Molecular evolution of regulatory genes in spruces from different species and continents: heterogeneous patterns of linkage disequilibrium and selection but correlated recent demographic changes

Selective Sweeps and Polygenic Adaptation Drive Local Adaptation along Moisture and Temperature Gradients in Natural Populations of Coast Redwood and Giant Sequoia

Dissecting the genomic basis of local adaptation is a major goal in evolutionary biology and conservation science. Rapid changes in the climate pose significant challenges to the survival of natural populations, and the genomic basis of long-generation plant species is still poorly understood. Here, we investigated genome-wide climate adaptation in giant sequoia and coast redwood, two iconic and ecologically important tree species. We used a combination of univariate and multivariate genotype-environment association methods and a selective sweep analysis using non-overlapping sliding windows. We identified genomic regions of potential adaptive importance, showing strong associations to moisture variables and mean annual temperature. Our results found a complex architecture of climate adaptation in the species, with genomic regions showing signatures of selective sweeps, polygenic adaptation, or a combination of both, suggesting recent or ongoing climate adaptation along moisture and temperature gradients in giant sequoia and coast redwood. The results of this study provide a first step toward identifying genomic regions of adaptive significance in the species and will provide information to guide management and conservation strategies that seek to maximize adaptive potential in the face of climate change.

Association genetics identifies a specifically regulated Norway spruce laccase gene, PaLAC5, linked to Heterobasidion parviporum resistance

It is important to improve the understanding of the interactions between the trees and pathogens and integrate this knowledge about disease resistance into tree breeding programs. The conifer Norway spruce (Picea abies) is an important species for the forest industry in Europe. Its major pathogen is Heterobasidion parviporum, causing stem and root rot. In this study, we identified 11 Norway spruce QTLs (Quantitative trait loci) that correlate with variation in resistance to H. parviporum in a population of 466 trees by association genetics. Individual QTLs explained between 2.1 and 5.2% of the phenotypic variance. The expression of candidate genes associated with the QTLs was analysed in silico and in response to H. parviporum hypothesizing that (a) candidate genes linked to control of fungal sapwood growth are more commonly expressed in sapwood, and; (b) candidate genes associated with induced defences are respond to H. parviporum inoculation. The Norway spruce laccase PaLAC5 associated with control of lesion length development is likely to be involved in the induced defences. Expression analyses showed that PaLAC5 responds specifically and strongly in close proximity to the H. parviporum inoculation. Thus, PaLAC5 may be associated with the lignosuberized boundary zone formation in bark adjacent to the inoculation site.

Genome-wide association study identified novel candidate loci affecting wood formation in Norway spruce

Norway spruce is a boreal forest tree species of significant ecological and economic importance. Hence there is a strong imperative to dissect the genetics underlying important wood quality traits in the species. We performed a functional genome-wide association study (GWAS) of 17 wood traits in Norway spruce using 178 101 single nucleotide polymorphisms (SNPs) generated from exome genotyping of 517 mother trees. The wood traits were defined using functional modelling of wood properties across annual growth rings. We applied a Least Absolute Shrinkage and Selection Operator (LASSO-based) association mapping method using a functional multilocus mapping approach that utilizes latent traits, with a stability selection probability method as the hypothesis testing approach to determine a significant quantitative trait locus. The analysis provided 52 significant SNPs from 39 candidate genes, including genes previously implicated in wood formation and tree growth in spruce and other species. Our study represents a multilocus GWAS for complex wood traits in Norway spruce. The results advance our understanding of the genetics influencing wood traits and identifies candidate genes for future functional studies.

Novel Insights into Plant Genome Evolution and Adaptation as Revealed through Transposable Elements and Non-Coding RNAs in Conifers

Plant genomes are punctuated by repeated bouts of proliferation of transposable elements (TEs), and these mobile bursts are followed by silencing and decay of most of the newly inserted elements. As such, plant genomes reflect TE-related genome expansion and shrinkage. In general, these genome activities involve two mechanisms: small RNA-mediated epigenetic repression and long-term mutational decay and deletion, that is, genome-purging. Furthermore, the spatial relationships between TE insertions and genes are an important force in shaping gene regulatory networks, their downstream metabolic and physiological outputs, and thus their phenotypes. Such cascading regulations finally set up a fitness differential among individuals. This brief review demonstrates factual evidence that unifies most updated conceptual frameworks covering genome size, architecture, epigenetic reprogramming, and gene expression. It aims to give an overview of the impact that TEs may have on genome and adaptive evolution and to provide novel insights into addressing possible causes and consequences of intimidating genome sizes (20⁻30 Gb) in a taxonomic group, conifers.

