Long noncoding RNAs (lncRNAs) are transcripts longer than 200 nucleotides with little or no protein coding potential. The expanding list of lncRNAs and accumulating evidence of their functions in plants have necessitated the creation of a comprehensive database for lncRNA research. However, currently available plant lncRNA databases have some deficiencies, including the lack of lncRNA data from some model plants, uneven annotation standards, a lack of visualization for expression patterns, and the absence of epigenetic information. To overcome these problems, we upgraded our Plant Long noncoding RNA Database (PLncDB, http://plncdb.tobaccodb.org/), which was based on a uniform annotation pipeline. PLncDB V2.0 currently contains 1 246 372 lncRNAs for 80 plant species based on 13 834 RNA-Seq datasets, integrating lncRNA information from four other resources including EVLncRNAs, RNAcentral and etc. Expression patterns and epigenetic signals can be visualized using multiple tools (JBrowse, eFP Browser and EPexplorer). Targets and regulatory networks for lncRNAs are also provided for function exploration. In addition, PLncDB V2.0 is hierarchical and user-friendly and has five built-in search engines. We believe PLncDB V2.0 is useful for the plant lncRNA community and data mining studies and provides a comprehensive resource for data-driven lncRNA research in plants.

CB-1 and K326 are closely related tobacco cultivars; however, their cold tolerance capacities are different. K326 is much more cold tolerant than CB-1. We studied the transcriptomes and metabolomes of CB-1 and K326 leaf samples treated with cold stress. Totally, we have identified 14,590 differentially expressed genes (DEGs) in CB-1 and 14,605 DEGs in K326; there was also 200 differentially expressed metabolites in CB-1 and 194 in K326. Moreover, there were many overlapping genes (around 50%) that were cold-responsive in both plant cultivars, although there were also many differences in the cold responsive genes between the two cultivars. Importantly, for most of the overlapping cold responsive genes, the extent of the changes in expression were typically much more pronounced in K326 than in CB-1, which may help explain the superior cold tolerance of K326. Similar results were found in the metabolome analysis, particularly with the analysis of primary metabolites, including amino acids, organic acids, and sugars. The large number of specific responsive genes and metabolites highlight the complex regulatory mechanisms associated with cold stress in tobacco. In addition, our work implies that the energy metabolism and hormones may function distinctly between CB-1 and K326. Differences in gene expression and metabolite levels following cold stress treatment seem likely to have contributed to the observed difference in the cold tolerance phenotype of these two tobacco cultivars.

The advent of single-cell sequencing opened a new era in transcriptomic and genomic research. To understand cell composition using single-cell studies, a variety of cell markers have been widely used to label individual cell types. However, the specific database of cell markers for use by the plant research community remains very limited. To overcome this problem, we developed the Plant Cell Marker DataBase (PCMDB, http://www.tobaccodb.org/pcmdb/), which is based on a uniform annotation pipeline. By manually curating over 130 000 research publications, we collected a total of 81 117 cell marker genes of 263 cell types in 22 tissues across six plant species. Tissue- and cell-specific expression patterns can be visualized using multiple tools: eFP Browser, Bar, and UMAP/TSNE graph. The PCMDB also supports several analysis tools, including SCSA and SingleR, which allows for user annotation of cell types. To provide information about plant species currently unsupported in PCMDB, potential marker genes for other plant species can be searched based on homology with the supported species. PCMDB is a user-friendly hierarchical platform that contains five built-in search engines. We believe PCMDB will constitute a useful resource for researchers working on cell type annotation and the prediction of the biological function of individual cells.

