Background: Camellia oleifera (C.oleifera) is one of the most important wood oil species in the world. C.oleifera was propagated by nurse seedling grafting. Since the morphology of rootstocks has a significant impact on grafting efficiency and seedling quality, it is necessary to understand the molecular mechanism of morphogenesis for cultivating high-quality and controllable rootstocks. However, the genomic resource for this species is relatively limited, which hinders us from fully understanding the molecular mechanisms of seed germination in C.oleifera. Results: In this paper, using transcriptome sequencing, we measured the gene expression in the C.oleifera cotyledon in different stages of development and the global gene expression profiles. Approximately 45.4 gigabases (GB) of paired-end clean reads were assembled into 113,582 unigenes with an average length of 396 bp. Six public protein databases annotate 61.5% (68,217) of unigenes. We identified 11,391 differentially expressed genes (DEGs) throughout different stages of germination. Enrichment analysis revealed that DEGs were mainly involved in hormone signal transduction and starch sucrose metabolism pathways. The gravitropism regulator UNE10, the meristem regulators STM, KNAT1, PLT2, and root-specific transcription factor WOX11 all have higher gene expression levels in the CAM2 stage (seed soaking), which indicates that the cotyledon-regulated program for germination had initiated when the seeds were imbibition. Our data showed differentially reprogrammed to multiple hormone-related genes in cotyledons during C.oleifera seed germination. Conclusion: Cotyledons play vital roles, both as the main nutrient provider and as one primary instructor for seed germination and seedling growth. Together, our study will significantly enrich the genomic resources of Camellia and help us understand the molecular mechanisms of the development in the seed germination and seedling growth of C.oleifera. It is helpful to culture standard and superior quality rootstock for C.oleifera breeding.

Camellia oleifera is one of the essential wood oil trees in the world. C.oleifera was propagated by nurse seedling grafting. Since the scion of C.oleifera had a significant regulated effect on the properties of rootstock after grafting and impacted on the growth of the grafted seedlings, it was necessary to understand the characteristics of buds among varieties to cultivate high-quality grafted seedlings. The metabolome was thought to be a powerful tool for understanding connecting phenotype-genotype interactions, which has an important impact on plant growth and development. In this study, UPLC-MS was used to determine the metabolites of the apical buds of CL3, CL4, CL40, and CL53 spring shoots after 30 days of sprout and to measure the growth characteristics of roots and stems after grafting. Metabolomics analysis revealed 554 kinds of metabolites were significant differences among four varieties, and 29 metabolic pathways were identified to have significant changes (p< 0.05), including carboxylic acids and derivatives, fatty Acyls, organooxygen compounds, and prenol lipids metabolites. The metabolites appeared in all varieties, including phenethyl rutinoside in glycosyl compounds and hovenidulcioside A1 in terpene glycosides. Metabolite–metabolite correlations in varieties revealed more complex patterns in relation to bud and enabled the recognition of key metabolites (e.g., Glutamate, (±)Catechin, GA₅₂, ABA, and cs-Zeatin) affecting grafting and growth ability. Each variety has a unique metabolite type and correlation network relationship. Differentiated metabolites showed different growth trends for development after grafting. Many metabolites regulate the growth of scions in buds before grafting, which plays a crucial role in the growth of seedlings after grafting. It not only regulates the growth of roots but also affects the development of this stem. Finally, those results were associated with the genetic background of each cultivar, showing that metabolites could be potentially used as indicators for the genetic background, indicating that metabolites could potentially be used as indicators for seedling growth characteristics. Together, this study will enrich the theoretical basis of seedling growth and lay a foundation for further research on the molecular regulation mechanism interaction between rootstock and scion, rootstock growth, and the development of grafted seedlings after grafting.

Background: Camellia oleifera, an essential woody oil tree in China, propagates through grafting. However, in production, it has been found that the interaction between rootstocks and scions may affect fruit characteristics. Therefore, it is necessary to predict fruit characteristics after grafting to identify suitable rootstock types. Methods: This study used Deep Neural Network (DNN) methods to analyze the impact of 106 6-year-old grafting combinations on the characteristics of C.oleifera, including fruit and seed characteristics, and fatty acids. The prediction of characteristics changes after grafting was explored to provide technical support for the cultivation and screening of specialized rootstocks. After determining the unsaturated fat acids, palmitoleic acid C16:1, cis-11 eicosenoic acid C20:1, oleic acid C18:1, linoleic acid C18:2, linolenic acid C18:3, kernel oil content, fruit height, fruit diameter, fresh fruit weight, pericarp thickness, fresh seed weight, and the number of fresh seeds, the DNN method was used to calculate and analyze the model. The model was screened using the comprehensive evaluation index of Mean Absolute Error (MAPE), determinate correlation R² and and time consumption. Results: When using 36 neurons in 3 hidden layers, the deep neural network model had a MAPE of less than or equal to 16.39% on the verification set and less than or equal to 13.40% on the test set. Compared with traditional machine learning methods such as support vector machines and random forests, the DNN method demonstrated more accurate predictions for fruit phenotypic characteristics, with MAPE improvement rates of 7.27 and 3.28 for the 12 characteristics on the test set and maximum R² improvement values of 0.19 and 0.33. In conclusion, the DNN method developed in this study can effectively predict the oil content and fruit phenotypic characteristics of C. oleifera, providing a valuable tool for predicting the impact of grafting combinations on the fruit of C. oleifera.

