The Influence of Emodin Succinyl Ethyl Ester on Non-alcoholic Steatohepatitis Induced by a Diet High in Fructose, Cholesterol, and Fat in Mice.

Nonalcoholic steatohepatitis (NASH) is a subtype of nonalcoholic fatty liver disease (NAFLD) characterized by hepatic steatosis and evidence of hepatocyte injury (ballooning) and inflammation, with or without liver fibrosis. In this study, after 12 weeks of induction, the mice were treated with emodin succinyl ethyl ester (ESEE) for four weeks at doses of 10/30/90 mg/kg/d. The blood analysis of experimental endpoints showed that ESEE exhibited significant therapeutic effects on the progression of disorders of glycolipid metabolism and the induced liver injury in the model animals. Histopathological diagnosis of the liver and total triglyceride measurements revealed that ESEE had a significant therapeutic effect on the histopathological features of nonalcoholic fatty liver disease/hepatitis, such as cellular steatosis and activation of intrahepatic inflammation. Additionally, ESEE was able to improve hepatocyte fat deposition, steatosis, and the course of intrahepatic inflammatory activity. Furthermore, it showed some inhibitory effect on liver fibrosis in the model animals. In summary, this study confirms the therapeutic effects of ESEE on the NAFLD/NASH model in C57BL/6J mice induced by a high-fat, high cholesterol, and fructose diet. These effects were observed through improvements in liver function, inhibition of fibrosis, and inflammatory responses. Changes in blood glucose levels, blood lipid metabolism, liver histopathological staining, liver fibrosis staining, and related pathological scores further supported the therapeutic effects of ESEE. Therefore, this study has important implications for the exploration of novel drugs for nonalcoholic fatty liver disease.

Common drivers shaping niche distribution and climate change responses of one hundred tree species.

Climate change is increasingly contributing to climatic mismatches, in which habitat suitability changes outpace the dispersal abilities of species. Climate niche models (CNM) have been widely used to assess such impacts on tree species. However, most studies have focused on either a single or a limited number of species, or have employed a fixed set of climate variables for multiple species. These limitations are largely due to the constraints of data availability, the complexity of the modeling algorithms, and integration approaches for the projections of diverse species. Therefore, whether specific climatic drivers determine the climatic niches of multiple tree species remains unclear. In this study, CNMs were developed for 100 economically and ecologically important tree species in China and were used to project their future distribution individually and collectively. Continentality was the predominant climate variable, affecting 71 species, followed by seasonal precipitation, which also significantly influenced over 50 species. Of the 100 tree species, the climate niche extent was projected to expand for 29 ("winners"), contract for 36 ("losers"), be stable for 27, and fluctuate for the remaining eight species. Principal component analysis showed that winners and losers were differentiated by geographic variables and the top five climatic variables, however, not by species type (deciduous vs. evergreen or conifer vs. broadleaf). The regions with the highest species richness were mainly distributed in the Hengduan Mountains, a global biodiversity hotspot, and were predicted to increase from 5.2% to 7.5% of the total area. Areas with low species richness were projected to increase from 33.0% to 42.4%. Significant shifts in species composition were anticipated in these biodiversity-rich areas, suggesting potential disruption owing to species reshuffling. This study highlights the urgent need for proactive forest management and conservation strategies to address the impacts of climate change on tree species and preserve ecological functions by mitigating climatic mismatches. In addition, this study establishes a framework to identify the common environmental drivers affecting niche distribution and evaluates the collective patterns of multiple tree species, thereby providing a scientific reference for enhanced forestry management and climate change mitigation.

Using landscape genomics to delineate seed and breeding zones for lodgepole pine.

Seed and breeding zones traditionally are delineated based on local adaptation of phenotypic traits associated with climate variables, an approach requiring long-term field experiments. In this study, we applied a landscape genomics approach to delineate seed and breeding zones for lodgepole pine. We used a gradient forest (GF) model to select environment-associated single nucleotide polymorphisms (SNPs) using three SNP datasets (full, neutral and candidate) and 20 climate variables for 1906 lodgepole pine (Pinus contorta) individuals in British Columbia and Alberta, Canada. The two GF models built with the full (28 954) and candidate (982) SNPs were compared. The GF models identified winter-related climate as major climatic factors driving genomic patterns of lodgepole pine's local adaptation. Based on the genomic gradients predicted by the full and candidate GF models, lodgepole pine distribution range in British Columbia and Alberta was delineated into six seed and breeding zones. Our approach is a novel and effective alternative to traditional common garden approaches for delineating seed and breeding zone, and could be applied to tree species lacking data from provenance trials or common garden experiments.

