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Understanding how species respond to climate change can facilitate species conservation and crop breeding. Current prediction frameworks about population vulnerability focused on predicting range shifts or local adaptation but ignored genetic load, which is also crucial for adaptation. By analyzing 1115 globally distributed Arabidopsis thaliana natural accessions, we find that effective population size (Ne) is the major contributor of genetic load variation, both along genome and among populations, and can explain 74-94% genetic load variation in natural populations. Intriguingly, Ne affects genetic load by changing both effectiveness of purifying selection and GC biased gene conversion strength. In particular, by incorporating genetic load, genetic offset and species distribution models (SDM), we predict that, the populations at species’ range edge are generally at higher risk. The populations at the eastern range perform poorer in all aspects, southern range have higher genetic offset and lower SDM suitability, while northern range have higher genetic load. Among the diverse natural populations, the Yangtze River basin population is the most vulnerable population under future climate change. Overall, here we deciphered the driving forces of genetic load in A. thaliana, and incorporated SDM, local adaptation and genetic load to predict the fate of populations under future climate change.

The high biosynthetic and energetic demands of floral thermogenesis render thermogenic plants the ideal systems to characterize energy metabolism in plants, but real-time tracking of energy metabolism in plant cells remains challenging. In this study, a new method was developed for tracking the mitochondrial energy metabolism at the single mitochondria level by real-time imaging of mitochondrial superoxide production (i.e., mitoflash). Using this method, we observed the increased mitoflash frequencies in the receptacles of Nelumbo nucifera Gaertn. at the thermogenic stages. This increase, combined with the higher expression of antioxidant response-related genes identified through time-series transcriptomics at the same stages, shows us a new regulatory mechanism for plant redox balance. Furthermore, we found that the upregulation of respiratory metabolism-related genes during the thermogenic stages not only correlates with changes in mitoflash frequency but also underscores the critical roles of these pathways in ensuring adequate substrate supply for thermogenesis. Metabolite analysis revealed that sugars are likely one of the substrates for thermogenesis and may be transported over long distances by sugar transporters. Taken together, our findings demonstrate that mitoflash is a reliable tool for tracking energy metabolism in thermogenic plants and contributes to our understanding of the regulatory mechanisms underlying floral thermogenesis.

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.

The genus Rhododendron exhibits an immense diversity of flower colors and represents one of the largest groups of woody plants, which is of great importance for ornamental plant research. This review summarizes recent progress in deciphering the genetic basis for flower coloration in Rhododendron. We describe advances in phylogenetic reconstruction and genome sequencing of Rhododendron species. The metabolic pathways of flower color are outlined, focusing on key structural and regulatory genes involved in pigment synthesis. Gene duplications and losses associated with color diversification are discussed. In addition, the application of multi-omics approaches and analysis of gene co-expression networks to elucidate complex gene regulatory mechanisms is emphasized. This synthesis of current knowledge provides a foundation for future research on the evolution of flower color diversity within the Rhododendron lineage. Ultimately, these discoveries will support breeding endeavors aimed at harnessing the genetics of flower coloration and developing novel cultivars that exhibit desired floral traits.

Populus tomentosa, an indigenous tree species, is widely distributed and cultivated over 1,000,000 km² in China, contributing significantly to forest production, ecological conservation and urban–rural greening. Although a reference genome is available for P. tomentosa, the intricate interspecific hybrid origins, chromosome structural variations (SVs) and sex determination mechanisms remain confusion and unclear due to its broad and even overlapping geographical distribution, extensive morphological variations and cross infiltration among white poplar species. We conducted a haplotype-resolved de novo assembly of P. tomentosa elite individual GM107, which comprises subgenomes a and b with a total genome size of 714.9 Mb. We then analysed the formation of hybrid species and the phylogenetic evolution and sex differentiation across the entire genus. Phylogenomic analyses suggested that GM107 likely originated from a hybridisation event between P. alba (♀) and P. davidiana (♂) approximately 3.8 Mya. A total of 1551 chromosome SVs were identified between the two subgenomes. More noteworthily, a distinctive inversion structure spanning 2.15–2.95 Mb was unveiled among Populus, Tacamahaca, Turaga, Aigeiros poplar species and Salix, highlighting a unique evolutionary feature. Intriguingly, a novel sex genotype of the ZY type, which represents a crossover between XY and ZW systems, was identified and confirmed through both natural and artificial hybrids populations. These novel insights offer significant theoretical value for the study of the species' evolutionary origins and serve as a valuable resource for ecological genetics and forest biotechnology.

