Association genetics of carbon isotope discrimination, height and foliar nitrogen in a natural population of Pinus taeda L

Genome-wide association analysis reveal candidate genes and haplotypes related to root weight in cucumber (Cucumis sativus L.)

Background

The plant root system is critical for the absorption of water and nutrients, and have a direct influence on growth and yield. In cucumber, a globally consumed crop, the molecular mechanism of root development remains unclear, and this has implications for developing stress tolerant varieties. This study sought to determine the genetic patterns and related genes of cucumber root weight. A core cucumber germplasms population was used to do the GWAS analysis in three environments.

Results

Here, we investigated four root-weight related traits including root fresh weight (RFW), root dry weight (RDW), ratio of root dry weight to root fresh weight (RDFW) and the comprehensive evaluation index, D-value of root weight (DRW) deduced based on the above three traits for the core germplasm of the cucumber global repository. According to the D-value, we identified 21 and 16 accessions with light and heavy-root, respectively. We also found that the East Asian ecotype accessions had significantly heavier root than other three ecotypes. The genome-wide association study (GWAS) for these four traits reveals that 4 of 10 significant loci (gDRW3.1, gDRW3.2, gDRW4.1 and gDRW5.1) were repeatedly detected for at least two traits. Further haplotype and expression analysis for protein-coding genes positioned within these 4 loci between light and heavy-root accessions predicted five candidate genes (i.e., Csa3G132020 and Csa3G132520 both encoding F-box protein PP2-B1 for gDRW3.1, Csa3G629240 encoding a B-cell receptor-associated protein for gDRW3.2, Csa4G499330 encodes a GTP binding protein for gDRW4.1, and Csa5G286040 encodes a proteinase inhibitor for gDRW5.1).

Conclusions

We conducted a systematic analysis of the root genetic basis and characteristics of cucumber core germplasms population. We detected four novel loci, which regulate the root weight in cucumber. Our study provides valuable candidate genes and haplotypes for the improvement of root system in cucumber breeding.

Multiple-trait analyses improved the accuracy of genomic prediction and the power of genome-wide association of productivity and climate change-adaptive traits in lodgepole pine

Background

Genomic prediction (GP) and genome-wide association (GWA) analyses are currently being employed to accelerate breeding cycles and to identify alleles or genomic regions of complex traits in forest trees species. Here, 1490 interior lodgepole pine (Pinus contorta Dougl. ex. Loud. var. latifolia Engelm) trees from four open-pollinated progeny trials were genotyped with 25,099 SNPs, and phenotyped for 15 growth, wood quality, pest resistance, drought tolerance, and defense chemical (monoterpenes) traits. The main objectives of this study were to: (1) identify genetic markers associated with these traits and determine their genetic architecture, and to compare the marker detected by single- (ST) and multiple-trait (MT) GWA models; (2) evaluate and compare the accuracy and control of bias of the genomic predictions for these traits underlying different ST and MT parametric and non-parametric GP methods. GWA, ST and MT analyses were compared using a linear transformation of genomic breeding values from the respective genomic best linear unbiased prediction (GBLUP) model. GP, ST and MT parametric and non-parametric (Reproducing Kernel Hilbert Spaces, RKHS) models were compared in terms of prediction accuracy (PA) and control of bias.

Results

MT-GWA analyses identified more significant associations than ST. Some SNPs showed potential pleiotropic effects. Averaging across traits, PA from the studied ST-GP models did not differ significantly from each other, with generally a slight superiority of the RKHS method. MT-GP models showed significantly higher PA (and lower bias) than the ST models, being generally the PA (bias) of the RKHS approach significantly higher (lower) than the GBLUP.

Conclusions

The power of GWA and the accuracy of GP were improved when MT models were used in this lodgepole pine population. Given the number of GP and GWA models fitted and the traits assessed across four progeny trials, this work has produced the most comprehensive empirical genomic study across any lodgepole pine population to date.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08747-7.

Genetic Variation in Drought-Tolerance Traits and Their Relationships to Growth in Pinus radiata D. Don Under Water Stress

The selection of drought-tolerant genotypes is globally recognized as an effective strategy to maintain the growth and survival of commercial tree species exposed to future drought periods. New genomic selection tools that reduce the time of progeny trials are required to substitute traditional tree breeding programs. We investigated the genetic variation of water stress tolerance in New Zealand-grown Pinus radiata D. Don using 622 commercially-used genotypes from 63 families. We used quantitative pedigree-based (Genomic Best Linear Unbiased Prediction or ABLUP) and genomic-based (Genomic Best Linear Unbiased Prediction or GBLUP) approaches to examine the heritability estimates associated with water stress tolerance in P. radiata. Tree seedling growth traits, foliar carbon isotope composition (δ13C), and dark-adapted chlorophyll fluorescence (Y) were monitored before, during and after 10 months of water stress. Height growth showed a constant and moderate heritability level, while the heritability estimate for diameter growth and δ13C decreased with water stress. In contrast, chlorophyll fluorescence exhibited low heritability after 5 and 10 months of water stress. The GBLUP approach provided less breeding value accuracy than ABLUP, however, the relative selection efficiency of GBLUP was greater compared with ABLUP selection techniques. Although there was no significant relationship directly between δ13C and Y, the genetic correlations were significant and stronger for GBLUP. The positive genetic correlations between δ13C and tree biomass traits under water stress indicated that intraspecific variation in δ13C was likely driven by differences in the genotype's photosynthetic capacity. The results show that foliar δ13C can predict P. radiata genotype tolerance to water stress using ABLUP and GBLUP approaches and that such approaches can provide a faster screening and selection of drought-tolerant genotypes for forestry breeding programs.