Adaptation to climate change through seasonal migration revealed by climatic versus demographic niche models.

Predicting the geographic range of species and their response to climatic variation and change are entwined goals in conservation and evolutionary ecology. Species distribution models (SDMs) are foundational in this effort and used to visualize the geographic range of species as the spatial representation of its realized niche. SDMs are also used to forecast range shifts under climate change, but often in the absence of empirical evidence that climate limits population growth. We explored the influence of climate on demography, seasonal migration, and the extent of the geographic range in song sparrows (Melospiza melodia), a species thought to display marked local adaptation to regional climate. To do so, we developed SDMs to predict the demographic and climate niches of migratory and resident song sparrows across our study area in western North America from California to Alaska, using 48 years of demographic data from a focal population in British Columbia and 1.2 million continental-scale citizen science observations. Spatial agreement of our demographic and climate niche models in the region of our focal population was strong (76%), supporting the hypothesis that demographic performance and the occurrence of seasonal migration varied predictably with climatic conditions. In contrast, agreement at the northern (58%) and southern (40%) extents of our study area was lower, as expected if the factors limiting population growth vary regionally. Our results support the hypothesis that local climate drives spatial variation in the occurrence of seasonal migration in song sparrows by limiting the fitness of year-round residents, and suggest that climate warming has favored range expansions and facilitated an upward shift in elevational range song sparrows that forgo seasonal migration. Our work highlights the potential role of seasonal migration in climate adaptation and limits on the reliability of climate niche models not validated with demographic data.

Metabolome and Transcriptome Analyses Reveal the Regulatory Mechanisms of Photosynthesis in Developing Ginkgo biloba Leaves.

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.

Metabolomic and transcriptomic analyses of mutant yellow leaves provide insights into pigment synthesis and metabolism in Ginkgo biloba.

BACKGROUND: Ginkgo (Ginkgo biloba L.) is an excellent landscape species. Its yellow-green leaf mutants are ideal materials for research on pigment synthesis, but the regulatory mechanism of leaf coloration in these ginkgo mutants remains unclear. RESULTS: We compared the metabolomes and transcriptomes of green and mutant yellow leaves of ginkgo over the same period in this study. The results showed that the chlorophyll content of normal green leaves was significantly higher than that of mutant yellow leaves of ginkgo. We obtained 931.52M clean reads from different color leaves of ginkgo. A total of 283 substances in the metabolic profiles were finally detected, including 50 significantly differentially expressed metabolites (DEMs). We identified these DEMs and 1361 differentially expressed genes (DEGs), with 37, 4, 3 and 13 DEGs involved in the photosynthesis, chlorophyll, carotenoid, and flavonoid biosynthesis pathways, respectively. Moreover, integrative analysis of the metabolomes and transcriptomes revealed that the flavonoid pathway contained the upregulated DEM (-)-epicatechin. Fourteen DEGs from the photosynthesis pathway were positively or negatively correlated with the DEMs. CONCLUSIONS: Our findings suggest a complex metabolic network in mutant yellow leaves. This study will provide a basis for studies of leaf color variation and regulation.

Overexpression of GbF3'5'H1 Provides a Potential to Improve the Content of Epicatechin and Gallocatechin.

The flavonoids in Ginkgo biloba L. (ginkgo) have important medicinal uses due to their antioxidant, antitumor, and blood circulation-promoting effects. However, the genetic mechanisms underlying flavonoid biosynthesis in ginkgo remain elusive. Flavonoid 3', 5'-hydroxylase (F3'5'H) is an important enzyme in flavonoid synthesis. We detected a novel differentially expressed GbF3'5'H1 gene homologous to the F3'5'H enzyme involved in the flavonoid synthesis pathway through transcriptome sequencing. In this study, we characterized this gene, performed an expression analysis, and heterologously overexpressed GbF3'5'H1 in Populus. Our results showed that GbF3'5'H1 is abundant in the leaf and highly expressed during April. We also found four metabolites closely related to flavonoid biosynthesis. Importantly, the contents of 4',5-dihydroxy-7-glucosyloxyflavanone, epicatechin, and gallocatechin were significantly higher in transgenic plants than in nontransgenic plants. Our findings revealed that the GbF3'5'H1 gene functions in the biosynthesis of flavonoid-related metabolites, suggesting that GbF3'5'H1 represents a prime candidate for future studies (e.g., gene-editing) aiming to optimize ginkgo flavonoid production, especially that of flavan-3-ols.

