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

Association mapping and candidate gene identification for yield traits in European hazelnut (Corylus avellana L.)

European hazelnut (Corylus avellana L.) is an important nut crop due to its nutritional benefits, culinary uses, and economic value. Türkiye is the leading producer of hazelnut, followed by Italy and the United States. Quantitative trait locus studies offer promising opportunities for breeders and geneticists to identify genomic regions controlling desirable traits in hazelnut. A genome-wide association analysis was conducted with 5,567 single nucleotide polymorphisms on a Turkish core set of 86 hazelnut accessions, revealing 189 quantitative trait nucleotides (QTNs) associated with 22 of 31 traits (p < 2.9E-07). These QTNs were associated with plant and leaf, phenological, reproductive, nut, and kernel traits. Based on the close physical distance of QTNs associated with the same trait, we identified 23 quantitative trait loci. Furthermore, we identified 23 loci of multiple QTs comprising chromosome locations associated with more than one trait at the same position or in close proximity. A total of 159 candidate genes were identified for 189 QTNs, with 122 of them containing significant conserved protein domains. Some candidate matches to known proteins/domains were highly significant, suggesting that they have similar functions as their matches. This comprehensive study provides valuable insights for the development of breeding strategies and the improvement of hazelnut and enhances the understanding of the genetic architecture of complex traits by proposing candidate genes and potential functions.

Epigenetic stress memory in gymnosperms

Gymnosperms are long-lived, cone-bearing seed plants that include some of the most ancient extant plant species. These relict land plants have evolved to survive in habitats marked by chronic or episodic stress. Their ability to thrive in these environments is partly due to their phenotypic flexibility, and epigenetic regulation likely plays a crucial part in this plasticity. We review the current knowledge on abiotic and biotic stress memory in gymnosperms and the possible epigenetic mechanisms underlying long-term phenotypic adaptations. We also discuss recent technological improvements and new experimental possibilities that likely will advance our understanding of epigenetic regulation in these ancient and hard-to-study plants.

Comparison of ddRADseq and EUChip60K SNP genotyping systems for population genetics and genomic selection in Eucalyptus dunnii (Maiden)

Eucalyptus dunnii is one of the most important Eucalyptus species for short-fiber pulp production in regions where other species of the genus are affected by poor soil and climatic conditions. In this context, E. dunnii holds promise as a resource to address and adapt to the challenges of climate change. Despite its rapid growth and favorable wood properties for solid wood products, the advancement of its improvement remains in its early stages. In this work, we evaluated the performance of two single nucleotide polymorphism, (SNP), genotyping methods for population genetics analysis and Genomic Selection in E. dunnii. Double digest restriction-site associated DNA sequencing (ddRADseq) was compared with the EUChip60K array in 308 individuals from a provenance-progeny trial. The compared SNP set included 8,011 and 19,008 informative SNPs distributed along the 11 chromosomes, respectively. Although the two datasets differed in the percentage of missing data, genome coverage, minor allele frequency and estimated genetic diversity parameters, they revealed a similar genetic structure, showing two subpopulations with little differentiation between them, and low linkage disequilibrium. GS analyses were performed for eleven traits using Genomic Best Linear Unbiased Prediction (GBLUP) and a conventional pedigree-based model (ABLUP). Regardless of the SNP dataset, the predictive ability (PA) of GBLUP was better than that of ABLUP for six traits (Cellulose content, Total and Ethanolic extractives, Total and Klason lignin content and Syringyl and Guaiacyl lignin monomer ratio). When contrasting the SNP datasets used to estimate PAs, the GBLUP-EUChip60K model gave higher and significant PA values for six traits, meanwhile, the values estimated using ddRADseq gave higher values for three other traits. The PAs correlated positively with narrow sense heritabilities, with the highest correlations shown by the ABLUP and GBLUP-EUChip60K. The two genotyping methods, ddRADseq and EUChip60K, are generally comparable for population genetics and genomic prediction, demonstrating the utility of the former when subjected to rigorous SNP filtering. The results of this study provide a basis for future whole-genome studies using ddRADseq in non-model forest species for which SNP arrays have not yet been developed.

