Whole genome scanning of a Mediterranean basin hotspot collection provides new insights into olive tree biodiversity and biology.

Olive tree (Olea europaea L. subsp. europaea var. europaea) is one of the most important species of the Mediterranean region and one of the most ancient species domesticated. The availability of whole genome assemblies and annotations of olive tree cultivars and oleaster (O. europaea subsp. europaea var. sylvestris) has contributed to a better understanding of genetic and genomic differences between olive tree cultivars. However, compared to other plant species there is still a lack of genomic resources for olive tree populations that span the entire Mediterranean region. In the present study we developed the most complete genomic variation map and the most comprehensive catalog/resource of molecular variation to date for 89 olive tree genotypes originating from the entire Mediterranean basin, revealing the genetic diversity of this commercially significant crop tree and explaining the divergence/similarity among different variants. Additionally, the monumental ancient tree 'Throuba Naxos' was studied to characterize the potential origin or routes of olive tree domestication. Several candidate genes known to be associated with key agronomic traits, including olive oil quality and fruit yield, were uncovered by a selective sweep scan to be under selection pressure on all olive tree chromosomes. To further exploit the genomic and phenotypic resources obtained from the current work, genome-wide association analyses were performed for 23 morphological and two agronomic traits. Significant associations were detected for eight traits that provide valuable candidates for fruit tree breeding and for deeper understanding of olive tree biology.

Polygenic adaptation of rosette growth in Arabidopsis thaliana.

The rate at which plants grow is a major functional trait in plant ecology. However, little is known about its evolution in natural populations. Here, we investigate evolutionary and environmental factors shaping variation in the growth rate of Arabidopsis thaliana. We used plant diameter as a proxy to monitor plant growth over time in environments that mimicked latitudinal differences in the intensity of natural light radiation, across a set of 278 genotypes sampled within four broad regions, including an outgroup set of genotypes from China. A field experiment conducted under natural conditions confirmed the ecological relevance of the observed variation. All genotypes markedly expanded their rosette diameter when the light supply was decreased, demonstrating that environmental plasticity is a predominant source of variation to adapt plant size to prevailing light conditions. Yet, we detected significant levels of genetic variation both in growth rate and growth plasticity. Genome-wide association studies revealed that only 2 single nucleotide polymorphisms associate with genetic variation for growth above Bonferroni confidence levels. However, marginally associated variants were significantly enriched among genes with an annotated role in growth and stress reactions. Polygenic scores computed from marginally associated variants confirmed the polygenic basis of growth variation. For both light regimes, phenotypic divergence between the most distantly related population (China) and the various regions in Europe is smaller than the variation observed within Europe, indicating that the evolution of growth rate is likely to be constrained by stabilizing selection. We observed that Spanish genotypes, however, reach a significantly larger size than Northern European genotypes. Tests of adaptive divergence and analysis of the individual burden of deleterious mutations reveal that adaptive processes have played a more important role in shaping regional differences in rosette growth than maladaptive evolution.

Transposable element polymorphisms improve prediction of complex agronomic traits in rice.

KEY MESSAGE: Transposon insertion polymorphisms can improve prediction of complex agronomic traits in rice compared to using SNPs only, especially when accessions to be predicted are less related to the training set. Transposon insertion polymorphisms (TIPs) are significant sources of genetic variation. Previous work has shown that TIPs can improve detection of causative loci on agronomic traits in rice. Here, we quantify the fraction of variance explained by single nucleotide polymorphisms (SNPs) compared to TIPs, and we explore whether TIPs can improve prediction of traits when compared to using only SNPs. We used eleven traits of agronomic relevance from by five different rice population groups (Aus, Indica, Aromatic, Japonica, and Admixed), 738 accessions in total. We assess prediction by applying data split validation in two scenarios. In the within-population scenario, we predicted performance of improved Indica varieties using the rest of Indica accessions. In the across population scenario, we predicted all Aromatic and Admixed accessions using the rest of populations. In each scenario, Bayes C and a Bayesian reproducible kernel Hilbert space regression were compared. We find that TIPs can explain an important fraction of total genetic variance and that they also improve genomic prediction. In the across population prediction scenario, TIPs outperformed SNPs in nine out of the eleven traits analyzed. In some traits like leaf senescence or grain width, using TIPs increased predictive correlation by 30-50%. Our results evidence, for the first time, that TIPs genotyping can improve prediction on complex agronomic traits in rice, especially when accessions to be predicted are less related to training accessions.

