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Ginkgo (Ginkgo biloba L.) is a high-value medicinal tree species characterized by its flavonoids beneficial effects that are abundant in leaves. We performed a temporospatial comprehensive transcriptome and metabolome dynamics analyses of clonally propagated Ginkgo plants at four developmental stages (time: May to August) across three different environments (space) to unravel leaves flavonoids biosynthesis variation. Principal component analysis revealed clear gene expression separation across samples from different environments and leaf-developmental stages. We found that flavonoid-related metabolism was more active in the early stage of leaf development, and the content of total flavonoid glycosides and the expression of some genes in flavonoid biosynthesis pathway peaked in May. We also constructed a co-expression regulation network and identified eight GbMYBs and combining with other TF genes (3 GbERFs, 1 GbbHLH, and 1 GbTrihelix) positively regulated the expression of multiple structural genes in the flavonoid biosynthesis pathway. We found that part of these GbTFs (Gb_11316, Gb_32143, and Gb_00128) expressions was negatively correlated with mean minimum temperature and mean relative humidity, while positively correlated with sunshine duration. This study increased our understanding of the molecular mechanisms of flavonoids biosynthesis in Ginkgo leaves and provided insight into the proper production and management of Ginkgo commercial plantations.

Understanding the genetic variation and differentiation of natural populations is essential for their protection, specifically if the species status is endangered as with Pinus bungeana. Here, we used 346,840 high density and strong specificity SNP loci to carry out genetic analyses (i.e., genetic diversity, genetic structure, phylogeny, and geographical differentiation) on 52 P. bungeana individuals from 5 populations (4 natural and one artificial) representing the main regions of the species distribution in China. Genetic diversity assessment indicated a trend of genetic diversity gradual decrease from west to east across the species distribution areas. Population genetic structure, PCA and phylogenetic analyses consistently indicated that populations in the central and eastern regions were clustered together, while those from the western regions were separated. Mantel test values indicated the presence of geographic isolation among populations, an important factor contributing to the observed genetic differentiation. The maximum likelihood tree and potential migration events inferred from TreeMix analysis indicated the presence of historical genetic exchanges between the west of Qinling Mountains and the Lvliang Mountains populations. Based on the generated genetic information, in situ and ex situ conservation strategies for P.bungeana germplasm resources are proposed, these strategies could be valuable for the conservation, protection and genetic improvement of this endangered species.

Picea crassifolia Kom. is one of the timber and ecological conifers in China and its wood tracheid traits directly affect wood formation and adaptability under harsh environment. Molecular studies on P. crassifolia remain inadequate because relatively few genes have been associated with these traits. To identify markers and candidate genes that can potentially be used for genetic improvement of wood tracheid traits, we examined 106 clones of P. crassifolia, and investigated phenotypic data for 14 wood tracheid traits before specific-locus amplified fragment sequencing (SLAF-seq) was employed to perform a genome wide association study (GWAS). Subsequently, the results were used to screen single nucleotide polymorphism (SNP) loci and candidate genes that exhibited a significant correlation with the studied traits. We developed 4,058,883 SLAF-tags and 12,275,765 SNP loci, and our analyses identified a total of 96 SNP loci that showed significant correlations with three earlywood tracheid traits using a mixed linear model (MLM). Next, candidate genes were screened in the 100 kb zone (50 kb upstream, 50 kb downstream) of each of the SNP loci, whereby 67 candidate genes were obtained in earlywood tracheid traits, including 34 genes of known function and 33 genes of unknown function. We provide the most significant SNP for each trait-locus combination and candidate genes occurring within the GWAS hits. These resources provide a foundation for the development of markers that could be used in wood traits improvement and candidate genes for the development of earlywood tracheid in P. crassifolia.

Ostrya rehderiana is a famous plant species with extremely small populations. With ongoing global climate change, the extremely small populations would face more uncertainties and risks, including the loss of genetic diversity and extirpation. Thus, assessing the impact of climate change on suitable habitat of O. rehderiana is particularly important for its conservation and restoration. Here, we built niche models with climate variables and soil and human footprint variables. Furthermore, new methods were applied to avoid confounding effects between climate and soil and human footprint variables to simulate the potential habitats of O. rehderiana in current and future climates. We found that the Hargreaves climatic moisture deficit, degree-days below 0 °C, chilling degree-days, and the temperature difference between mean warmest month temperature and mean coldest month temperature, or continentality, were the most important climate factors. The topsoil USDA texture classification, topsoil cation exchange capacity of (clay), and topsoil sodicity (ESP) were the key soil factors determining the suitable distribution of O. rehderiana. Compared with soil factors, human footprint has less influence on the suitable distribution of O. rehderiana. The niche range of this species was projected to expand and shift to north in the Representative Concentration Pathway (RCP) 4.5 scenario for the 2050s. Our study results could be referenced in further extremely small populations ecological restoration studies and provide the scientific strategies for the conservation and restoration of O. rehderiana.

