Optimizing genomic selection for blight resistance in American chestnut backcross populations: A trade-off with American chestnut ancestry implies resistance is polygenic

Genomic prediction of resistance to Hymenoscyphus fraxineus in common ash (Fraxinus excelsior L.) populations

The increase in introduced insect pests and pathogens due to anthropogenic environmental changes has become a major concern for tree species worldwide. Common ash (Fraxinus excelsior L.) is one of such species facing a significant threat from the invasive fungal pathogen Hymenoscyphus fraxineus. Some studies have indicated that the susceptibility of ash to the pathogen is genetically determined, providing some hope for accelerated breeding programs that are aimed at increasing the resistance of ash populations. To address this challenge, we used a genomic selection strategy to identify potential genetic markers that are associated with resistance to the pathogen causing ash dieback. Through genome-wide association studies (GWAS) of 300 common ash individuals from 30 populations across Poland (ddRAD, dataset A), we identified six significant SNP loci with a p-value ≤1 × 10-4 associated with health status. To further evaluate the effectiveness of GWAS markers in predicting health status, we considered two genomic prediction scenarios. Firstly, we conducted cross-validation on dataset A. Secondly, we trained markers on dataset A and tested them on dataset B, which involved whole-genome sequencing of 20 individuals from two populations. Genomic prediction analysis revealed that the top SNPs identified via GWAS exhibited notably higher prediction accuracies compared to randomly selected SNPs, particularly with a larger number of SNPs. Cross-validation analyses using dataset A showcased high genomic prediction accuracy, predicting tree health status with over 90% accuracy across the top SNP sets ranging from 500 to 10,000 SNPs from the GWAS datasets. However, no significant results emerged for health status when the model trained on dataset A was tested on dataset B. Our findings illuminate potential genetic markers associated with resistance to ash dieback, offering support for future breeding programs in Poland aimed at combating ash dieback and bolstering conservation efforts for this invaluable tree species.

Mapping QTLs for blight resistance and morpho-phenological traits in inter-species hybrid families of chestnut (Castanea spp.)

Chestnut blight (caused by Cryphonectria parasitica), together with Phytophthora root rot (caused by Phytophthora cinnamomi), has nearly extirpated American chestnut (Castanea dentata) from its native range. In contrast to the susceptibility of American chestnut, many Chinese chestnut (C. mollissima) genotypes are resistant to blight. In this research, we performed a series of genome-wide association studies for blight resistance originating from three unrelated Chinese chestnut trees (Mahogany, Nanking and M16) and a Quantitative Trait Locus (QTL) study on a Mahogany-derived inter-species F2 family. We evaluated trees for resistance to blight after artificial inoculation with two fungal strains and scored nine morpho-phenological traits that are the hallmarks of species differentiation between American and Chinese chestnuts. Results support a moderately complex genetic architecture for blight resistance, as 31 QTLs were found on 12 chromosomes across all studies. Additionally, although most morpho-phenological trait QTLs overlap or are adjacent to blight resistance QTLs, they tend to aggregate in a few genomic regions. Finally, comparison between QTL intervals for blight resistance and those previously published for Phytophthora root rot resistance, revealed five common disease resistance regions on chromosomes 1, 5, and 11. Our results suggest that it will be difficult, but still possible to eliminate Chinese chestnut alleles for the morpho-phenological traits while achieving relatively high blight resistance in a backcross hybrid tree. We see potential for a breeding scheme that utilizes marker-assisted selection early for relatively large effect QTLs followed by genome selection in later generations for smaller effect genomic regions.