Magnolia champaca, commonly known as champak is a well-known tree due to its highly fragrant flowers. Champak floral scent is attributed to a complex mix of volatile organic compounds (VOCs). These aromatic flowers are widely used in flavors and fragrances industry. Despite its commercial importance, the VOC biosynthesis pathways in these flowers are largely unknown. Here, we combine metabolite and RNA sequencing (RNA-seq) analyses of fully opened champak flowers to discover the active VOC biosynthesis pathways as well as floral scent-related genes. Volatile collection by headspace method and analysis by gas chromatography-mass spectrometry (GC-MS) identified a total of 43 VOCs from fully opened champak flowers, of which 46.9% were terpenoids, 38.9% were volatile esters and 5.2% belonged to phenylpropanoids/benzenoids. Sequencing and de novo assembly of champak flower transcriptome yielded 47,688 non-redundant unigenes. Transcriptome assembly was validated using standard polymerase chain reaction (PCR) based approach for randomly selected unigenes. The detailed profiles of VOCs led to the discovery of pathways and genes involved in floral scent biosynthesis from RNA-seq data. Analysis of expression levels of many floral-scent biosynthesis-related unigenes in flowers and leaves showed that most of them were expressed higher in flowers than in leaf tissues. Moreover, our metabolite-guided transcriptomics, in vitro and in vivo enzyme assays and transgenic studies identified (R)-linalool synthase that is essential for the production of major VOCs of champak flowers, (R)-linalool and linalool oxides. As our study is the first report on transcriptome analysis of Magnolia champaca, this transcriptome dataset that serves as an important public information for functional genomics will not only facilitate better understanding of ecological functions of champak floral VOCs, but also provide biotechnological targets for sustainable production of champak floral scent.

Class III peroxidases (PODs) are plant-specific enzymes that play significant roles in plant physiological processes and stress responses. However, a comprehensive analysis of the POD gene family in tobacco has not yet been conducted. In this study, 210 non-redundant POD gene members (NtPODs) were identified in tobacco (Nicotiana tabacum) and distributed unevenly throughout 24 tobacco chromosomes. Phylogenetic analysis clustered these genes into six subgroups (I-VI). Gene structure and motif analyses showed the structural and functional diversity among the subgroups. Segmental duplication and purifying selection were the main factors affecting NtPOD gene evolution. Our analyses also suggested that NtPODs might be regulated by miRNAs and cis-acting regulatory elements of transcription factors that are involved in various biological processes. In addition, the expression patterns in different tissues and under various stress treatments were investigated. The results showed that the majority of NtPODs had tissue-specific expression patterns and may be involved in many biotic and abiotic responses. qRT-PCR analyses of different tissues and stress treatments were performed to verify transcriptome patterns. Expression of a green fluorescent protein-NtPOD fusion confirmed the plasma membrane localization of NtPOD121 and NtPOD4. Furthermore, 3D structures provided evidences of membrane-bound peroxidase. These findings provide useful information to better understand the evolution of the NtPOD gene family and lay the foundation for further studies on POD gene function in tobacco.

Carbon nanosol (CNS) is a carbon-based nanomaterial that promotes plant growth; however, its functional mechanisms and effects on the microbiome are not fully understood. Here, we explored the effects of CNS on the relationship between the soil, endophytic microbiomes and plant productivity. CNS treatment increased the fresh biomass of tobacco (Nicotiana tabacum L.) plants by 27.4% ± 9.9%. Amplicon sequencing analysis showed that the CNS treatment significantly affected the composition and diversity of the microbial communities in multiple ecological niches associated with tobacco, especially the bulk soil and stem endophytic microbiome. Furthermore, the application of CNS resulted in enhanced network connectivity and stability of the microbial communities in different niches, particularly in the soil, implying a strengthening of certain microbial interactions. Certain potentially growth-promoting root endophytic bacteria were more abundant under the CNS treatment. In addition, CNS increased the abundance of some endophytic microbial functional genes known to enhance plant growth, such as those associated with nutrient metabolism and the plant hormone biosynthesis pathways. We isolated two bacterial strains (Sphingopyxis sp. and Novosphingobium sp.) that were enriched under CNS treatment, and they were confirmed to promote tobacco plant growth in vitro. These results suggested that CNS might, at least in part, promote plant growth by enriching beneficial bacteria in the microbiome. Graphical Abstract