DnaSP 6: DNA Sequence Polymorphism Analysis of Large Data Sets.

We present version 6 of the DNA Sequence Polymorphism (DnaSP) software, a new version of the popular tool for performing exhaustive population genetic analyses on multiple sequence alignments. This major upgrade incorporates novel functionalities to analyze large data sets, such as those generated by high-throughput sequencing technologies. Among other features, DnaSP 6 implements: 1) modules for reading and analyzing data from genomic partitioning methods, such as RADseq or hybrid enrichment approaches, 2) faster methods scalable for high-throughput sequencing data, and 3) summary statistics for the analysis of multi-locus population genetics data. Furthermore, DnaSP 6 includes novel modules to perform single- and multi-locus coalescent simulations under a wide range of demographic scenarios. The DnaSP 6 program, with extensive documentation, is freely available at http://www.ub.edu/dnasp.

The neutral frequency spectrum of linked sites.

We introduce the conditional Site Frequency Spectrum (SFS) for a genomic region linked to a focal mutation of known frequency. An exact expression for its expected value is provided for the neutral model without recombination. Its relation with the expected SFS for two sites, 2-SFS, is discussed. These spectra derive from the coalescent approach of Fu (1995) for finite samples, which is reviewed. Remarkably simple expressions are obtained for the linked SFS of a large population, which are also solutions of the multi-allelic Kolmogorov equations. These formulae are the immediate extensions of the well known single site θ∕f neutral SFS. Besides the general interest in these spectra, they relate to relevant biological cases, such as structural variants and introgressions. As an application, a recipe to adapt Tajima's D and other SFS-based neutrality tests to a non-recombining region containing a neutral marker is presented.

Porcine Y-chromosome variation is consistent with the occurrence of paternal gene flow from non-Asian to Asian populations.

Pigs (Sus scrofa) originated in Southeast Asia and expanded to Europe and North Africa approximately 1 MYA. Analyses of porcine Y-chromosome variation have shown the existence of two main haplogroups that are highly divergent, a result that is consistent with previous mitochondrial and autosomal data showing that the Asian and non-Asian pig populations remained geographically isolated until recently. Paradoxically, one of these Y-chromosome haplogroups is extensively shared by pigs and wild boars from Asia and Europe, an observation that is difficult to reconcile with a scenario of prolonged geographic isolation. To shed light on this issue, we genotyped 33 Y-linked SNPs and one indel in a worldwide sample of pigs and wild boars and sequenced a total of 9903 nucleotide sites from seven loci distributed along the Y-chromosome. Notably, the nucleotide diversity per site at the Y-linked loci (0.0015 in Asian pigs) displayed the same order of magnitude as that described for autosomal loci (~0.0023), a finding compatible with a process of sustained and intense isolation. We performed an approximate Bayesian computation analysis focused on the paternal diversity of wild boars and local pig breeds in which we compared three demographic models: two isolation models (I models) differing in the time of isolation and a model of isolation with recent unidirectional migration (IM model). Our results suggest that the most likely explanation for the extensive sharing of one Y-chromosome haplogroup between non-Asian and Asian populations is a recent and unidirectional (non-Asian > Asian) paternal migration event.

Identification of protein-damaging mutations in 10 swine taste receptors and 191 appetite-reward genes.

