Many prediction tools for microRNA (miRNA) targets have been developed, but inconsistent predictions were observed across multiple algorithms, which can make further analysis difficult. Moreover, the nomenclature of human miRNAs changes rapidly. To address these issues, we developed a web-based system, miRSystem, for converting queried miRNAs to the latest annotation and predicting the function of miRNA by integrating miRNA target gene prediction and function/pathway analyses. First, queried miRNA IDs were converted to the latest annotated version to prevent potential conflicts resulting from multiple aliases. Next, by combining seven algorithms and two validated databases, potential gene targets of miRNAs and their functions were predicted based on the consistency across independent algorithms and observed/expected ratios. Lastly, five pathway databases were included to characterize the enriched pathways of target genes through bootstrap approaches. Based on the enriched pathways of target genes, the functions of queried miRNAs could be predicted. MiRSystem is a user-friendly tool for predicting the target genes and their associated pathways for many miRNAs simultaneously. The web server and the documentation are freely available at http://mirsystem.cgm.ntu.edu.tw/.

Background: Although cigarette smoking is the major risk factor for lung cancer, only 7% of female lung cancer patients in Taiwan have a history of smoking. The genetic mechanisms of carcinogenesis in nonsmokers are unclear, but semaphorins have been suggested to play a role as lung tumor suppressors. This report is a comprehensive analysis of the molecular signature of nonsmoking female lung cancer patients in Taiwan, with a particular focus on the semaphorin gene family.

DNA arrays were used to investigate the functional role of Rox1 in mediating acclimatization to anaerobic conditions in Saccharomyces cerevisiae . Multiple growth conditions for wild-type and rox1 null strains were used to identify open reading frames with a statistically robust response to this repressor. These results were compared to those obtained for a wild-type strain in response to oxygen availability. Transcripts of nearly one-sixth of the genome were differentially expressed ( P < 0.05) with respect to oxygen availability, the majority (>65%) being down-regulated under anoxia. Of the anaerobically induced genes, about one-third (106) contain putative Rox1-binding sites in their promoters and were significantly ( P < 0.05) up-regulated in the rox1 null strains under aerobiosis. Additional promoter searches revealed that nearly one-third of the anaerobically induced genes contain an AR1 site(s) for the Upc2 transcription factor, suggesting that Upc2 and Rox1 regulate the majority of anaerobically induced genes in S. cerevisiae . Functional analyses indicate that a large fraction of the anaerobically induced genes are involved in cell stress (∼1/3), cell wall maintenance (∼1/8), carbohydrate metabolism (∼1/10), and lipid metabolism (∼1/12), with both Rox1 and Upc2 predominating in the regulation of this latter group and Upc2 predominating in cell wall maintenance. Mapping the changes in expression of functional regulons onto metabolic pathways has provided novel insight into the role of Rox1 and other trans -acting factors in mediating the physiological response of S. cerevisiae to anaerobic conditions.

MicroRNAs (miRNAs) are short, non-coding RNA molecules that play critical roles in human malignancy. However, the regulatory characteristics of miRNAs in triple-negative breast cancer, a phenotype of breast cancer that does not express the genes for estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2, are still poorly understood. In this study, miRNA expression profiles of 24 triple-negative breast cancers and 14 adjacent normal tissues were analyzed using deep sequencing technology. Expression levels of miRNA reads were normalized with the quantile-quantile scaling method. Deregulated miRNAs in triple-negative breast cancer were identified from the sequencing data using the Student’s t-test. Quantitative reverse transcription PCR validations were carried out to examine miRNA expression levels. Potential target candidates of a miRNA were predicted using published target prediction algorithms. Luciferase reporter assay experiments were performed to verify a putative miRNA-target relationship. Validated molecular targets of the deregulated miRNAs were retrieved from curated databases and their associations with cancer progression were discussed. A novel 25-miRNA expression signature was found to effectively distinguish triple-negative breast cancers from surrounding normal tissues in a hierarchical clustering analysis. We documented the evidence of seven polycistronic miRNA clusters preferentially harboring deregulated miRNAs in triple-negative breast cancer. Two of these miRNA clusters (miR-143-145 at 5q32 and miR-497-195 at 17p13.1) were markedly down-regulated in triple-negative breast cancer, while the other five miRNA clusters (miR-17-92 at 13q31.3, miR-183-182 at 7q32.2, miR-200-429 at 1p36.33, miR-301b-130b at 22q11.21, and miR-532-502 at Xp11.23) were up-regulated in triple-negative breast cancer. Moreover, miR-130b-5p from the miR-301b-130b cluster was shown to directly repress the cyclin G2 (CCNG2) gene, a crucial cell cycle regulator, in triple-negative breast cancer cells. Luciferase reporter assays showed that miR-130b-5p-mediated repression of CCNG2 was dependent on the sequence of the 3′-untranslated region. The findings described in this study implicate a miR-130b-5p-CCNG2 axis that may be involved in the malignant progression of triple-negative breast cancer. Our work delivers a clear picture of the global miRNA regulatory characteristics in triple-negative breast cancer and extends the current knowledge of microRNA regulatory network.

We conducted a comprehensive genomic analysis of the temporal response of yeast to anaerobiosis (six generations) and subsequent aerobic recovery (≈2 generations) to reveal metabolic-state (galactose versus glucose)-dependent differences in gene network activity and function. Analysis of variance showed that far fewer genes responded (raw P value of ≤10 ⁻⁸ ) to the O ₂ shifts in glucose (1,603 genes) than in galactose (2,388 genes). Gene network analysis reveals that this difference is due largely to the failure of “stress”-activated networks controlled by Msn2/4, Fhl1, MCB, SCB, PAC, and RRPE to transiently respond to the shift to anaerobiosis in glucose as they did in galactose. After ≈1 generation of anaerobiosis, the response was similar in both media, beginning with the deactivation of Hap1 and Hap2/3/4/5 networks involved in mitochondrial functions and the concomitant derepression of Rox1-regulated networks for carbohydrate catabolism and redox regulation and ending (≥2 generations) with the activation of Upc2- and Mot3-regulated networks involved in sterol and cell wall homeostasis. The response to reoxygenation was rapid (<5 min) and similar in both media, dominated by Yap1 networks involved in oxidative stress/redox regulation and the concomitant activation of heme-regulated ones. Our analyses revealed extensive networks of genes subject to combinatorial regulation by both heme-dependent (e.g., Hap1, Hap2/3/4/5, Rox1, Mot3, and Upc2) and heme-independent (e.g., Yap1, Skn7, and Puf3) factors under these conditions. We also uncover novel functions for several cis -regulatory sites and trans -acting factors and define functional regulons involved in the physiological acclimatization to changes in oxygen availability.