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Xanthoceras sorbifolium (yellowhorn) is a woody oil plant with super stress resistance and excellent oil characteristics. The yellowhorn oil can be used as biofuel and edible oil with high nutritional and medicinal value. However, genetic studies on yellowhorn are just in the beginning, and fundamental biological questions regarding its very long-chain fatty acid (VLCFA) biosynthesis pathway remain largely unknown. In this study, we reconstructed the VLCFA biosynthesis pathway and annotated 137 genes encoding relevant enzymes. We identified four oleosin genes that package triacylglycerols (TAGs) and are specifically expressed in fruits, likely playing key roles in yellowhorn oil production. Especially, by examining time-ordered gene co-expression network (TO-GCN) constructed from fruit and leaf developments, we identified key enzymatic genes and potential regulatory transcription factors involved in VLCFA synthesis. In fruits, we further inferred a hierarchical regulatory network with MYB-related (XS03G0296800) and B3 (XS02G0057600) transcription factors as top-tier regulators, providing clues into factors controlling carbon flux into fatty acids. Our results offer new insights into key genes and transcriptional regulators governing fatty acid production in yellowhorn, laying the foundation for efforts to optimize oil content and fatty acid composition. Moreover, the gene expression patterns and putative regulatory relationships identified here will inform metabolic engineering and molecular breeding approaches tailored to meet biofuel and bioproduct demands.

Poplar (Populus) is a well-established model system for tree genomics and molecular breeding, and hybrid poplar is widely used in forest plantations. However, distinguishing its diploid homologous chromosomes is difficult, complicating advanced functional studies on specific alleles. In this study, we applied a trio-binning design and PacBio high-fidelity long-read sequencing to obtain haplotype-phased telomere-to-telomere genome assemblies for the 2 parents of the well-studied F1 hybrid “84K” (Populus alba × Populus tremula var. glandulosa). Almost all chromosomes, including the telomeres and centromeres, were completely assembled for each haplotype subgenome apart from 2 small gaps on one chromosome. By incorporating information from these haplotype assemblies and extensive RNA-seq data, we analyzed gene expression patterns between the 2 subgenomes and alleles. Transcription bias at the subgenome level was not uncovered, but extensive-expression differences were detected between alleles. We developed machine-learning (ML) models to predict allele-specific expression (ASE) with high accuracy and identified underlying genome features most highly influencing ASE. One of our models with 15 predictor variables achieved 77% accuracy on the training set and 74% accuracy on the testing set. ML models identified gene body CHG methylation, sequence divergence, and transposon occupancy both upstream and downstream of alleles as important factors for ASE. Our haplotype-phased genome assemblies and ML strategy highlight an avenue for functional studies in Populus and provide additional tools for studying ASE and heterosis in hybrids.

Long non-coding RNAs (lncRNAs) play essential roles in various biological processes, such as chromatin remodeling, post-transcriptional regulation, and epigenetic modifications. Despite their critical functions in regulating plant growth, root development, and seed dormancy, the identification of plant lncRNAs remains a challenge due to the scarcity of specific and extensively tested identification methods. Most mainstream machine learning-based methods used for plant lncRNA identification were initially developed using human or other animal datasets, and their accuracy and effectiveness in predicting plant lncRNAs have not been fully evaluated or exploited. To overcome this limitation, we retrained several models, including CPAT, PLEK, and LncFinder, using plant datasets and compared their performance with mainstream lncRNA prediction tools such as CPC2, CNCI, RNAplonc, and LncADeep. Retraining these models significantly improved their performance, and two of the retrained models, LncFinder-plant and CPAT-plant, alongside their ensemble, emerged as the most suitable tools for plant lncRNA identification. This underscores the importance of model retraining in tackling the challenges associated with plant lncRNA identification. Finally, we developed a pipeline (Plant-LncPipe) that incorporates an ensemble of the two best-performing models and covers the entire data analysis process, including reads mapping, transcript assembly, lncRNA identification, classification, and origin, for the efficient identification of lncRNAs in plants. The pipeline, Plant-LncPipe, is available at: https://github.com/xuechantian/Plant-LncRNA-pipline.

