Signatures of adaptation and genetic structure among the mainland populations of Pinus radiata (D. Don) inferred from SNP loci

Insights into the relative contributions of locus specific and genome-wide effects on population genetic diversity can be gained through separation of their resulting genetic signals. Here we explore patterns of adaptive and neutral genetic diversity in the disjunct natural populations of Pinus radiata (D. Don) from mainland California. A first-generation common garden of 447 individuals revealed significant differentiation of wood phenotypes among populations (P _ST), possibly reflecting local adaptation in response to environment. We subsequently screened all trees for genetic diversity at 149 candidate gene single nucleotide polymorphism (SNP) loci for signatures of adaptation. Ten loci were identified as being possible targets of diversifying selection following F _ST outlier tests. Multivariate canonical correlation performed on a data set of 444 individuals identified significant covariance between environment, adaptive phenotypes and outlier SNP diversity, lending support to the case for local adaptation suggested from F _ST and P _ST tests. Covariation among discrete sets of outlier SNPs and adaptive phenotypes (inferred from multivariate loadings) with environment are supported by existing studies of candidate gene function and genotype–phenotype association. Canonical analyses failed to detect significant correlations between environment and 139 non-outlier SNP loci, which were applied to estimate neutral patterns of genetic differentiation among populations (F _ST 4.3 %). Using this data set, significant hierarchical structure was detected, indicating three populations on the mainland. The hierarchical relationships based on neutral SNP markers (and SSR) were in contrast with those inferred from putatively adaptive loci, potentially highlighting the independent action of selection and demography in shaping genetic structure in this species.     

Identifying chromosomal selection‐sweep regions in facial eczema selection‐line animals using an ovine 50K‐SNP array

Facial eczema (FE) is a hepato‐mycotoxicosis found mainly in New Zealand sheep and cattle. When genetics was found to be a factor in FE susceptibility, resistant and susceptible selection lines of Romney sheep were established to enable further investigations of this disease trait. Using the Illumina OvineSNP50 BeadChip, we conducted a selection‐sweep experiment on these FE genetic lines. Two analytical methods were used to detect selection signals, namely the Peddrift test (Dodds & McEwan, 1997) and fixation index F_ST (Weir & Hill, 2002). Of 50 975 single nucleotide polymorphism (SNP) markers tested, there were three that showed highly significant allele frequency differences between the resistant and susceptible animals (Peddrift nominal P < 0.000001). These SNP loci are located on chromosomes OAR1, OAR11 and OAR12 that coincide precisely with the three highest genomic F_ST peaks. In addition, there are nine less significant Peddrift SNPs (nominal P ≤ 0.000009) on OAR6 (n = 2), OAR9 (n = 2), OAR12, OAR19 (n = 2), OAR24 and OAR26. In smoothed F_ST (five‐SNP moving average) plots, the five most prominent peaks are on OAR1, OAR6, OAR7, OAR13 and OAR19. Although these smoothed F_ST peaks do not coincide with the three most significant Peddrift SNP loci, two (on OAR6 and OAR19) overlap with the set of less significant Peddrift SNPs above. Of these 12 Peddrift SNPs and five smoothed F_ST regions, none is close to the FE candidate genes catalase and ABCG2; however, two on OAR1 and one on OAR13 fall within suggestive quantitative trait locus regions identified in a previous genome screen experiment. The present studies indicated that there are at least eight genomic regions that underwent a selection sweep in the FE lines.     

Identification and characterization of nuclear microsatellite loci in the aquatic moss Platyhypnidium riparioides (Brachytheciaceae)

Eight microsatellite loci from the aquatic moss Platyhypnidium riparioides were identified using the method of microsatellite‐enriched libraries. Polymorphism was assessed in a sample of four populations of 20 individuals each from four streams of the Meuse hydrographic basin in southern Belgium. The markers amplified three to seven alleles per locus. Comparison of observed and expected heterozygosities as well as F‐statistics (F_ST = 0.62) reveals a significant genetic differentiation among populations. These markers will be useful for further investigation of population genetic structure and diversity at different nested spatial scales.     