Transcriptional profiling of long noncoding RNAs associated with leaf-color mutation in Ginkgo biloba L.

BACKGROUND: Long noncoding RNAs (lncRNAs) play an important role in diverse biological processes and have been widely studied in recent years. However, the roles of lncRNAs in leaf pigment formation in ginkgo (Ginkgo biloba L.) remain poorly understood. RESULTS: In this study, lncRNA libraries for mutant yellow-leaf and normal green-leaf ginkgo trees were constructed via high-throughput sequencing. A total of 2044 lncRNAs were obtained with an average length of 702 nt and typically harbored 2 exons. We identified 238 differentially expressed lncRNAs (DELs), 32 DELs and 49 differentially expressed mRNAs (DEGs) that constituted coexpression networks. We also found that 48 cis-acting DELs regulated 72 target genes, and 31 trans-acting DELs regulated 31 different target genes, which provides a new perspective for the regulation of the leaf-color mutation. Due to the crucial regulatory roles of lncRNAs in a wide range of biological processes, we conducted in-depth studies on the DELs and their targets and found that the chloroplast thylakoid membrane subcategory and the photosynthesis pathways (ko00195) were most enriched, suggesting their potential roles in leaf coloration mechanisms. In addition, our correlation analysis indicates that eight DELs and 68 transcription factors (TFs) might be involved in interaction networks. CONCLUSIONS: This study has enriched the knowledge concerning lncRNAs and provides new insights into the function of lncRNAs in leaf-color mutations, which will benefit future selective breeding of ginkgo.

Geographic Variation in the Chemical Composition and Antioxidant Properties of Phenolic Compounds from Cyclocarya paliurus (Batal) Iljinskaja Leaves.

Cyclocarya paliurus has been widely used as an ingredient in functional foods in China. However, the antioxidant properties of phenolic compounds and the effect of the plant origin remain unclear. The present study evaluated the geographical variation of this plant in term of its phenolic composition and antioxidant activities based on leaf materials collected from five regions. high-performance liquid chromatography (HPLC) analysis showed that there are three major components, quercetin-3-O-glucuronide, kaempferol-3-O-glucuronide, and kaempferol-3-O-rhamnoside, and their contents varied significantly among sampling locations. The investigated phenolic compounds showed substantial antioxidant activities, both in vitro and in vivo, with the highest capacity observed from Wufeng and Jinzhongshan. Correlation analysis revealed that quercetin and kaempferol glycosides might be responsible for the antioxidant activities. Our results indicate the importance of geographic origin, with sunny hours and temperature as the main drivers affecting the accumulation of C. paliurus phenolics and their antioxidant properties.

Antidiabetic Effect of Cyclocarya paliurus Leaves Depends on the Contents of Antihyperglycemic Flavonoids and Antihyperlipidemic Triterpenoids.

Cyclocarya paliurus has been used commonly to treat diabetes in China. However, the effective components and the effect of plant origin remain unclear. In this study, C. paliurus leaves with different chemical compositions were selected from five geographical locations, and their effects on streptozotocin (STZ)-induced diabetic mice were evaluated with both ethanol and aqueous extracts. Glucose levels, lipid levels, and biomarkers of liver and kidney function were measured. The principal components of both C. paliurus ethanol and aqueous extracts from different geographical locations differed quantitatively and qualitatively. Results showed that C. paliurus extracts with better antihyperglycemic effects were characterized by higher contents of total flavonoids, especially quercetin-3-O-glucuronide and kaempferol-3-O-glucuronide. Furthermore, significantly negative correlations were found between triterpenoids contents and lipid levels. These results revealed the potential antihyperglycemic capacity of C. paliurus flavonoids and the antihyperlipidemic effect of C. paliurus triterpenoids. Thus, we suggest that the composition of C. paliurus compounds might help to design therapeutic alternatives for the treatment of diabetes mellitus. However, geographic origins and the extraction solvents can also affect the effectiveness of the treatment as these factors influence the chemical compositions and thereby the biological activities.

A closer look at novel climates: new methods and insights at continental to landscape scales.