Comprehensive Organ-Specific Profiling of Douglas Fir (Pseudotsuga menziesii) Proteome

The Douglas fir (Pseudotsuga menziesii) is a conifer native to North America that has become increasingly popular in plantations in France due to its many advantages as timber: rapid growth, quality wood, and good adaptation to climate change. Tree genetic improvement programs require knowledge of a species' genetic structure and history and the development of genetic markers. The very slow progress in this field, for Douglas fir as well as the entire genus Pinus, can be explained using the very large size of their genomes, as well as by the presence of numerous highly repeated sequences. Proteomics, therefore, provides a powerful way to access genomic information of otherwise challenging species. Here, we present the first Douglas fir proteomes acquired using nLC-MS/MS from 12 different plant organs or tissues. We identified 3975 different proteins and quantified 3462 of them, then examined the distribution of specific proteins across plant organs/tissues and their implications in various molecular processes. As the first large proteomic study of a resinous tree species with organ-specific profiling, this short note provides an important foundation for future genomic annotations of conifers and other trees.

Applying molecular and genetic methods to trees and their fungal communities

Forests provide invaluable economic, ecological, and social services. At the same time, they are exposed to several threats, such as fragmentation, changing climatic conditions, or increasingly destructive pests and pathogens. Trees, the inherent species of forests, cannot be viewed as isolated organisms. Manifold (micro)organisms are associated with trees playing a pivotal role in forest ecosystems. Of these organisms, fungi may have the greatest impact on the life of trees. A multitude of molecular and genetic methods are now available to investigate tree species and their associated organisms. Due to their smaller genome sizes compared to tree species, whole genomes of different fungi are routinely compared. Such studies have only recently started in forest tree species. Here, we summarize the application of molecular and genetic methods in forest conservation genetics, tree breeding, and association genetics as well as for the investigation of fungal communities and their interrelated ecological functions. These techniques provide valuable insights into the molecular basis of adaptive traits, the impacts of forest management, and changing environmental conditions on tree species and fungal communities and can enhance tree-breeding cycles due to reduced time for field testing. It becomes clear that there are multifaceted interactions among microbial species as well as between these organisms and trees. We demonstrate the versatility of the different approaches based on case studies on trees and fungi. KEY POINTS: • Current knowledge of genetic methods applied to forest trees and associated fungi. • Genomic methods are essential in conservation, breeding, management, and research. • Important role of phytobiomes for trees and their ecosystems.

Genome-Wide SNP Markers Accelerate Perennial Forest Tree Breeding Rate for Disease Resistance through Marker-Assisted and Genome-Wide Selection

The ecological and economic importance of forest trees is evident and their survival is necessary to provide the raw materials needed for wood and paper industries, to preserve the diversity of associated animal and plant species, to protect water and soil, and to regulate climate. Forest trees are threatened by anthropogenic factors and biotic and abiotic stresses. Various diseases, including those caused by fungal pathogens, are one of the main threats to forest trees that lead to their dieback. Genomics and transcriptomics studies using next-generation sequencing (NGS) methods can help reveal the architecture of resistance to various diseases and exploit natural genetic diversity to select elite genotypes with high resistance to diseases. In the last two decades, QTL mapping studies led to the identification of QTLs related to disease resistance traits and gene families and transcription factors involved in them, including NB-LRR, WRKY, bZIP and MYB. On the other hand, due to the limitation of recombination events in traditional QTL mapping in families derived from bi-parental crosses, genome-wide association studies (GWAS) that are based on linkage disequilibrium (LD) in unstructured populations overcame these limitations and were able to narrow down QTLs to single genes through genotyping of many individuals using high-throughput markers. Association and QTL mapping studies, by identifying markers closely linked to the target trait, are the prerequisite for marker-assisted selection (MAS) and reduce the breeding period in perennial forest trees. The genomic selection (GS) method uses the information on all markers across the whole genome, regardless of their significance for development of a predictive model for the performance of individuals in relation to a specific trait. GS studies also increase gain per unit of time and dramatically increase the speed of breeding programs. This review article is focused on the progress achieved in the field of dissecting forest tree disease resistance architecture through GWAS and QTL mapping studies. Finally, the merit of methods such as GS in accelerating forest tree breeding programs is also discussed.