Genome-wide association identifies candidate genes for drought tolerance in coast redwood and giant sequoia

Drought is a major limitation for survival and growth in plants. With more frequent and severe drought episodes occurring due to climate change, it is imperative to understand the genomic and physiological basis of drought tolerance to be able to predict how species will respond in the future. In this study, univariate and multitrait multivariate genome-wide association study methods were used to identify candidate genes in two iconic and ecosystem-dominating species of the western USA, coast redwood and giant sequoia, using 10 drought-related physiological and anatomical traits and genome-wide sequence-capture single nucleotide polymorphisms. Population-level phenotypic variation was found in carbon isotope discrimination, osmotic pressure at full turgor, xylem hydraulic diameter, and total area of transporting fibers in both species. Our study identified new 78 new marker × trait associations in coast redwood and six in giant sequoia, with genes involved in a range of metabolic, stress, and signaling pathways, among other functions. This study contributes to a better understanding of the genomic basis of drought tolerance in long-generation conifers and helps guide current and future conservation efforts in the species.

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.

Gene Frequency Shift in Relict Abies pinsapo Forests Associated with Drought-Induced Mortality: Preliminary Evidence of Local-Scale Divergent Selection

Current climate change constitutes a challenge for the survival of several drought-sensitive forests. The study of the genetic basis of adaptation offers a suitable way to understand how tree species may respond to future climatic conditions, as well as to design suitable conservation and management strategies. Here, we focus on selected genetic signatures of the drought-sensitive relict fir, Abies pinsapo Boiss. Field sampling of 156 individuals was performed in two elevation ecotones, characterized by widespread A. pinsapo decline and mortality. The DNA from dead trees was investigated and compared to living individuals, accounting for different ages and elevations. We studied the genes gated outwardly-rectifying K+ (GORK) channel and Plasma membrane Intrinsic Protein (PIP1) aquaporin, previously related to drought response in plant model species, to test whether drought was the main abiotic factor driving the decline of A. pinsapo forests. A combination of linear regression and factor models were used to test these selection signatures, as well as a fixation index (Fst), used here to analyze the genetic structure. The results were consistent among these approaches, supporting a statistically significant association of the GORK gene with survival in one of the A. pinsapo populations. These results provide preliminary evidence for the potential role of the GORK gene in the resilience to drought of A. pinsapo.

Toward genomic selection in Pinus taeda: Integrating resources to support array design in a complex conifer genome

PREMISE

An informatics approach was used for the construction of an Axiom genotyping array from heterogeneous, high-throughput sequence data to assess the complex genome of loblolly pine (Pinus taeda).

METHODS

High-throughput sequence data, sourced from exome capture and whole genome reduced-representation approaches from 2698 trees across five sequence populations, were analyzed with the improved genome assembly and annotation for the loblolly pine. A variant detection, filtering, and probe design pipeline was developed to detect true variants across and within populations. From 8.27 million variants, a total of 642,275 were evaluated and 423,695 of those were screened across a range-wide population.

RESULTS

The final informatics and screening approach delivered an Axiom array representing 46,439 high-confidence variants to the forest tree breeding and genetics community. Based on the annotated reference genome, 34% were located in or directly upstream or downstream of genic regions.

DISCUSSION

The Pita50K array represents a genome-wide resource developed from sequence data for an economically important conifer, loblolly pine. It uniquely integrates independent projects that assessed trees sampled across the native range. The challenges associated with the large and repetitive genome are addressed in the development of this resource.

Extensive Variation in Drought-Induced Gene Expression Changes Between Loblolly Pine Genotypes

Drought response is coordinated through expression changes in a large suite of genes. Interspecific variation in this response is common and associated with drought-tolerant and -sensitive genotypes. The extent to which different genetic networks orchestrate the adjustments to water deficit in tolerant and sensitive genotypes has not been fully elucidated, particularly in non-model or woody plants. Differential expression analysis via RNA-seq was evaluated in root tissue exposed to simulated drought conditions in two loblolly pine (Pinus taeda L.) clones with contrasting tolerance to drought. Loblolly pine is the prevalent conifer in southeastern U.S. and a major commercial forestry species worldwide. Significant changes in gene expression levels were found in more than 4,000 transcripts [drought-related transcripts (DRTs)]. Genotype by environment (GxE) interactions were prevalent, suggesting that different cohorts of genes are influenced by drought conditions in the tolerant vs. sensitive genotypes. Functional annotation categories and metabolic pathways associated with DRTs showed higher levels of overlap between clones, with the notable exception of GO categories in upregulated DRTs. Conversely, both differentially expressed transcription factors (TFs) and TF families were largely different between clones. Our results indicate that the response of a drought-tolerant loblolly pine genotype vs. a sensitive genotype to water limitation is remarkably different on a gene-by-gene level, although it involves similar genetic networks. Upregulated transcripts under drought conditions represent the most diverging component between genotypes, which might depend on the activation and repression of substantially different groups of TFs.