Novel climates - emerging conditions with no analog in the observational record - are an open problem in ecological modeling. Detecting extrapolation into novel conditions is a critical step in evaluating bioclimatic projections of how species and ecosystems will respond to climate change. However, biologically informed novelty detection methods remain elusive for many modeling algorithms. To assist with bioclimatic model design and evaluation, we present a first-approximation assessment of general novelty based on a simple and consistent characterization of climate. We build on the seminal global analysis of Williams et al. (2007 PNAS, 104, 5738) by assessing of end-of-21st-century novelty for North America at high spatial resolution and by refining their standardized Euclidean distance into an intuitive Mahalanobian metric called sigma dissimilarity. Like this previous study, we found extensive novelty in end-of-21st-century projections for the warm southern margin of the continent as well as the western Arctic. In addition, we detected localized novelty in lower topographic positions at all latitudes: By the end of the 21st century, novel climates are projected to emerge at low elevations in 80% and 99% of ecoregions in the RCP4.5 and RCP8.5 emissions scenarios, respectively. Novel climates are limited to 7% of the continent's area in RCP4.5, but are much more extensive in RCP8.5 (40% of area). These three risk factors for novel climates - regional susceptibility, topographic position, and the magnitude of projected climate change - represent a priori evaluation criteria for the credibility of bioclimatic projections. Our findings indicate that novel climates can emerge in any landscape. Interpreting climatic novelty in the context of nonlinear biological responses to climate is an important challenge for future research.

Scale-dependent complementarity of climatic velocity and environmental diversity for identifying priority areas for conservation under climate change.

As most regions of the earth transition to altered climatic conditions, new methods are needed to identify refugia and other areas whose conservation would facilitate persistence of biodiversity under climate change. We compared several common approaches to conservation planning focused on climate resilience over a broad range of ecological settings across North America and evaluated how commonalities in the priority areas identified by different methods varied with regional context and spatial scale. Our results indicate that priority areas based on different environmental diversity metrics differed substantially from each other and from priorities based on spatiotemporal metrics such as climatic velocity. Refugia identified by diversity or velocity metrics were not strongly associated with the current protected area system, suggesting the need for additional conservation measures including protection of refugia. Despite the inherent uncertainties in predicting future climate, we found that variation among climatic velocities derived from different general circulation models and emissions pathways was less than the variation among the suite of environmental diversity metrics. To address uncertainty created by this variation, planners can combine priorities identified by alternative metrics at a single resolution and downweight areas of high variation between metrics. Alternately, coarse-resolution velocity metrics can be combined with fine-resolution diversity metrics in order to leverage the respective strengths of the two groups of metrics as tools for identification of potential macro- and microrefugia that in combination maximize both transient and long-term resilience to climate change. Planners should compare and integrate approaches that span a range of model complexity and spatial scale to match the range of ecological and physical processes influencing persistence of biodiversity and identify a conservation network resilient to threats operating at multiple scales.

miR-193b promotes cell proliferation by targeting Smad3 in human glioma.

Studies have shown that several miRNAs play important roles in regulating a variety of cellular processes in gliomas. In these reports, upregulation of miR-193b has been found to be associated with a poor prognosis for glioma, but its functional mechanism in glioma remains unclear. This study investigates the roles of miR-193b in glioma tumor growth. We first showed that the expression of miR-193b was elevated in both glioma samples and glioma cells. Furthermore, downregulation of miR-193b by inhibitors was statistically correlated with a decrease in cell growth and a restored G1 accumulation. Luciferase assay and Western blot analysis revealed that Smad3 is a direct target of miR-193b. To prove that miR-193b regulated cell growth through the transforming growth factor-ß (TGF-ß) pathway in glioma cells by regulating Smad3, we tested endogenous targets of the TGF-ß pathway by measuring the accumulation of p21 mRNAs after downregulation of miR-193b. The results confirmed that induction of p21 was promoted by miR-193b inhibitors in glioma cells, although this induction disappeared when Smad3 was knocked down with siRNA. Moreover, downregulation of Smad3 mitigates the miR-193b suppression of glioma proliferation. In conclusion, these results suggest that miR-193b regulated cell growth in glioma through the TGF-ß pathway by regulating Smad3. Thus, our study indicates that miR-193b promotes cell proliferation by targeting Smad3 in human glioma, which may serve as a potentially useful target for development of miRNA-based therapies in the future.

Adaptation and exogenous selection in a Picea glauca × Picea engelmannii hybrid zone: implications for forest management under climate change.