Addressing Gender Inequities in Forest Science and Research

Forest research and professional workforces continue to be dominated by men, particularly at senior and management levels. In this review, we identify some of the historical and ongoing barriers to improved gender inclusion and suggest some solutions. We showcase a selection of women in forestry from different disciplines and parts of the globe to highlight a range of research being conducted by women in forests. Boosting gender equity in forest disciplines requires a variety of approaches across local, regional and global scales. It is also important to include intersectional analyses when identifying barriers for women in forestry, but enhanced equity, diversity and inclusion will improve outcomes for forest ecosystems and social values of forests, with potential additional economic benefits.

Achievements and Challenges of Genomics-Assisted Breeding in Forest Trees: From Marker-Assisted Selection to Genome Editing

Forest tree breeding efforts have focused mainly on improving traits of economic importance, selecting trees suited to new environments or generating trees that are more resilient to biotic and abiotic stressors. This review describes various methods of forest tree selection assisted by genomics and the main technological challenges and achievements in research at the genomic level. Due to the long rotation time of a forest plantation and the resulting long generation times necessary to complete a breeding cycle, the use of advanced techniques with traditional breeding have been necessary, allowing the use of more precise methods for determining the genetic architecture of traits of interest, such as genome-wide association studies (GWASs) and genomic selection (GS). In this sense, main factors that determine the accuracy of genomic prediction models are also addressed. In turn, the introduction of genome editing opens the door to new possibilities in forest trees and especially clustered regularly interspaced short palindromic repeats and CRISPR-associated protein 9 (CRISPR/Cas9). It is a highly efficient and effective genome editing technique that has been used to effectively implement targetable changes at specific places in the genome of a forest tree. In this sense, forest trees still lack a transformation method and an inefficient number of genotypes for CRISPR/Cas9. This challenge could be addressed with the use of the newly developing technique GRF-GIF with speed breeding.

Genome-wide shifts in climate-related variation underpin responses to selective breeding in a widespread conifer

Temperate trees originating from warmer localities usually grow faster and acclimate to winter later than trees of the same species from colder localities. However, when trees are selected for faster growth, are climatically adaptive genes and traits affected? Our research demonstrates a simple, sensitive, broadly applicable, and elusive approach to integrating complex polygenic variation into applied environmental management. We show that selective breeding increases allele frequencies of many trait-associated genes, and that alleles that increase most display strong genetic linkage and potential trade-offs among traits. Increasing tree growth while maintaining adaptation is essential to reforestation in a changing climate, but this may be challenging because trait-associated genetic variation that underpins climate adaptation is responsive to selection for tree growth.

Locally adapted temperate tree populations exhibit genetic trade-offs among climate-related traits that can be exacerbated by selective breeding and are challenging to manage under climate change. To inform climatically adaptive forest management, we investigated the genetic architecture and impacts of selective breeding on four climate-related traits in 105 natural and 20 selectively bred lodgepole pine populations from western Canada. Growth, cold injury, growth initiation, and growth cessation phenotypes were tested for associations with 18,600 single-nucleotide polymorphisms (SNPs) in natural populations to identify “positive effect alleles” (PEAs). The effects of artificial selection for faster growth on the frequency of PEAs associated with each trait were quantified in breeding populations from different climates. Substantial shifts in PEA proportions and frequencies were observed across many loci after two generations of selective breeding for height, and responses of phenology-associated PEAs differed strongly among climatic regions. Extensive genetic overlap was evident among traits. Alleles most strongly associated with greater height were often associated with greater cold injury and delayed phenology, although it is unclear whether potential trade-offs arose directly from pleiotropy or indirectly via genetic linkage. Modest variation in multilocus PEA frequencies among populations was associated with large phenotypic differences and strong climatic gradients, providing support for assisted gene flow polices. Relationships among genotypes, phenotypes, and climate in natural populations were maintained or strengthened by selective breeding. However, future adaptive phenotypes and assisted gene flow may be compromised if selective breeding further increases the PEA frequencies of SNPs involved in adaptive trade-offs among climate-related traits.