Comparative Study of Pine Reference Genomes Reveals Transposable Element Interconnected Gene Networks

Sequencing the giga-genomes of several pine species has enabled comparative genomic analyses of these outcrossing tree species. Previous studies have revealed the wide distribution and extraordinary diversity of transposable elements (TEs) that occupy the large intergenic spaces in conifer genomes. In this study, we analyzed the distribution of TEs in gene regions of the assembled genomes of Pinus taeda and Pinus lambertiana using high-performance computing resources. The quality of draft genomes and the genome annotation have significant consequences for the investigation of TEs and these aspects are discussed. Several TE families frequently inserted into genes or their flanks were identified in both species’ genomes. Potentially important sequence motifs were identified in TEs that could bind additional regulatory factors, promoting gene network formation with faster or enhanced transcription initiation. Node genes that contain many TEs were observed in multiple potential transposable element-associated networks. This study demonstrated the increased accumulation of TEs in the introns of stress-responsive genes of pines and suggests the possibility of rewiring them into responsive networks and sub-networks interconnected with node genes containing multiple TEs. Many such regulatory influences could lead to the adaptive environmental response clines that are characteristic of naturally spread pine populations.

Predicting Adaptive Genetic Variation of Loblolly Pine (Pinus taeda L.) Populations Under Projected Future Climates Based on Multivariate Models

Greenhouse gas emission and global warming are likely to cause rapid climate change within the natural range of loblolly pine over the next few decades, thus bringing uncertainty to their adaptation to the environment. Here, we studied adaptive genetic variation of loblolly pine and correlated genetic variation with bioclimatic variables using multivariate modeling methods—Redundancy Analysis, Generalized Dissimilarity Modeling, and Gradient Forests. Studied trees (N = 299) were originally sampled from their native range across eight states on the east side of the Mississippi River. Genetic variation was calculated using a total of 44,317 single-nucleotide polymorphisms acquired by exome target sequencing. The fitted models were used to predict the adaptive genetic variation on a large spatial and temporal scale. We observed east-to-west spatial genetic variation across the range, which presented evidence of isolation by distance. Different key factors drive adaptation of loblolly pine from different geographical regions. Trees residing near the northeastern edge of the range, spanning across Delaware and Maryland and mountainous areas of  Virginia, North Carolina, South Carolina, and northern Georgia, were identified to be most likely impacted by climate change based on the large difference in genetic composition under current and future climate conditions. This study provides new perspectives on adaptive genetic variation of loblolly pine in response to different climate scenarios, and the results can be used to target particular populations while developing adaptive forest management guidelines.

Detecting the genetic basis of local adaptation in loblolly pine (Pinus taeda L.) using whole exome-wide genotyping and an integrative landscape genomics analysis approach

In the Southern United States, the widely distributed loblolly pine contributes greatly to lumber and pulp production, as well as providing many important ecosystem services. Climate change may affect the productivity and range of loblolly pine. Nevertheless, we have insufficient knowledge of the adaptive potential and the genetics underlying the adaptability of loblolly pine. To address this, we tested the association of 2.8 million whole exome-based single nucleotide polymorphisms (SNPs) with climate and geographic variables, including temperature, precipitation, latitude, longitude, and elevation data. Using an integrative landscape genomics approach by combining multiple environmental association and outlier detection analyses, we identified 611 SNPs associated with 56 climate and geographic variables. Longitude, maximum temperature of the warm months and monthly precipitation associated with most SNPs, indicating their importance and complexity in shaping the genetic variation in loblolly pine. Functions of candidate genes related to terpenoid synthesis, pathogen defense, transcription factors, and abiotic stress response. We provided evidence that environment-associated SNPs also composed the genetic structure of adaptive phenotypic traits including height, diameter, metabolite levels, and gene transcript abundance. Our study promotes understanding of the genetic basis of local adaptation in loblolly pine and provides promising tools for selecting genotypes adapted to local environments in a changing climate.

The Resistance of Scots Pine (Pinus sylvestris L.) Half-sib Families to Heterobasidion annosum