Conservation Mitonuclear Replacement: Facilitated mitochondrial adaptation for a changing world

Most species will not be able to migrate fast enough to cope with climate change, nor evolve quickly enough with current levels of genetic variation. Exacerbating the problem are anthropogenic influences on adaptive potential, including the prevention of gene flow through habitat fragmentation and the erosion of genetic diversity in small, bottlenecked populations. Facilitated adaptation, or assisted evolution, offers a way to augment adaptive genetic variation via artificial selection, induced hybridization, or genetic engineering. One key source of genetic variation, particularly for climatic adaptation, are the core metabolic genes encoded by the mitochondrial genome. These genes influence environmental tolerance to heat, drought, and hypoxia, but must interact intimately and co-evolve with a suite of important nuclear genes. These coadapted mitonuclear genes form some of the important reproductive barriers between species. Mitochondrial genomes can and do introgress between species in an adaptive manner, and they may co-introgress with nuclear genes important for maintaining mitonuclear compatibility. Managers should consider the relevance of mitonuclear genetic variability in conservation decision-making, including as a tool for facilitating adaptation. I propose a novel technique dubbed Conservation Mitonuclear Replacement (CmNR), which entails replacing the core metabolic machinery of a threatened species-the mitochondrial genome and key nuclear loci-with those from a closely related species or a divergent population, which may be better-adapted to climatic changes or carry a lower genetic load. The most feasible route to CmNR is to combine CRISPR-based nuclear genetic editing with mitochondrial replacement and assisted reproductive technologies. This method preserves much of an organism's phenotype and could allow populations to persist in the wild when no other suitable conservation options exist. The technique could be particularly important on mountaintops, where rising temperatures threaten an alarming number of species with almost certain extinction in the next century.

Climate change reshaping plant-fungal interaction

Plant diseases pose a severe threat to modern agriculture, necessitating effective and lasting control solutions. Environmental factors significantly shape plant ecology. Human-induced greenhouse gas emissions have led to global temperature rise, impacting various aspects, including carbon dioxide (CO2) concentration, temperature, ozone (O3), and ultraviolet-B, all of which influence plant diseases. Altered pathogen ranges can accelerate disease transmission. This review explores environmental effects on plant diseases, with climate change affecting fungal biogeography, disease incidence, and severity, as well as agricultural production. Moreover, we have discussed how climate change influences pathogen development, host-fungal interactions, the emergence of new races of fungi, and the dissemination of emerging fungal diseases across the globe. The discussion about environment-mediated impact on pattern-triggered immunity (PTI), effector-triggered immunity (ETI), and RNA interference (RNAi) is also part of this review. In conclusion, the review underscores the critical importance of understanding how climate change is reshaping plant-fungal interactions. It highlights the need for continuous research efforts to elucidate the mechanisms driving these changes and their ecological consequences. As the global climate continues to evolve, it is imperative to develop innovative strategies for mitigating the adverse effects of fungal pathogens on plant health and food security.

Validation of an Alternative Small Stem Assay for Blight Resistance in Chestnut Seedlings and Recommendations for Broader Use

We evaluated an alternative small stem assay (AltSSA) for blight resistance in backcross hybrid chestnut trees (Castanea dentata/mollissima). Whereas standard small stem assays (SSAs) are done by inoculating small incisions in stems, in our AltSSA, 4- to 5-mm stems are cut off, and the exposed (living) stem tips are inoculated with discs of Cryphonectria parasitica inoculum and temporarily covered with plastic sleeves. Intended primarily for forward selection, this method was designed to be easy to implement, to consistently induce cankering, and to better enable seedling recovery via the development of lateral shoots from the lower stem. After 90+ days, cankers are evaluated and removed, and seedlings are prepared for out-planting. Previous results showed that AltSSAs performed at least as well as a common SSA method in distinguishing resistant and susceptible types. In this follow-up analysis of 35 lines of backcross seedlings studied in 2020 and 2021, we showed that mean orange zone canker length (OZCL) and a multifactor principal components analysis-based blight resistance index gave results consistent with predictions derived from two methods of blight resistance phenotyping and percentage of American chestnut ancestry of the parents of each line. As expected, based upon the apparent polygenic inheritance of blight resistance in backcross chestnut trees, mean OZCL of backcross families ranged from intermediate (F₁ hybrid-level) to low (wild-type American chestnut-level). Consistent with prior results, canker production was near 100%, survivorship after out-planting was very high, and postinoculation stem dieback was not apparently related to the stem tip inoculations. Altogether, these results suggest that the AltSSA is a viable method for early detection of relative blight resistance in seedlings and may enable a reduction in the numbers of trees out-planted and placed under care for long-term evaluation and breeding. Thus, the AltSSA can prevent time, resources, and orchard space from being used on susceptible trees.