BACKGROUND: Taste receptors (TASRs) are essential for the body's recognition of chemical compounds. In the tongue, TASRs sense the sweet and umami and the toxin-related bitter taste thus promoting a particular eating behaviour. Moreover, their relevance in other organs is now becoming evident. In the intestine, they regulate nutrient absorption and gut motility. Upon ligand binding, TASRs activate the appetite-reward circuitry to signal the nervous system and keep body homeostasis. With the aim to identify genetic variation in the swine TASRs and in the genes from the appetite and the reward pathways, we have sequenced the exons of 201 TASRs and appetite-reward genes from 304 pigs belonging to ten breeds, wild boars and to two phenotypically extreme groups from a F2 resource with data on growth and fat deposition. RESULTS: We identified 2,766 coding variants 395 of which were predicted to have a strong impact on protein sequence and function. 334 variants were present in only one breed and at predicted alternative allele frequency (pAAF) ≥ 0.1. The Asian pigs and the wild boars showed the largest proportion of breed specific variants. We also compared the pAAF of the two F2 groups and found that variants in TAS2R39 and CD36 display significant differences suggesting that these genes could influence growth and fat deposition. We developed a 128-variant genotyping assay and confirmed 57 of these variants. CONCLUSIONS: We have identified thousands of variants affecting TASRs as well as genes involved in the appetite and the reward mechanisms. Some of these genes have been already associated to taste preferences, appetite or behaviour in humans and mouse. We have also detected indications of a potential relationship of some of these genes with growth and fat deposition, which could have been caused by changes in taste preferences, appetite or reward and ultimately impact on food intake. A genotyping array with 57 variants in 31 of these genes is now available for genotyping and start elucidating the impact of genetic variation in these genes on pig biology and breeding.

Transposon Insertions, Structural Variations, and SNPs Contribute to the Evolution of the Melon Genome.

The availability of extensive databases of crop genome sequences should allow analysis of crop variability at an unprecedented scale, which should have an important impact in plant breeding. However, up to now the analysis of genetic variability at the whole-genome scale has been mainly restricted to single nucleotide polymorphisms (SNPs). This is a strong limitation as structural variation (SV) and transposon insertion polymorphisms are frequent in plant species and have had an important mutational role in crop domestication and breeding. Here, we present the first comprehensive analysis of melon genetic diversity, which includes a detailed analysis of SNPs, SV, and transposon insertion polymorphisms. The variability found among seven melon varieties representing the species diversity and including wild accessions and highly breed lines, is relatively high due in part to the marked divergence of some lineages. The diversity is distributed nonuniformly across the genome, being lower at the extremes of the chromosomes and higher in the pericentromeric regions, which is compatible with the effect of purifying selection and recombination forces over functional regions. Additionally, this variability is greatly reduced among elite varieties, probably due to selection during breeding. We have found some chromosomal regions showing a high differentiation of the elite varieties versus the rest, which could be considered as strongly selected candidate regions. Our data also suggest that transposons and SV may be at the origin of an important fraction of the variability in melon, which highlights the importance of analyzing all types of genetic variability to understand crop genome evolution.

Use of targeted SNP selection for an improved anchoring of the melon (Cucumis melo L.) scaffold genome assembly.