The nature of selection responsible for the maintenance of the economically and ecologically important Picea glauca × Picea engelmannii hybrid zone was investigated. Genomic, phenotypic and climatic data were used to test assumptions of hybrid zone maintenance and to model future scenarios under climate change. Genome-wide estimates of admixture based on a panel of 86 candidate gene single nucleotide polymorphisms were combined with long-term quantitative data on growth and survival (over 20 yr), as well as one-time assessments of bud burst and bud set phenology, and cold hardiness traits. A total of 15,498 individuals were phenotyped for growth and survival. Our results suggest that the P. glauca × P. engelmannii hybrid zone is maintained by local adaptation to growing season length and snowpack (exogenous selection). Hybrids appeared to be fitter than pure species in intermediate environments, which fits expectations of the bounded hybrid superiority model of hybrid zone maintenance. Adaptive introgression from parental species has probably contributed to increased hybrid fitness in intermediate habitats. While P. engelmannii ancestry is higher than P. glauca ancestry in hybrid populations, on average, selective breeding in managed hybrid populations is shifting genomic composition towards P. glauca, potentially pre-adapting managed populations to warmer climates.

Population-specific climate sensitive top height curves and their applications to assisted migration.

Growth and yield (G&Y) of forest plantations can be significantly impacted by maladaptation resulting from climate change, and assisted migration has been proposed to mitigate these impacts by restoring populations to their historic climates. However, genecology models currently used for guiding assisted migration do not account for impacts of climate change on cumulative growth and assume that responses of forest population to climate do not change with age. Using provenance trial data for interior lodgepole pine (Pinus contorta subsp. latifolia Douglas) and white spruce (Picea glauca (Moench) Voss) in western Canada, we integrated Universal Response Functions, representing the relationship of population performance with their provenance and site climates, into top height curves in a G&Y model (Growth and Yield Projection System, GYPSY) to develop population-specific climate sensitive top height curves for both species. These new models can estimate the impact of climate change on top height of local populations and populations from a range of provenances to help guide assisted migration. Our findings reveal that climate change is expected to have varying effects on forest productivity across the landscape, with some areas projected to experience a slight increase in productivity by the 2050s, while the remainder are projected to face a significant decline in productivity for both species. Adoption of assisted migration, however, with the optimal populations selected was projected to maintain and even improve productivity at the provincial scale. The findings of this study provide a novel approach to incorporating assisted migration approaches into forest management to mitigate the negative impacts of climate change.

GbFLSa overexpression negatively regulates proanthocyanin biosynthesis.

Flavonoids are important secondary metabolites with extensive pharmacological functions. Ginkgo biloba L. (ginkgo) has attracted extensive attention because of its high flavonoid medicinal value. However, little is understood about ginkgo flavonol biosynthesis. Herein, we cloned the full-length gingko GbFLSa gene (1314 bp), which encodes a 363 amino acid protein that has a typical 2-oxoglutarate (2OG)-Fe(II) oxygenase region. Recombinant GbFLSa protein with a molecular mass of 41 kDa was expressed in Escherichia coli BL21(DE3). The protein was localized to the cytoplasm. Moreover, proanthocyanins, including catechin, epicatechin, epigallocatechin and gallocatechin, were significantly less abundant in transgenic poplar than in nontransgenic (CK) plants. In addition, dihydroflavonol 4-reductase, anthocyanidin synthase and leucoanthocyanidin reductase expression levels were significantly lower than those of their CK counterparts. GbFLSa thus encodes a functional protein that might negatively regulate proanthocyanin biosynthesis. This study helps elucidate the role of GbFLSa in plant metabolism and the potential molecular mechanism of flavonoid biosynthesis.

Assessment of the impact of climate change on endangered conifer tree species by considering climate and soil dual suitability and interspecific competition.

Climate change results in the habitat loss of many conifer tree species and jeopardizes species biodiversity and forest ecological functions. Delineating suitable habitats for tree species via climate niche model (CNM) is widely used to predict the impact of climate change and develop conservation and management strategies. However, the robustness of CNM is broadly debated as it usually does not consider soil and competition factors. Here we developed a new approach to combine soil variables with CNM and evaluate interspecific competition potential in the niche overlapping areas. We used an endangered conifer species - Chamaecyparis formosensis (red cypress) - as a case study to predict the impact of climate change. We developed a novel approach to integrate the climate niche model and soil niche model predictions and considered interspecific competition to predict the impacts of climate change on tree species. Our results show that the suitable habitat for red cypress would decrease significantly in the future with an additional threat from the competition of an oak tree species. Our approach and results may represent significant implications in making conservation strategies and evaluating the impacts of climate change, and providing the direction of the refinement of the ecological niche model.