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.

Breeding for Climate Change Resilience: A Case Study of Loblolly Pine (Pinus taeda L.) in North America

Earth's atmosphere is warming and the effects of climate change are becoming evident. A key observation is that both the average levels and the variability of temperature and precipitation are changing. Information and data from new technologies are developing in parallel to provide multidisciplinary opportunities to address and overcome the consequences of these changes in forest ecosystems. Changes in temperature and water availability impose multidimensional environmental constraints that trigger changes from the molecular to the forest stand level. These can represent a threat for the normal development of the tree from early seedling recruitment to adulthood both through direct mortality, and by increasing susceptibility to pathogens, insect attack, and fire damage. This review summarizes the strengths and shortcomings of previous work in the areas of genetic variation related to cold and drought stress in forest species with particular emphasis on loblolly pine (Pinus taeda L.), the most-planted tree species in North America. We describe and discuss the implementation of management and breeding strategies to increase resilience and adaptation, and discuss how new technologies in the areas of engineering and genomics are shaping the future of phenotype-genotype studies. Lessons learned from the study of species important in intensively-managed forest ecosystems may also prove to be of value in helping less-intensively managed forest ecosystems adapt to climate change, thereby increasing the sustainability and resilience of forestlands for the future.

Population structure, diversifying selection, and local adaptation in Pinus patula

PREMISE

Climate change is predicted to affect natural and plantation forests. The responses of conifers to overcome changing environments will depend on their adaptation to local conditions; however, intraspecific adaptive genetic variation is unknown for most gymnosperms. Studying genetic diversity associated with phenotypic variability along environmental gradients will enhance our understanding of adaptation and may reveal genetic pools important for conservation and management.

METHODS

We used target enrichment and genome skimming to obtain single nucleotide polymorphisms (SNPs) from 61 individuals of Pinus patula, a pine tree native to Mexico widely used in plantation forestry. We investigated the adaptive genetic variation of two varieties with morphological and distributional differences potentially related to genetic and adaptive divergence.

RESULTS

Population structure and haplotype network analyses revealed that genetic diversity between P. patula var. patula and P. patula var. longipedunculata was structured, even within populations of P. patula var. longipedunculata. We observed high genetic diversity, low inbreeding rate, and rapid linkage disequilibrium (LD) decay in the varieties. Based on outlier tests, loci showing signatures of natural selection were detected in geographically distant P. patula var. longipedunculata populations. For both varieties, we found significant correlations between climate-related environmental variation and SNP diversity at loci involved in abiotic stress, cell transport, defense, and cell wall biogenesis, pointing to local adaptation.

CONCLUSIONS

Overall, significant intraspecific adaptive genetic variation in P. patula was detected, highlighting the presence of different genetic pools and signs of local adaptation that should be considered in forestry and conservation.

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.

Genomics of Clinal Local Adaptation in Pinus sylvestris Under Continuous Environmental and Spatial Genetic Setting