Quercus dentata Thunb., a dominant forest tree species in northern China, has significant ecological and ornamental value due to its adaptability and beautiful autumn coloration, with color changes from green to yellow into red resulting from the autumnal shifts in leaf pigmentation. However, the key genes and molecular regulatory mechanisms for leaf color transition remain to be investigated.

First, we presented a high-quality chromosome-scale assembly for Q. dentata. This 893.54 Mb sized genome (contig N50 = 4.21 Mb, scaffold N50 = 75.55 Mb; 2n = 24) harbors 31 584 protein-coding genes. Second, our metabolome analyses uncovered pelargonidin-3-O-glucoside, cyanidin-3-O-arabinoside, and cyanidin-3-O-glucoside as the main pigments involved in leaf color transition. Third, gene co-expression further identified the MYB-bHLH-WD40 (MBW) transcription activation complex as central to anthocyanin biosynthesis regulation.

Notably, transcription factor (TF) QdNAC (QD08G038820) was highly co-expressed with this MBW complex and may regulate anthocyanin accumulation and chlorophyll degradation during leaf senescence through direct interaction with another TF, QdMYB (QD01G020890), as revealed by our further protein–protein and DNA–protein interaction assays.

Our high-quality genome assembly, metabolome, and transcriptome resources further enrich Quercus genomics and will facilitate upcoming exploration of ornamental values and environmental adaptability in this important genus.

Coriaria nepalensis Wall. (Coriariaceae) is a nitrogen-fixing shrub which forms root nodules with the actinomycete Frankia. Oils and extracts of C. nepalensis have been reported to be bacteriostatic and insecticidal, and C. nepalensis bark provides a valuable tannin resource. Here, by combining PacBio HiFi sequencing and Hi-C scaffolding techniques, we generated a haplotype-resolved chromosome-scale genome assembly for C. nepalensis. This genome assembly is approximately 620 Mb in size with a contig N50 of 11 Mb, with 99.9% of the total assembled sequences anchored to 40 pseudochromosomes. We predicted 60,862 protein-coding genes of which 99.5% were annotated from databases. We further identified 939 tRNAs, 7,297 rRNAs, and 982 ncRNAs. The chromosome-scale genome of C. nepalensis is expected to be a significant resource for understanding the genetic basis of root nodulation with Frankia, toxicity, and tannin biosynthesis.

Nervonic acid (C24:1 Δ15, NA) is a very long-chain monounsaturated fatty acid, a clinically indispensable resource in maintaining the brain and nerve cells development and regeneration. Till now, NA has been found in 38 plant species, among which the garlic-fruit tree (Malania oleifera) has been evaluated to be the best candidate for NA production. Here, we generated a high-quality chromosome-scale assembly of M. oleifera employing PacBio long-read, short-read Illumina as well as Hi-C sequencing data. The genome assembly consisted of 1.5 Gb with a contig N50 of ~4.9 Mb and a scaffold N50 of ~112.6 Mb. ~98.2% of the assembly was anchored into 13 pseudo-chromosomes. It contains ~1123 Mb repeat sequences, and 27,638 protein-coding genes, 568 tRNAs, 230 rRNAs and 352 other non-coding RNAs. Additionally, we documented candidate genes involved in NA biosynthesis including 20 KCSs, 4 KCRs, 1 HCD and 1 ECR, and profiled the expression patterns of these genes in developing seeds. The high-quality assembly of the genome provides insights into the genome evolution of the M. oleifera genome and candidate genes involved in NA biosynthesis in the seeds of this important woody tree.