A Beta-mixture model for assessing genetic population structure

Summary An important fraction of recently generated molecular data is dominant markers. They contain substantial information about genetic variation but dominance makes it impossible to apply standard techniques to calculate measures of genetic differentiation, such as F‐statistics. In this article, we propose a new Bayesian beta‐mixture model that more accurately describes the genetic structure from dominant markers and estimates multiple F_ST s from the sample. The model also has important application for codominant markers and single‐nucleotide polymorphism (SNP) data. The number of F_ST is assumed unknown beforehand and follows a random distribution. The reversible jump algorithm is used to estimate the unknown number of multiple F_ST s. We evaluate the performance of three split proposals and the overall performance of the proposed model based on simulated dominant marker data. The model could reliably identify and estimate a spectrum of degrees of genetic differentiation present in multiple loci. The estimates of F_ST s also incorporate uncertainty about the magnitude of within‐population inbreeding coefficient. We illustrate the method with two examples, one using dominant marker data from a rare orchid and the other using codominant marker data from human populations.     

Generalization of the QST framework in hierarchically structured populations: Impacts of inbreeding and dominance

Q_ST is a differentiation parameter based on the decomposition of the genetic variance of a trait. In the case of additive inheritance and absence of selection, it is analogous to the genic differentiation measured on individual loci, F_ST. Thus, Q_ST?F_ST comparison is used to infer selection: selective divergence when Q_ST > F_ST, or convergence when Q_ST < F_ST. The definition of Q‐statistics was extended to two‐level hierarchical population structures with Hardy–Weinberg equilibrium. Here, we generalize the Q‐statistics framework to any hierarchical population structure. First, we developed the analytical definition of hierarchical Q‐statistics for populations not at Hardy–Weinberg equilibrium. We show that the Q‐statistics values obtained with the Hardy–Weinberg definition are lower than their corresponding F‐statistics when F_IS > 0 (higher when F_IS < 0). Then, we used an island model simulation approach to investigate the impact of inbreeding and dominance on the Q_ST?F_ST framework in a hierarchical population structure. We show that, while differentiation at the lower hierarchical level (Q_SR) is a monotonic function of migration, differentiation at the upper level (Q_RT) is not. In the case of additive inheritance, we show that inbreeding inflates the variance of Q_RT, which can increase the frequency of Q_RT > F_RT cases. We also show that dominance drastically reduces Q‐statistics below F‐statistics for any level of the hierarchy. Therefore, high values of Q‐statistics are good indicators of selection, but low values are not in the case of dominance.     

The empirical Bayes estimators of fine‐scale population structure in high gene flow species

An empirical Bayes (EB) pairwise F_ST estimator was previously introduced and evaluated for its performance by numerical simulation. In this study, we conducted coalescent simulations and generated genetic population structure mechanistically, and compared the performance of the EBF_ST with Nei's G_ST, Nei and Chesser's bias‐corrected G_ST (G_{ST_NC}), Weir and Cockerham's θ (θ_WC) and θ with finite sample correction (θ_{WC_F}). We also introduced EB estimators for Hedrick’ G’_ST and Jost’ D. We applied these estimators to publicly available SNP genotypes of Atlantic herring. We also examined the power to detect the environmental factors causing the population structure. Our coalescent simulations revealed that the finite sample correction of θ_WC is necessary to assess population structure using pairwise F_ST values. For microsatellite markers, EBF_ST performed the best among the present estimators regarding both bias and precision under high gene flow scenarios (). For 300 SNPs, EBF_ST had the highest precision in all cases, but the bias was negative and greater than those for G_{ST_NC} and θ_{WC_F} in all cases. G_{ST_NC} and θ_{WC_F} performed very similarly at all levels of F_ST. As the number of loci increased up to 10 000, the precision of G_{ST_NC} and θ_{WC_F} became slightly better than for EBF_ST for cases with , even though the size of the bias remained constant. The EB estimators described the fine‐scale population structure of the herring and revealed that ~56% of the genetic differentiation was caused by sea surface temperature and salinity. The R package finepop for implementing all estimators used here is available on CRAN.     

Statistical power for detecting genetic divergence—organelle versus nuclear markers

Statistical power is critical in conservation for detecting genetic differences in space or time from allele frequency data. Organelle and nuclear genetic markers have fundamentally different transmission dynamics; the potential effect of these differences on power to detect divergence have been speculated on but not investigated. We examine, analytically and with computer simulations, the relative performance of organelle and nuclear markers under basic, ideal situations. We conclude that claims of a generally higher resolving power of either marker type are not correct. The ratio R = F _ST,organelle/F _ST,nuclear varies between 1 and 4 during differentiation and this greatly affects the power relationship. When nuclear F _ST is associated with organelle differentiation four times higher, the power of the organelle marker is similar to two nuclear loci with the same allele frequency distribution. With large sample sizes (n ≥ 50) and several populations or many alleles per locus (≥5), the power difference may typically be disregarded when nuclear F _ST > 0.05. To correctly interpret observed patterns of genetic differentiation in practical situations, the expected F _STs and the statistical properties (i.e., power analysis) of the genetic markers used should be evaluated, taking the observed allele frequency distributions into consideration.     