Genome-wide association mapping of latex yield and girth in Amazonian accessions of Hevea brasiliensis grown in a suboptimal climate zone

Latex yield and growth are the key complex traits in commercial rubber production. The present study is the first to report genome-wide association mapping of latex yield and girth, for 170 Amazonian accessions grown in a suboptimal area characterized by limited rainfall and a lengthy dry season. Targeted sequence enrichment to capture gene transcripts generated 14,155 high quality filtered single nucleotide polymorphisms (SNPs) of which 94.3% resided in coding regions. The rapid decay of linkage disequilibrium over physical and genetic distance found in the accessions was comparable to those previously reported for several outcrossing species. A mixed linear model detected three significant SNPs in three candidate genes involved in plant adaptation to drought stress, individually explaining 12.7-15.7% of the phenotypic variance. The SNPs identified in the study will help to extend understanding, and to support genetic improvement of rubber trees grown in drought-affected regions.

A high-resolution reference genetic map positioning 8.8 K genes for the conifer white spruce: structural genomics implications and correspondence with physical distance

Over the last decade, extensive genetic and genomic resources have been developed for the conifer white spruce (Picea glauca, Pinaceae), which has one of the largest plant genomes (20 Gbp). Draft genome sequences of white spruce and other conifers have recently been produced, but dense genetic maps are needed to comprehend genome macrostructure, delineate regions involved in quantitative traits, complement functional genomic investigations, and assist the assembly of fragmented genomic sequences. A greatly expanded P. glauca composite linkage map was generated from a set of 1976 full-sib progeny, with the positioning of 8793 expressed genes. Regions with significant low or high gene density were identified. Gene family members tended to be mapped on the same chromosomes, with tandemly arrayed genes significantly biased towards specific functional classes. The map was integrated with transcriptome data surveyed across eight tissues. In total, 69 clusters of co-expressed and co-localising genes were identified. A high level of synteny was found with pine genetic maps, which should facilitate the transfer of structural information in the Pinaceae. Although the current white spruce genome sequence remains highly fragmented, dozens of scaffolds encompassing more than one mapped gene were identified. From these, the relationship between genetic and physical distances was examined and the genome-wide recombination rate was found to be much smaller than most estimates reported for angiosperm genomes. This gene linkage map shall assist the large-scale assembly of the next-generation white spruce genome sequence and provide a reference resource for the conifer genomics community.

The challenge of separating signatures of local adaptation from those of isolation by distance and colonization history: The case of two white pines

Accurately detecting signatures of local adaptation using genetic‐environment associations (GEAs) requires controlling for neutral patterns of population structure to reduce the risk of false positives. However, a high degree of collinearity between climatic gradients and neutral population structure can greatly reduce power, and the performance of GEA methods in such case is rarely evaluated in empirical studies. In this study, we attempted to disentangle the effects of local adaptation and isolation by environment (IBE) from those of isolation by distance (IBD) and isolation by colonization from glacial refugia (IBC) using range‐wide samples in two white pine species. For this, SNPs from 168 genes, including 52 candidate genes for growth and phenology, were genotyped in 133 and 61 populations of Pinus strobus and P. monticola, respectively. For P. strobus and using all 153 SNPs, climate (IBE) did not significantly explained among‐population variation when controlling for IBD and IBC in redundancy analyses (RDAs). However, 26 SNPs were significantly associated with climate in single‐locus GEA analyses (Bayenv2 and LFMM), suggesting that local adaptation took place in the presence of high gene flow. For P. monticola, we found no evidence of IBE using RDAs and weaker signatures of local adaptation using GEA and F_ST outlier tests, consistent with adaptation via phenotypic plasticity. In both species, the majority of the explained among‐population variation (69 to 96%) could not be partitioned between the effects of IBE, IBD, and IBC. GEA methods can account differently for this confounded variation, and this could explain the small overlap of SNPs detected between Bayenv2 and LFMM. Our study illustrates the inherent difficulty of taking into account neutral structure in natural populations and the importance of sampling designs that maximize climatic variation, while minimizing collinearity between climatic gradients and neutral structure.

Exome genotyping, linkage disequilibrium and population structure in loblolly pine (Pinus taeda L.)

Background

Loblolly pine (Pinus taeda L.) is one of the most widely planted and commercially important forest tree species in the USA and worldwide, and is an object of intense genomic research. However, whole genome resequencing in loblolly pine is hampered by its large size and complexity and a lack of a good reference. As a valid and more feasible alternative, entire exome sequencing was hence employed to identify the gene-associated single nucleotide polymorphisms (SNPs) and to genotype the sampled trees.