BACKGROUND: The genome of the melon (Cucumis melo L.) double-haploid line DHL92 was recently sequenced, with 87.5 and 80.8% of the scaffold assembly anchored and oriented to the 12 linkage groups, respectively. However, insufficient marker coverage and a lack of recombination left several large, gene rich scaffolds unanchored, and some anchored scaffolds unoriented. To improve the anchoring and orientation of the melon genome assembly, we used resequencing data between the parental lines of DHL92 to develop a new set of SNP markers from unanchored scaffolds. RESULTS: A high-resolution genetic map composed of 580 SNPs was used to anchor 354.8 Mb of sequence, contained in 141 scaffolds (average size 2.5 Mb) and corresponding to 98.2% of the scaffold assembly, to the 12 melon chromosomes. Over 325.4 Mb (90%) of the assembly was oriented. The genetic map revealed regions of segregation distortion favoring SC alleles as well as recombination suppression regions coinciding with putative centromere, 45S, and 5S rDNA sites. New chromosome-scale pseudomolecules were created by incorporating to the previous v3.5 version an additional 38.3 Mb of anchored sequence representing 1,837 predicted genes contained in 55 scaffolds. Using fluorescent in situ hybridization (FISH) with BACs that produced chromosome-specific signals, melon chromosomes that correspond to the twelve linkage groups were identified, and a standardized karyotype of melon inbred line T111 was developed. CONCLUSIONS: By utilizing resequencing data and targeted SNP selection combined with a large F2 mapping population, we significantly improved the quantity of anchored and oriented melon scaffold genome assembly. Using genome information combined with FISH mapping provided the first cytogenetic map of an inodorus melon type. With these results it was possible to make inferences on melon chromosome structure by relating zones of recombination suppression to centromeres and 45S and 5S heterochromatic regions. This study represents the first steps towards the integration of the high-resolution genetic and cytogenetic maps with the genomic sequence in melon that will provide more information on genome organization and allow for the improvement of the melon genome draft sequence.

PopGenome: an efficient Swiss army knife for population genomic analyses in R.

Although many computer programs can perform population genetics calculations, they are typically limited in the analyses and data input formats they offer; few applications can process the large data sets produced by whole-genome resequencing projects. Furthermore, there is no coherent framework for the easy integration of new statistics into existing pipelines, hindering the development and application of new population genetics and genomics approaches. Here, we present PopGenome, a population genomics package for the R software environment (a de facto standard for statistical analyses). PopGenome can efficiently process genome-scale data as well as large sets of individual loci. It reads DNA alignments and single-nucleotide polymorphism (SNP) data sets in most common formats, including those used by the HapMap, 1000 human genomes, and 1001 Arabidopsis genomes projects. PopGenome also reads associated annotation files in GFF format, enabling users to easily define regions or classify SNPs based on their annotation; all analyses can also be applied to sliding windows. PopGenome offers a wide range of diverse population genetics analyses, including neutrality tests as well as statistics for population differentiation, linkage disequilibrium, and recombination. PopGenome is linked to Hudson's MS and Ewing's MSMS programs to assess statistical significance based on coalescent simulations. PopGenome's integration in R facilitates effortless and reproducible downstream analyses as well as the production of publication-quality graphics. Developers can easily incorporate new analyses methods into the PopGenome framework. PopGenome and R are freely available from CRAN (http://cran.r-project.org/) for all major operating systems under the GNU General Public License.

A generalized Watterson estimator for next-generation sequencing: From trios to autopolyploids.

Several variations of the Watterson estimator of variability for Next Generation Sequencing (NGS) data have been proposed in the literature. We present a unified framework for generalized Watterson estimators based on Maximum Composite Likelihood, which encompasses most of the existing estimators. We propose this class of unbiased estimators as generalized Watterson estimators for a large class of NGS data, including pools and trios. We also discuss the relation with the estimators proposed in the literature and show that they admit two equivalent but seemingly different forms, deriving a set of combinatorial identities as a byproduct. Finally, we give a detailed treatment of Watterson estimators for single or multiple autopolyploid individuals.

Evaluation of deep learning for predicting rice traits using structural and single-nucleotide genomic variants.