The phenotyping of Pinus massoniana seedlings is essential for breeding, vegetation protection, resource investigation, and so on. Few reports regarding estimating phenotypic parameters accurately in the seeding stage of Pinus massoniana plants using 3D point clouds exist. In this study, seedlings with heights of approximately 15-30 cm were taken as the research object, and an improved approach was proposed to automatically calculate five key parameters. The key procedure of our proposed method includes point cloud preprocessing, stem and leaf segmentation, and morphological trait extraction steps. In the skeletonization step, the cloud points were sliced in vertical and horizontal directions, gray value clustering was performed, the centroid of the slice was regarded as the skeleton point, and the alternative skeleton point of the main stem was determined by the DAG single source shortest path algorithm. Then, the skeleton points of the canopy in the alternative skeleton point were removed, and the skeleton point of the main stem was obtained. Last, the main stem skeleton point after linear interpolation was restored, while stem and leaf segmentation was achieved. Because of the leaf morphological characteristics of Pinus massoniana, its leaves are large and dense. Even using a high-precision industrial digital readout, it is impossible to obtain a 3D model of Pinus massoniana leaves. In this study, an improved algorithm based on density and projection is proposed to estimate the relevant parameters of Pinus massoniana leaves. Finally, five important phenotypic parameters, namely plant height, stem diameter, main stem length, regional leaf length, and total leaf number, are obtained from the skeleton and the point cloud after separation and reconstruction. The experimental results showed that there was a high correlation between the actual value from manual measurement and the predicted value from the algorithm output. The accuracies of the main stem diameter, main stem length, and leaf length were 93.5%, 95.7%, and 83.8%, respectively, which meet the requirements of real applications.

Background: Camellia chekiangoleosa is the most widely planted red-flowered and large-fruited oil-camellia species, with high value in edible oil production and landscaping. To better understand the weak scion development and slow graft-union healing underlying grafting propagation challenges in C. chekiangoleosa, we conducted temporal RNA-seq on current-year shoots with five time points determined according to changes in cell wall composition, aiming to reveal dynamic developmental regulation. Results: Analysis of temporal expression characteristics of genome-wide genes and differentially expressed genes (DEGs) revealed that genes differentially patterned between stem and apical bud were enriched in functions related to cell division and differentiation, hormone responses, and vascular or flower development. Coexpression network analysis revealed that red/far-red light and gibberellin (GA) signaling were closely correlated with flowering development in C. chekiangoleosa shoots. We further analyzed a unique module showing a negative correlation between the module and traits (cell wall composition, i.e., lignin, cellulose, and hemicellulose content). Genes in the top-scored sub-cluster of this module were enriched in shoot development-related processes, including cell wall dynamics, xylem development, secondary cell wall biogenesis, lignin biosynthesis, and procambium histogenesis. WOX4 and PXY, known markers of cambium cells, were identified as key hub genes, along with the actin-binding protein WLIM1. These coexpressed hub genes associated with vascular system development peaked in June in stems and were validated by qRT-PCR, suggesting that June may be an optimal grafting season for C. chekiangoleosa. Conclusions: Integrating transcriptomics and physiology defined the dynamic signature of changes in composition of cell wall and gene activity during the development of current-year shoots in C. chekiangoleosa. Our findings provide insights into a potential molecular strategy for breeders, targeting key regulators specific to cambium differentiation, and physiological strategy for hormone or light supplied artificially to enhance grafting productivity of C. chekiangoleosa.

Camellia chekiangoleosa Hu. is a unique woody oil tree with significant economic and ornamental value in China, but the fruit is easily sunburned in low-altitude areas. However, few studies on their sunburn mechanism, especially the types and content of endogenous hormones with stress resistance, have not been reported, making it challenging to take reasonable preventive measures. Here, we analyzed the endogenous hormones before sunburn and found that salicylic acid (SA) and gibberellins (GAs) were very significantly correlated between pericarp and seed kernel. However, there weren't closely related to abscisic acid (ABA), auxin, jasmonic acids (JAs), and cytokinin. The content of indole-3-carboxylic acid (ICA) and 3-indolebutyric acid (IBA) in the pericarp was higher than in seed kernel, and IBA was only found in the pericarp. GAs in seed kernel were higher than that in pericarp, and GA₃ and GA₁₅ may regulate pericarp development. Contents of trans-Zeatin (tZ), indole-3-acetic acid (IAA), and GAs in seed kernel and pericarp gradually decreased to very low, while ABA and indole-3-carboxaldehyde (ICAld) gradually increased. SA was positively correlated with ABA in pericarp and GAs and SA in seed kernel and pericarp. JAs in fruit generally showed a downward trend, and methyl jasmonate (ME-JA) appeared in pericarp.