No abstract

Lycoris aurea (L' Hér.) Herb, a perennial grass species, produces a unique variety of pharmacologically active Amaryllidaceae alkaloids. However, the key enzymes and their expression pattern involved in the biosynthesis of Amaryllidaceae alkaloids (especially for galanthamine) are far from being fully understood. Quantitative real-time polymerase chain reaction (qRT-PCR), a commonly used method for quantifying gene expression, requires stable reference genes to normalize its data. In this study, to choose the appropriate reference genes under different experimental conditions, 14 genes including YLS8 (mitosis protein YLS8), CYP2 (Cyclophilin 2), CYP 1 (Cyclophilin 1), TIP41 (TIP41-like protein), EXP2 (Expressed protein 2), PTBP1 (Polypyrimidine tract-binding protein 1), EXP1 (Expressed protein 1), PP2A (Serine/threonine-protein phosphatase 2A), β-TUB (β-tubulin), α-TUB (α-tubulin), EF1-α (Elongation factor 1-α), UBC (Ubiquitin-conjugating enzyme), ACT (Actin) and GAPDH (Glyceraldehyde 3-phosphate dehydrogenase) were selected from the transcriptome datasets of L. aurea. And then, expressions of these genes were assessed by qRT-PCR in various tissues and the roots under different treatments. The expression stability of the 14 candidates was analyzed by three commonly used software programs (geNorm, NormFinder, and BestKeeper), and their results were further integrated into a comprehensive ranking based on the geometric mean. The results show the relatively stable genes for each subset as follows: (1) EXP1 and TIP41 for all samples; (2) UBC and EXP1 for NaCl stress; (3) PTBP1 and EXP1 for heat stress, polyethylene glycol (PEG) stress and ABA treatment; (4) UBC and CYP2 for cold stress; (5) PTBP1 and PP2A for sodium nitroprusside (SNP) treatment; (6) CYP1 and TIP41 for methyl jasmonate (MeJA) treatment; and (7) EXP1 and TIP41 for various tissues. The reliability of these results was further enhanced through comparison between part qRT-PCR result and RNA sequencing (RNA-seq) data. In summary, our results identified appropriate reference genes for qRT-PCR in L. aurea, and will facilitate gene expression studies under these conditions.

In hepatocellular carcinoma (HCC), dysregulated expression of DDX5 (DEAD box protein 5) and impaired autophagy have been reported separately. However, the relationship between them has not been explored. Here we present evidence to show that, by interacting with autophagic receptor p62, DDX5 promotes autophagy and suppresses tumorigenesis. DDX5 inversely correlated with p62/sequestosome 1 (SQSTM1) expression in hepatitis B virus (HBV)‐associated and non‐HBV‐associated HCCs. Patients with low DDX5 expression showed poor prognosis after tumor resection. We found that DDX5 overexpression induced, while DDX5 knockdown attenuated, autophagic flux in HepG2 and Huh7 cells. DDX5 promoted p62 degradation and markedly reduced the half‐life of p62. Moreover, DDX5 overexpression dramatically reduced, while DDX5 knockdown promoted, cancer cell growth and tumorigenesis in vitro and in vivo. We found that DDX5 bound to p62 and interfered with p62/TRAF6 (tumor necrosis factor receptor–associated factor 6) interaction. Further findings revealed that the N‐terminal domain of DDX5, involved in the interaction with p62, was sufficient to induce autophagy independent of its RNA binding and helicase activity. DDX5 overexpression decreased p62/TRAF6‐mediated lysine 63‐linked ubiquitination of mammalian target of rapamycin (mTOR) and subsequently inhibited the mTOR signaling pathway. Knockdown of TRAF6 blocked DDX5‐induced autophagy. Furthermore, we showed that miR‐17‐5p downregulated DDX5 and impaired autophagy. Inhibition of miR‐17‐5p promoted autophagic flux and suppressed tumor growth in HCC xenograft models. Conclusion: Our findings define a noncanonical pathway that links miR‐17‐5p, DDX5, p62/TRAF6, autophagy, and HCC. These findings open an avenue for the treatment of HCC.

Volvariella volvacea (V. volvacea), commonly referred to as Chinese (paddy straw) mushroom, is a basidiomycete with a protein-rich volva and pileus. Selecting appropriate reference genes is a crucial step in the normalization of quantitative real-time PCR data. Therefore, 12 candidate reference genes were selected from the V. volvacea transcriptome based on previous studies and then BestKeeper, geNorm, and NormFinder were used to identify reference genes stably expressed during different developmental stages and conditions. Of the 12 candidate reference genes, SPRY domain protein (SPRYp), alpha-tubulin (TUBα), cyclophilin (CYP), L-asparaginase (L-asp), and MSF1-domain-containing protein (MSF1) were the most stably expressed under different experimental conditions, while 18S ribosomal RNA (18S), 28S ribosomal RNA (28S), and beta-actin (ACTB) were the least stably expressed. This investigation not only revealed potential factors influencing the suitability of reference genes, but also identified optimal reference genes from a pool of candidate genes under a wide range of conditions.

Peucedanum praeruptorum Dunn is well-known traditional Chinese medicine. However, little is known in the biosynthesis and the transport mechanisms of its coumarin compounds at the molecular level. Although transcriptomic sequence is playing an increasingly significant role in gene discovery, it is not sufficient in predicting the specific function of target gene. Furthermore, there is also a huge database to be analyzed. In this study, RNA sequencing assisted transcriptome dataset and high-performance liquid chromatography (HPLC) coupled with electrospray-ionization quadrupole time-of-flight mass spectrometry (Q-TOF MS)-based metabolomics dataset of P. praeruptorum were firstly constructed for gene discovery and compound identification. Subsequently, methyl jasmonate (MeJA)-induced gene expression analysis and metabolomics analysis were conducted to narrow-down the dataset for selecting the candidate genes and the potential marker metabolites. Finally, the genes involved in coumarins biosynthesis and transport were predicted with parallel analysis of transcript and metabolic profiles. As a result, a total of 40,952 unigenes and 19 coumarin compounds were obtained. Based on the results of gene expression and metabolomics analysis, 7 cytochrome-P450 and 8 multidrug resistance transporter unigenes were selected as candidate genes and 8 marker compounds were selected as biomarkers, respectively. The parallel analysis of gene expression and metabolites accumulation indicated that the gene labeled as 23,746, 228, and 30,922 were related to the formation of the coumarin core compounds whereas 36,276 and 9533 participated in the prenylation, hydroxylation, cyclization or structural modification. Similarly, 1462, 20,815, and 15,318 participated in the transport of coumarin core compounds while 124,029 and 324,293 participated in the transport of the modified compounds. This finding suggested that integration of a decrescent transcriptome and metabolomics dataset could largely narrow down the number of gene to be investigated and significantly improve the efficiency of functional gene predication. In addition, the large amount of transcriptomic data produced from P. praeruptorum and the genes discovered in this study would provide useful information in investigating the biosynthesis and transport mechanism of coumarins.