BackgroundInsect odorant binding proteins (OBPs) and chemosensory proteins (CSPs) play an important role in chemical communication of insects. Gene discovery of these proteins is a time-consuming task. In recent years, expressed sequence tags (ESTs) of many insect species have accumulated, thus providing a useful resource for gene discovery.ResultsWe have developed a computational pipeline to identify OBP and CSP genes from insect ESTs. In total, 752,841 insect ESTs were examined from 54 species covering eight Orders of Insecta. From these ESTs, 142 OBPs and 177 CSPs were identified, of which 117 OBPs and 129 CSPs are new. The complete open reading frames (ORFs) of 88 OBPs and 123 CSPs were obtained by electronic elongation. We randomly chose 26 OBPs from eight species of insects, and 21 CSPs from four species for RT-PCR validation. Twenty two OBPs and 16 CSPs were confirmed by RT-PCR, proving the efficiency and reliability of the algorithm. Together with all family members obtained from the NCBI (OBPs) or the UniProtKB (CSPs), 850 OBPs and 237 CSPs were analyzed for their structural characteristics and evolutionary relationship.ConclusionsA large number of new OBPs and CSPs were found, providing the basis for deeper understanding of these proteins. In addition, the conserved motif and evolutionary analysis provide some new insights into the evolution of insect OBPs and CSPs. Motif pattern fine-tune the functions of OBPs and CSPs, leading to the minor difference in binding sex pheromone or plant volatiles in different insect Orders.

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.

BackgroundCB-1 and K326 are closely related tobacco cultivars; however, their cold tolerance capacities are different. K326 is much more cold tolerant than CB-1.ResultsWe 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.ConclusionsDifferences 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-017-3871-7) contains supplementary material, which is available to authorized users.

Main conclusionProvide an evolutionary and an empirical molecular genetic foundation of the Sus gene family in tobacco and will be beneficial for further investigations of Sus gene functionsSucrose synthase (Sus) has been well characterized as the key enzyme participating in sucrose metabolism, and the gene family encoding different Sus isozymes has been cloned and characterized in several plant species. However, scant information about this gene family is available to date in tobacco. Here, we identified 14, 6, and 7 Sus genes in the genomes of Nicotiana tabacum, N.sylvestris and N.tomentosiformis, respectively. These tobacco Sus family members shared high levels of similarity in their nucleotide and amino acid sequences. Phylogenetic analysis revealed distinct evolutionary paths for the tobacco Sus genes. Sus1–4, Sus5, and Sus6–7 originated from three Sus precursors, respectively, which were generated by duplication before the split of monocots and eudicots. There were two additional duplications, before and after the differentiation of the Solanaceae, which separately gave rise to Sus3/4 and Sus1/2. Gene exon/intron structure analysis showed that the tobacco Sus genes contain varying numbers of conserved introns, resulting from intron loss under different selection pressures during the course of evolution. The expression patterns of the NtSus genes differed from each other in various tobacco tissues. Transcripts of Ntab0259170 and Ntab0259180 were detected in leaves at all tested developmental stages, suggesting that these two genes play a predominant role in sucrose metabolism during leaf development. Expression of Ntab0288750 and Ntab0234340 were conspicuously induced by low temperature and virus treatment, indicating that these two isozymes are important in meeting the increased glycolytic demand that occurs during abiotic stress. Our results provide an evolutionary and an empirical molecular genetic foundation of the Sus gene family in tobacco, and will be beneficial for further investigations of Sus gene functions in the processes of tobacco leaf development and tobacco resistance to environmental stresses.Electronic supplementary materialThe online version of this article (doi:10.1007/s00425-015-2297-1) contains supplementary material, which is available to authorized users.

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.

Applying plant community diversity techniques and SPSS statistic analysis, we quantified the relationship between crown volume of 18 (Sophora japonica) tree communities and elevation along different elevation gradient in Ye County in the study. We concluded that there was a significantly positive correlation between crown volume of 18 (Sophora japonica) tree communities and elevation gradient (P < 0.01). Elevation was the dominant environment driver crown volume of (Sophora japonica) tree communities increased along elevation from 50 m to 200 m in Ye County in 2018. Therefore, understanding dynamic connecting crown volume of 18 (Sophora japonica) communities and elevation can be not just applied to preserve of (Sophora japonica) tree communities, but also applied to sustainable of biodiversity and processes of tree community's crown volume along elevation.

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Tobacco (Nicotiana tabacum) is one of the most widely cultivated commercial non-food crops with significant social and economic impacts. Here we profiled transcriptome and metabolome from 54 tobacco samples (2–3 replicates; n = 151 in total) collected from three varieties (i.e. genetic factor), three locations (i.e. environmental factor), and six developmental stages (i.e. developmental process). We identified 3,405 differentially expressed (DE) genes (DEGs) and 371 DE metabolites, respectively. We used quantitative real-time PCR to validate 20 DEGs, and confirmed 18/20 (90%) DEGs between three locations and 16/20 (80%) with the same trend across developmental stages. We then constructed nine co-expression gene modules and four co-expression metabolite modules , and defined seven de novo regulatory networks, including nicotine- and carotenoid-related regulatory networks. A novel two-way Pearson correlation approach was further proposed to integrate co-expression gene and metabolite modules to identify joint gene–metabolite relations. Finally, we further integrated DE and network results to prioritize genes by its functional importance and identified a top-ranked novel gene, LOC107773232, as a potential regulator involved in the carotenoid metabolism pathway. Thus, the results and systems-biology approaches provide a new avenue to understand the molecular mechanisms underlying complex genetic and environmental perturbations in tobacco.