Understanding the consequences of local adaptation at the genomic diversity is a central goal in evolutionary genetics of natural populations. In species with large continuous geographical distributions the phenotypic signal of local adaptation is frequently clear, but the genetic basis often remains elusive. We examined the patterns of genetic diversity in Pinus sylvestris, a keystone species in many Eurasian ecosystems with a huge distribution range and decades of forestry research showing that it is locally adapted to the vast range of environmental conditions. Making P. sylvestris an even more attractive subject of local adaptation study, population structure has been shown to be weak previously and in this study. However, little is known about the molecular genetic basis of adaptation, as the massive size of gymnosperm genomes has prevented large scale genomic surveys. We generated a both geographically and genomically extensive dataset using a targeted sequencing approach. By applying divergence-based and landscape genomics methods we identified several loci contributing to local adaptation, but only few with large allele frequency changes across latitude. We also discovered a very large (ca. 300 Mbp) putative inversion potentially under selection, which to our knowledge is the first such discovery in conifers. Our results call for more detailed analysis of structural variation in relation to genomic basis of local adaptation, emphasize the lack of large effect loci contributing to local adaptation in the coding regions and thus point out the need for more attention toward multi-locus analysis of polygenic adaptation.

SECNVs: A Simulator of Copy Number Variants and Whole-Exome Sequences From Reference Genomes

Copy number variants are duplications and deletions of the genome that play an important role in phenotypic changes and human disease. Many software applications have been developed to detect copy number variants using either whole-genome sequencing or whole-exome sequencing data. However, there is poor agreement in the results from these applications. Simulated datasets containing copy number variants allow comprehensive comparisons of the operating characteristics of existing and novel copy number variant detection methods. Several software applications have been developed to simulate copy number variants and other structural variants in whole-genome sequencing data. However, none of the applications reliably simulate copy number variants in whole-exome sequencing data. We have developed and tested Simulator of Exome Copy Number Variants (SECNVs), a fast, robust and customizable software application for simulating copy number variants and whole-exome sequences from a reference genome. SECNVs is easy to install, implements a wide range of commands to customize simulations, can output multiple samples at once, and incorporates a pipeline to output rearranged genomes, short reads and BAM files in a single command. Variants generated by SECNVs are detected with high sensitivity and precision by tools commonly used to detect copy number variants. SECNVs is publicly available at https://github.com/YJulyXing/SECNVs.

275 years of forestry meets genomics in Pinus sylvestris

Pinus sylvestris has a long history of basic and applied research that is relevant for both forestry and evolutionary studies. Its patterns of adaptive variation and role in forest economic and ecological systems have been studied extensively for nearly 275 years, detailed demography for a 100 years and mating system more than 50 years. However, its reference genome sequence is not yet available and genomic studies have been lagging compared to, for example, Pinus taeda and Picea abies, two other economically important conifers. Despite the lack of reference genome, many modern genomic methods are applicable for a more detailed look at its biological characteristics. For example, RNA-seq has revealed a complex transcriptional landscape and targeted DNA sequencing displays an excess of rare variants and geographically homogenously distributed molecular genetic diversity. Current DNA and RNA resources can be used as a reference for gene expression studies, SNP discovery, and further targeted sequencing. In the future, specific consequences of the large genome size, such as functional effects of regulatory open chromatin regions and transposable elements, should be investigated more carefully. For forest breeding and long-term management purposes, genomic data can help in assessing the genetic basis of inbreeding depression and the application of genomic tools for genomic prediction and relatedness estimates. Given the challenges of breeding (long generation time, no easy vegetative propagation) and the economic importance, application of genomic tools has a potential to have a considerable impact. Here, we explore how genomic characteristics of P. sylvestris, such as rare alleles and the low extent of linkage disequilibrium, impact the applicability and power of the tools.

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.

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.

A high-density exome capture genotype-by-sequencing panel for forestry breeding in Pinus radiata