Increasing genomic prediction accuracy for unphenotyped full-sib families by modeling additive and dominance effects with large datasets in white spruce

INTRODUCTION

Genomic selection is becoming a standard technique in plant breeding and is now being introduced into forest tree breeding. Despite promising results to predict the genetic merit of superior material based on their additive breeding values, many studies and operational programs still neglect non-additive effects and their potential for enhancing genetic gains.

METHODS

Using two large comprehensive datasets totaling 4,066 trees from 146 full-sib families of white spruce (Picea glauca (Moench) Voss), we evaluated the effect of the inclusion of dominance on the precision of genetic parameter estimates and on the accuracy of conventional pedigree-based (ABLUP-AD) and genomic-based (GBLUP-AD) models.

RESULTS

While wood quality traits were mostly additively inherited, considerable non-additive effects and lower heritabilities were detected for growth traits. For growth, GBLUP-AD better partitioned the additive and dominance effects into roughly equal variances, while ABLUP-AD strongly overestimated dominance. The predictive abilities of breeding and total genetic value estimates were similar between ABLUP-AD and GBLUP-AD when predicting individuals from the same families as those included in the training dataset. However, GBLUP-AD outperformed ABLUP-AD when predicting for new unphenotyped families that were not represented in the training dataset, with, on average, 22% and 53% higher predictive ability of breeding and genetic values, respectively. Resampling simulations showed that GBLUP-AD required smaller sample sizes than ABLUP-AD to produce precise estimates of genetic variances and accurate predictions of genetic values. Still, regardless of the method used, large training datasets were needed to estimate additive and non-additive genetic variances precisely.

DISCUSSION

This study highlights the different quantitative genetic architectures between growth and wood traits. Furthermore, the usefulness of genomic additive-dominance models for predicting new families should allow practicing mating allocation to maximize the total genetic values for the propagation of elite material.

DNA release from plant tissue using focused ultrasound extraction (FUSE)

PREMISE

Sample preparation in genomics is a critical step that is often overlooked in molecular workflows and impacts the success of downstream genetic applications. This study explores the use of a recently developed focused ultrasound extraction (FUSE) technique to enable the rapid release of DNA from plant tissues for genetic analysis.

METHODS

FUSE generates a dense acoustic cavitation bubble cloud that pulverizes targeted tissue into acellular debris. This technique was applied to leaf samples of American chestnut (Castanea dentata), tulip poplar (Liriodendron tulipifera), red maple (Acer rubrum), and chestnut oak (Quercus montana).

RESULTS

We observed that FUSE can extract high quantities of DNA in 9-15 min, compared to the 30 min required for control DNA extraction methods. FUSE extracted DNA quantities of 24.33 ± 6.51 ng/mg and 35.32 ± 9.21 ng/mg from American chestnut and red maple, respectively, while control methods yielded 6.22 ± 0.87 ng/mg and 11.51 ± 1.95 ng/mg, respectively. The quality of the DNA released by FUSE allowed for successful amplification and next-generation sequencing.

DISCUSSION

These results indicate that FUSE can improve DNA extraction efficiency for leaf tissues. Continued development of this technology aims to adapt to field-deployable systems to increase the cataloging of genetic biodiversity, particularly in low-resource biodiversity hotspots.

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.

European and American chestnuts: An overview of the main threats and control efforts

Chestnuts are multipurpose trees significant for the economy and wildlife. These trees are currently found around the globe, demonstrating their genetic adaptation to different environmental conditions. Several biotic and abiotic stresses have challenged these species, contributing to the decline of European chestnut production and the functional extinction of the American chestnut. Several efforts started over the last century to understand the cellular, molecular, and genetic interactions behind all chestnut biotic and abiotic interactions. Most efforts have been toward breeding for the primary diseases, chestnut blight and ink disease caused by the pathogens, Cryphonectria parasitica and Phytophthora cinnamomi, respectively. In Europe and North America, researchers have been using the Asian chestnut species, which co-evolved with the pathogens, to introgress resistance genes into the susceptible species. Breeding woody trees has several limitations which can be mostly related to the long life cycles of these species and the big genome landscapes. Consequently, it takes decades to improve traits of interest, such as resistance to pathogens. Currently, the availability of genome sequences and next-generation sequencing techniques may provide new tools to help overcome most of the problems tree breeding is still facing. This review summarizes European and American chestnut's main biotic stresses and discusses breeding and biotechnological efforts developed over the last decades, having ink disease and chestnut blight as the main focus. Climate change is a rising concern, and in this context, the adaptation of chestnuts to adverse environmental conditions is of extreme importance for chestnut production. Therefore, we also discuss the abiotic challenges on European chestnuts, where the response to abiotic stress at the genetic and molecular level has been explored.