Predicting suitable habitats of Melia azedarach L. in China using data mining.

Melia azedarach L. is an important economic tree widely distributed in tropical and subtropical regions of China and some other countries. However, it is unclear how the species' suitable habitat will respond to future climate changes. We aimed to select the most accurate one among seven data mining models to predict the current and future suitable habitats for M. azedarach in China. These models include: maximum entropy (MaxEnt), support vector machine (SVM), generalized linear model (GLM), random forest (RF), naive bayesian model (NBM), extreme gradient boosting (XGBoost), and gradient boosting machine (GBM). A total of 906 M. azedarach locations were identified, and sixteen climate predictors were used for model building. The models' validity was assessed using three measures (Area Under the Curves (AUC), kappa, and overall accuracy (OA)). We found that the RF provided the most outstanding performance in prediction power and generalization capacity. The top climate factors affecting the species' suitable habitats were mean coldest month temperature (MCMT), followed by the number of frost-free days (NFFD), degree-days above 18 °C (DD > 18), temperature difference between MWMT and MCMT, or continentality (TD), mean annual precipitation (MAP), and degree-days below 18 °C (DD < 18). We projected that future suitable habitat of this species would increase under both the RCP4.5 and RCP8.5 scenarios for the 2011-2040 (2020s), 2041-2070 (2050s), and 2071-2100 (2080s). Our findings are expected to assist in better understanding the impact of climate change on the species and provide scientific basis for its planting and conservation.

Full-Length Transcriptome Sequencing and Comparative Transcriptomic Analyses Provide Comprehensive Insight Into Molecular Mechanisms of Cellulose and Lignin Biosynthesis in Cunninghamia lanceolata.

Cunninghamia lanceolata is an essential timber species that provide 20%-30% raw materials for China's timber industry. Although a few transcriptomes have been published in C. lanceolata, full-length mRNA transcripts and regulatory mechanisms behind the cellulose and lignin biosynthesis have not been thoroughly investigated. Here, PacBio Iso-seq and RNA-seq analyses were adapted to identify the full-length and differentially expressed transcripts along a developmental gradient from apex to base of C. lanceolata shoots. A total of 48,846 high-quality full-length transcripts were obtained, of which 88.0% are completed transcriptome based on benchmarking universal single-copy orthologs (BUSCO) assessment. Along stem developmental gradient, 18,714 differentially expressed genes (DEGs) were detected. Further, 28 and 125 DEGs were identified as enzyme-coding genes of cellulose and lignin biosynthesis, respectively. Moreover, 57 transcription factors (TFs), including MYB and NAC, were identified to be involved in the regulatory network of cellulose and lignin biosynthesis through weighted gene co-expression network analysis (WGCNA). These TFs are composed of a comparable regulatory network of secondary cell wall formation in angiosperms, revealing a similar mechanism may exist in gymnosperms. Further, through qRT-PCR, we also investigated eight specific TFs involved in compression wood formation. Our findings provide a comprehensive and valuable source for molecular genetics breeding of C. lanceolata and will be beneficial for molecular-assisted selection.

A comprehensive annotation dataset of intact LTR retrotransposons of 300 plant genomes.

LTR retrotransposons (LTR-RTs) are ubiquitous and represent the dominant repeat element in plant genomes, playing important roles in functional variation, genome plasticity and evolution. With the advent of new sequencing technologies, a growing number of whole-genome sequences have been made publicly available, making it possible to carry out systematic analyses of LTR-RTs. However, a comprehensive and unified annotation of LTR-RTs in plant groups is still lacking. Here, we constructed a plant intact LTR-RTs dataset, which is designed to classify and annotate intact LTR-RTs with a standardized procedure. The dataset currently comprises a total of 2,593,685 intact LTR-RTs from genomes of 300 plant species representing 93 families of 46 orders. The dataset is accompanied by sequence, diverse structural and functional annotation, age determination and classification information associated with the LTR-RTs. This dataset will contribute valuable resources for investigating the evolutionary dynamics and functional implications of LTR-RTs in plant genomes.