Risso’s dolphins (<Emphasis Type="Italic">Grampus griseus</Emphasis>) in UK waters are differentiated from a population in the Mediterranean Sea and genetically less diverse

The Risso’s dolphin (Grampus griseus) has a worldwide distribution, but little is known about their population genetic structure. Local coastal populations are never known to be abundant, and are sometimes under anthropogenic impact. Therefore the question of regional differentiation by genetic drift and overall diversity levels is of conservation interest. Here we present preliminary data that clearly indicate genetic differentiation and lower genetic diversity of a population sampled in UK waters (primarily from the Western Isles, Scotland) compared to a Mediterranean sample. Significant differentiation was found in comparison with a sample from the Mediterranean for both microsatellite DNA markers (F _ST = 0.0296) and mtDNA sequence data (F _ST = 0.260; ϕ _ST = 0.542). Allelic diversity was lower in the UK for nearly all loci.     

Development and preliminary evaluation of a genomewide single nucleotide polymorphisms resource generated by RAD‐seq for the small yellow croaker (Larimichthys polyactis)

Recent advances in high‐throughput sequencing technologies have offered the possibility to generate genomewide sequence data to delineate previously unidentified genetic structure, obtain more accurate estimates of demographic parameters and to evaluate potential adaptive divergence. Here, we identified 27 556 single nucleotide polymorphisms for the small yellow croaker (Larimichthys polyactis) using restriction‐site‐associated DNA (RAD) sequencing of 24 individuals from two populations. Significant sources of genetic variation were identified, with an average nucleotide diversity (π) of 0.00105 ± 0.000425 across individuals, and long‐term effective population size was thus estimated to range between 26 172 and 261 716. According to the results, no differentiation between the two populations was detected based on the SNP data set of top quality score per contig or neutral loci. However, the two analysed populations were highly differentiated based on SNP data set of both top F_ST value per contig and the outlier SNPs. Moreover, local adaptation was highlighted by an F_ST‐based outlier tests implemented in LOSITAN and a total of 538 potentially locally selected SNPs were identified. blast2go annotation of contigs containing the outlier SNPs yielded hits for 37 (66%) of 56 significant blastx matches. Candidate genes for local adaptation constituted a wide array of biological functions, including cellular response to oxidative stress, actin filament binding, ion transmembrane transport and synapse assembly. The generated SNP resources in this study provided a valuable tool for future population genetics and genomics studies of L. polyactis.     

Comparison of genetic differentiation at marker loci and quantitative traits

The comparison of the degree of differentiation in neutral marker loci and genes coding quantitative traits with standardized and equivalent measures of genetic differentiation (F_ST and Q_ST, respectively) can provide insights into two important but seldom explored questions in evolutionary genetics: (i) what is the relative importance of random genetic drift and directional natural selection as causes of population differentiation in quantitative traits, and (ii) does the degree of divergence in neutral marker loci predict the degree of divergence in genes coding quantitative traits? Examination of data from 18 independent studies of plants and animals using both standard statistical and meta‐analytical methods revealed a number of interesting points. First, the degree of differentiation in quantitative traits (Q_ST) typically exceeds that observed in neutral marker genes (F_ST), suggesting a prominent role for natural selection in accounting for patterns of quantitative trait differentiation among contemporary populations. Second, the F_ST – Q_ST difference is more pronounced for allozyme markers and morphological traits, than for other kinds of molecular markers and life‐history traits. Third, very few studies reveal situations were Q_ST < F_ST, suggesting that selection pressures, and hence optimal phenotypes, in different populations of the same species are unlikely to be often similar. Fourth, there is a strong correlation between Q_ST and F_ST indices across the different studies for allozyme (r=0.81), microsatellite (r=0.87) and combined (r=0.75) marker data, suggesting that the degree of genetic differentiation in neutral marker loci is closely predictive of the degree of differentiation in loci coding quantitative traits. However, these interpretations are subject to a number of assumptions about the data and methods used to derive the estimates of population differentiation in the two sets of traits.     