This study observed the genotypic variation among Scots pine (Pinus sylvestris L.) half-sib families’ susceptibility to Heterobasidion annosum. Scots pine susceptibility was tested in 12 half-sib families by inoculating them with four different H. annosum strains. At two, six, and ten months after the inoculations, the susceptibility indicators (incidence rate, pathogen spread, and mortality rate) were compared and the total phenolic compounds (TPC) in the inoculated and control groups determined using the Folin–Ciocalteu method. Among half-sib families, significant differences were found for seedling mortality (range: 1.3%–21.2%); however, the differences in incidence rate (range: 54%–77%) and pathogen spread (range: 24–53 mm) were not significant. The incidence rate among half-sib families correlated positively and significantly (r = 0.72, p < 0.05) with the mortality rate, while the pathogen spread correlated negatively with mortality, although the correlation was not significant (r = −0.29, p > 0.05). The TPC comparison with susceptibility indicators showed that the half-sib families with lower susceptibility were characterized by the ability to increase TPC after inoculation compared to the control group. This tendency was most apparent in stems and roots six and two months after inoculation, respectively. Correlation analyses revealed that higher TPC in stems six months after inoculation determined a lower incidence rate (r = −0.32, p < 0.05), while higher Change in concentration of total phenolic compounds (TPCΔ) indicated a lower pathogen spread (r = −0.60, p < 0.05). The lowest incidence of the pathogen was determined in half-sib families with the highest TPCΔ in the roots two months after inoculation. The lower susceptibility of Scots pine half-sib families is based on a combination of enhanced constitutive and inducible phenolic defense mechanisms. The data may facilitate the selection of Scots pine half-sib families with low susceptibility for breeding programs and forest management strategies.

Genomic architecture of complex traits in loblolly pine

Dissecting the genetic and genomic architecture of complex traits is essential to understand the forces maintaining the variation in phenotypic traits of ecological and economical importance. Whole-genome resequencing data were used to generate high-resolution polymorphic single nucleotide polymorphism (SNP) markers and genotype individuals from common gardens across the loblolly pine (Pinus taeda) natural range. Genome-wide associations were tested with a large phenotypic dataset comprising 409 variables including morphological traits (height, diameter, carbon isotope discrimination, pitch canker resistance), and molecular traits such as metabolites and expression of xylem development genes. Our study identified 2335 new SNP × trait associations for the species, with many SNPs located in physical clusters in the genome of the species; and the genomic location of hotspots for metabolic × genotype associations. We found a highly polygenic basis of quantitative inheritance, with significant differences in number, effects size, genomic location and frequency of alleles contributing to variation in phenotypes in the different traits. While mutation-selection balance might be shaping the genetic variation in metabolic traits, balancing selection is more likely to shape the variation in expression of xylem development genes. Our work contributes to the study of complex traits in nonmodel plant species by identifying associations at a whole-genome level.

Quantitative Genetics and Genomics Converge to Accelerate Forest Tree Breeding

Forest tree breeding has been successful at delivering genetically improved material for multiple traits based on recurrent cycles of selection, mating, and testing. However, long breeding cycles, late flowering, variable juvenile-mature correlations, emerging pests and diseases, climate, and market changes, all pose formidable challenges. Genetic dissection approaches such as quantitative trait mapping and association genetics have been fruitless to effectively drive operational marker-assisted selection (MAS) in forest trees, largely because of the complex multifactorial inheritance of most, if not all traits of interest. The convergence of high-throughput genomics and quantitative genetics has established two new paradigms that are changing contemporary tree breeding dogmas. Genomic selection (GS) uses large number of genome-wide markers to predict complex phenotypes. It has the potential to accelerate breeding cycles, increase selection intensity and improve the accuracy of breeding values. Realized genomic relationships matrices, on the other hand, provide innovations in genetic parameters' estimation and breeding approaches by tracking the variation arising from random Mendelian segregation in pedigrees. In light of a recent flow of promising experimental results, here we briefly review the main concepts, analytical tools and remaining challenges that currently underlie the application of genomics data to tree breeding. With easy and cost-effective genotyping, we are now at the brink of extensive adoption of GS in tree breeding. Areas for future GS research include optimizing strategies for updating prediction models, adding validated functional genomics data to improve prediction accuracy, and integrating genomic and multi-environment data for forecasting the performance of genetic material in untested sites or under changing climate scenarios. The buildup of phenotypic and genome-wide data across large-scale breeding populations and advances in computational prediction of discrete genomic features should also provide opportunities to enhance the application of genomics to tree breeding.

Exploring the genetic basis of gene transcript abundance and metabolite levels in loblolly pine (Pinus taeda L.) using association mapping and network construction

BACKGROUND

Identifying genetic variations that shape important complex traits is fundamental to the genetic improvement of important forest tree species, such as loblolly pine (Pinus taeda L.), which is one of the most commonly planted forest tree species in the southern U.S. Gene transcripts and metabolites are important regulatory intermediates that link genetic variations to higher-order complex traits such as wood development and drought response. A few prior studies have associated intermediate phenotypes including mRNA expression and metabolite levels with a limited number of molecular markers, but the identification of genetic variations that regulate intermediate phenotypes needs further investigation.

RESULTS

We identified 1841 single nucleotide polymorphisms (SNPs) associated with 191 gene expression mRNA phenotypes and 524 SNPs associated with 53 metabolite level phenotypes using 2.8 million exome-derived SNPs. The identified SNPs reside in genes with a wide variety of functions. We further integrated the identified SNPs and the associated expressed genes and metabolites into networks. We described the SNP-SNP interactions that significantly impacted the gene transcript abundance and metabolite level in the networks. Key loci and genes in the wood development and drought response networks were identified and analyzed.