BACKGROUND: Structural genomic variants (SVs) are prevalent in plant genomes and have played an important role in evolution and domestication, as they constitute a significant source of genomic and phenotypic variability. Nevertheless, most methods in quantitative genetics focusing on crop improvement, such as genomic prediction, consider only Single Nucleotide Polymorphisms (SNPs). Deep Learning (DL) is a promising strategy for genomic prediction, but its performance using SVs and SNPs as genetic markers remains unknown. RESULTS: We used rice to investigate whether combining SVs and SNPs can result in better trait prediction over SNPs alone and examine the potential advantage of Deep Learning (DL) networks over Bayesian Linear models. Specifically, the performances of BayesC (considering additive effects) and a Bayesian Reproducible Kernel Hilbert space (RKHS) regression (considering both additive and non-additive effects) were compared to those of two different DL architectures, the Multilayer Perceptron, and the Convolution Neural Network, to explore their prediction ability by using various marker input strategies. We found that exploiting structural and nucleotide variation slightly improved prediction ability on complex traits in 87% of the cases. DL models outperformed Bayesian models in 75% of the studied cases, considering the four traits and the two validation strategies used. Finally, DL systematically improved prediction ability of binary traits against the Bayesian models. CONCLUSIONS: Our study reveals that the use of structural genomic variants can improve trait prediction in rice, independently of the methodology used. Also, our results suggest that Deep Learning (DL) networks can perform better than Bayesian models in the prediction of binary traits, and in quantitative traits when the training and target sets are not closely related. This highlights the potential of DL to enhance crop improvement in specific scenarios and the importance to consider SVs in addition to SNPs in genomic selection.

Dissecting structural and nucleotide genome-wide variation in inbred Iberian pigs.

BACKGROUND: In contrast to international pig breeds, the Iberian breed has not been admixed with Asian germplasm. This makes it an important model to study both domestication and relevance of Asian genes in the pig. Besides, Iberian pigs exhibit high meat quality as well as appetite and propensity to obesity. Here we provide a genome wide analysis of nucleotide and structural diversity in a reduced representation library from a pool (n=9 sows) and shotgun genomic sequence from a single sow of the highly inbred Guadyerbas strain. In the pool, we applied newly developed tools to account for the peculiarities of these data. RESULTS: A total of 254,106 SNPs in the pool (79.6 Mb covered) and 643,783 in the Guadyerbas sow (1.47 Gb covered) were called. The nucleotide diversity (1.31x10-3 per bp in autosomes) is very similar to that reported in wild boar. A much lower than expected diversity in the X chromosome was confirmed (1.79x10-4 per bp in the individual and 5.83x10-4 per bp in the pool). A strong (0.70) correlation between recombination and variability was observed, but not with gene density or GC content. Multicopy regions affected about 4% of annotated pig genes in their entirety, and 2% of the genes partially. Genes within the lowest variability windows comprised interferon genes and, in chromosome X, genes involved in behavior like HTR2C or MCEP2. A modified Hudson-Kreitman-Aguadé test for pools also indicated an accelerated evolution in genes involved in behavior, as well as in spermatogenesis and in lipid metabolism. CONCLUSIONS: This work illustrates the strength of current sequencing technologies to picture a comprehensive landscape of variability in livestock species, and to pinpoint regions containing genes potentially under selection. Among those genes, we report genes involved in behavior, including feeding behavior, and lipid metabolism. The pig X chromosome is an outlier in terms of nucleotide diversity, which suggests selective constraints. Our data further confirm the importance of structural variation in the species, including Iberian pigs, and allowed us to identify new paralogs for known gene families.

Evolution of recombination in eutherian mammals: insights into mechanisms that affect recombination rates and crossover interference.

Recombination allows faithful chromosomal segregation during meiosis and contributes to the production of new heritable allelic variants that are essential for the maintenance of genetic diversity. Therefore, an appreciation of how this variation is created and maintained is of critical importance to our understanding of biodiversity and evolutionary change. Here, we analysed the recombination features from species representing the major eutherian taxonomic groups Afrotheria, Rodentia, Primates and Carnivora to better understand the dynamics of mammalian recombination. Our results suggest a phylogenetic component in recombination rates (RRs), which appears to be directional, strongly punctuated and subject to selection. Species that diversified earlier in the evolutionary tree have lower RRs than those from more derived phylogenetic branches. Furthermore, chromosome-specific recombination maps in distantly related taxa show that crossover interference is especially weak in the species with highest RRs detected thus far, the tiger. This is the first example of a mammalian species exhibiting such low levels of crossover interference, highlighting the uniqueness of this species and its relevance for the study of the mechanisms controlling crossover formation, distribution and resolution.