Comparison of quantitative and molecular variation in agroforestry populations of the shea tree (Vitellaria paradoxa C.F. Gaertn) in Mali

In this study we investigated the within- and between-population genetic variation using microsatellite markers and quantitative traits of the shea tree, Vitellaria paradoxa, an important agroforestry tree species of the Sudano–Sahelian region in Africa. Eleven populations were sampled across Mali and in northern Côte d’Ivoire. Leaf size and form and growth traits were measured in a progeny test at the nursery stage. Eight microsatellites were used to assess neutral genetic variation. Low levels of heterozygosity were recorded (1.6–3.0 alleles/locus; H_E = 0.25–0.42) and the fixation index (F_IS = −0.227–0.186) was not significantly different from zero suggesting that Hardy–Weinberg equilibrium is encountered in all populations sampled. Quantitative traits exhibited a strong genetic variation between populations and between families within populations. The degree of population differentiation of the quantitative traits (Q_ST = 0.055–0.283, Q_STmean = 0.189) strongly exceeds that in eight microsatellite loci (F_ST = −0.011–0.142, F_STmean = 0.047). Global and pairwise F_ST values were very low and not significantly different from zero suggesting agroforestry practices are amplifying gene flow (Nm = 5.07). The population means for quantitative traits and the rainfall variable were not correlated, showing variation was not linked with this climatic cline. It is suggested that this marked differentiation for quantitative traits, independent of environmental clines and despite a high gene flow, is a result of local adaptation and human selection of shea trees. This process has induced high linkage disequilibrium between underlying loci of polygenic characters.     

Analysis of F ST outliers at allozyme loci in Pacific salmon: implications for natural selection

Natural selection has been invoked to explain the observed geographic distribution of allozyme allele frequencies for a number of teleost species. The effects of selection on allozyme loci in three species of Pacific salmon were tested. A simulation-based approach to estimate the null distribution of population differentiation (F _ST) and test for F _ST outliers was used. This approach showed that a majority of allozyme loci conform to neutral expectations predicted by the simulation model, with relatively few F _ST outliers found. No consistent F _ST outlier loci were found across species. Analysis of population sub-groups based on geography and genetic identity reduced the number of outlier loci for some species, indicating that large geographic groups may include genetically divergent populations and/or that there is geographic heterogeneity in selection pressure upon allozyme loci. Two outlier allozyme loci found in this analysis, lactate dehydrogenase-B and malic enzyme, have been shown to be influenced by selection in other teleost species. This approach is also useful in identifying allozyme loci (or other genetic markers) that meet assumptions for population genetic study.     

Does GST underestimate genetic differentiation from marker data?

The widely applied genetic differentiation statistics F_ST and G_ST have recently been criticized for underestimating differentiation when applied to highly polymorphic markers such as microsatellites. New statistics claimed to be unaffected by marker polymorphisms have been proposed and advocated to replace the traditional F_ST and G_ST. This study shows that G_ST gives accurate estimates and underestimates of differentiation when demographic factors are more and less important than mutations, respectively. In the former case, all markers, regardless of diversity (H_S), have the same G_ST value in expectation and thus give replicated estimates of differentiation. In the latter case, markers of higher H_S have lower G_ST values, resulting in a negative, roughly linear correlation between G_ST and H_S across loci. I propose that the correlation coefficient between G_ST and H_S across loci, r_GH, can be used to distinguish the two cases and to detect mutational effects on G_ST. A highly negative and significant r_GH, when coupled with highly variable G_ST values among loci, would reveal that marker G_ST values are affected substantially by mutations and marker diversity, underestimate population differentiation, and are not comparable among studies, species and markers. Simulated and empirical data sets are used to check the power and statistical behaviour, and to demonstrate the usefulness of the correlation analysis.     

Relative performance of Bayesian clustering software for inferring population substructure and individual assignment at low levels of population differentiation

Traditional methods for characterizing genetic differentiation among populations rely on a priori grouping of individuals. Bayesian clustering methods avoid this limitation by using linkage and Hardy–Weinberg disequilibrium to decompose a sample of individuals into genetically distinct groups. There are several software programs available for Bayesian clustering analyses, all of which describe a decrease in the ability to detect distinct clusters as levels of genetic differentiation among populations decrease. However, no study has yet compared the performance of such methods at low levels of population differentiation, which may be common in species where populations have experienced recent separation or high levels of gene flow. We used simulated data to evaluate the performance of three Bayesian clustering software programs, PARTITION, STRUCTURE, and BAPS, at levels of population differentiation below F _ST=0.1. PARTITION was unable to correctly identify the number of subpopulations until levels of F _ST reached around 0.09. Both STRUCTURE and BAPS performed very well at low levels of population differentiation, and were able to correctly identify the number of subpopulations at F _ST around 0.03. The average proportion of an individual’s genome assigned to its true population of origin increased with increasing F _ST for both programs, reaching over 92% at an F _ST of 0.05. The average number of misassignments (assignments to the incorrect subpopulation) continued to decrease as F _ST increased, and when F _ST was 0.05, fewer than 3% of individuals were misassigned using either program. Both STRUCTURE and BAPS worked extremely well for inferring the number of clusters when clusters were not well-differentiated (F _ST=0.02–0.03), but our results suggest that F _ST must be at least 0.05 to reach an assignment accuracy of greater than 97%.     

