. However, even with nearly complete genomic sequence information, our ability to detect the signature of selection on specific genomic regions depends on choosing experimental and analytical tools appropriate to the biological situation. For example, processes that occur at different timescales, such as sorting of standing genetic variation, mutation-selection balance, or fixed interspecific divergence, have different consequences for genomic patterns of variation. Inappropriate experimental or analytical approaches may fail to detect even strong selection or falsely identify a signature of selection. Here we outline the conceptual framework of population genomics, relate genomic patterns of variation to evolutionary processes, and identify major biological factors to be considered in studies of selection. As data-gathering technology continues to advance, our ability to understand selection in natural populations will be limited more by conceptual and analytical weaknesses than by the amount of molecular data. Our aim is to bring critical biological considerations to the fore in population genomics research and to spur the development and application of analytical tools appropriate to diverse biological systems.

Effectiveness of in situ and ex situ conservation of crop diversity. What a Phaseolus vulgaris L. landrace case study can tell us

The effectiveness of in situ (on-farm) and ex situ conservation strategies to maintain total genetic diversity was assessed in a threatened Phaseolus vulgaris L. landrace. Farmer seed lots (subpopulations) were sampled initially and then after in situ and ex situ multiplication (two locations). The number of plants used in the ex situ multiplications (120) was much larger than that normally used in germplasm bank procedures and the farmer seed lots were kept separate. In situ, the landrace was multiplied by each farmer with the usual population size. Eighty plants from the initial population, the in situ and the two ex situ multiplications were individually tested using 26 microsatellite markers. Most of the genetic parameters showed a consistent decline in the ex situ populations compared with the in situ population, with a notable loss of less frequent alleles. The differentiation among the farmer subpopulations increased when the multiplication took place outside of the adaptation area. Although 120 plants were multiplied in each ex situ cycle, a bottleneck effect was present. In addition, tests for neutrality detected three loci that are involved in pathogen response and are potentially under selective effects. The diversity conservation and the management practices of autogamous landrace crops are discussed.

Genetic diversity and differentiation at MHC genes in island populations of tuatara (Sphenodon spp.)

Neutral genetic markers are commonly used to understand the effects of fragmentation and population bottlenecks on genetic variation in threatened species. Although neutral markers are useful for inferring population history, the analysis of functional genes is required to determine the significance of any observed geographical differences in variation. The genes of the major histocompatibility complex (MHC) are well-known examples of genes of adaptive significance and are particularly relevant to conservation because of their role in pathogen resistance. In this study, we survey diversity at MHC class I loci across a range of tuatara populations. We compare the levels of MHC variation with that observed at neutral microsatellite markers to determine the relative roles of balancing selection, diversifying selection and genetic drift in shaping patterns of MHC variation in isolated populations. In general, levels of MHC variation within tuatara populations are concordant with microsatellite variation. Tuatara populations are highly differentiated at MHC genes, particularly between the northern and Cook Strait regions, and a trend towards diversifying selection across populations was observed. However, overall our results indicate that population bottlenecks and isolation have a larger influence on patterns of MHC variation in tuatara populations than selection.

A microsatellite-based analysis for the detection of selection on BTA1 and BTA20 in northern Eurasian cattle (Bos taurus) populations

BACKGROUND

Microsatellites surrounding functionally important candidate genes or quantitative trait loci have received attention as proxy measures of polymorphism level at the candidate loci themselves. In cattle, selection for economically important traits is a long-term strategy and it has been reported that microsatellites are linked to these important loci.

METHODS

We have investigated the variation of seven microsatellites on BTA1 (Bos taurus autosome 1) and 16 on BTA20, using bovine populations of typical production types and horn status in northern Eurasia. Genetic variability of these loci and linkage disequilibrium among these loci were compared with those of 28 microsatellites on other bovine chromosomes. Four different tests were applied to detect molecular signatures of selection.