Results

The exons were captured in the ADEPT2 association mapping population of 375 clonally-propagated loblolly pine trees using NimbleGen oligonucleotide hybridization probes, and then exome-enriched genomic DNA fragments were sequenced using the Illumina HiSeq 2500 platform. Oligonucleotide probes were designed based on 199,723 exons (≈49 Mbp) partitioned from the loblolly pine reference genome (PineRefSeq v. 1.01). The probes covered 90.2 % of the target regions. Capture efficiency was high; on average, 67 % of the sequence reads generated for each tree could be mapped to the capture target regions, and more than 70 % of the captured target bases had at least 10X sequencing depth per tree. A total of 972,720 high quality SNPs were identified after filtering. Among them, 53 % were located in coding regions (CDS), 5 % in 5’ or 3’ untranslated regions (UTRs) and 42 % in non-target and non-coding regions, such as introns and adjacent intergenic regions collaterally captured. We found that linkage disequilibrium (LD) decayed very rapidly, with the correlation coefficient (r²) between pairs of SNPs linked within single scaffolds decaying to half maximum (r² = 0.22) within 55 bp, to r² = 0.1 within 192 bp, and to r² = 0.05 within 451 bp. Population structure analysis using unlinked SNPs demonstrated the presence of two main distinct clusters representing western and eastern parts of the loblolly pine range included in our sample of trees.

Conclusions

The obtained results demonstrated the efficiency of exome capture for genotyping species such as loblolly pine with a large and complex genome. The highly diverse genetic variation reported in this study will be a valuable resource for future genetic and genomic research in loblolly pine.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3081-8) contains supplementary material, which is available to authorized users.

Local Adaptation in European Firs Assessed through Extensive Sampling across Altitudinal Gradients in Southern Europe

BACKGROUND

Local adaptation is a key driver of phenotypic and genetic divergence at loci responsible for adaptive traits variations in forest tree populations. Its experimental assessment requires rigorous sampling strategies such as those involving population pairs replicated across broad spatial scales.

METHODS

A hierarchical Bayesian model of selection (HBM) that explicitly considers both the replication of the environmental contrast and the hierarchical genetic structure among replicated study sites is introduced. Its power was assessed through simulations and compared to classical 'within-site' approaches (FDIST, BAYESCAN) and a simplified, within-site, version of the model introduced here (SBM).

RESULTS

HBM demonstrates that hierarchical approaches are very powerful to detect replicated patterns of adaptive divergence with low false-discovery (FDR) and false-non-discovery (FNR) rates compared to the analysis of different sites separately through within-site approaches. The hypothesis of local adaptation to altitude was further addressed by analyzing replicated Abies alba population pairs (low and high elevations) across the species' southern distribution range, where the effects of climatic selection are expected to be the strongest. For comparison, a single population pair from the closely related species A. cephalonica was also analyzed. The hierarchical model did not detect any pattern of adaptive divergence to altitude replicated in the different study sites. Instead, idiosyncratic patterns of local adaptation among sites were detected by within-site approaches.

CONCLUSION

Hierarchical approaches may miss idiosyncratic patterns of adaptation among sites, and we strongly recommend the use of both hierarchical (multi-site) and classical (within-site) approaches when addressing the question of adaptation across broad spatial scales.

Conifer genomics and adaptation: at the crossroads of genetic diversity and genome function

Conifers have been understudied at the genomic level despite their worldwide ecological and economic importance but the situation is rapidly changing with the development of next generation sequencing (NGS) technologies. With NGS, genomics research has simultaneously gained in speed, magnitude and scope. In just a few years, genomes of 20-24 gigabases have been sequenced for several conifers, with several others expected in the near future. Biological insights have resulted from recent sequencing initiatives as well as genetic mapping, gene expression profiling and gene discovery research over nearly two decades. We review the knowledge arising from conifer genomics research emphasizing genome evolution and the genomic basis of adaptation, and outline emerging questions and knowledge gaps. We discuss future directions in three areas with potential inputs from NGS technologies: the evolutionary impacts of adaptation in conifers based on the adaptation-by-speciation model; the contributions of genetic variability of gene expression in adaptation; and the development of a broader understanding of genetic diversity and its impacts on genome function. These research directions promise to sustain research aimed at addressing the emerging challenges of adaptation that face conifer trees.

Genetic Adaptation to Climate in White Spruce Involves Small to Moderate Allele Frequency Shifts in Functionally Diverse Genes

Understanding the genetic basis of adaptation to climate is of paramount importance for preserving and managing genetic diversity in plants in a context of climate change. Yet, this objective has been addressed mainly in short-lived model species. Thus, expanding knowledge to nonmodel species with contrasting life histories, such as forest trees, appears necessary. To uncover the genetic basis of adaptation to climate in the widely distributed boreal conifer white spruce (Picea glauca), an environmental association study was conducted using 11,085 single nucleotide polymorphisms representing 7,819 genes, that is, approximately a quarter of the transcriptome.

Linear and quadratic regressions controlling for isolation-by-distance, and the Random Forest algorithm, identified several dozen genes putatively under selection, among which 43 showed strongest signals along temperature and precipitation gradients. Most of them were related to temperature. Small to moderate shifts in allele frequencies were observed. Genes involved encompassed a wide variety of functions and processes, some of them being likely important for plant survival under biotic and abiotic environmental stresses according to expression data. Literature mining and sequence comparison also highlighted conserved sequences and functions with angiosperm homologs.