Using Genomic Selection to Develop Performance-Based Restoration Plant Materials

Effective native plant materials are critical to restoring the structure and function of extensively modified ecosystems, such as the sagebrush steppe of North America’s Intermountain West. The reestablishment of native bunchgrasses, e.g., bluebunch wheatgrass (Pseudoroegneria spicata [Pursh] À. Löve), is the first step for recovery from invasive species and frequent wildfire and towards greater ecosystem resiliency. Effective native plant material exhibits functional traits that confer ecological fitness, phenotypic plasticity that enables adaptation to the local environment, and genetic variation that facilitates rapid evolution to local conditions, i.e., local adaptation. Here we illustrate a multi-disciplinary approach based on genomic selection to develop plant materials that address environmental issues that constrain local populations in altered ecosystems. Based on DNA sequence, genomic selection allows rapid screening of large numbers of seedlings, even for traits expressed only in more mature plants. Plants are genotyped and phenotyped in a training population to develop a genome model for the desired phenotype. Populations with modified phenotypes can be used to identify plant syndromes and test basic hypotheses regarding relationships of traits to adaptation and to one another. The effectiveness of genomic selection in crop and livestock breeding suggests this approach has tremendous potential for improving restoration outcomes for species such as bluebunch wheatgrass.

Frozen in time: rangewide genomic diversity, structure, and demographic history of relict American chestnut populations

American chestnut (Castanea dentata) was once the most economically and ecologically important hardwood species in the eastern United States. In the first half of the 20th century, an exotic fungal pathogen - Cryphonectria parasitica - decimated the species, killing billions of chestnut trees. Two approaches to developing blight resistant American chestnut populations show promise, but both will require introduction of adaptive genomic diversity from wild germplasm to produce diverse, locally adapted restoration populations. Here we characterize population structure, demographic history, and genomic diversity in a range-wide sample of 384 wild American chestnuts to inform conservation and breeding with blight resistant varieties. Population structure analyses suggest that the chestnut range can be roughly divided into northeast, central, and southwest populations. Within-population genomic diversity estimates revealed a clinal pattern with the highest diversity in the southwest, which likely reflects bottleneck events associated with Quaternary glaciation. Finally, we identified genomic regions under positive selection within each population, which suggests that defense against fungal pathogens is a common target of selection across all populations. Taken together, these results show that American chestnut underwent a postglacial expansion from the southern portion of its range leading to three extant genetic populations. These populations will serve as management units for breeding adaptive genetic variation into the blight-resistant tree populations for targeted reintroduction efforts.

Identifying and testing marker-trait associations for growth and phenology in three pine species: Implications for genomic prediction

In tree species, genomic prediction offers the potential to forecast mature trait values in early growth stages, if robust marker-trait associations can be identified. Here we apply a novel multispecies approach using genotypes from a new genotyping array, based on 20,795 single nucleotide polymorphisms (SNPs) from three closely related pine species (Pinus sylvestris, Pinus uncinata and Pinus mugo), to test for associations with growth and phenology data from a common garden study. Predictive models constructed using significantly associated SNPs were then tested and applied to an independent multisite field trial of P. sylvestris and the capability to predict trait values was evaluated. One hundred and eighteen SNPs showed significant associations with the traits in the pine species. Common SNPs (MAF > 0.05) associated with bud set were only found in genes putatively involved in growth and development, whereas those associated with growth and budburst were also located in genes putatively involved in response to environment and, to a lesser extent, reproduction. At one of the two independent sites, the model we developed produced highly significant correlations between predicted values and observed height data (YA, height 2020: r = 0.376, p < 0.001). Predicted values estimated with our budburst model were weakly but positively correlated with duration of budburst at one of the sites (GS, 2015: r = 0.204, p = 0.034; 2018: r = 0.205, p = 0.034-0.037) and negatively associated with budburst timing at the other (YA: r = -0.202, p = 0.046). Genomic prediction resulted in the selection of sets of trees whose mean height was taller than the average for each site. Our results provide tentative support for the capability of prediction models to forecast trait values in trees, while highlighting the need for caution in applying them to trees grown in different environments.

