LncRNAs are regulatory noncoding RNAs that play crucial roles in many biological processes. The dysregulation of lncRNA is thought to be involved in many complex diseases; lncRNAs are often the targets of miRNAs in the indirect regulation of gene expression. Numerous studies have indicated that miRNA-lncRNA interactions are closely related to the occurrence and development of cancers. Thus, it is important to develop an effective method for the identification of cancer-related miRNA-lncRNA interactions. In this study, we compiled 155653 experimentally validated and predicted miRNA-lncRNA associations, which we defined as basic interactions. We next constructed an individual-specific miRNA-lncRNA network (ISMLN) for each cancer sample and a basic miRNA-lncRNA network (BMLN) for each type of cancer by examining the expression profiles of miRNAs and lncRNAs in the TCGA (The Cancer Genome Atlas) database. We then selected potential miRNA-lncRNA biomarkers based on the BLMN. Using this method, we identified cancer-related miRNA-lncRNA biomarkers and modules specific to a certain cancer. This method of profiling will contribute to the diagnosis and treatment of cancers at the level of gene regulatory networks.

Motivation Recent studies have shown that DNA N6-methyladenine (6mA) plays an important role in epigenetic modification of eukaryotic organisms. It has been found that 6mA is closely related to embryonic development, stress response and so on. Developing a new algorithm to quickly and accurately identify 6mA sites in genomes is important for explore their biological functions. Results In this paper, we proposed a new classification method called MM-6mAPred based on a Markov model which makes use of the transition probability between adjacent nucleotides to identify 6mA site. The sensitivity and specificity of our method are 89.32% and 90.11%, respectively. The overall accuracy of our method is 89.72%, which is 6.59% higher than that of the previous method i6mA-Pred. It indicated that, compared with the 41 nucleotide chemical properties used by i6mA-Pred, the transition probability between adjacent nucleotides can capture more discriminant sequence information. Availability and implementation The web server of MM-6mAPred is freely accessible at http://www.insect-genome.com/MM-6mAPred/ Supplementary information Supplementary data are available at Bioinformatics online.

As a novel class of noncoding RNAs, long noncoding RNAs (lncRNAs) have been verified to be associated with various diseases. As large scale transcripts are generated every year, it is significant to accurately and quickly identify lncRNAs from thousands of assembled transcripts. To accurately discover new lncRNAs, we develop a classification tool of random forest (RF) named LncRNApred based on a new hybrid feature. This hybrid feature set includes three new proposed features, which are MaxORF, RMaxORF and SNR. LncRNApred is effective for classifying lncRNAs and protein coding transcripts accurately and quickly. Moreover,our RF model only requests the training using data on human coding and non-coding transcripts. Other species can also be predicted by using LncRNApred. The result shows that our method is more effective compared with the Coding Potential Calculate (CPC). The web server of LncRNApred is available for free at http://mm20132014.wicp.net:57203/LncRNApred/home.jsp.

Granulosa cells are crucial for follicular growth, development, and follicular atresia. X-box binding protein 1 (XBP1), a basic region-leucine zipper protein, is widely involved in cell differentiation, proliferation, apoptosis, cellular stress response, and other signaling pathways. In this study, RNA interference, flow cytometry, western blot, real-time PCR, Cell Counting Kit (CCK8), and ELISA were used to investigate the effect of XBP1 on steroidogenesis, apoptosis, cell cycle, and proliferation of mouse granulosa cells. ELISA analysis showed that XBP1 depletion significantly decreased the concentrations of estradiol (E2). Additionally, the expression of estrogen synthesis enzyme Cyp19a1 was sharply downregulated. Moreover, flow cytometry showed that knockdown of XBP1 increased the apoptosis rate and arrests the cell cycle in S-phase in granulosa cells (GCs). Further study confirmed these results. The expression of CCAAT-enhancer-binding protein homologous protein (CHOP), cysteinyl aspartate specific proteases-3 (caspase-3), cleaved caspase-3, and Cyclin E was upregulated, while that of Bcl-2, Cyclin A1, and Cyclin B1 was downregulated. Simultaneously, CCK8 analysis indicated that XBP1 disruption inhibited cell proliferation. In addition, XBP1 knockdown also alters the expression of Has2 and Ptgs2, two essential genes for folliculogenesis. Collectively, these data reveal a novel critical role of XBP1 in folliculogenesis by regulating the cell cycle, apoptosis, and steroid synthesis of mouse granulosa cells.

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Rapid multi-species sensing is an overarching goal in time-resolved studies of chemical kinetics. Most current laser sources cannot achieve this goal due to their narrow spectral coverage and/or slow wavelength scanning. In this work, a novel mid-IR dual-comb spectrometer is utilized for chemical kinetic investigations. The spectrometer is based on two quantum cascade laser frequency combs and provides rapid (4 µs) measurements over a wide spectral range (~1175–1235 cm−1). Here, the spectrometer was applied to make time-resolved absorption measurements of methane, acetone, propene, and propyne at high temperatures (>1000 K) and high pressures (>5 bar) in a shock tube. Such a spectrometer will be of high value in chemical kinetic studies of future fuels.

Recent studies have shown elongase of very‐long‐chain fatty acids 6 (ELOVL6) is a vital protein for endogenous synthesis of saturated and monounsaturated long‐chain fatty acids in some mammals. Nevertheless, its role in lipid synthesis in buffalo mammary gland is still unclear. In this work, the full‐length coding sequence (CDS) of ELOVL6 was cloned and identified from buffalo mammary gland. As a result, the CDS of this gene is 795 bp, which encodes a polypeptide of 264 amino acid residues. The buffalo ELOVL6 contains an ELO domain which belongs to the ELO superfamily. Among the 10 tissues of buffalo in peak lactation detected by RT‐qPCR, the expression level of ELOVL6 was the highest in the brain, followed by the spleen, and then decreased in the mammary gland, muscle, kidney, heart, liver, rumen, intestine and lung. However, only the expression in the brain and spleen was statistically different from that in other tissues (p < 0.05). Compared with that of the dry‐off period, the mRNA abundance of ELOVL6 in the mammary gland was significantly increased in peak lactation. The experiments based on lentivirus transfection in buffalo mammary epithelial cells (BuMECs) displayed that the overexpression of ELOVL6 markedly promoted the expression of INSIG1, INSIG2, SREBP, PPARG, FASN, GPAM, DGAT2 and APGAT6 genes, and the knockdown of ELOVL6 significantly decreased the mRNA abundance of INSIG2, SREBP, FASN, SCD, GPAM, APGAT6 and TIP47 genes. In addition, the increase or decrease of ELOVL6 expression level also caused the corresponding change of total triglyceride content in the BuMECs. The results here suggest that the ELOVL6 can catalyse the synthesis of long‐chain fatty acids in the BuMECs, and it can indirectly affect the expression of genes related to milk fat synthesis through its catalytic products to promote the lipid biosynthesis of BuMECs.