Our results are consistent with theoretical predictions that local adaptation involves genes with small frequency shifts when selection is recent and gene flow among populations is high. Accordingly, genetic adaptation to climate in P. glauca appears to be complex, involving many independent and interacting gene functions, biochemical pathways, and processes. From an applied perspective, these results shall lead to specific functional/association studies in conifers and to the development of markers useful for the conservation of genetic resources.

Genome-wide patterns of recombination, linkage disequilibrium and nucleotide diversity from pooled resequencing and single nucleotide polymorphism genotyping unlock the evolutionary history of Eucalyptus grandis

We used high-density single nucleotide polymorphism (SNP) data and whole-genome pooled resequencing to examine the landscape of population recombination (ρ) and nucleotide diversity (ϴw ), assess the extent of linkage disequilibrium (r(2) ) and build the highest density linkage maps for Eucalyptus. At the genome-wide level, linkage disequilibrium (LD) decayed within c. 4-6 kb, slower than previously reported from candidate gene studies, but showing considerable variation from absence to complete LD up to 50 kb. A sharp decrease in the estimate of ρ was seen when going from short to genome-wide inter-SNP distances, highlighting the dependence of this parameter on the scale of observation adopted. Recombination was correlated with nucleotide diversity, gene density and distance from the centromere, with hotspots of recombination enriched for genes involved in chemical reactions and pathways of the normal metabolic processes. The high nucleotide diversity (ϴw = 0.022) of E. grandis revealed that mutation is more important than recombination in shaping its genomic diversity (ρ/ϴw = 0.645). Chromosome-wide ancestral recombination graphs allowed us to date the split of E. grandis (1.7-4.8 million yr ago) and identify a scenario for the recent demographic history of the species. Our results have considerable practical importance to Genome Wide Association Studies (GWAS), while indicating bright prospects for genomic prediction of complex phenotypes in eucalypt breeding.

Development of highly reliable in silico SNP resource and genotyping assay from exome capture and sequencing: an example from black spruce (Picea mariana)

Picea mariana is a widely distributed boreal conifer across Canada and the subject of advanced breeding programmes for which population genomics and genomic selection approaches are being developed. Targeted sequencing was achieved after capturing P. mariana exome with probes designed from the sequenced transcriptome of Picea glauca, a distant relative. A high capture efficiency of 75.9% was reached although spruce has a complex and large genome including gene sequences interspersed by some long introns. The results confirmed the relevance of using probes from congeneric species to perform successfully interspecific exome capture in the genus Picea. A bioinformatics pipeline was developed including stringent criteria that helped detect a set of 97,075 highly reliable in silico SNPs. These SNPs were distributed across 14,909 genes. Part of an Infinium iSelect array was used to estimate the rate of true positives by validating 4267 of the predicted in silico SNPs by genotyping trees from P. mariana populations. The true positive rate was 96.2% for in silico SNPs, compared to a genotyping success rate of 96.7% for a set 1115 P. mariana control SNPs recycled from previous genotyping arrays. These results indicate the high success rate of the genotyping array and the relevance of the selection criteria used to delineate the new P. mariana in silico SNP resource. Furthermore, in silico SNPs were generally of medium to high frequency in natural populations, thus providing high informative value for future population genomics applications.

Patterns of nucleotide diversity at photoperiod related genes in Norway spruce [Picea abies (L.) Karst]

The ability of plants to track seasonal changes is largely dependent on genes assigned to the photoperiod pathway, and variation in those genes is thereby important for adaptation to local day length conditions. Extensive physiological data in several temperate conifer species suggest that populations are adapted to local light conditions, but data on the genes underlying this adaptation are more limited. Here we present nucleotide diversity data from 19 genes putatively involved in photoperiodic response in Norway spruce (Picea abies). Based on similarity to model plants the genes were grouped into three categories according to their presumed position in the photoperiod pathway: photoreceptors, circadian clock genes, and downstream targets. An HKA (Hudson, Kreitman and Aquade) test showed a significant excess of diversity at photoreceptor genes, but no departure from neutrality at circadian genes and downstream targets. Departures from neutrality were also tested with Tajima's D and Fay and Wu's H statistics under three demographic scenarios: the standard neutral model, a population expansion model, and a more complex population split model. Only one gene, the circadian clock gene PaPRR3 with a highly positive Tajima's D value, deviates significantly from all tested demographic scenarios. As the PaPRR3 gene harbours multiple non-synonymous variants it appears as an excellent candidate gene for control of photoperiod response in Norway spruce.