Floral symmetry (corolla symmetry) has important biological significance in plant genetics and evolution. However, it is often multi-dimensional and difficult to quantify. Here, we constructed a multi-dimensional data matrix [X Y Z] by extracting three qualitative variables with binary properties (X: corolla regularity of interval and coplanarity; Y: petal regularity of shape and size; Z: petal local regularity of curling and wrinkle) from different dimensions of petals (overall to individual, and then to the local): all petals (corolla), individual petals, and local areas of petals. To quantitatively express the degree of Malus corolla symmetry, these variables were then combined with weight assignments (X: 22 > Y: 21 > Z: 20) based on their contributions to the corolla symmetry and the algorithm rule of converting binary to decimal values, which facilitated the unification of qualitative and quantitative analyses. Our results revealed significant reduction in degrees of Malus corolla symmetry along the direction of local to overall. Species showed higher degree of corolla symmetry than cultivars; however, taxa with stronger corolla symmetry might not necessarily be species. These findings provide new insights into the circumscription of Malus controversial species. The matrix model should be reference for future evaluation of angiosperm flower symmetry (lack of corolla fusion).

Sustainable and efficient forestry in a rapidly changing climate is a daunting task. The sessile nature of trees makes adaptation to climate change challenging; thereby, ecological services and economic potential are under risk. Current long-term and costly gene resources management practices have been primarily directed at a few economically important species and are confined to defined ecological boundaries. Here, we present a novel in situ gene-resource management approach that conserves forest biodiversity and improves productivity and adaptation through utilizing basic forest regeneration installations located across a wide range of environments without reliance on structured tree breeding/conservation methods. We utilized 4,267 25- to 35-year-old European larch trees growing in 21 reforestation installations across four distinct climatic regions in Austria. With the aid of marker-based pedigree reconstruction, we applied multi-trait, multi-site quantitative genetic analyses that enabled the identification of broadly adapted and productive individuals. Height and wood density, proxies to fitness and productivity, yielded in situ heritability estimates of 0.23 ± 0.07 and 0.30 ± 0.07, values similar to those from traditional “structured” pedigrees methods. In addition, individual trees selected with this approach are expected to yield genetic response of 1.1 and 0.7 standard deviations for fitness and productivity attributes, respectively, and be broadly adapted to a range of climatic conditions. Genetic evaluation across broad climatic gradients permitted the delineation of suitable reforestation areas under current and future climates. This simple and resource-efficient management of gene resources is applicable to most tree species.

Local adaptation, adaptation to specialized niches and environmental clines have been extensively reported for forest trees. Investigation of the adaptive genetic variation is crucial for forest resource management and breeding, especially in the context of global climate change. Here, we utilized a Pinus yunnanensis common garden experiments established at high and low elevation sites to assess the differences in growth and survival among populations and between the two common garden sites. The studied traits showed significant variation between the two test sites and among populations, suggesting adaptive divergence. To detect genetic variation related to environment, we captured 103,608 high quality SNPs based on RNA sequencing, and used them to assess the genetic diversity and population structure. We identified 321 outlier SNPs from 131 genes showing significant divergence in allelic frequency between survival populations of two sites. Functional categories associated with adaptation to high elevation were found to be related to flavonoid biosynthesis, response to UV, DNA repair, response to reactive oxygen species, and membrane lipid metabolic process. Further investigation of the outlier genes showed overrepresentation of the flavonoid biosynthesis pathway, suggesting that this pathway may play a key role in P. yunnanensis adaptation to high elevation environments. The outlier genes identified, and their variants, provide a basic reference for advanced investigations.

Genome-wide association studies are powerful tools to elucidate the genome-to-phenome relationship. In order to explain most of the observed heritability of a phenotypic trait, a sufficient number of individuals and a large set of genetic variants must be examined. The development of high-throughput technologies and cost-efficient resequencing of complete genomes have enabled the genome-wide identification of genetic variation at large scale. As such, almost all existing genetic variation becomes available, and it is now possible to identify rare genetic variants in a population sample. Rare genetic variants that were usually filtered out in most genetic association studies are the most numerous genetic variations across genomes and hold great potential to explain a significant part of the missing heritability observed in association studies. Rare genetic variants must be identified with high confidence, as they can easily be confounded with sequencing errors. In this study, we used a pre-filtered data set of 1,014 pure Populus trichocarpa entire genomes to identify rare and common small genetic variants across individual genomes. We compared variant calls between Platypus and HaplotypeCaller pipelines, and we further applied strict quality filters for improved genetic variant identification. Finally, we only retained genetic variants that were identified by both variant callers increasing calling confidence. Based on these shared variants and after stringent quality filtering, we found high genomic diversity in P. trichocarpa germplasm, with 7.4 million small genetic variants. Importantly, 377k non-synonymous variants (5% of the total) were uncovered. We highlight the importance of genomic diversity and the potential of rare defective genetic variants in explaining a significant portion of P. trichocarpa's phenotypic variability in association genetics. The ultimate goal is to associate both rare and common alleles with poplar's wood quality traits to support selective breeding for an improved bioenergy feedstock.