CONCLUSIONS

This work provides new candidate genes for research on the genetic basis of gene expression and metabolism linked to wood development and drought response in loblolly pine and highlights the efficiency of using association-mapping-based networks to discover candidate genes with important roles in complex biological processes.

The genetics of drought tolerance in conifers

Contents 1034 I. 1034 II. 1035 III. 1037 IV. 1038 V. 1042 VI. 1043 VII. 1045 References 1045 SUMMARY: As temperatures warm and precipitation patterns shift as a result of climate change, interest in the identification of tree genotypes that will thrive under more arid conditions has grown. In this review, we discuss the multiple definitions of 'drought tolerance' and the biological processes involved in drought responses. We describe the three major approaches taken in the study of genetic variation in drought responses, the advantages and shortcomings of each, and what each of these approaches has revealed about the genetic basis of adaptation to drought in conifers. Finally, we discuss how a greater knowledge of the genetics of drought tolerance may aid forest management, and provide recommendations for how future studies may overcome the limitations of past approaches. In particular, we urge a more direct focus on survival, growth and the traits that directly predict them (rather than on proxies, such as water use efficiency), combining research approaches with complementary strengths and weaknesses, and the inclusion of a wider range of taxa and life stages.

Association genetics of phenolic needle compounds in Norway spruce with variable susceptibility to needle bladder rust

KEY MESSAGE

Accumulation of phenolic needle metabolites in Norway spruce is regulated by many genes with small and additive effects and is correlated with the susceptibility against fungal attack. Norway spruce accumulates high foliar concentrations of secondary phenolic metabolites, with important functions for pathogen defence responses. However, the molecular genetic basis underlying the quantitative variation of phenolic compounds and their role in enhanced resistance of spruce to infection by needle bladder rust are unknown. To address these questions, a set of 1035 genome-wide single nucleotide polymorphisms (SNPs) was associated to the quantitative variation of four simple phenylpropanoids, eight stilbenes, nine flavonoids, six related arithmetic parameters and the susceptibility to infection by Chrysomyxa rhododendri in an unstructured natural population of Norway spruce. Thirty-one significant genetic associations for the flavonoids gallocatechin, kaempferol 3-glucoside and quercetin 3-glucoside and the stilbenes resveratrol, piceatannol, astringin and isorhapontin were discovered, explaining 22-59% of phenotypic variation, and indicating a regulation of phenolic accumulation by many genes with small and additive effects. The phenolics profile differed between trees with high and low susceptibility to the fungus, underlining the importance of phenolic compounds in the defence mechanisms of Norway spruce to C. rhododendri. Results highlight the utility of association studies in non-model tree species and may enable marker-assisted selection of Norway spruce adapted to severe pathogen attack.

Linkage and Association Mapping for Two Major Traits Used in the Maritime Pine Breeding Program: Height Growth and Stem Straightness

Background

Increasing our understanding of the genetic architecture of complex traits, through analyses of genotype-phenotype associations and of the genes/polymorphisms accounting for trait variation, is crucial, to improve the integration of molecular markers into forest tree breeding. In this study, two full-sib families and one breeding population of maritime pine were used to identify quantitative trait loci (QTLs) for height growth and stem straightness, through linkage analysis (LA) and linkage disequilibrium (LD) mapping approaches.

Results

The populations used for LA consisted of two unrelated three-generation full-sib families (n = 197 and n = 477). These populations were assessed for height growth or stem straightness and genotyped for 248 and 217 markers, respectively. The population used for LD mapping consisted of 661 founders of the first and second generations of the breeding program. This population was phenotyped for the same traits and genotyped for 2,498 single-nucleotide polymorphism (SNP) markers corresponding to 1,652 gene loci. The gene-based reference genetic map of maritime pine was used to localize and compare the QTLs detected by the two approaches, for both traits. LA identified three QTLs for stem straightness and two QTLs for height growth. The LD study yielded seven significant associations (P ≤ 0.001): four for stem straightness and three for height growth. No colocalisation was found between QTLs identified by LA and SNPs detected by LD mapping for the same trait.

Conclusions

This study provides the first comparison of LA and LD mapping approaches in maritime pine, highlighting the complementary nature of these two approaches for deciphering the genetic architecture of two mandatory traits of the breeding program.

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.

Genetic architecture of wood properties based on association analysis and co-expression networks in white spruce

Association studies are widely utilized to analyze complex traits but their ability to disclose genetic architectures is often limited by statistical constraints, and functional insights are usually minimal in nonmodel organisms like forest trees. We developed an approach to integrate association mapping results with co-expression networks. We tested single nucleotide polymorphisms (SNPs) in 2652 candidate genes for statistical associations with wood density, stiffness, microfibril angle and ring width in a population of 1694 white spruce trees (Picea glauca). Associations mapping identified 229-292 genes per wood trait using a statistical significance level of P < 0.05 to maximize discovery. Over-representation of genes associated for nearly all traits was found in a xylem preferential co-expression group developed in independent experiments. A xylem co-expression network was reconstructed with 180 wood associated genes and several known MYB and NAC regulators were identified as network hubs. The network revealed a link between the gene PgNAC8, wood stiffness and microfibril angle, as well as considerable within-season variation for both genetic control of wood traits and gene expression. Trait associations were distributed throughout the network suggesting complex interactions and pleiotropic effects. Our findings indicate that integration of association mapping and co-expression networks enhances our understanding of complex wood traits.