Terpenes and terpenoids are key natural compounds for plant defense, development, and composition of plant oil. The synthesis and accumulation of a myriad of volatile terpenoid compounds in these plants may dramatically alter the quality and flavor of the oils, which provide great commercial utilization value for oil-producing plants. Terpene synthases (TPSs) are important enzymes responsible for terpenic diversity. Investigating the differentiation of the TPS gene family could provide valuable theoretical support for the genetic improvement of oil-producing plants. While the origin and function of TPS genes have been extensively studied, the exact origin of the initial gene fusion event - it occurred in plants or microbes - remains uncertain. Furthermore, a comprehensive exploration of the TPS gene differentiation is still pending. Here, phylogenetic analysis revealed that the fusion of the TPS gene likely occurred in the ancestor of land plants, following the acquisition of individual C- and N- terminal domains. Potential mutual transfer of TPS genes was observed among microbes and plants. Gene synteny analysis disclosed a differential divergence pattern between TPS-c and TPS-e/f subfamilies involved in primary metabolism and those (TPS-a/b/d/g/h subfamilies) crucial for secondary metabolites. Biosynthetic gene clusters (BGCs) analysis suggested a correlation between lineage divergence and potential natural selection in structuring terpene diversities. This study provides fresh perspectives on the origin and evolution of the TPS gene family.

The genus Rhododendron (Ericaceae), with more than 1000 species highly diverse in flower color, is providing distinct ornamental values and a model system for flower color studies. Here, we investigated the divergence between two parental species with different flower color widely used for azalea breeding. Gapless genome assembly was generated for the yellow-flowered azalea, Rhododendron molle. Comparative genomics found recent proliferation of long terminal repeat retrotransposons (LTR-RTs), especially Gypsy, has resulted in a 125 Mb (19%) genome size increase in species-specific regions, and a significant amount of dispersed gene duplicates (13 402) and pseudogenes (17 437). Metabolomic assessment revealed that yellow flower coloration is attributed to the dynamic changes of carotenoids/flavonols biosynthesis and chlorophyll degradation. Time-ordered gene co-expression networks (TO-GCNs) and the comparison confirmed the metabolome and uncovered the specific gene regulatory changes underpinning the distinct flower pigmentation. B3 and ERF TFs were found dominating the gene regulation of carotenoids/flavonols characterized pigmentation in R. molle, while WRKY, ERF, WD40, C2H2, and NAC TFs collectively regulated the anthocyanins characterized pigmentation in the red-flowered R simsii. This study employed a multi-omics strategy in disentangling the complex divergence between two important azaleas and provided references for further functional genetics and molecular breeding.

Wood decay resistance (WDR) is marking the value of wood utilization. Many trees of the Lauraceae have exceptional WDR, as evidenced by their use in ancient royal palace buildings in China. However, the genetics of WDR remain elusive. Here, through comparative genomics, we revealed the unique characteristics related to the high WDR in Lauraceae trees. We present a 1.27-Gb chromosome-level assembly for Lindera megaphylla (Lauraceae). Comparative genomics integrating major groups of angiosperm revealed Lauraceae species have extensively shared gene microsynteny associated with the biosynthesis of specialized metabolites such as isoquinoline alkaloids, flavonoid, lignins and terpenoid, which play significant roles in WDR. In Lauraceae genomes, tandem and proximal duplications (TD/PD) significantly expanded the coding space of key enzymes of biosynthesis pathways related to WDR, which may enhance the decay resistance of wood by increasing the accumulation of these compounds. Among Lauraceae species, genes of WDR-related biosynthesis pathways showed remarkable expansion by TD/PD and conveyed unique and conserved motifs in their promoter and protein sequences, suggesting conserved gene collinearity, gene expansion and gene regulation supporting the high WDR. Our study thus reveals genomic profiles related to biochemical transitions among major plant groups and the genomic basis of WDR in the Lauraceae.

Xanthoceras sorbifolium (yellowhorn) is a woody oil plant with super stress resistance and excellent oil characteristics. The yellowhorn oil can be used as biofuel and edible oil with high nutritional and medicinal value. However, genetic studies on yellowhorn are just in the beginning, and fundamental biological questions regarding its very long-chain fatty acid (VLCFA) biosynthesis pathway remain largely unknown. In this study, we reconstructed the VLCFA biosynthesis pathway and annotated 137 genes encoding relevant enzymes. We identified four oleosin genes that package triacylglycerols (TAGs) and are specifically expressed in fruits, likely playing key roles in yellowhorn oil production. Especially, by examining time-ordered gene co-expression network (TO-GCN) constructed from fruit and leaf developments, we identified key enzymatic genes and potential regulatory transcription factors involved in VLCFA synthesis. In fruits, we further inferred a hierarchical regulatory network with MYB-related (XS03G0296800) and B3 (XS02G0057600) transcription factors as top-tier regulators, providing clues into factors controlling carbon flux into fatty acids. Our results offer new insights into key genes and transcriptional regulators governing fatty acid production in yellowhorn, laying the foundation for efforts to optimize oil content and fatty acid composition. Moreover, the gene expression patterns and putative regulatory relationships identified here will inform metabolic engineering and molecular breeding approaches tailored to meet biofuel and bioproduct demands.