Genetically distinct populations of northern shrimp,Pandalus borealis,in the North Atlantic: adaptation to different temperatures as an isolation factor

The large‐scale population genetic structure of northern shrimp, Pandalus borealis, was investigated over the species’ range in the North Atlantic, identifying multiple genetically distinct groups. Genetic divergence among sample localities varied among 10 microsatellite loci (range: F_ST = ?0.0002 to 0.0475) with a highly significant average (F_ST = 0.0149; P < 0.0001). In contrast, little or no genetic differences were observed among temporal replicates from the same localities (F_ST = 0.0004; P = 0.33). Spatial genetic patterns were compared to geographic distances, patterns of larval drift obtained through oceanographic modelling, and temperature differences, within a multiple linear regression framework. The best‐fit model included all three factors and explained approximately 29% of all spatial genetic divergence. However, geographic distance and larval drift alone had only minor effects (2.5–4.7%) on large‐scale genetic differentiation patterns, whereas bottom temperature differences explained most (26%). Larval drift was found to promote genetic homogeneity in parts of the study area with strong currents, but appeared ineffective across large temperature gradients. These findings highlight the breakdown of gene flow in a species with a long pelagic larval phase (up to 3 months) and indicate a role for local adaptation to temperature conditions in promoting evolutionary diversification and speciation in the marine environment.     

Empirical Distributions of F ST from Large-Scale Human Polymorphism Data

Studies of the apportionment of human genetic variation have long established that most human variation is within population groups and that the additional variation between population groups is small but greatest when comparing different continental populations. These studies often used Wright’s F _ST that apportions the standardized variance in allele frequencies within and between population groups. Because local adaptations increase population differentiation, high-F _ST may be found at closely linked loci under selection and used to identify genes undergoing directional or heterotic selection. We re-examined these processes using HapMap data. We analyzed 3 million SNPs on 602 samples from eight worldwide populations and a consensus subset of 1 million SNPs found in all populations. We identified four major features of the data: First, a hierarchically F _ST analysis showed that only a paucity (12%) of the total genetic variation is distributed between continental populations and even a lesser genetic variation (1%) is found between intra-continental populations. Second, the global F _ST distribution closely follows an exponential distribution. Third, although the overall F _ST distribution is similarly shaped (inverse J), F _ST distributions varies markedly by allele frequency when divided into non-overlapping groups by allele frequency range. Because the mean allele frequency is a crude indicator of allele age, these distributions mark the time-dependent change in genetic differentiation. Finally, the change in mean-F _ST of these groups is linear in allele frequency. These results suggest that investigating the extremes of the F _ST distribution for each allele frequency group is more efficient for detecting selection. Consequently, we demonstrate that such extreme SNPs are more clustered along the chromosomes than expected from linkage disequilibrium for each allele frequency group. These genomic regions are therefore likely candidates for natural selection.     

Microgeographic structure of Anopheles gambiae in western Kenya based on mtDNA and microsatellite loci

The population genetic structure of the Anopheles gambiae in western Kenya was studied using length variation at five microsatellite loci and sequence variation in a 648-nt mtDNA fragment. Mosquitoes were collected from houses in villages spanning up to 50 km distance, The following questions were answered, (i) Are mosquitoes in a house more related genetically to each other than mosquitoes between houses? (ii) What degree of genetic differentiation occurs on these geographical scales? (iii) How consistent are the results obtained with both types of genetic markers? At the house level, no differentiation was detected by F_ST and R_ST, and the band sharing index test revealed no significant associations of alleles across loci. Likewise, indices of kinship based on mtDNA haplotypes in houses were even lower than in the pooled sample. Therefore, the hypothesis that mosquitoes in a house are more related genetically was rejected. At increasing geographical scales, microsatellite allele distributions were similar among all population samples and no subdivision of the gene pool was detected by F_ST or R_ST. Likewise, estimates of haplotype divergence of mtDNA between populations were not higher than the within population estimates, and mtDNA-based F_ST values were not significantly different from zero. That sequence variation in mtDNA provided matching results with microsatellite loci (while high genetic variation was observed in all loci), suggested that this pattern represents the whole genome. The minimum area associated with a deme of A. gambiae in western Kenya is therefore larger than 50 km in diameter.     