From Genome Sequencing to CRISPR-Based Genome Editing for Climate-Resilient Forest Trees

Due to the economic and ecological importance of forest trees, modern breeding and genetic manipulation of forest trees have become increasingly prevalent. The CRISPR-based technology provides a versatile, powerful, and widely accepted tool for analyzing gene function and precise genetic modification in virtually any species but remains largely unexplored in forest species. Rapidly accumulating genetic and genomic resources for forest trees enabled the identification of numerous genes and biological processes that are associated with important traits such as wood quality, drought, or pest resistance, facilitating the selection of suitable gene editing targets. Here, we introduce and discuss the latest progress, opportunities, and challenges of genome sequencing and editing for improving forest sustainability.

Genetic approaches for increasing fitness in endangered species

The global rate of wildlife extinctions is accelerating, and the persistence of many species requires conservation breeding programs. A central paradigm of these programs is to preserve the genetic diversity of the founder populations. However, this may preserve original characteristics that make them vulnerable to extinction. We introduce targeted genetic intervention (TGI) as an alternative approach that promotes traits that enable species to persist in the face of threats by changing the incidence of alleles that impact on fitness. The TGI toolkit includes methods with established efficacy in model organisms and agriculture but are largely untried for conservation, such as synthetic biology and artificial selection. We explore TGI approaches as a species-restoration tool for intractable threats including infectious disease and climate change.

Finding common ground: Toward comparable indicators of adaptive capacity of tree species to a changing climate

Adaptive capacity, one of the three determinants of vulnerability to climate change, is defined as the capacity of species to persist in their current location by coping with novel environmental conditions through acclimation and/or evolution. Although studies have identified indicators of adaptive capacity, few have assessed this capacity in a quantitative way that is comparable across tree species. Yet, such multispecies assessments are needed by forest management and conservation programs to refine vulnerability assessments and to guide the choice of adaptation measures. In this paper, we propose a framework to quantitatively evaluate five key components of tree adaptive capacity to climate change: individual adaptation through phenotypic plasticity, population phenotypic diversity as influenced by genetic diversity, genetic exchange within populations, genetic exchange between populations, and genetic exchange between species. For each component, we define the main mechanisms that underlie adaptive capacity and present associated metrics that can be used as indices. To illustrate the use of this framework, we evaluate the relative adaptive capacity of 26 northeastern North American tree species using values reported in the literature. Our results show adaptive capacity to be highly variable among species and between components of adaptive capacity, such that no one species ranks consistently across all components. On average, the conifer Picea glauca and the broadleaves Acer rubrum and A. saccharinum show the greatest adaptive capacity among the 26 species we documented, whereas the conifers Picea rubens and Thuja occidentalis, and the broadleaf Ostrya virginiana possess the lowest. We discuss limitations that arise when comparing adaptive capacity among species, including poor data availability and comparability issues in metrics derived from different methods or studies. The breadth of data required for such an assessment exemplifies the multidisciplinary nature of adaptive capacity and the necessity of continued cross-collaboration to better anticipate the impacts of a changing climate.