RESULTS

No marked difference in locus variability was found between microsatellites on BTA1, BTA20 and the other chromosomes in terms of different diversity indices. Average D' values of pairwise syntenic markers (0.32 and 0.28 across BTA 1 and BTA20 respectively) were significantly (P < 0.05) higher than for non-syntenic markers (0.15). The Ewens-Watterson test, the Beaumont and Nichol's modified frequentist test and the Bayesian FST-test indicated elevated or decreased genetic differentiation, at SOD1 and AGLA17 markers respectively, deviating significantly (P < 0.05) from neutral expectations. Furthermore, lnRV, lnRH and lnRtheta' statistics were used for the pairwise population comparison tests and were significantly less variable in one population relative to the other, providing additional evidence of selection signatures for two of the 51 loci. Moreover, the three Finnish native populations showed evidence of subpopulation divergence at SOD1 and AGLA17. Our data also indicate significant intergenic linkage disequilibrium around the candidate loci and suggest that hitchhiking selection has played a role in shaping the pattern of observed linkage disequilibrium.

CONCLUSION

Hitchhiking due to tight linkage with alleles at candidate genes, e.g. the POLL gene, is a possible explanation for this pattern. The potential impact of selective breeding by man on cattle populations is discussed in the context of selection effects. Our results also suggest that a practical approach to detect loci under selection is to simultaneously apply multiple neutrality tests based on different assumptions and estimations.

Identification of local- and habitat-dependent selection: scanning functionally important genes in nine-spined sticklebacks (Pungitius pungitius)

Understanding the selective forces promoting adaptive population divergence is a central issue in evolutionary biology. The role of environmental salinity in driving adaptation and evolution in aquatic organisms is still poorly understood. We investigated the relative impacts of habitat type (cf. saltwater vs. freshwater) and geographic area in shaping adaptive population divergence, as well as genes responsible for adaptation to different salinities in nine-spined sticklebacks (Pungitius pungitius). To this end, we employed a hitchhiking mapping approach with 111 microsatellite loci and one insertion/deletion locus including 63 loci situated within or close to genes with important physiological functions such as osmoregulation, growth, and thermal response. Using three pairs of marine and freshwater populations from different geographic areas, we identified several loci showing consistent evidence of being under directional selection in different outlier tests. Analyses of molecular variance at the loci under selection indicated that geographic area rather than habitat type has been acting as a central force in shaping adaptive population divergence. Nevertheless, both outlier tests and a spatial analysis method indicated that two loci (growth hormone receptor 2 and DEAD box polypeptide 56) are involved in adaptation to different habitats, implying that environmental salinity has been affecting them as a selective force. These loci are promising candidates for further investigations focusing on the molecular mechanisms of adaptation to marine and freshwater environments.

Integration of genome and phenotypic scanning gives evidence of genetic structure in Mesoamerican common bean (Phaseolus vulgaris L.) landraces from the southwest of Europe

Southwestern Europe has been considered as a secondary centre of genetic diversity for the common bean. The dispersal of domesticated materials from their centres of origin provides an experimental system that reveals how human selection during cultivation and adaptation to novel environments affects the genetic composition. In this paper, our goal was to elucidate how distinct events could modify the structure and level of genetic diversity in the common bean. The genome-wide genetic composition was analysed at 42 microsatellite loci in individuals of 22 landraces of domesticated common bean from the Mesoamerican gene pool. The accessions were also characterised for phaseolin seed protein and for nine allozyme polymorphisms and phenotypic traits. One of this study's important findings was the complementary information obtained from all the polymorphisms examined. Most of the markers found to be potentially under the influence of selection were located in the proximity of previously mapped genes and quantitative trait loci (QTLs) related to important agronomic traits, which indicates that population genomics approaches are very efficient in detecting QTLs. As it was revealed by outlier simple sequence repeats, loci analysis with STRUCTURE software and multivariate analysis of phenotypic data, the landraces were grouped into three clusters according to seed size and shape, vegetative growth habit and genetic resistance. A total of 151 alleles were detected with an average of 4 alleles per locus and an average polymorphism information content of 0.31. Using a model-based approach, on the basis of neutral markers implemented in the software STRUCTURE, three clusters were inferred, which were in good agreement with multivariate analysis. Geographic and genetic distances were congruent with the exception of a few putative hybrids identified in this study, suggesting a predominant effect of isolation by distance. Genomic scans using both markers linked to genes affected by selection (outlier) and neutral markers showed advantages relative to other approaches, since they help to create a more complete picture of how adaptation to environmental conditions has sculpted the common bean genomes in southern Europe. The use of outlier loci also gives a clue about what selective forces gave rise to the actual phenotypes of the analysed landraces.