To study the effect of N-P-K fertilization on Phoebe bournei seedlings’ organs dry biomass, and nutrients accumulation and allocation, and to further uncover how nutrients regulating dry biomass formation through fertilization, we utilized the “3414” experiment design. The results showed that N, P, and K fertilizer promoted dry biomass accumulation, and root, stem, and total plant N, P, and K content and accumulation in seedlings. The dry biomass accumulations of root, stem, and total plant increased first and then decreased with the increase of N, P, and K application rates, which was basically consistent with the change in dry biomass allocations and N, P, and K contents, accumulations, and allocations. Root N accumulation, root P accumulation, and total plant K accumulation were the key indicators for seedlings growth. N fertilizer had the greatest effect on total dry biomass and root N accumulation, was the most important fertilizer for the growth of Phoebe bournei seedlings, can regulate the growth of root and leaves, is beneficial to root growth at medium-low N fertilizer levels (N: 0.266–0.532 g·plant−1), and leaves growth at high N fertilizer level (N: 0.798 g·plant−1). P fertilizer rate can regulate the seedling stem growth, reaching the maximum at the medium level P application (P2O5: 0.1332 g·plant−1). K fertilizer had the greatest effect on the root P accumulation and total K accumulation, promoting K transport from leaves to root, improved root and stem growth, and inhibited leaves growth. The N, P, and K fertilizer three-factor application can better promote nutrient uptake than double-factor and single-factor fertilization, with highest dry biomass accumulation at the medium level of N, P, K fertilizer (N: 0.532 g·plant−1; P2O5: 0.1232 g·plant−1; K2O: 0.356 g·plant−1). In conclusion, N, P, and K fertilization promoted the N, P, and K absorption, increased root, stem, and leaves N, P, and K content and accumulation, and promoted the seedling dry biomass accumulation, but reversed under excessive application of N, P, and K fertilizer; and N fertilizer was beneficial to root and leaves growth, P fertilizer to stem growth, and K fertilizer to material transfer, which provided a theoretical basis for robust Phoebe bournei seedling cultivation.

The genetic efficiency of seed orchards is crucial for determining seed crops’ genetic gain and diversity. Platycladus orientalis is a conifer tree of important ecological value in China. Here, we assessed the reproductive output (fertility) variation for 166 clones in a first-generation P. orientalis seed orchard over five years and across three years for each gender (female: 2017, 2018, and 2020 and male: 2017, 2019, and 2021). Fertility variation and genetic diversity parameters were estimated for each gender-year combination. The reproductive output (fertility) variation differed among years, provinces, clones nested within provinces, and ramets within clones. We observed asymmetry in the gender reproductive output and parental imbalance and determined their profound effects on the genetic diversity of these seed crops. The maleness index revealed the existence of female-biased or male-biased clones. When seeds from multiple individuals and years were blended, we found an increase in the effective number of parents (Np) and in genetic diversity (GD), and a reduced fertility variation (Ψ) in the seed orchard. When we set the effective number of parents (Np) to 30, the GD of the seed orchard could be maintained at more than 95%. Thus, achieving genetic diversity balance in seed production can be accomplished through monitoring the fertility variation of orchards and through the utilization of the thereby generated information for the advanced generation of seed orchards.