Single-step genomic BLUP enables joint analysis of disconnected breeding programs: an example with Eucalyptus globulus Labill

Single-step GBLUP (HBLUP) efficiently combines genomic, pedigree, and phenotypic information for holistic genetic analyses of disjunct breeding populations. We combined data from two independent multigenerational Eucalyptus globulus breeding populations to provide direct comparisons across the programs and indirect predictions in environments where pedigreed families had not been evaluated. Despite few known pedigree connections between the programs, genomic relationships provided the connectivity required to create a unified relationship matrix, H, which was used to compare pedigree-based and HBLUP models. Stem volume data from 48 sites spread across three regions of southern Australia and wood quality data across 20 sites provided comparisons of model accuracy. Genotyping proved valuable for correcting pedigree errors and HBLUP more precisely defines relationships within and among populations, with relationships among the genotyped individuals used to connect the pedigrees of the two programs. Cryptic relationships among the native range populations provided evidence of population structure and evidence of the origin of landrace populations. HBLUP across programs improved the prediction accuracy of parents and genotyped individuals and enabled breeding value predictions to be directly compared and inferred in regions where little to no testing has been undertaken. The impact of incorporating genetic groups in the estimation of H will further align traditional genetic evaluation pipelines with approaches that incorporate marker-derived relationships into prediction models.

Integrative Pre-Breeding for Biotic Resistance in Forest Trees

Climate change is unleashing novel biotic antagonistic interactions for forest trees that may jeopardize populations' persistence. Therefore, this review article envisions highlighting major opportunities from ecological evolutionary genomics to assist the identification, conservation, and breeding of biotic resistance in forest tree species. Specifically, we first discuss how assessing the genomic architecture of biotic stress resistance enables us to recognize a more polygenic nature for a trait typically regarded Mendelian, an expectation from the Fisherian runaway pathogen-host concerted arms-race evolutionary model. Secondly, we outline innovative pipelines to capture and harness natural tree pre-adaptations to biotic stresses by merging tools from the ecology, phylo-geography, and omnigenetics fields within a predictive breeding platform. Promoting integrative ecological genomic studies promises a better understanding of antagonistic co-evolutionary interactions, as well as more efficient breeding utilization of resistant phenotypes.

The relevance of pedigrees in the conservation genomics era

Over the past 50 years conservation genetics has developed a substantive toolbox to inform species management. One of the most long‐standing tools available to manage genetics—the pedigree—has been widely used to characterize diversity and maximize evolutionary potential in threatened populations. Now, with the ability to use high throughput sequencing to estimate relatedness, inbreeding, and genome‐wide functional diversity, some have asked whether it is warranted for conservation biologists to continue collecting and collating pedigrees for species management. In this perspective, we argue that pedigrees remain a relevant tool, and when combined with genomic data, create an invaluable resource for conservation genomic management. Genomic data can address pedigree pitfalls (e.g., founder relatedness, missing data, uncertainty), and in return robust pedigrees allow for more nuanced research design, including well‐informed sampling strategies and quantitative analyses (e.g., heritability, linkage) to better inform genomic inquiry. We further contend that building and maintaining pedigrees provides an opportunity to strengthen trusted relationships among conservation researchers, practitioners, Indigenous Peoples, and Local Communities.

Evolution of Castanea in North America: restriction-site-associated DNA sequencing and ecological modeling reveal a history of radiation, range shifts, and disease

PREMISE

Although chestnuts and chinquapins are some of the best known and most widely loved of any plants in North America, relatively little genomic sequencing has been done, and much is still unknown about their evolution.

METHODS

We used double-digest restriction-site-associated DNA (ddRAD) sequencing data to infer the species-level phylogeny for Castanea and assess the phylogeography of the North American species using samples collected from populations that span the full extent of the species' ranges. We also constructed species distribution models using digitized herbarium specimens and observational data from field surveys.

RESULTS

We identified strong population structure within Castanea dentata (American chestnut) that reflects a stepwise northern migration since the last glacial maximum. Our species distribution models further confirmed this scenario and matched closely with the Castanea fossil pollen record. We also found significant structure within the Castanea pumila lineage, most notably a genetic cluster that corresponds to the frequently recognized Castanea pumila var. ozarkensis.

CONCLUSIONS

The two North American Castanea species have contrasting patterns of population structure, but each is typical of plant phylogeography in North America. Within the C. pumila complex, we found novel genetic structure that provides new insights about C. pumila taxonomy. Our results also identified a series of distinctive populations that will be valuable in ongoing efforts to conserve and restore chestnuts and chinquapins in North America.