Population genomics from pool sequencing.

Next generation sequencing of pooled samples is an effective approach for studies of variability and differentiation in populations. In this paper we provide a comprehensive set of estimators of the most common statistics in population genetics based on the frequency spectrum, namely the Watterson estimator θW, nucleotide pairwise diversity Π, Tajima's D, Fu and Li's D and F, Fay and Wu's H, McDonald-Kreitman and HKA tests and FST, corrected for sequencing errors and ascertainment bias. In a simulation study, we show that pool and individual θ estimates are highly correlated and discuss how the performance of the statistics vary with read depth and sample size in different evolutionary scenarios. As an application, we reanalyse sequences from Drosophila mauritiana and from an evolution experiment in Drosophila melanogaster. These methods are useful for population genetic projects with limited budget, study of communities of individuals that are hard to isolate, or autopolyploid species.

A General Framework for Neutrality Tests Based on the Site Frequency Spectrum.

One of the main necessities for population geneticists is the availability of sensitive statistical tools that enable to accept or reject the standard Wright-Fisher model of neutral evolution. A number of statistical tests have been developed to detect specific deviations from the null frequency spectrum in different directions (e.g., Tajima's D, Fu and Li's F and D tests, Fay and Wu's H). A general framework exists to generate all neutrality tests that are linear functions of the frequency spectrum. In this framework, it is possible to develop a family of optimal tests with almost maximum power against a specific alternative evolutionary scenario. In this paper we provide a thorough discussion of the structure and properties of linear and nonlinear neutrality tests. First, we present the general framework for linear tests and emphasise the importance of the property of scalability with the sample size (that is, the interpretation of the tests should not depend on the sample size), which, if missing, can lead to errors in interpreting the data. After summarising the motivation and structure of linear optimal tests, we present a more general framework for the optimisation of linear tests, leading to a new family of tunable neutrality tests. In a further generalisation, we extend the framework to nonlinear neutrality tests and we derive nonlinear optimal tests for polynomials of any degree in the frequency spectrum.

Development and Evaluation of an AxiomTM 60K SNP Array for Almond (Prunus dulcis).

A high-density single nucleotide polymorphism (SNP) array is essential to enable faster progress in plant breeding for new cultivar development. In this regard, we have developed an Axiom 60K almond SNP array by resequencing 81 almond accessions. For the validation of the array, a set of 210 accessions were genotyped and 82.8% of the SNPs were classified in the best recommended SNPs. The rate of missing data was between 0.4% and 2.7% for the almond accessions and less than 15.5% for the few peach and wild accessions, suggesting that this array can be used for peach and interspecific peach × almond genetic studies. The values of the two SNPs linked to the RMja (nematode resistance) and SK (bitterness) genes were consistent. We also genotyped 49 hybrids from an almond F2 progeny and could build a genetic map with a set of 1159 SNPs. Error rates, less than 1%, were evaluated by comparing replicates and by detection of departures from Mendelian inheritance in the F2 progeny. This almond array is commercially available and should be a cost-effective genotyping tool useful in the search for new genes and quantitative traits loci (QTL) involved in the control of agronomic traits.

Copy Number Variation on ABCC2-DNMBP Loci Affects the Diversity and Composition of the Fecal Microbiota in Pigs.