Abstract Background Genomic selection (GS) can offer unprecedented gains, in terms of cost efficiency and generation turnover, to forest tree selective breeding; especially for late expressing and low heritability traits. Here, we used: 1) exome capture as a genotyping platform for 1372 Douglas-fir trees representing 37 full-sib families growing on three sites in British Columbia, Canada and 2) height growth and wood density (EBVs), and deregressed estimated breeding values (DEBVs) as phenotypes. Representing models with (EBVs) and without (DEBVs) pedigree structure. Ridge regression best linear unbiased predictor (RR-BLUP) and generalized ridge regression (GRR) were used to assess their predictive accuracies over space (within site, cross-sites, multi-site, and multi-site to single site) and time (age-age/ trait-trait). Results The RR-BLUP and GRR models produced similar predictive accuracies across the studied traits. Within-site GS prediction accuracies with models trained on EBVs were high (RR-BLUP: 0.79–0.91 and GRR: 0.80–0.91), and were generally similar to the multi-site (RR-BLUP: 0.83–0.91, GRR: 0.83–0.91) and multi-site to single-site predictive accuracies (RR-BLUP: 0.79–0.92, GRR: 0.79–0.92). Cross-site predictions were surprisingly high, with predictive accuracies within a similar range (RR-BLUP: 0.79–0.92, GRR: 0.78–0.91). Height at 12 years was deemed the earliest acceptable age at which accurate predictions can be made concerning future height (age-age) and wood density (trait-trait). Using DEBVs reduced the accuracies of all cross-validation procedures dramatically, indicating that the models were tracking pedigree (family means), rather than marker-QTL LD. Conclusions While GS models’ prediction accuracies were high, the main driving force was the pedigree tracking rather than LD. It is likely that many more markers are needed to increase the chance of capturing the LD between causal genes and markers.

Soil bacteria play a key role in the plant–soil system and can regulate the growth of Phoebe bournei seedlings under fertilization. However, there are few reports on how soil bacteria respond to fertilization and regulate seedling growth. This study adopted the “3414” field fertilization experiment, combined with soil microbial sequencing, nutrient contents, and biomass measurement, to explore the changes of soil chemical properties and bacterial structure under different NPK fertilization conditions and to establish the coupling relationship between soil bacteria, soil nutrients, and plant growth. The results showed that NPK fertilization decreased soil pH; increased soil N, P, and K content; reduced bacterial diversity and abundance; promoted the growth of dominant bacterial species; and enhanced Phoebe bournei seedlings’ soil N, P, and K elements. NPK fertilization promoted Proteobacteria growth, especially of three genera (Methylobacterium, Sphingobium, and Acinetobacter) and Actinobacteria, while it decreased Acidobacteria and Chloroflexi. By reducing the ratio of N to K and increasing P, NPK fertilization can slow soil acidification, promote bacterial reproduction, maintain P. bournei seedlings’ soil ecological stability, and balance the seedlings’ growth and sustainable soil utilization. AD3, Pseudomonas, and Rhodanobacter can be used as the marker species for N, P, and K fertilization, respectively, while Methylobacterium, Brevundimonas, Acinetobacter, and Sphingobium can be used as indicator species for soil pH and soil N, P, and K content changes, respectively. These results provided a theoretical basis and technical guidance for the effective fertilization and cultivation of robust P. bournei seedlings.

Abstract Background Camellia species are ancient oilseed plants with a history of cultivation over two thousand years. Prior to oil extraction, natural seed drying is often practiced, a process affecting fatty acid quality and quantity. MicroRNAs (miRNA) of lipid metabolism associated with camellia seed natural drying are unexplored. To obtain insight into the function of miRNAs in lipid metabolism during natural drying, Illumina sequencing of C. oleifera and C. meiocarpa small-RNA was conducted. Results A total of 274 candidate miRNAs were identified and 3733 target unigenes were annotated by performing a BLASTX. Through integrated GO and KEGG function annotation, 23 miRNA regulating 131 target genes were identified as lipid metabolism, regulating fatty acid biosynthesis, accumulation and catabolism. We observed one, two, and four miRNAs of lipid metabolism which were specially expressed in C. Meiocarpa, C. oleifera, and the two species collectively, respectively. At 30% moisture contents, C. meiocarpa and C. oleifer produced nine and eight significant differentially expressed miRNAs, respectively, with high fatty acid synthesis and accumulation activities. Across the two species, 12 significant differentially expressed miRNAs were identified at the 50% moisture content. Conclusions Sequencing of small-RNA revealed the presence of 23 miRNAs regulating lipid metabolism in camellia seed during natural drying and permitted comparative miRNA profiles between C. Meiocarpa and C. oleifera. Furthermore, this study successfully identified the best drying environment at which the quantity and quality of lipid in camellia seed are at its maximum.

