Determination of Volatile Organic Compounds and Endogenous Extracts and Study of Expression Patterns of TPS and BSMT in the Flowers of Seven Lilium Cultivars.

Lily is one of the most important cut flowers in the world, with a rich floral fragrance. To further explore the fragrance emission mechanisms of lily cultivars, headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) and organic solvent extraction-gas chromatography-mass spectrometry (OSE-GC-MS) were used to unveil the volatile organic compounds (VOCs) and endogenous extracts of seven lily cultivars. Furthermore, real-time quantitative PCR (qRT-PCR) was used to determine the expression levels of two key genes (TPS and BSMT) related to the biosynthesis of monoterpenoids and methyl benzoate. The results show that forty-five VOCs were detected in the petals of seven lily cultivars, and the main compounds were monoterpenoids and phenylpropanoids/benzenoids. Dichloromethane was the best solvent for extracting the endogenous extracts of Lilium 'Viviana' petals and eighteen endogenous extracts were detected using dichloromethane to extract the petals of seven lily cultivars. Each compound's emission ratio (natural logarithm of the ratio of VOC content to endogenous extract content) was calculated, and linear regression analyses between emission ratios and boiling points were conducted. Significant linear negative correlations existed between the emission ratios and boiling points of compounds, and the regression equations' coefficients of determination (R2) were all greater than 0.7. TPS was expressed highly in 'Viviana', 'Pink News', and 'Palazzo', and BSMT was expressed highly in 'Pink News' and 'Palazzo'. Correlation analyses between the gene expression levels and the monoterpenoids and methyl benzoate contents found that the TPS expression levels have strong positive correlations with monoterpenoids content, while no correlations were found between the expression levels of BSMT and the contents of methyl benzoate. This study lays the foundation for research on the release patterns of VOCs in the flowers of Lilium, and the breeding of lilies for their floral fragrance.

Identification and Expression Analysis of Chemosensory Genes in the Antennal Transcriptome of Chrysanthemum Aphid Macrosiphoniella sanborni.

As one of the most destructive oligophagous pests, the chrysanthemum aphid (Macrosiphoniella sanborni) has seriously restricted the sustainable development of the chrysanthemum industry. Olfaction plays a critical role in the environmental perception of aphids, but very little is currently known about the chemosensory mechanism of M. sanborni. In this study, four MsanOBPs, four MsanCSPs, eight MsanORs, two MsanIRs and one MsanSNMP were identified among the 28,323 unigenes derived from the antennal transcriptome bioinformatic analysis of M. sanborni adults. Then, comprehensive phylogenetic analyses of these olfactory-related proteins in different aphid species were performed using multiple sequence alignment. Subsequently, the odor-specific and wing-specific expression profiles of these candidate chemosensory genes were investigated using quantitative real-time PCR. The data showed that most of these chemosensory genes exhibited higher expression levels in alate aphids. Among them, MsanOBP9, MsanOR2, MsanOR4, MsanOR43b-1, MsanCSP1, MsanCSP2, MsanCSP4, MsanIR25a and MsanIR40a in alate aphids showed remarkably higher expression levels than in apterous aphids under the effect of the host plant volatiles, indicating that these genes may take part in the specific behaviors of alate adults, such as host recognition, oviposition site selection and so on. This study lays the groundwork for future research into the molecular mechanism of olfactory recognition in M. sanborni.

Identification of heterogeneous nuclear ribonucleoprotein as a candidate biomarker for diagnosis and prognosis of hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the most common type of liver cancer with a high mortality rate. However, spliceosomal genes are still lacking in the diagnosis and prognosis of HCC. METHODS: Identification of differentially expressed genes (DEGs) was performed using the limma package in R software. Modules highly related to HCC were obtained by weighted gene co-expression network analysis (WGCNA), and the module genes were analyzed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. The biomarker for diagnosing HCC was determined by receiver operating characteristic (ROC) curve analysis, and the effect of the biomarker in the diagnosis of HCC was evaluated by performing five-fold cross-validation with logistic regression. HCC specimens from preoperatively treated patients were tested for biomarker by real-time quantitative polymerase chain reaction (RT-qPCR). Kaplan-Meier analysis was used to assess the relationship between biomarker and patient survival. The role of biomarker was evaluated using ESTIMATE analysis in the tumor microenvironment. RESULTS: In this study, 389 DEGs were screened out from three Gene Expression Omnibus (GEO) datasets. We also found that the turquoise module of 123 genes from The Cancer Genome Atlas (TCGA) data was the key module with the highest correlation with HCC traits. Then, 123 genes were analyzed using the KEGG enrichment pathway, and eight genes were found to be most significantly related to the spliceosome pathway. We selected 8 genes and 389 DEGs shared genes, and finally got the only gene, heterogeneous nuclear ribonucleoprotein (hnRNPU). The high expression of hnRNPU was associated with poor prognosis of HCC, and hnRNPU was a biomarker for diagnosing HCC. In the tissues of patients with excellent HCC treatment hnRNPU messenger RNA (mRNA) was lower than in the tissues of patients with poor HCC treatment. High expression of hnRNPU was significantly increased in HCC patients with low stromal (P<0.05), low immune (P<0.05), and low estimation scores (P<0.05), and with high tumor purity (P<0.05) and high malignant progression (P<0.05) of the HCC. CONCLUSIONS: The hnRNPU gene identified in this study may become a new biomarker for the diagnosis and prognosis of HCC.