Genetic variation in the pig genome partially modulates the composition of porcine gut microbial communities. Previous studies have been focused on the association between single nucleotide polymorphisms (SNPs) and the gut microbiota, but little is known about the relationship between structural variants and fecal microbial traits. The main goal of this study was to explore the association between porcine genome copy number variants (CNVs) and the diversity and composition of pig fecal microbiota. For this purpose, we used whole-genome sequencing data to undertake a comprehensive identification of CNVs followed by a genome-wide association analysis between the estimated CNV status and the fecal bacterial diversity in a commercial Duroc pig population. A CNV predicted as gain (DUP) partially harboring ABCC2-DNMBP loci was associated with richness (P = 5.41 × 10-5, false discovery rate [FDR] = 0.022) and Shannon α-diversity (P = 1.42 × 10-4, FDR = 0.057). The in silico predicted gain of copies was validated by real-time quantitative PCR (qPCR), and its segregation, and positive association with the richness and Shannon α-diversity of the porcine fecal bacterial ecosystem was confirmed in an unrelated F1 (Duroc × Iberian) cross. Our results advise the relevance of considering the role of host-genome structural variants as potential modulators of microbial ecosystems and suggest the ABCC2-DNMBP CNV as a host-genetic factor for the modulation of the diversity and composition of the fecal microbiota in pigs. IMPORTANCE A better understanding of the environmental and host factors modulating gut microbiomes is a topic of greatest interest. Recent evidence suggests that genetic variation in the pig genome partially controls the composition of porcine gut microbiota. However, since previous studies have been focused on the association between single nucleotide polymorphisms and the fecal microbiota, little is known about the relationship between other sources of genetic variation, like the structural variants and microbial traits. Here, we identified, experimentally validated, and replicated in an independent population a positive link between the gain of copies of ABCC2-DNMBP loci and the diversity and composition of pig fecal microbiota. Our results advise the relevance of considering the role of host-genome structural variants as putative modulators of microbial ecosystems and open the possibility of implementing novel holobiont-based management strategies in breeding programs for the simultaneous improvement of microbial traits and host performance.

Multilocus patterns of nucleotide diversity, population structure and linkage disequilibrium in Boechera stricta, a wild relative of Arabidopsis.

Information about polymorphism, population structure, and linkage disequilibrium (LD) is crucial for association studies of complex trait variation. However, most genomewide studies have focused on model systems, with very few analyses of undisturbed natural populations. Here, we sequenced 86 mapped nuclear loci for a sample of 46 genotypes of Boechera stricta and two individuals of B. holboellii, both wild relatives of Arabidopsis. Isolation by distance was significant across the species range of B. stricta, and three geographic groups were identified by structure analysis, principal coordinates analysis, and distance-based phylogeny analyses. The allele frequency spectrum indicated a genomewide deviation from an equilibrium neutral model, with silent nucleotide diversity averaging 0.004. LD decayed rapidly, declining to background levels in approximately 10 kb or less. For tightly linked SNPs separated by <1 kb, LD was dependent on the reference population. LD was lower in the specieswide sample than within populations, suggesting that low levels of LD found in inbreeding species such as B. stricta, Arabidopsis thaliana, and barley may result from broad geographic sampling that spans heterogeneous genetic groups. Finally, analyses also showed that inbreeding B. stricta and A. thaliana have approximately 45% higher recombination per kilobase than outcrossing A. lyrata.

Population history in Arabidopsis halleri using multilocus analysis.

A. halleri is a psuedometallophyte with a patchy distribution in Europe and is often spread by human activity. To determine the population history and whether this history is consistent with potential human effects, we surveyed nucleotide variation using 24 loci from 12 individuals in a large A. halleri population. The means of total and silent nucleotide variation (theta(W)) are within the range expected for the species. The population genetic neutrality tests Tajima's D and Wall's B had significant composite results rejecting panmixia, and Approximate Bayesian Computation analysis revealed that a subdivision model better explained the variation than the standard neutral model, refugia (or admixture), bottleneck or change of population size models. A categorical regression analysis further supports the subdivision model, and under the subdivision model, the neutrality tests are no longer significant. The best support was for two source populations, a situation consistent with the mixing of two populations possibly mediated by human activity. This scenario might limit the genetic diversity and adaptive potential of the population. The non-neutral population variation described here should be considered in bioinformatic searches for adaptation.