Species–area relationship has been widely addressed on many plant communities, but very few have conducted on epiphytic communities. Epiphytic plants are plentiful on ancient tea trees (Camelia sinensis var. assamica) in the well-known Jingmai tea plantation area, Langcang region of Yunnan Province, SW China, and add to the plant community biodiversity. We investigated 343 tea trees with various ground diameter, canopy area, under branch height, and tree height. A total of 146 vascular epiphytic plants, belonging to 19 species in seven families were recorded from the trunk or branches of 93 (27.11%) investigated trees. We examined in situ abundance, richness, and diversity (Shannon–Weiner index) of the recorded vascular epiphytes, and their relationships to tree variables. Our results showed that the distribution (abundance, richness, and diversity) of epiphytic plants are significantly related to the canopy area (p

Maximization of genetic gain in forest tree breeding programs is contingent on the accuracy of the predicted breeding values and precision of the estimated genetic parameters. We investigated the effect of the combined use of contemporary pedigree information and genomic relatedness estimates on the accuracy of predicted breeding values and precision of estimated genetic parameters, as well as rankings of selection candidates, using single-step genomic evaluation (HBLUP). In this study, two traits with diverse heritabilities [tree height (HT) and wood density (WD)] were assessed at various levels of family genotyping efforts (0, 25, 50, 75, and 100%) from a population of white spruce (Picea glauca) consisting of 1694 trees from 214 open-pollinated families, representing 43 provenances in Québec, Canada. The results revealed that HBLUP bivariate analysis is effective in reducing the known bias in heritability estimates of open-pollinated populations, as it exposes hidden relatedness, potential pedigree errors, and inbreeding. The addition of genomic information in the analysis considerably improved the accuracy in breeding value estimates by accounting for both Mendelian sampling and historical coancestry that were not captured by the contemporary pedigree alone. Increasing family genotyping efforts were associated with continuous improvement in model fit, precision of genetic parameters, and breeding value accuracy. Yet, improvements were observed even at minimal genotyping effort, indicating that even modest genotyping effort is effective in improving genetic evaluation. The combined utilization of both pedigree and genomic information may be a cost-effective approach to increase the accuracy of breeding values in forest tree breeding programs where shallow pedigrees and large testing populations are the norm.

Abstract Seed dormancy and size are two important life‐history traits that interplay as adaptation to varying environmental settings. As evolution of both traits involves correlated selective pressures, it is of interest to comparatively investigate the evolution of the two traits jointly as well as independently. We explore evolutionary trajectories of seed dormancy and size using adaptive dynamics in scenarios of deterministic or stochastic temperature variations. Ecological dynamics usually result in unbalanced population structures, and temperature shifts or fluctuations of high magnitude give rise to more balanced ecological structures. When only seed dormancy evolves, it is counter‐selected and temperature shifts hasten this evolution. Evolution of seed size results in the fixation of a given strategy and evolved seed size decreases when seed dormancy is lowered. When coevolution is allowed, evolutionary variations are reduced while the speed of evolution becomes faster given temperature shifts. Such coevolution scenarios systematically result in reduced seed dormancy and size and similar unbalanced population structures. We discuss how this may be linked to the system stability. Dormancy is counter‐selected because population dynamics lead to stable equilibrium, while small seeds are selected as the outcome of size‐number trade‐offs. Our results suggest that unlike random temperature variation between generations, temperature shifts with high magnitude can considerably alter population structures and accelerate life‐history evolution. This study increases our understanding of plant evolution and persistence in the context of climate changes.

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

Ginkgo (Ginkgo biloba L.) is a deciduous tree species with high timber, medicinal, ecological, ornamental, and scientific values, and is widely cultivated worldwide. However, for such an important tree species, the regulatory mechanisms involved in the photosynthesis of developing leaves remain largely unknown. Here, we observed variations in light response curves (LRCs) and photosynthetic parameters (photosynthetic capacity (Pnmax) and dark respiration rate (Rd)) of leaves across different developmental stages. We found the divergence in the abundance of compounds (such as 3-phospho-d-glyceroyl phosphate, sedoheptulose-1,7-bisphosphate, and malate) involved in photosynthetic carbon metabolism. Additionally, a co-expression network was constructed to reveal 242 correlations between transcription factors (TFs) and photosynthesis-related genes (p < 0.05, |r| > 0.8). We found that the genes involved in the photosynthetic light reaction pathway were regulated by multiple TFs, such as bHLH, WRKY, ARF, IDD, and TFIIIA. Our analysis allowed the identification of candidate genes that most likely regulate photosynthesis, primary carbon metabolism, and plant development and as such, provide a theoretical basis for improving the photosynthetic capacity and yield of ginkgo trees.