The landscape of nucleotide polymorphism among 13,500 genes of the conifer picea glauca, relationships with functions, and comparison with medicago truncatula

Gene families differ in composition, expression, and chromosomal organization between conifers and angiosperms, but little is known regarding nucleotide polymorphism. Using various sequencing strategies, an atlas of 212k high-confidence single nucleotide polymorphisms (SNPs) with a validation rate of more than 92% was developed for the conifer white spruce (Picea glauca). Nonsynonymous and synonymous SNPs were annotated over the corresponding 13,498 white spruce genes representative of 2,457 known gene families. Patterns of nucleotide polymorphisms were analyzed by estimating the ratio of nonsynonymous to synonymous numbers of substitutions per site (A/S). A general excess of synonymous SNPs was expected and observed. However, the analysis from several perspectives enabled to identify groups of genes harboring an excess of nonsynonymous SNPs, thus potentially under positive selection. Four known gene families harbored such an excess: dehydrins, ankyrin-repeats, AP2/DREB, and leucine-rich repeat. Conifer-specific sequences were also generally associated with the highest A/S ratios. A/S values were also distributed asymmetrically across genes specifically expressed in megagametophytes, roots, or in both, harboring on average an excess of nonsynonymous SNPs. These patterns confirm that the breadth of gene expression is a contributing factor to the evolution of nucleotide polymorphism. The A/S ratios of Medicago truncatula genes were also analyzed: several gene families shared between P. glauca and M. truncatula data sets had similar excess of synonymous or nonsynonymous SNPs. However, a number of families with high A/S ratios were found specific to P. glauca, suggesting cases of divergent evolution at the functional level.

Accuracy of genomic selection models in a large population of open-pollinated families in white spruce

Genomic selection (GS) is of interest in breeding because of its potential for predicting the genetic value of individuals and increasing genetic gains per unit of time. To date, very few studies have reported empirical results of GS potential in the context of large population sizes and long breeding cycles such as for boreal trees. In this study, we assessed the effectiveness of marker-aided selection in an undomesticated white spruce (Picea glauca (Moench) Voss) population of large effective size using a GS approach. A discovery population of 1694 trees representative of 214 open-pollinated families from 43 natural populations was phenotyped for 12 wood and growth traits and genotyped for 6385 single-nucleotide polymorphisms (SNPs) mined in 2660 gene sequences. GS models were built to predict estimated breeding values using all the available SNPs or SNP subsets of the largest absolute effects, and they were validated using various cross-validation schemes. The accuracy of genomic estimated breeding values (GEBVs) varied from 0.327 to 0.435 when the training and the validation data sets shared half-sibs that were on average 90% of the accuracies achieved through traditionally estimated breeding values. The trend was also the same for validation across sites. As expected, the accuracy of GEBVs obtained after cross-validation with individuals of unknown relatedness was lower with about half of the accuracy achieved when half-sibs were present. We showed that with the marker densities used in the current study, predictions with low to moderate accuracy could be obtained within a large undomesticated population of related individuals, potentially resulting in larger gains per unit of time with GS than with the traditional approach.

The evolutionary genetics of the genes underlying phenotypic associations for loblolly pine (Pinus taeda, Pinaceae)

A primary goal of evolutionary genetics is to discover and explain the genetic basis of fitness-related traits and how this genetic basis evolves within natural populations. Unprecedented technological advances have fueled the discovery of genetic variants associated with ecologically relevant phenotypes in many different life forms, as well as the ability to scan genomes for deviations from selectively neutral models of evolution. Theoretically, the degree of overlap between lists of genomic regions identified using each approach is related to the genetic architecture of fitness-related traits and the strength and type of natural selection molding variation at these traits within natural populations. Here we address for the first time in a plant the degree of overlap between these lists, using patterns of nucleotide diversity and divergence for >7000 unique amplicons described from the extensive expressed sequence tag libraries generated for loblolly pine (Pinus taeda L.) in combination with the >1000 published genetic associations. We show that loci associated with phenotypic traits are distinct with regard to neutral expectations. Phenotypes measured at the whole plant level (e.g., disease resistance) exhibit an approximately twofold increase in the proportion of adaptive nonsynonymous substitutions over the genome-wide average. As expected for polygenic traits, these signals were apparent only when loci were considered at the level of functional sets. The ramifications of this result are discussed in light of the continued efforts to dissect the genetic basis of quantitative traits.

The genomic architecture and association genetics of adaptive characters using a candidate SNP approach in boreal black spruce

BACKGROUND

The genomic architecture of adaptive traits remains poorly understood in non-model plants. Various approaches can be used to bridge this gap, including the mapping of quantitative trait loci (QTL) in pedigrees, and genetic association studies in non-structured populations. Here we present results on the genomic architecture of adaptive traits in black spruce, which is a widely distributed conifer of the North American boreal forest. As an alternative to the usual candidate gene approach, a candidate SNP approach was developed for association testing.