A Consensus Genetic Map for Pinus taeda and Pinus elliottii and Extent of Linkage Disequilibrium in Two Genotype-Phenotype Discovery Populations of Pinus taeda

A consensus genetic map for Pinus taeda (loblolly pine) and Pinus elliottii (slash pine) was constructed by merging three previously published P. taeda maps with a map from a pseudo-backcross between P. elliottii and P. taeda. The consensus map positioned 3856 markers via genotyping of 1251 individuals from four pedigrees. It is the densest linkage map for a conifer to date. Average marker spacing was 0.6 cM and total map length was 2305 cM. Functional predictions of mapped genes were improved by aligning expressed sequence tags used for marker discovery to full-length P. taeda transcripts. Alignments to the P. taeda genome mapped 3305 scaffold sequences onto 12 linkage groups. The consensus genetic map was used to compare the genome-wide linkage disequilibrium in a population of distantly related P. taeda individuals (ADEPT2) used for association genetic studies and a multiple-family pedigree used for genomic selection (CCLONES). The prevalence and extent of LD was greater in CCLONES as compared to ADEPT2; however, extended LD with LGs or between LGs was rare in both populations. The average squared correlations, r², between SNP alleles less than 1 cM apart were less than 0.05 in both populations and r² did not decay substantially with genetic distance. The consensus map and analysis of linkage disequilibrium establish a foundation for comparative association mapping and genomic selection in P. taeda and P. elliottii.

Genetic architecture of carbon isotope composition and growth in Eucalyptus across multiple environments

In the context of climate change, the water-use efficiency (WUE) of highly productive tree varieties, such as eucalypts, has become a major issue for breeding programmes. This study set out to dissect the genetic architecture of carbon isotope composition (δ(13) C), a proxy of WUE, across several environments. A family of Eucalyptus urophylla × E. grandis was planted in three trials and phenotyped for δ(13) C and growth traits. High-resolution genetic maps enabled us to target genomic regions underlying δ(13) C quantitative trait loci (QTLs) on the E. grandis genome. Of the 15 QTLs identified for δ(13) C, nine were stable across the environments and three displayed significant QTL-by-environment interaction, suggesting medium to high genetic determinism for this trait. Only one colocalization was found between growth and δ(13) C. Gene ontology (GO) term enrichment analysis suggested candidate genes related to foliar δ(13) C, including two involved in the regulation of stomatal movements. This study provides the first report of the genetic architecture of δ(13) C and its relation to growth in Eucalyptus. The low correlations found between the two traits at phenotypic and genetic levels suggest the possibility of improving the WUE of Eucalyptus varieties without having an impact on breeding for growth.

Genome-wide association implicates numerous genes underlying ecological trait variation in natural populations of Populus trichocarpa

In order to uncover the genetic basis of phenotypic trait variation, we used 448 unrelated wild accessions of black cottonwood (Populus trichocarpa) from much of its range in western North America. Extensive data from large-scale trait phenotyping (with spatial and temporal replications within a common garden) and genotyping (with a 34 K Populus single nucleotide polymorphism (SNP) array) of all accessions were used for gene discovery in a genome-wide association study (GWAS). We performed GWAS with 40 biomass, ecophysiology and phenology traits and 29,355 filtered SNPs representing 3518 genes. The association analyses were carried out using a Unified Mixed Model accounting for population structure effects among accessions. We uncovered 410 significant SNPs using a Bonferroni-corrected threshold (P<1.7×10(-6)). Markers were found across 19 chromosomes, explained 1-13% of trait variation, and implicated 275 unique genes in trait associations. Phenology had the largest number of associated genes (240 genes), followed by biomass (53 genes) and ecophysiology traits (25 genes). The GWAS results propose numerous loci for further investigation. Many traits had significant associations with multiple genes, underscoring their genetic complexity. Genes were also identified with multiple trait associations within and/or across trait categories. In some cases, traits were genetically correlated while in others they were not.

In situ genetic association for serotiny, a fire-related trait, in Mediterranean maritime pine (Pinus pinaster)

Wildfire is a major ecological driver of plant evolution. Understanding the genetic basis of plant adaptation to wildfire is crucial, because impending climate change will involve fire regime changes worldwide. We studied the molecular genetic basis of serotiny, a fire-related trait, in Mediterranean maritime pine using association genetics. A single nucleotide polymorphism (SNP) set was used to identify genotype : phenotype associations in situ in an unstructured natural population of maritime pine (eastern Iberian Peninsula) under a mixed-effects model framework. RR-BLUP was used to build predictive models for serotiny in this region. Model prediction power outside the focal region was tested using independent range-wide serotiny data. Seventeen SNPs were potentially associated with serotiny, explaining approximately 29% of the trait phenotypic variation in the eastern Iberian Peninsula. Similar prediction power was found for nearby geographical regions from the same maternal lineage, but not for other genetic lineages. Association genetics for ecologically relevant traits evaluated in situ is an attractive approach for forest trees provided that traits are under strong genetic control and populations are unstructured, with large phenotypic variability. This will help to extend the research focus to ecological keystone non-model species in their natural environments, where polymorphisms acquired their adaptive value.