Identifying the ecological processes determining spatial variation in community composition and structure is a central issue in arid areas, especially in the face of climate change. This study aims to estimate how environmental and spatial processes jointly determine vegetation attributes across scales in the Min dry valley, one of the dry valleys in Hengduan Mountainous region suffering severe ecological degradation. A total of 48 plots along slope transects were investigated at three sites along the dry valley, with vegetation and environmental information gathered. Distance-based Moran’s eigenvector maps (dbMEM) was used to extract local spatial variables, while geographic coordinates were used as regional spatial variables. We used redundancy analysis (RDA) and variation partitioning to detect the relative importance of environmental and spatial processes in influencing community composition and vegetation structure (including biomass, coverage, height, density, α and β diversity), and to identify the most determinant environmental variables at different spatial scales. Results showed that both environmental and spatial processes accounted for significant and comparable variations in both vegetation composition and structure. Local spatial variables provided significant and comparable contribution as regional spatial variables to vegetation composition, while provided more contribution than regional spatial variables to vegetation structure. Topography had an overriding effect relative to soil on both vegetation composition and structure. Multi-scale analyses showed elevation was the most important variable (associated with soil moisture and nutrient) at the regional scale; while microtopography, especially slope aspect and shape, dominated at the local scale. We also demonstrated how vegetation composition and structure varied along environmental gradients. The study revealed the overriding role of topography in determining vegetation attributes in this mountainous dry valley, highlighting the advantage of multi-scale spatial analysis for better understanding spatial variation in vegetation pattern and with their important implications for biodiversity conservation and ecological management in the arid mountain areas.

The open-pollinated (OP) family testing combines the simplest known progeny evaluation and quantitative genetics analyses as candidates’ offspring are assumed to represent independent half-sib families. The accuracy of genetic parameter estimates is often questioned as the assumption of “half-sibling” in OP families may often be violated. We compared the pedigree- vs. marker-based genetic models by analysing 22-yr height and 30-yr wood density for 214 white spruce [Picea glauca (Moench) Voss] OP families represented by 1694 individuals growing on one site in Quebec, Canada. Assuming half-sibling, the pedigree-based model was limited to estimating the additive genetic variances which, in turn, were grossly overestimated as they were confounded by very minor dominance and major additive-by-additive epistatic genetic variances. In contrast, the implemented genomic pairwise realized relationship models allowed the disentanglement of additive from all nonadditive factors through genetic variance decomposition. The marker-based models produced more realistic narrow-sense heritability estimates and, for the first time, allowed estimating the dominance and epistatic genetic variances from OP testing. In addition, the genomic models showed better prediction accuracies compared to pedigree models and were able to predict individual breeding values for new individuals from untested families, which was not possible using the pedigree-based model. Clearly, the use of marker-based relationship approach is effective in estimating the quantitative genetic parameters of complex traits even under simple and shallow pedigree structure.

Phoebe bournei is a rare and endangered woody species and the success of its plantation development is dependent upon proper seedling cultivation. This study explored the regulation of N, P and K fertilizer and the interaction of these macronutrients on the growth of Phoebe bournei seedlings. To determine the optimum rate and ratio of N–P–K fertilizer in seedling cultivation, we used the unique “3414” incomplete orthogonal regression design to evaluate the effects of N–P–K fertilization on seedling morphological development. One-year-old Phoebe bournei bareroot seedlings were grown for one growing season under the defined fertilization regime, with their morphological development determined by measuring seedling attributes—root, stem, leaves and total biomass, root collar diameter and seedling height. These attributes were then combined to calculate the following indices: height-diameter ratio, shoot-root ratio and the seedling quality index (QI). Results showed that the N–P–K fertilizer had significant and beneficial effect on seedling cultivation. N effect was highest, followed by K and P. The three-way N×P×K interaction effect was strong, and the two-way interactions effect was highest for N×P, followed by P×K and N×K. At the “2” level of N (0.532 g·plant−1), P (P2O5, 0.133 g·plant−1), and K fertilizer (K2O, 0.356 g·plant−1), seedling growth and biomass accumulation were at their maximum. Unary, binary, and ternary quadratic fertilizer effect function equations of QI were established. Through comparative analysis, the ternary quadratic model was the optimal model and through a simulation–optimization, the optimal N–P–K fertilizer rates were 0.373~0.420 g·plant−1 (N), 0.086~0.106 g·plant−1 (P2O5), 0.243~0.280 g·plant−1 (K2O), with a N–P–K ratio of 1:0.20:0.43~1:0.65:0.75.