Selection pressures have caused genome-wide population differentiation of Anthoxanthum odoratum despite the potential for high gene flow

The extent to which divergent selection can drive genome-wide population differentiation remains unclear. Theory predicts that in the face of ongoing gene flow, population differentiation should be apparent only at those markers that are directly or indirectly (i.e. through linkage) under selection. However, if reproductive barriers limit gene flow, genome-wide population differentiation may occur even in geographically proximate populations. Some insight into the link between selection and genetic differentiation in the presence of ongoing gene flow can come from long-term experiments such as The Park Grass Experiment, which has been running for over 150 years, and provides a unique example of a heterogeneous environment with a long and detailed history. Fertilizer treatments applied in the Park Grass Experiment have led to rapid evolutionary change in sweet vernal grass Anthoxanthum odoratum, but until now, nothing was known of how these changes would be reflected in neutral molecular markers. We have genotyped ten A. odoratum populations from the Park Grass Experiment using Amplified Fragment Length Polymorphisms (AFLPs). Our data show that nutrient additions have resulted in genome-wide divergence among plots despite the high potential for ongoing gene flow. This provides a well-documented example of concordance between genomes and environmental conditions that has arisen in continuous populations across a time span of fewer than 75 generations.

Divergence between sympatric rice- and maize-infecting populations of Rhizoctonia solani AG-1 IA from Latin America

ABSTRACT The basidiomycetous fungus Rhizoctonia solani anastomosis group (AG)-1 IA is a major pathogen in Latin America causing sheath blight (SB) of rice. Particularly in Venezuela, the fungus also causes banded leaf and sheath blight (BLSB) on maize, which is considered an emerging disease problem where maize replaced traditional rice-cropping areas or is now planted in adjacent fields. Our goals in this study were to elucidate (i) the effects of host specialization on gene flow between sympatric and allopatric rice and maize-infecting fungal populations and (ii) the reproductive mode of the fungus, looking for evidence of recombination. In total, 375 isolates of R. solani AG1 IA sampled from three sympatric rice and maize fields in Venezuela (Portuguesa State) and two allopatric rice fields from Colombia (Meta State) and Panama (Chiriquí State) were genotyped using 10 microsatellite loci. Allopatric populations from Venezuela, Colombia, and Panama were significantly differentiated (Phi(ST) of 0.16 to 0.34). Partitioning of the genetic diversity indicated differentiation between sympatric populations from different host species, with 17% of the total genetic variation distributed between hosts while only 3 to 6% was distributed geographically among the sympatric Venezuelan fields. We detected symmetrical historical migration between the rice- and the maize-infecting populations from Venezuela. Rice- and maize-derived isolates were able to infect both rice and maize but were more aggressive on their original hosts, consistent with host specialization. Because the maize- and rice-infecting populations are still cross-pathogenic, we postulate that the genetic differentiation was relatively recent and mediated via a host shift. An isolation with migration analysis indicated that the maize-infecting population diverged from the rice-infecting population between 40 and 240 years ago. Our findings also suggest that maize-infecting populations have a mainly recombining reproductive system whereas the rice-infecting populations have a mixed reproductive system in Latin America.