Development of genome-wide resources for application in genomic selection or genome-wide association studies, in the absence of full reference genomes, present a challenge to the forestry industry, where longer breeding cycles could benefit from the accelerated selection possible through marker-based breeding value predictions. In particular, large conifer megagenomes require a strategy to reduce complexity, whilst ensuring genome-wide coverage is achieved. Using a transcriptome-based reference template, we have successfully developed a high density exome capture genotype-by-sequencing panel for radiata pine (Pinus radiata D.Don), capable of capturing in excess of 80,000 single nucleotide polymorphism (SNP) markers with a minor allele frequency above 0.03 in the population tested. This represents approximately 29,000 gene models from a core set of 48,914 probes. A set of 704 SNP markers capable of pedigree reconstruction and differentiating individual genotypes were tested within two full-sib mapping populations. While as few as 70 markers could reconstruct parentage in almost all cases, the impact of missing genotypes was noticeable in several offspring. Therefore, 60 sets of 110 randomly selected SNP markers were compared for both parentage reconstruction and clone differentiation. The performance in parentage reconstruction showed little variation over 60 iterations. However, there was notable variation in discriminatory power between closely related individuals, indicating a higher density SNP marker panel may be required to elucidate hidden relationships in complex pedigrees.

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.

Multiomics analysis reveals a distinct mechanism of oleaginousness in the emerging model alga Chromochloris zofingiensis

Chromochloris zofingiensis, featured due to its capability to simultaneously synthesize triacylglycerol (TAG) and astaxanthin, is emerging as a leading candidate alga for production uses. To better understand the oleaginous mechanism of this alga, we conducted a multiomics analysis by systematically integrating time-resolved transcriptomes, lipidomes and metabolomes in response to nitrogen deprivation. The data analysis unraveled the distinct mechanism of TAG accumulation, which involved coordinated stimulation of multiple biological processes including supply of energy and reductants, carbon reallocation from protein and starch, and 'pushing' and 'pulling' carbon to TAG synthesis. Unlike the model alga Chlamydomonas, de novo fatty acid synthesis in C. zofingiensis was promoted, together with enhanced turnover of both glycolipids and phospholipids, supporting the drastic need of acyls for TAG assembly. Moreover, genomewide analysis identified many key functional enzymes and transcription factors that had engineering potential for TAG modulation. Two genes encoding glycerol-3-phosphate acyltransferase (GPAT), the first committed enzyme for TAG assembly, were found in the C. zofingiensis genome; in vivo functional characterization revealed that extrachloroplastic GPAT instead of chloroplastic GPAT played a central role in TAG synthesis. These findings illuminate distinct oleaginousness mechanisms in C. zofingiensis and pave the way towards rational manipulation of this alga to becone an emerging model for trait improvements.

Exome Resequencing Reveals Evolutionary History, Genomic Diversity, and Targets of Selection in the Conifers Pinus taeda and Pinus elliottii

Loblolly pine (Pinus taeda) and slash pine (Pinus elliottii) are ecologically and economically important pine species that dominate many forest ecosystems in the southern United States, but like all conifers, the study of their genetic diversity and demographic history has been hampered by their large genome size. A small number of studies mainly based on candidate-gene sequencing have been reported for P. taeda to date, whereas none are available for P. elliottii. Targeted exome resequencing has recently enabled population genomics studies for conifers, approach used here to assess genomic diversity, signatures of selection, population structure, and demographic history of P. elliottii and P. taeda. Extensive similarities were revealed between these species: both species feature rapid linkage disequilibrium decay and high levels of genetic diversity. Moreover, genome-wide positive correlations for measures of genetic diversity between the species were also observed, likely due to shared structural genomic constraints. Also, positive selection appears to be targeting a common set of genes in both pines. Demographic history differs between both species, with only P. taeda being affected by a dramatic bottleneck during the last glacial period. The ability of P. taeda to recover from a dramatic reduction in population size while still retaining high levels of genetic diversity shows promise for other pines facing environmental stressors associated with climate change, indicating that these too may be able to adapt successfully to new future conditions even after a drastic population size contraction.