Cytokinins play important roles in the growth and development of plants. Physiological and photosynthetic characteristics are common indicators to measure the growth and development in plants. However, few reports have described the molecular mechanisms of physiological and photosynthetic changes in response to cytokinin, particularly in woody plants. DNA methylation is an essential epigenetic modification that dynamically regulates gene expression in response to the external environment. In this study, we examined genome-wide DNA methylation variation and transcriptional variation in poplar (Populus tomentosa) after short-term treatment with the synthetic cytokinin 6-benzylaminopurine (6-BA). We identified 460 significantly differentially methylated regions (DMRs) in response to 6-BA treatment. Transcriptome analysis showed that 339 protein-coding genes, 262 long non-coding RNAs (lncRNAs), and 15,793 24-nt small interfering RNAs (siRNAs) were differentially expressed under 6-BA treatment. Among these, 79% were differentially expressed between alleles in P. tomentosa, and 102,819 allele-specific expression (ASE) loci in 19,200 genes were detected showing differences in ASE levels after 6-BA treatment. Combined DNA methylation and gene expression analysis demonstrated that DNA methylation plays an important role in regulating allele-specific gene expression. To further investigate the relationship between these 6-BA-responsive genes and phenotypic variation, we performed SNP analysis of 460 6-BA-responsive DMRs via re-sequencing using a natural population of P. tomentosa, and we identified 206 SNPs that were significantly associated with growth and wood properties. Association analysis indicated that 53% of loci with allele-specific expression had primarily dominant effects on poplar traits. Our comprehensive analyses of P. tomentosa DNA methylation and the regulation of allele-specific gene expression suggest that DNA methylation is an important regulator of imbalanced expression between allelic loci.

Traditional gene-resource management programs for forest trees are long-term endeavors requiring sustained organizational commitment covering extensive landscapes. While successful in maintaining adaptation, genetic diversity and capturing traditional growth attributes gains, these programs are dependent on rigid methods requiring elaborate mating schemes, thus making them slow in coping with climate change challenges. Here, we review the significance of Norway spruce in the boreal region and its current management practices. Next, we discuss opportunities offered by novel technologies and, with the use of computer simulations, we propose and evaluate a dynamic landscape gene-resource management in Norway. Our suggested long-term management approach capitalizes on: (1) existing afforestation activities, natural crosses, and DNA-based pedigree assembly to create structured pedigree for evaluation, thus traditional laborious control crosses are avoided and (2) landscape level genetic evaluation, rather than localized traditional progeny trials, allowing for screening of adapted individuals across multiple environmental gradients under changing climate. These advantages lead to greater genetic response to selection in adaptive traits without the traditional breeding and testing scheme, facilitating conservation of genetic resources within the breeding population of the most important forest tree species in Norway. The use of in situ selection from proven material exposed to realistic conditions over vast territories has not been conducted in forestry before. Our proposed approach is in contrast to worldwide current programs, where genetic evaluation is constrained by the range of environments where testing is conducted, which may be insufficient to capture the broad environmental variation necessary to tackle adaptation under changing climate.

While DNA methylation carries genetic signals and is instrumental in the evolution of organismal complexity, small RNAs (sRNAs), ~18–24 ribonucleotide (nt) sequences, are crucial mediators of methylation as well as gene silencing. However, scant study deals with sRNA evolution via featuring their expression dynamics coupled with species of different evolutionary time. Here we report an atlas of sRNAs and microRNAs (miRNAs, single-stranded sRNAs) produced over time at seed-set of two major spermatophytes represented by populations of Picea glauca and Arabidopsis thaliana with different seed-set duration. We applied diverse profiling methods to examine sRNA and miRNA features, including size distribution, sequence conservation and reproduction-specific regulation, as well as to predict their putative targets. The top 27 most abundant miRNAs were highly overlapped between the two species (e.g., miR166,−319 and−396), but in P. glauca, they were less abundant and significantly less correlated with seed-set phases. The most abundant sRNAs in libraries were deeply conserved miRNAs in the plant kingdom for Arabidopsis but long sRNAs (24-nt) for P. glauca. We also found significant difference in normalized expression between populations for population-specific sRNAs but not for lineage-specific ones. Moreover, lineage-specific sRNAs were enriched in the 21-nt size class. This pattern is consistent in both species and alludes to a specific type of sRNAs (e.g., miRNA, tasiRNA) being selected for. In addition, we deemed 24 and 9 sRNAs in P. glauca and Arabidopsis, respectively, as sRNA candidates targeting known adaptive genes. Temperature had significant influence on selected gene and miRNA expression at seed development in both species. This study increases our integrated understanding of sRNA evolution and its potential link to genomic architecture (e.g., sRNA derivation from genome and sRNA-mediated genomic events) and organismal complexity (e.g., association between different sRNA expression and their functionality).