Impacts of population structure and analytical models in genome-wide association studies of complex traits in forest trees: a case study in Eucalyptus globulus

The promise of association genetics to identify genes or genomic regions controlling complex traits has generated a flurry of interest. Such phenotype-genotype associations could be useful to accelerate tree breeding cycles, increase precision and selection intensity for late expressing, low heritability traits. However, the prospects of association genetics in highly heterozygous undomesticated forest trees can be severely impacted by the presence of cryptic population and pedigree structure. To investigate how to better account for this, we compared the GLM and five combinations of the Unified Mixed Model (UMM) on data of a low-density genome-wide association study for growth and wood property traits carried out in a Eucalyptus globulus population (n = 303) with 7,680 Diversity Array Technology (DArT) markers. Model comparisons were based on the degree of deviation from the uniform distribution and estimates of the mean square differences between the observed and expected p-values of all significant marker-trait associations detected. Our analysis revealed the presence of population and family structure. There was not a single best model for all traits. Striking differences in detection power and accuracy were observed among the different models especially when population structure was not accounted for. The UMM method was the best and produced superior results when compared to GLM for all traits. Following stringent correction for false discoveries, 18 marker-trait associations were detected, 16 for tree diameter growth and two for lignin monomer composition (S∶G ratio), a key wood property trait. The two DArT markers associated with S∶G ratio on chromosome 10, physically map within 1 Mbp of the ferulate 5-hydroxylase (F5H) gene, providing a putative independent validation of this marker-trait association. This study details the merit of collectively integrate population structure and relatedness in association analyses in undomesticated, highly heterozygous forest trees, and provides additional insights into the nature of complex quantitative traits in Eucalyptus.

Demonstration of genome-wide association studies for identifying markers for wood property and male strobili traits in Cryptomeria japonica

Genome-wide association studies (GWAS) are an alternative to bi-parental QTL mapping in long-lived perennials. In the present study, we examined the potential of GWAS in conifers using 367 unrelated plus trees of Cryptomeria japonica D. Don, which is the most widely planted and commercially important tree species in Japan, and tried to detect significant associations between wood property traits and quantity of male strobili on the one hand, and 1,032 single nucleotide polymorphisms (SNPs) assigned to 1,032 genes on the other. Association analysis was performed with the mixed linear model taking into account kinship relationships and subpopulation structure. In total, 6 SNPs were found to have significant associations with the variations in phenotype. These SNPs were not associated with the positions of known genes and QTLs that have been reported to date, thus they may identify novel QTLs. These 6 SNPs were all found in sequences showing similarities with known genes, although further analysis is required to dissect the ways in which they affect wood property traits and abundance of male strobili. These presumptive QTL loci provide opportunities for improvement of C. japonica, based on a marker approach. The results suggest that GWAS has potential for use in future breeding programs in C. japonica.

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.

Association of loblolly pine xylem development gene expression with single-nucleotide polymorphisms

Variation in the expression of genes with putative roles in wood development was associated with single-nucleotide polymorphisms (SNPs) using a population of loblolly pine (Pinus taeda L.) that included individuals from much of the native range. Association studies were performed using 3938 SNPs and expression data obtained using quantitative real-time polymerase chain reaction (PCR) (qRT-PCR) for 106 xylem development genes in 400 clonally replicated loblolly pine individuals. A general linear model (GLM) approach, which takes the underlying population structure into consideration, was used to discover significant associations. After adjustment for multiple testing using a false discovery rate correction, 88 statistically significant associations (Q<0.05) were observed for 80 SNPs with the expression data of 33 xylem development genes. Thirty SNPs caused nonsynonymous mutations, 18 resulted in synonymous mutations, 11 were in 3' untranslated regions (UTRs), 1 was in a 5' UTR and 20 were in introns. Using AraNet, we found that Arabidopsis genes with high similarity to the loblolly pine genes involved in 21 of the 88 statistically significant associations are connected in functional gene networks. Comparisons of gene expression values revealed that in most cases the average expression in plants homozygous for the rare SNP allele was lower than that of plants that were heterozygous or homozygous for the abundant allele. Although there are association studies of SNPs and expression profiles for humans, Arabidopsis and white spruce, to the best of our knowledge, this is the first example of such an association genetic study in pines. Functional validation of these associations will lead to a deeper understanding of the molecular basis of phenotypic differences in wood development among individuals in conifer populations.

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.