Bumble bee (Bombus impatiens) survival, pollen usage, and reproduction are not affected by oxalate oxidase at realistic concentrations in American chestnut (Castanea dentata) pollen

Transgenic American chestnut trees expressing a wheat gene for oxalate oxidase (OxO) can tolerate chestnut blight, but as with any new restoration material, they should be carefully evaluated before being released into the environment. Native pollinators such as bumble bees are of particular interest: Bombus impatiens use pollen for both a source of nutrition and a hive building material. Bees are regular visitors to American chestnut flowers and likely contribute to their pollination, so depending on transgene expression in chestnut pollen, they could be exposed to this novel source of OxO during potential restoration efforts. To evaluate the potential risk to bees from OxO exposure, queenless microcolonies of bumble bees were supplied with American chestnut pollen containing one of two concentrations of OxO, or a no-OxO control. Bees in microcolonies exposed to a conservatively estimated field-realistic concentration of OxO in pollen performed similarly to no-OxO controls; there were no significant differences in survival, bee size, pollen use, hive construction activity, or reproduction. A ten-fold increase in OxO concentration resulted in noticeable but non-significant decreases in some measures of pollen usage and reproduction compared to the no-OxO control. These effects are similar to what is often seen when naturally produced secondary metabolites are supplied to bees at unrealistically high concentrations. Along with the presence of OxO in many other environmental sources, these data collectively suggest that oxalate oxidase at field-realistic concentrations in American chestnut pollen is unlikely to present substantial risk to bumble bees.

Evaluation of an Alternative Small Stem Assay for Blight Resistance in American, Chinese, and Hybrid Chestnuts (Castanea spp.)

We tested an alternative small stem assay (SSA) for blight resistance in chestnuts (Castanea spp.). Whereas standard SSAs are done by inoculating small incisions in stems, we cut off stems (4 to 5 mm diameter), inoculated the cut ends with discs of Cryphonectria parasitica inoculum, and covered them with plastic sleeves. This method was designed to be simple to implement, to consistently induce cankering, and to better enable seedlings to recover by developing shoots from the lower stem (standard SSAs delay removal of blighted stems until late in the growing season, if at all). We conducted six experiments with seedlings and orchard trees of Castanea dentata (susceptible), Castanea mollissima (resistant), and hybrids expected to vary in resistance. Experiments with seedlings and two of the three orchard experiments showed clear differentiation between susceptible and resistant types, especially >90 days postinoculation and when the orange-colored zone of the canker was measured. One orchard experiment failed to give clear results but was ended earlier (60 days) than the other experiments. We observed only two failed inoculations out of >200 performed. Comparisons with other studies suggest that this SSA method performs at least as well as the standard SSA method in distinguishing resistant and susceptible types, at least in seedlings. Survivorship after 1 year for seedlings inoculated in 2018 ranged from 70% for C. dentata to 100% for C. mollissima, and in 2019 they ranged from 40% in hybrids to 100% for C. mollissima. Deaths of seedlings after SSAs were mostly unrelated to the inoculations (e.g., root rot).

Transformation of American Chestnut (Castanea dentata (Marsh.) Borkh) Using RITA® Temporary Immersion Bioreactors and We Vitro Containers

American chestnut (Castanea dentata (Marsh.) Borkh) was almost completely wiped out by the fungal pathogen, Cryphonectria parasitica (Murrill) M.E. Barr. Another invasive pathogen, Phytophthora cinnamomi Rands, is devastating American chestnuts in the southern region of the United States. An alternative approach for controlling these pathogens is to use genetic engineering or gene editing. We successfully transformed American chestnut with a detoxifying enzyme, oxalate oxidase, to enhance blight tolerance and more recently with the Cast_Gnk2-like gene, which encodes for an antifungal protein, to be tested for P. cinnamomi putative tolerance. Eight somatic embryo lines were transformed using three methods of selection: semisolid medium in Petri plates, liquid medium in RITA® temporary immersion bioreactors, or liquid medium in We Vitro containers. No significant differences were found between the treatments. These methods will allow for further testing of transgenes and the development of enhanced pathogen resistance in chestnut. It can serve as a model for other tree species threatened by invasive pests and pathogens.