Molecular markers have proven to be invaluable tools for assessing plants’ genetic resources by improving our understanding with regards to the distribution and the extent of genetic variation within and among species. Recently developed marker technologies allow the uncovering of the extent of the genetic variation in an unprecedented way through increased coverage of the genome. Markers have diverse applications in plant sciences, but certain marker types, due to their inherent characteristics, have also shown their limitations. A combination of diverse marker types is usually recommended to provide an accurate assessment of the extent of intra- and inter-population genetic diversity of naturally distributed plant species on which proper conservation directives for species that are at risk of decline can be issued. Here, specifically, natural populations of forest trees are reviewed by summarizing published reports in terms of the status of genetic variation in the pure species. In general, for outbred forest tree species, the genetic diversity within populations is larger than among populations of the same species, indicative of a negligible local spatial structure. Additionally, as is the case for plants in general, the diversity at the phenotypic level is also much larger than at the marker level, as selectively neutral markers are commonly used to capture the extent of genetic variation. However, more and more, nucleotide diversity within candidate genes underlying adaptive traits are studied for signatures of selection at single sites. This adaptive genetic diversity constitutes important potential for future forest management and conservation purposes.

Knowledge about the local adaptation and response of forest tree populations to the climate is important for assessing the impact of climate change and developing adaptive genetic resource management strategies. However, such information is not available for most plant species. Here, based on 69 provenances tested at 19 common garden experimental sites, we developed a universal response function (URF) for tree height at seven years of age for the important and wide-spread native Chinese tree species Platycladus orientalis (L.) Franco. URF was recently used to predict the potential growth response of a population originating from any climate and growing in any climate conditions. The developed model integrated both genetic and environmental effects, and explained 55% of the total variation in tree height observed among provenances and test sites in China. We found that local provenances performed better than non-local counterparts in habitats located in central, eastern, and southwestern China, showing the evidence of local adaptation as compared to other regions. In contrast, non-local provenances outperformed local ones in peripheral areas in northern and northwestern China, suggesting an adaptational lag in these areas. Future projections suggest that the suitable habitat areas of P. orientalis would expand by 15%−39% and shift northward by 0.8−3 degrees in latitude; however, the projected tree height of this species would decline by 4%−8% if local provenances were used. If optimal provenances were used, tree height growth could be improved by 13%−15%, along with 59%−71% suitable habitat expansion. Thus, assisted migration with properly selected seed sources would be effective in avoiding maladaptation in new plantations under a changing climate for P. orientalis.

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

Currently, there has been an increasing demand on seed orchard designs with respect to mitigating inbreeding in advanced generations or facing severe mortality at sites. Optimum Neighborhood Algorithm design (ONA) excels in solving these issues, as shown in two case studies. The first demonstrates the application of the ONA for populating empty positions in an existing orchard. Following this concept, the ONA can be used for upgrading existing orchards, where only high-value parents are retained and new parents are introduced, thus avoiding the genetic penalty associated with the establishment of new-generation seed orchards. The second illustrates benefits of combining the ONA with the Minimum Inbreeding (MI) seed orchard design. Utilizing the MI, distances among clonal rows of selected clones were maximized on the orchard grid while the remaining single-tree positions were populated by ONA.

As part of a multi-year monitoring study of pollination dynamics in a second generation Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) seed orchard, we estimated with the aid of eight microsatellite markers three important reproductive biology characteristics affecting the genetic worth and diversity of seed crops; namely parental reproductive success, pollen contamination, and selfing rate. The obtained results were compared to those from two previous years to gauge appropriate seed crop management practices and ultimately allow approximate generalization of seed crop genetic quality. We determined that 80% of parental gametes were produced by 52% of the parents, 13% of paternal gametes resulted from pollen contamination (i.e., gene flow), and 12% of the seed were the product of selfing. The obtained results were in line with those observed for 2005 and 2009 where 80% of gametes being produced by 37–48% of the parents, 10–18% pollen contamination, and 15–17% selfing rate. The observed reproductive biology parameters differences are attributable to the various crop management practices implemented (i.e., bloom delay and supplemental-mass-pollination) across years and calls for justification due to the observed minimal differences on seed crops genetic quality.

Climate niche modeling has been widely used to assess the impact of climate change on forest trees at the species level. However, geographically divergent tree populations are expected to respond differently to climate change. Considering intraspecific local adaptation in modeling species responses to climate change will thus improve the credibility and usefulness of climate niche models, particularly for genetic resources management. In this study, we used five Platycladus orientalis (L.) seed zones (Northwestern; Northern; Central; Southern; and Subtropical) covering the entire species range in China. A climate niche model was developed and used to project the suitable climatic conditions for each of the five seed zones for current and various future climate scenarios (Representative Concentration Pathways: RCP2.6, RCP4.5, RCP6.0, and RCP8.5). Our results indicated that the Subtropical seed zone would show consistent reduction for all climate change scenarios. The remaining seed zones, however, would experience various degrees of expansion in suitable habitat relative to their current geographic distributions. Most of the seed zones would gain suitable habitats at their northern distribution margins and higher latitudes. Thus, we recommend adjusting the current forest management strategies to mitigate the negative impacts of climate change.