Potential for evolutionary responses to climate change - evidence from tree populations

Evolutionary responses are required for tree populations to be able to track climate change. Results of 250 years of common garden experiments show that most forest trees have evolved local adaptation, as evidenced by the adaptive differentiation of populations in quantitative traits, reflecting environmental conditions of population origins. On the basis of the patterns of quantitative variation for 19 adaptation-related traits studied in 59 tree species (mostly temperate and boreal species from the Northern hemisphere), we found that genetic differentiation between populations and clinal variation along environmental gradients were very common (respectively, 90% and 78% of cases). Thus, responding to climate change will likely require that the quantitative traits of populations again match their environments. We examine what kind of information is needed for evaluating the potential to respond, and what information is already available. We review the genetic models related to selection responses, and what is known currently about the genetic basis of the traits. We address special problems to be found at the range margins, and highlight the need for more modeling to understand specific issues at southern and northern margins. We need new common garden experiments for less known species. For extensively studied species, new experiments are needed outside the current ranges. Improving genomic information will allow better prediction of responses. Competitive and other interactions within species and interactions between species deserve more consideration. Despite the long generation times, the strong background in quantitative genetics and growing genomic resources make forest trees useful species for climate change research. The greatest adaptive response is expected when populations are large, have high genetic variability, selection is strong, and there is ecological opportunity for establishment of better adapted genotypes.

Association genetics of chemical wood properties in black poplar (Populus nigra)

Black poplar (Populus nigra) is a potential feedstock for cellulosic ethanol production, although breeding for this specific end use is required. Our goal was to identify associations between single nucleotide polymorphism (SNP) markers within candidate genes encoding cellulose and lignin biosynthetic enzymes, with chemical wood property phenotypic traits, toward the aim of developing genomics-based breeding technologies for bioethanol production. Pyrolysis molecular beam mass spectrometry was used to determine contents of five- and six-carbon sugars, lignin, and syringyl : guaiacyl ratio. The association population included 599 clones from 17 half-sib families, which were successfully genotyped using 433 SNPs from 39 candidate genes. Statistical analyses were performed to estimate genetic parameters, linkage disequilibrium (LD), and single marker and haplotype-based associations. A moderate to high heritability was observed for all traits. The LD, across all candidate genes, showed a rapid decay with physical distance. Analysis of single marker-phenotype associations identified six significant marker-trait pairs, whereas nearly 280 haplotypes were associated with phenotypic traits, in both an individual and multiple trait-specific manner. The rapid decay of LD within candidate genes in this population and the genetic associations identified suggest a close relationship between the associated SNPs and the causative polymorphisms underlying the genetic variation of lignocellulosic traits in black poplar.

A novel stress-induced sugarcane gene confers tolerance to drought, salt and oxidative stress in transgenic tobacco plants

BACKGROUND

Drought is a major abiotic stress that affects crop productivity worldwide. Sugarcane can withstand periods of water scarcity during the final stage of culm maturation, during which sucrose accumulation occurs. Meanwhile, prolonged periods of drought can cause severe plant losses.

METHODOLOGY/PRINCIPAL FINDINGS

In a previous study, we evaluated the transcriptome of drought-stressed plants to better understand sugarcane responses to drought. Among the up-regulated genes was Scdr1 (sugarcane drought-responsive 1). The aim of the research reported here was to characterize this gene. Scdr1 encodes a putative protein containing 248 amino acids with a large number of proline (19%) and cysteine (13%) residues. Phylogenetic analysis showed that ScDR1is in a clade with homologs from other monocotyledonous plants, separate from those of dicotyledonous plants. The expression of Scdr1 in different varieties of sugarcane plants has not shown a clear association with drought tolerance.

CONCLUSIONS/SIGNIFICANCE

The overexpression of Scdr1 in transgenic tobacco plants increased their tolerance to drought, salinity and oxidative stress, as demonstrated by increased photosynthesis, water content, biomass, germination rate, chlorophyll content and reduced accumulation of ROS. Physiological parameters, such as transpiration rate (E), net photosynthesis (A), stomatal conductance (gs) and internal leaf CO(2) concentration, were less affected by abiotic stresses in transgenic Scdr1 plants compared with wild-type plants. Overall, our results indicated that Scdr1 conferred tolerance to multiple abiotic stresses, highlighting the potential of this gene for biotechnological applications.

Association genetics of the loblolly pine (Pinus taeda, Pinaceae) metabolome

The metabolome of a plant comprises all small molecule metabolites, which are produced during cellular processes. The genetic basis for metabolites in nonmodel plants is unknown, despite frequently observed correlations between metabolite concentrations and stress responses. A quantitative genetic analysis of metabolites in a nonmodel plant species is thus warranted. Here, we use standard association genetic methods to correlate 3563 single nucleotide polymorphisms (SNPs) to concentrations of 292 metabolites measured in a single loblolly pine (Pinus taeda) association population. A total of 28 single locus associations were detected, representing 24 and 20 unique SNPs and metabolites, respectively. Multilocus Bayesian mixed linear models identified 2998 additional associations for a total of 1617 unique SNPs associated to 255 metabolites. These SNPs explained sizeable fractions of metabolite heritabilities when considered jointly (56.6% on average) and had lower minor allele frequencies and magnitudes of population structure as compared with random SNPs. Modest sets of SNPs (n = 1-23) explained sizeable portions of genetic effects for many metabolites, thus highlighting the importance of multi-SNP models to association mapping, and exhibited patterns of polymorphism consistent with being linked to targets of natural selection. The implications for association mapping in forest trees are discussed.