Plant-LncPipe: a computational pipeline providing significant improvement in plant lncRNA identification.

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.

High-quality genome assembly enables prediction of allele-specific gene expression in hybrid poplar.

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.

Haplotype-resolved genome assembly of Coriaria nepalensis a non-legume nitrogen-fixing shrub.

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.

Gapless genome assembly of azalea and multi-omics investigation into divergence between two species with distinct flower color.

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.

Differential gene expression and potential regulatory network of fatty acid biosynthesis during fruit and leaf development in yellowhorn (Xanthoceras sorbifolium), an oil-producing tree with significant deployment values.

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.

Myriapod genomes reveal ancestral horizontal gene transfer and hormonal gene loss in millipedes.

Animals display a fascinating diversity of body plans. Correspondingly, genomic analyses have revealed dynamic evolution of gene gains and losses among animal lineages. Here we sequence six new myriapod genomes (three millipedes, three centipedes) at key phylogenetic positions within this major but understudied arthropod lineage. We combine these with existing genomic resources to conduct a comparative analysis across all available myriapod genomes. We find that millipedes generally have considerably smaller genomes than centipedes, with the repeatome being a major contributor to genome size, driven by independent large gains of transposons in three centipede species. In contrast to millipedes, centipedes gained a large number of gene families after the subphyla diverged, with gains contributing to sensory and locomotory adaptations that facilitated their ecological shift to predation. We identify distinct horizontal gene transfer (HGT) events from bacteria to millipedes and centipedes, with no identifiable HGTs shared among all myriapods. Loss of juvenile hormone O-methyltransferase, a key enzyme in catalysing sesquiterpenoid hormone production in arthropods, was also revealed in all millipede lineages. Our findings suggest that the rapid evolution of distinct genomic pathways in centipede and millipede lineages following their divergence from the myriapod ancestor, was shaped by differing ecological pressures.

Concentrations and Related Health Risk Assessment of Pesticides, Phthalates, and Heavy Metals in Strawberries from Shanghai, China.

ABSTRACT: In the present study, a risk assessment of pesticides, phthalates, and heavy metals in strawberries (n = 335) in recent years was conducted by determining the estimated daily intake, target hazard quotient, and hazard index. The study used 128 pesticides, 18 phthalates, and three heavy metals in this determination. It detected 51 pesticide residues in the strawberry samples, and 97.91% samples had levels of at least 1 of the 51 pesticides above the limit of detection. In addition, 2.39% of samples had pesticides higher than the Chinese maximum residue limit. Multiple pesticide residues were detected in most samples. Bis-2-ethylhexyl phthalate, diisobutyl phthalate, and dibutyl phthalate were detected in the strawberry samples, with a high frequency of detection. Their detectable rates were 100, 100, and 89.9%, respectively. In most samples, lead, cadmium, and nickel were detected, with detectable rates 75.76, 92.93, and 92.93%, respectively. The estimated daily intake of analyzed pesticide, phthalate, and heavy metal residues appears to be relatively low compared with the acceptable daily intake. The average target hazard quotients and hazard indices were less than 1. That means that customers who are exposed to the average contaminant levels may not pose a significant health risk. Our results show that the strawberries may be polluted by many kinds of contaminants. Therefore, monitoring of pesticide, phthalate, and heavy metal residues in strawberries should be increasingly developed to fully protect the health of the consumer.