Genomic pattern of adaptive divergence in Arabidopsis halleri, a model species for tolerance to heavy metal

Pollution by heavy metals is one of the strongest environmental constraints in human-altered environments that only a handful of species can cope with. Identifying the genes conferring to those species the ability to grow in polluted areas is a first step towards a global understanding of the evolutionary processes involved and will eventually improve phytoremediation practices. We used a genome-scan approach to detect loci under divergent selection among four populations of Arabidopsis halleri growing on either polluted or nonpolluted habitats. Based on a high density of amplified fragment length polymorphism (AFLP) markers (820 AFLP markers, i.e. approximately 1 marker per 0.3Mb), evidence for selection was found for some markers in every sampled population. Four loci departed from neutrality in both metallicolous populations and thus constitute high-quality candidates for general adaptation to pollution. Interestingly, some candidates differed between the two metallicolous populations, suggesting the possibility that different loci may be involved in adaptation in the different metallicolous populations.

Spatial and genetic structure of host-associated differentiation in the parasitoid Copidosoma gelechiae

Host-associated differentiation (HAD) appears to be an important driver of diversification in the hyperdiverse phytophagous and parasitoid insects. The gallmaking moth Gnorimoschema gallaesolidaginis has undergone HAD on two sympatric goldenrods (Solidago), and HAD has also been documented in its parasitoid Copidosoma gelechiae, with the intriguing suggestion that differentiation has proceeded independently in multiple populations. We tested this suggestion with analysis of Amplified Fragment Length Polymorphism (AFLP) markers for C. gelechiae collections from the midwestern and northeastern United States and eastern Canada. AFLP data were consistent with the existence of HAD, with between-host F(ST) significant before Bonferroni correction in two of seven sympatric populations. amova analysis strongly rejected a model of HAD with a single historical origin, and thus supported the repeated-HAD hypothesis. Copidosoma gelechiae shows significant host-associated divergence at a number of allozyme loci (Stireman et al., 2006), but only weak evidence via AFLPs for genome-wide differentiation, suggesting that this species is at a very early stage of HAD.

Introgression from modern hybrid varieties into landrace populations of maize (Zea mays ssp. mays L.) in central Italy

Landraces are domesticated local plant varieties that did not experience a deliberate and intensive selection during a formal breeding programme. In Europe, maize landraces are still cultivated, particularly in marginal areas where traditional farming is often practiced. Here, we have studied the evolution of flint maize landraces from central Italy over 50 years of on-farm cultivation, when dent hybrid varieties were introduced and their use was widespread. We have compared an 'old' collection, obtained during the 1950s, before the introduction of hybrids, and a recent collection of maize landraces. For comparison, a sample of maize landraces from north Italy, and of improved germplasm, including hybrids and inbred lines were also used. A total of 296 genotypes were analysed using 21 microsatellites. Our results show that the maize landraces collected in the last 5-10 years have evolved directly from the flint landrace gene pool cultivated in central Italy before the introduction of modern hybrids. The population structure, diversity and linkage disequilibrium analyses indicate a significant amount of introgression from hybrid varieties into the recent landrace populations. No evidence of genetic erosion of the maize landraces was seen, suggesting that in situ conservation of landraces is an efficient strategy for preserving genetic diversity. Finally, the level of introgression detected was very variable among recent landraces, with most of them showing a low level of introgression; this suggests that coexistence between different types of agriculture is possible, with the adoption of correct practices that are aimed at avoiding introgression from undesired genetic sources.

Spatial analysis method (sam): a software tool combining molecular and environmental data to identify candidate loci for selection

sam is a Windows program designed to detect candidate loci for selection in whole-genome scans. It also gives valuable clues as regards the ecological factors at stake in the selection process. The method used is based on multiple univariate logistic regression models to test for association between allelic frequencies at marker loci and environmental variables. The software reads matrices constituted of presence/absence of molecular markers, and of the corresponding environmental parameters at sampling locations. It provides dynamic analysis tables to process the results. The tool is freely available for download at http://www.econogene.eu/software/sam/.