Climate variables explain neutral and adaptive variation within salmonid metapopulations: the importance of replication in landscape genetics

Understanding how environmental variation influences population genetic structure is important for conservation management because it can reveal how human stressors influence population connectivity, genetic diversity and persistence. We used riverscape genetics modelling to assess whether climatic and habitat variables were related to neutral and adaptive patterns of genetic differentiation (population‐specific and pairwise F_ST) within five metapopulations (79 populations, 4583 individuals) of steelhead trout (Oncorhynchus mykiss) in the Columbia River Basin, USA. Using 151 putatively neutral and 29 candidate adaptive SNP loci, we found that climate‐related variables (winter precipitation, summer maximum temperature, winter highest 5% flow events and summer mean flow) best explained neutral and adaptive patterns of genetic differentiation within metapopulations, suggesting that climatic variation likely influences both demography (neutral variation) and local adaptation (adaptive variation). However, we did not observe consistent relationships between climate variables and F_ST across all metapopulations, underscoring the need for replication when extrapolating results from one scale to another (e.g. basin‐wide to the metapopulation scale). Sensitivity analysis (leave‐one‐population‐out) revealed consistent relationships between climate variables and F_ST within three metapopulations; however, these patterns were not consistent in two metapopulations likely due to small sample sizes (N = 10). These results provide correlative evidence that climatic variation has shaped the genetic structure of steelhead populations and highlight the need for replication and sensitivity analyses in land and riverscape genetics.     

Genome-Wide Scan for Signatures of Human Population Differentiation and Their Relationship with Natural Selection,Functional Pathways and Diseases

Genetic differences both between individuals and populations are studied for their evolutionary relevance and for their potential medical applications. Most of the genetic differentiation among populations are caused by random drift that should affect all loci across the genome in a similar manner. When a locus shows extraordinary high or low levels of population differentiation, this may be interpreted as evidence for natural selection. The most used measure of population differentiation was devised by Wright and is known as fixation index, or F_ST. We performed a genome-wide estimation of F_ST on about 4 millions of SNPs from HapMap project data. We demonstrated a heterogeneous distribution of F_ST values between autosomes and heterochromosomes. When we compared the F_ST values obtained in this study with another evolutionary measure obtained by comparative interspecific approach, we found that genes under positive selection appeared to show low levels of population differentiation. We applied a gene set approach, widely used for microarray data analysis, to detect functional pathways under selection. We found that one pathway related to antigen processing and presentation showed low levels of F_ST, while several pathways related to cell signalling, growth and morphogenesis showed high F_ST values. Finally, we detected a signature of selection within genes associated with human complex diseases. These results can help to identify which process occurred during human evolution and adaptation to different environments. They also support the hypothesis that common diseases could have a genetic background shaped by human evolution.     

Imprints of Natural Selection Along Environmental Gradients in Phenology-Related Genes of Quercus petraea

We explored single nucleotide polymorphism (SNP) variation in candidate genes for bud burst from Quercus petraea populations sampled along gradients of latitude and altitude in Western Europe. SNP diversity was monitored for 106 candidate genes, in 758 individuals from 32 natural populations. We investigated whether SNP variation reflected the clinal pattern of bud burst observed in common garden experiments. We used different methods to detect imprints of natural selection (F_ST outlier, clinal variation at allelic frequencies, association tests) and compared the results obtained for the two gradients. F_ST outlier SNPs were found in 15 genes, 5 of which were common to both gradients. The type of selection differed between the two gradients (directional or balancing) for 3 of these 5. Clinal variations were observed for six SNPs, and one cline was conserved across both gradients. Association tests between the phenotypic or breeding values of trees and SNP genotypes identified 14 significant associations, involving 12 genes. The results of outlier detection on the basis of population differentiation or clinal variation were not very consistent with the results of association tests. The discrepancies between these approaches may reflect the different hierarchical levels of selection considered (inter- and intrapopulation selection). Finally, we obtained evidence for convergent selection (similar for gradients) and clinal variation for a few genes, suggesting that comparisons between parallel gradients could be used to screen for major candidate genes responding to natural selection in trees.