A few north Appalachian populations are the source of European black locust

The role of evolution in biological invasion studies is often overlooked. In order to evaluate the evolutionary mechanisms behind invasiveness, it is crucial to identify the source populations of the introduction. Studies in population genetics were carried out on Robinia pseudoacacia L., a North American tree which is now one of the worst invasive tree species in Europe. We realized large-scale sampling in both the invasive and native ranges: 63 populations were sampled and 818 individuals were genotyped using 113 SNPs. We identified clonal genotypes in each population and analyzed between and within range population structure, and then, we compared genetic diversity between ranges, enlarging the number of SNPs to mitigate the ascertainment bias. First, we demonstrated that European black locust was introduced from just a limited number of populations located in the Appalachian Mountains, which is in agreement with the historical documents briefly reviewed in this study. Within America, population structure reflected the effects of long-term processes, whereas in Europe it was largely impacted by human activities. Second, we showed that there is a genetic bottleneck between the ranges with a decrease in allelic richness and total number of alleles in Europe. Lastly, we found more clonality within European populations. Black locust became invasive in Europe despite being introduced from a reduced part of its native distribution. Our results suggest that human activity, such as breeding programs in Europe and the seed trade throughout the introduced range, had a major role in promoting invasion; therefore, the introduction of the missing American genetic cluster to Europe should be avoided.

Repurposing population genetics data to discern genomic architecture: A case study of linkage cohort detection in mountain pine beetle (Dendroctonus ponderosae)

Genetic surveys of the population structure of species can be used as resources for exploring their genomic architecture. By adjusting filtering assumptions, genome-wide single-nucleotide polymorphism (SNP) datasets can be reused to give new insights into the genetic basis of divergence and speciation without targeted resampling of specimens. Filtering only for missing data and minor allele frequency, we used a combination of principal components analysis and linkage disequilibrium network analysis to distinguish three cohorts of variable SNPs in the mountain pine beetle in western Canada, including one that was sex-linked and one that was geographically associated. These marker cohorts indicate genomically localized differentiation, and their detection demonstrates an accessible and intuitive method for discovering potential islands of genomic divergence without a priori knowledge of a species' genomic architecture. Thus, this method has utility for directly addressing the genomic architecture of species and generating new hypotheses for functional research.

Association mapping of ectomycorrhizal traits in loblolly pine (Pinus taeda L.)

To understand how diverse mutualisms coevolve and how species adapt to complex environments, a description of the underlying genetic basis of the traits involved must be provided. For example, in diverse coevolving mutualisms, such as the interaction of host plants with a suite of symbiotic mycorrhizal fungi, a key question is whether host plants can coevolve independently with multiple species of symbionts, which depends on whether those interactions are governed independently by separate genes or pleiotropically by shared genes. To provide insight into this question, we employed an association mapping approach in a clonally replicated field experiment of loblolly pine (Pinus taeda L.) to identify genetic components of host traits governing ectomycorrhizal (EM) symbioses (mycorrhizal traits). The relative abundances of different EM fungi as well as the total number of root tips per cm root colonized by EM fungi were analyzed as separate mycorrhizal traits of loblolly pine. Single-nucleotide polymorphisms (SNPs) within candidate genes of loblolly pine were associated with loblolly pine mycorrhizal traits, mapped to the loblolly pine genome, and their putative protein function obtained when available. The results support the hypothesis that ectomycorrhiza formation is governed by host genes of large effect that apparently have independent influences on host interactions with different symbiont species.

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.

Potential of Genome-Wide Studies in Unrelated Plus Trees of a Coniferous Species, Cryptomeria japonica (Japanese Cedar)

A genome-wide association study (GWAS) was conducted on more than 30,000 single nucleotide polymorphisms (SNPs) in unrelated first-generation plus tree genotypes from three populations of Japanese cedar Cryptomeria japonica D. Don with genomic prediction for traits of growth, wood properties and male fecundity. Among the assessed populations, genetic characteristics including the extent of linkage disequilibrium (LD) and genetic structure differed and these differences are considered to be due to differences in genetic background. Through population-independent GWAS, several significant SNPs found close to the regions associated with each of these traits and shared in common across the populations were identified. The accuracies of genomic predictions were dependent on the traits and populations and reflected the genetic architecture of traits and genetic characteristics. Prediction accuracies using SNPs selected based on GWAS results were similar to those using all SNPs for several combinations of traits and populations. We discussed the application of genome-wide studies for C. japonica improvement.

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.