RESULTS

A genetic map containing 231 gene loci was used to identify QTL that were related to budset timing and to tree height assessed over multiple years and sites. Twenty-two unique genomic regions were identified, including 20 that were related to budset timing and 6 that were related to tree height. From results of outlier detection and bulk segregant analysis for adaptive traits using DNA pool sequencing of 434 genes, 52 candidate SNPs were identified and subsequently tested in genetic association studies for budset timing and tree height assessed over multiple years and sites. A total of 34 (65%) SNPs were significantly associated with budset timing, or tree height, or both. Although the percentages of explained variance (PVE) by individual SNPs were small, several significant SNPs were shared between sites and among years.

CONCLUSIONS

The sharing of genomic regions and significant SNPs between budset timing and tree height indicates pleiotropic effects. Significant QTLs and SNPs differed quite greatly among years, suggesting that different sets of genes for the same characters are involved at different stages in the tree's life history. The functional diversity of genes carrying significant SNPs and low observed PVE further indicated that a large number of polymorphisms are involved in adaptive genetic variation. Accordingly, for undomesticated species such as black spruce with natural populations of large effective size and low linkage disequilibrium, efficient marker systems that are predictive of adaptation should require the survey of large numbers of SNPs. Candidate SNP approaches like the one developed in the present study could contribute to reducing these numbers.

Distribution of long-range linkage disequilibrium and Tajima's D values in Scandinavian populations of Norway Spruce (Picea abies)

The site frequency spectrum of mutations (SFS) and linkage disequilibrium (LD) are the two major sources of information in population genetics studies. In this study we focus on the levels of LD and the SFS and on the effect of sample size on summary statistics in 10 Scandinavian populations of Norway spruce. We found that previous estimates of a low level of LD were highly influenced by both sampling strategy and the fact that data from multiple loci were analyzed jointly. Estimates of LD were in fact heterogeneous across loci and increased within individual populations compared with the estimate from the total data. The variation in levels of LD among populations most likely reflects different demographic histories, although we were unable to detect population structure by using standard approaches. As in previous studies, we also found that the SFS-based test Tajima’s D was highly sensitive to sample size, revealing that care should be taken to draw strong conclusions from this test when sample size is small. In conclusion, the results from this study are in line with recent studies in other conifers that have revealed a more complex and variable pattern of LD than earlier studies suggested and with studies in trees and humans that suggest that Tajima’s D is sensitive to sample size. This has large consequences for the design of future association and population genetic studies in Norway spruce.

Parallel and lineage-specific molecular adaptation to climate in boreal black spruce

In response to selective pressure, adaptation may follow different genetic pathways throughout the natural range of a species due to historical differentiation in standing genetic variation. Using 41 populations of black spruce (Picea mariana), the objectives of this study were to identify adaptive genetic polymorphisms related to temperature and precipitation variation across the transcontinental range of the species, and to evaluate the potential influence of historical events on their geographic distribution. Population structure was first inferred using 50 control nuclear markers. Then, 47 candidate gene SNPs identified in previous genome scans were tested for relationship with climatic factors using an F(ST) -based outlier method and regressions between allele frequencies and climatic variations. Two main intraspecific lineages related to glacial vicariance were detected at the transcontinental scale. Within-lineage analyses of allele frequencies allowed the identification of 23 candidate SNPs significantly related to precipitation and/or temperature variation, among which seven were common to both lineages, eight were specific to the eastern lineage and eight were specific to the western lineage. The implication of these candidate SNPs in adaptive processes was further supported by gene functional annotations. Multiple evidences indicated that the occurrence of lineage-specific adaptive SNPs was better explained by selection acting on historically differentiated gene pools rather than differential selection due to heterogeneity of interacting environmental factors and pleiotropic effects. Taken together, these findings suggest that standing genetic variation of potentially adaptive nature has been modified by historical events, hence affecting the outcome of recent selection and leading to different adaptive routes between intraspecific lineages.

Scanning SNPs from a large set of expressed genes to assess the impact of artificial selection on the undomesticated genetic diversity of white spruce

A scan involving 1134 single-nucleotide polymorphisms (SNPs) from 709 expressed genes was used to assess the potential impact of artificial selection for height growth on the genetic diversity of white spruce. Two case populations of different sizes simulating different family selection intensities (K = 13% and 5%, respectively) were delineated from the Quebec breeding program. Their genetic diversity and allele frequencies were compared with those of control populations of the same size and geographic origin to assess the effect of increasing the selection intensity. The two control populations were also compared to assess the effect of reducing the sampling size. On one hand, in all pairwise comparisons, genetic diversity parameters were comparable and no alleles were lost in the case populations compared with the control ones, except for few rare alleles in the large case population. Also, the distribution of allele frequencies did not change significantly (P ≤ 0.05) between the populations compared, but ten and nine SNPs (0.8%) exhibited significant differences in frequency (P ≤ 0.01) between case and control populations of large and small sizes, respectively. Results of association tests between breeding values for height at 15 years of age and these SNPs supported the hypothesis of a potential effect of selection on the genes harboring these SNPs. On the other hand, contrary to expectations, there was no evidence that selection induced an increase in linkage disequilibrium in genes potentially affected by selection. These results indicate that neither the reduction in the sampling size nor the increase in selection intensity was sufficient to induce a significant change in the genetic diversity of the selected populations. Apparently, no loci were under strong selection pressure, confirming that the genetic control of height growth in white spruce involves many genes with small effects. Hence, selection for height growth at the present intensities did not appear to compromise background genetic diversity but, as predicted by theory, effects were detected at a few gene SNPs harboring intermediate allele frequencies.

