Background: Before studying gene expression of different organisms, it is important to determine the best reference gene. At present, the most accurate method of detecting gene expression is quantitative real-time PCR (RT-qPCR). With this method, reference genes that are stable in different biological systems and under different conditions can be obtained. Toona ciliata Roem (T. ciliata). is a valuable and fast-growing timber specie. In this study, 20 reference genes were identified using RT-qPCR, as a primary prerequisite for future gene expression analysis. Four different methods, geNorm, NormFinder, BestKeeper, and RankAggreg were used to evaluate the expression stability of the 20 candidate reference genes in various tissues under different conditions. Results: The experimental results showed that TUB-α was the most stably expressed reference gene across all samples and UBC17 was the most stable in leaves and young stems under Hypsipyla robusta (H. robusta) and methyl jasmonate (MeJA) treatments. In addition, PP2C59 and UBC5B were the best-performing genes in leaves under H. robusta treatment, while HIS1 and ACT7 were the best reference genes in young stems. The two best reference genes were 60S-18 and TUB-α after treatment at 4 °C. The expression of HIS6 and MUB1 was the most stable under PEG6000 treatment. The accuracy of the selected reference genes was verified using the transcription factor MYB3 (TcMYB3) gene. Conclusions: This is the first report to verify the best reference genes for normalizing gene expression in T. ciliata under different conditions, which will facilitate future elucidation of gene regulations in this species.

Background. Tuberculosis (TB), caused by the bacterium Mycobacterium tuberculosis, affects approximately one-quarter of the global population and is considered one of the most lethal infectious diseases worldwide. The prevention of latent tuberculosis infection (LTBI) from progressing into active tuberculosis (ATB) is crucial for controlling and eradicating TB. Unfortunately, currently available biomarkers have limited effectiveness in identifying subpopulations that are at risk of developing ATB. Hence, it is imperative to develop advanced molecular tools for TB risk stratification. Methods. The TB datasets were downloaded from the GEO database. Three machine learning models, namely LASSO, RF, and SVM-RFE, were used to identify the key characteristic genes related to inflammation during the progression of LTBI to ATB. The expression and diagnostic accuracy of these characteristic genes were subsequently verified. These genes were then used to develop diagnostic nomograms. In addition, single-cell expression clustering analysis, immune cell expression clustering analysis, GSVA analysis, immune cell correlation, and immune checkpoint correlation of characteristic genes were conducted. Furthermore, the upstream shared miRNA was predicted, and a miRNA–genes network was constructed. Candidate drugs were also analyzed and predicted. Results. In comparison to LTBI, a total of 96 upregulated and 26 downregulated genes related to the inflammatory response were identified in ATB. These characteristic genes have demonstrated excellent diagnostic performance and significant correlation with many immune cells and immune sites. The results of the miRNA–genes network analysis suggested a potential role of hsa-miR-3163 in the molecular mechanism of LTBI progressing into ATB. Moreover, retinoic acid may offer a potential avenue for the prevention of LTBI progression to ATB and for the treatment of ATB. Conclusion. Our research has identified key inflammatory response-related genes that are characteristic of LTBI progression to ATB and hsa-miR-3163 as a significant node in the molecular mechanism of this progression. Our analyses have demonstrated the excellent diagnostic performance of these characteristic genes and their significant correlation with many immune cells and immune checkpoints. The CD274 immune checkpoint presents a promising target for the prevention and treatment of ATB. Furthermore, our findings suggest that retinoic acid may have a role in preventing LTBI from progressing to ATB and in treating ATB. This study provides a new perspective for differential diagnosis of LTBI and ATB and may uncover potential inflammatory immune mechanisms, biomarkers, therapeutic targets, and effective drugs in the progression of LTBI into ATB.

Background Toona ciliata is a traditional woody plant that can be used as a medicinal material in China. The extracts of roots, stems, leaves, and flowers all have a wide range of bioactivities. However, T. ciliata has been facing an unresolved pest problem caused by Hypsipyla robusta Moore (HRM), which seriously affects its growth and development. Results In this study, transcriptome sequencing of young stems was eaten by HRM for 0, 3, 12, and 21h were performed. A large number of differentially expressed genes (DGEs) were identified including jointly up-regulated genes (263) and down-regulated genes (378). JA synthesis and signaling transduction, terpene biosynthesis, and MAPKs signaling pathway were analyzed in depth and found that some key genes TcOPR3, TcJAR1, TcJAZs, and TcTPS9 possessed anti-insect potential. Moreover, MYBs and ERFs transcription factor family were significantly strengthened that may participate in induced defense mechanism in T. ciliata. Conclusions The novel transcriptome and DGE profiling provide an important resource for functional genomics during HRM stress in T. ciliata. These data not only provide insights into the molecular mechanisms in resistance of T. ciliata to HRM but also helps to explore the new biocontrol strategies against insects in eco-friendly woody plant.

Background: Before studying the gene expression of different organisms, it is important to determine the best reference gene. At present, the most accurate method for detecting gene expression is quantitative real-time PCR(RT-qPCR). By using this method, reference genes that are stable in different biological systems and under different conditions can be obtained. Toona ciliata Roem (T. ciliata). is a valuable and fast-growing timber species. In this study, 20 reference genes were identified through RT-qPCR, as a primary prerequisite for future gene expression analysis. Four different methods, geNorm, NormFinder, BestKeeper, and RankAggreg were used to evaluate the stability of expression of 20 candidate reference genes in various tissues under different conditions. Results: The experimental results showed that TUB-α was the most stably expressed reference gene across all samples; UBC17 was found to be the most stable in leaves & young stems under Hypsipyla robusta (H. robusta) and methyl jasmonate (MeJA) treatment. In addition, under H. robusta treatment, PP2C59 and UBC5B were the best-performing genes in leaves, while HIS1 and ACT7 were the best reference genes in young stems. Under low temperature (4℃) treatment, the two best reference genes were 60S-18 and TUB-α. The expression of HIS6 and MUB1 was the most stable under PEG6000 treatment. The accuracy of the selected reference genes was verified using transcription factor MYB3(TcMYB3) genes. Conclusions: This is the first report to verify the best reference genes for normalizing gene expression in T. ciliata under different conditions, which will facilitate the future elucidation of gene regulations in this species.

Background: Before studying gene expression of different organisms, it is important to determine the best reference gene. At present, the most accurate method of detecting gene expression is quantitative real-time PCR (RT-qPCR). With this method, reference genes that are stable in different biological systems and under different conditions can be obtained. Toona ciliata Roem (T. ciliata). is a valuable and fast-growing timber specie. In this study, 20 reference genes were identified using RT-qPCR, as a primary prerequisite for future gene expression analysis. Four different methods, geNorm, NormFinder, BestKeeper, and RankAggreg were used to evaluate the expression stability of the 20 candidate reference genes in various tissues under different conditions. Results: The experimental results showed that TUB-α was the most stably expressed reference gene across all samples and UBC17 was the most stable in leaves and young stems under Hypsipyla robusta (H. robusta) and methyl jasmonate (MeJA) treatments. In addition, PP2C59 and UBC5B were the best-performing genes in leaves under H. robusta treatment, while HIS1 and ACT7 were the best reference genes in young stems. The two best reference genes were 60S-18 and TUB-α after treatment at 4 °C. The expression of HIS6 and MUB1 was the most stable under PEG6000 treatment. The accuracy of the selected reference genes was verified using the transcription factor MYB3 (TcMYB3) gene. Conclusions: This is the first report to verify the best reference genes for normalizing gene expression in T. ciliata under different conditions, which will facilitate future elucidation of gene regulations in this species.