Genomic Selection for Forest Tree Improvement: Methods, Achievements and Perspectives

The breeding of forest trees is only a few decades old, and is a much more complicated, longer, and expensive endeavor than the breeding of agricultural crops. One breeding cycle for forest trees can take 20–30 years. Recent advances in genomics and molecular biology have revolutionized traditional plant breeding based on visual phenotype assessment: the development of different types of molecular markers has made genotype selection possible. Marker-assisted breeding can significantly accelerate the breeding process, but this method has not been shown to be effective for selection of complex traits on forest trees. This new method of genomic selection is based on the analysis of all effects of quantitative trait loci (QTLs) using a large number of molecular markers distributed throughout the genome, which makes it possible to assess the genomic estimated breeding value (GEBV) of an individual. This approach is expected to be much more efficient for forest tree improvement than traditional breeding. Here, we review the current state of the art in the application of genomic selection in forest tree breeding and discuss different methods of genotyping and phenotyping. We also compare the accuracies of genomic prediction models and highlight the importance of a prior cost-benefit analysis before implementing genomic selection. Perspectives for the further development of this approach in forest breeding are also discussed: expanding the range of species and the list of valuable traits, the application of high-throughput phenotyping methods, and the possibility of using epigenetic variance to improve of forest trees.

Modern Strategies to Assess and Breed Forest Tree Adaptation to Changing Climate

Studying the genetics of adaptation to new environments in ecologically and industrially important tree species is currently a major research line in the fields of plant science and genetic improvement for tolerance to abiotic stress. Specifically, exploring the genomic basis of local adaptation is imperative for assessing the conditions under which trees will successfully adapt in situ to global climate change. However, this knowledge has scarcely been used in conservation and forest tree improvement because woody perennials face major research limitations such as their outcrossing reproductive systems, long juvenile phase, and huge genome sizes. Therefore, in this review we discuss predictive genomic approaches that promise increasing adaptive selection accuracy and shortening generation intervals. They may also assist the detection of novel allelic variants from tree germplasm, and disclose the genomic potential of adaptation to different environments. For instance, natural populations of tree species invite using tools from the population genomics field to study the signatures of local adaptation. Conventional genetic markers and whole genome sequencing both help identifying genes and markers that diverge between local populations more than expected under neutrality, and that exhibit unique signatures of diversity indicative of "selective sweeps." Ultimately, these efforts inform the conservation and breeding status capable of pivoting forest health, ecosystem services, and sustainable production. Key long-term perspectives include understanding how trees' phylogeographic history may affect the adaptive relevant genetic variation available for adaptation to environmental change. Encouraging "big data" approaches (machine learning-ML) capable of comprehensively merging heterogeneous genomic and ecological datasets is becoming imperative, too.

Forest genomics: Advancing climate adaptation, forest health, productivity, and conservation

Forest ecosystems provide important ecological services and resources, from habitat for biodiversity to the production of environmentally friendly products, and play a key role in the global carbon cycle. Humanity is counting on forests to sequester and store a substantial portion of the anthropogenic carbon dioxide produced globally. However, the unprecedented rate of climate change, deforestation, and accidental importation of invasive insects and diseases are threatening the health and productivity of forests, and their capacity to provide these services. Knowledge of genetic diversity, local adaptation, and genetic control of key traits is required to predict the adaptive capacity of tree populations, inform forest management and conservation decisions, and improve breeding for productive trees that will withstand the challenges of the 21st century. Genomic approaches have well accelerated the generation of knowledge of the genetic and evolutionary underpinnings of nonmodel tree species, and advanced their applications to address these challenges. This special issue of Evolutionary Applications features 14 papers that demonstrate the value of a wide range of genomic approaches that can be used to better understand the biology of forest trees, including species that are widespread and managed for timber production, and others that are threatened or endangered, or serve important ecological roles. We highlight some of the major advances, ranging from understanding the evolution of genomes since the period when gymnosperms separated from angiosperms 300 million years ago to using genomic selection to accelerate breeding for tree health and productivity. We also discuss some of the challenges and future directions for applying genomic tools to address long-standing questions about forest trees.