The heterogeneous levels of linkage disequilibrium in white spruce genes and comparative analysis with other conifers

In plants, knowledge about linkage disequilibrium (LD) is relevant for the design of efficient single-nucleotide polymorphism arrays in relation to their use in population and association genomics studies. Previous studies of conifer genes have shown LD to decay rapidly within gene limits, but exceptions have been reported. To evaluate the extent of heterogeneity of LD among conifer genes and its potential causes, we examined LD in 105 genes of white spruce (Picea glauca) by sequencing a panel of 48 haploid megagametophytes from natural populations and further compared it with LD in other conifer species. The average pairwise r(2) value was 0.19 (s.d.=0.19), and LD dropped quickly with a half-decay being reached at a distance of 65 nucleotides between sites. However, LD was significantly heterogeneous among genes. A first group of 29 genes had stronger LD (mean r(2)=0.28), and a second group of 38 genes had weaker LD (mean r(2)=0.12). While a strong relationship was found with the recombination rate, there was no obvious relationship between LD and functional classification. The level of nucleotide diversity, which was highly heterogeneous across genes, was also not significantly correlated with LD. A search for selection signatures highlighted significant deviations from the standard neutral model, which could be mostly attributed to recent demographic changes. Little evidence was seen for hitchhiking and clear relationships with LD. When compared among conifer species, on average, levels of LD were similar in genes from white spruce, Norway spruce and Scots pine, whereas loblolly pine and Douglas fir genes exhibited a significantly higher LD.

Impact of selection on genes involved in regulatory network: a modelling study

Complex phenotypes are often controlled by many interacting genes. One question emerging from such organization is how selection, acting at the phenotypic level, shapes the evolution of genes involved in regulatory networks controlling the phenotypes. We studied this issue through a matrix model of such networks. In a population submitted to selection, we simulated the evolution of a quantitative trait controlled by a set of loci that regulate each other through positive or negative interactions. Investigating several levels of selection intensity on the trait, we studied the evolution of regulation intensity between the genes and the evolution of the genetic diversity of those genes as an indirect measure of the strength of selection acting on them. We show that an increasing intensity of selection on the phenotype leads to an increased level of regulation between the loci. Moreover, we found that the genes responding more strongly to selection within the network were those evolving towards stronger regulatory action on the other genes and/or those that are the less regulated by the other genes. This observation is strongest for an intermediate level of selection. This may explain why several experimental studies have shown evidence of selection on regulatory genes inside gene networks.

Association genetics of wood physical traits in the conifer white spruce and relationships with gene expression

Marker-assisted selection holds promise for highly influencing tree breeding, especially for wood traits, by considerably reducing breeding cycles and increasing selection accuracy. In this study, we used a candidate gene approach to test for associations between 944 single-nucleotide polymorphism markers from 549 candidate genes and 25 wood quality traits in white spruce. A mixed-linear model approach, including a weak but nonsignificant population structure, was implemented for each marker-trait combination. Relatedness among individuals was controlled using a kinship matrix estimated either from the known half-sib structure or from the markers. Both additive and dominance effect models were tested. Between 8 and 21 single-nucleotide polymorphisms (SNPs) were found to be significantly associated (P ≤ 0.01) with each of earlywood, latewood, or total wood traits. After controlling for multiple testing (Q ≤ 0.10), 13 SNPs were still significant across as many genes belonging to different families, each accounting for between 3 and 5% of the phenotypic variance in 10 wood characters. Transcript accumulation was determined for genes containing SNPs associated with these traits. Significantly different transcript levels (P ≤ 0.05) were found among the SNP genotypes of a 1-aminocyclopropane-1-carboxylate oxidase, a β-tonoplast intrinsic protein, and a long-chain acyl-CoA synthetase 9. These results should contribute toward the development of efficient marker-assisted selection in an economically important tree species.

QTL mapping in white spruce: gene maps and genomic regions underlying adaptive traits across pedigrees, years and environments

BACKGROUND

The genomic architecture of bud phenology and height growth remains poorly known in most forest trees. In non model species, QTL studies have shown limited application because most often QTL data could not be validated from one experiment to another. The aim of our study was to overcome this limitation by basing QTL detection on the construction of genetic maps highly-enriched in gene markers, and by assessing QTLs across pedigrees, years, and environments.

RESULTS

Four saturated individual linkage maps representing two unrelated mapping populations of 260 and 500 clonally replicated progeny were assembled from 471 to 570 markers, including from 283 to 451 gene SNPs obtained using a multiplexed genotyping assay. Thence, a composite linkage map was assembled with 836 gene markers.For individual linkage maps, a total of 33 distinct quantitative trait loci (QTLs) were observed for bud flush, 52 for bud set, and 52 for height growth. For the composite map, the corresponding numbers of QTL clusters were 11, 13, and 10. About 20% of QTLs were replicated between the two mapping populations and nearly 50% revealed spatial and/or temporal stability. Three to four occurrences of overlapping QTLs between characters were noted, indicating regions with potential pleiotropic effects. Moreover, some of the genes involved in the QTLs were also underlined by recent genome scans or expression profile studies.Overall, the proportion of phenotypic variance explained by each QTL ranged from 3.0 to 16.4% for bud flush, from 2.7 to 22.2% for bud set, and from 2.5 to 10.5% for height growth. Up to 70% of the total character variance could be accounted for by QTLs for bud flush or bud set, and up to 59% for height growth.

CONCLUSIONS

This study provides a basic understanding of the genomic architecture related to bud flush, bud set, and height growth in a conifer species, and a useful indicator to compare with Angiosperms. It will serve as a basic reference to functional and association genetic studies of adaptation and growth in Picea taxa. The putative QTNs identified will be tested for associations in natural populations, with potential applications in molecular breeding and gene conservation programs. QTLs mapping consistently across years and environments could also be the most important targets for breeding, because they represent genomic regions that may be least affected by G × E interactions.

Scanning the genome for gene SNPs related to climate adaptation and estimating selection at the molecular level in boreal black spruce

Outlier detection methods were used to scan the genome of the boreal conifer black spruce (Picea mariana [Mill.] B.S.P.) for gene single-nucleotide polymorphisms (SNPs) potentially involved in adaptations to temperature and precipitation variations. The scan involved 583 SNPs from 313 genes potentially playing adaptive roles. Differentiation estimates among population groups defined following variation in temperature and precipitation were moderately high for adaptive quantitative characters such as the timing of budset or tree height (Q(ST) = 0.189-0.314). Average differentiation estimates for gene SNPs were null, with F(ST) values of 0.005 and 0.006, respectively, among temperature and precipitation population groups. Using two detection approaches, a total of 26 SNPs from 25 genes distributed among 11 of the 12 linkage groups of black spruce were detected as outliers with F(ST) as high as 0.078. Nearly half of the outlier SNPs were located in exons and half of those were nonsynonymous. The functional annotations of genes carrying outlier SNPs and regression analyses between the frequencies of these SNPs and climatic variables supported their implication in adaptive processes. Several genes carrying outlier SNPs belonged to gene families previously found to harbour outlier SNPs in a reproductively isolated but largely sympatric congeneric species, suggesting differential subfunctionalization of gene duplicates. Selection coefficient estimates (S) were moderate but well above the magnitude of drift (>>1/N(e)), indicating that the signature of natural selection could be detected at the nucleotide level despite the recent establishment of these populations during the Holocene.

Back to nature: ecological genomics of loblolly pine (Pinus taeda, Pinaceae)

Genetic variation is often arrayed in latitudinal or altitudinal clines, reflecting either adaptation along environmental gradients, migratory routes, or both. For forest trees, climate is one of the most important drivers of adaptive phenotypic traits. Correlations of single and multilocus genotypes with environmental gradients have been identified for a variety of forest trees. These correlations are interpreted normally as evidence of natural selection. Here, we use a genome-wide dataset of single nucleotide polymorphisms (SNPs) typed from 1730 loci in 682 loblolly pine (Pinus taeda L.) trees sampled from 54 local populations covering the full-range of the species to examine allelic correlations to five multivariate measures of climate. Applications of a Bayesian generalized linear mixed model, where the climate variable was a fixed effect and an estimated variance-covariance matrix controlled random effects due to shared population history, identified several well-supported SNPs associating to principal components corresponding to geography, temperature, growing degree-days, precipitation and aridity. Functional annotation of those genes with putative orthologs in Arabidopsis revealed a diverse set of abiotic stress response genes ranging from transmembrane proteins to proteins involved in sugar metabolism. Many of these SNPs also had large allele frequency differences among populations (F(ST) = 0.10-0.35). These results illustrate a first step towards a ecosystem perspective of population genomics for non-model organisms, but also highlight the need for further integration of the methodologies employed in spatial statistics, population genetics and climate modeling during scans for signatures of natural selection from genomic data.