Background MicroRNAs （miRNAs） are small noncoding regulatory RNAs whose aberrant expression may be observed in many malignancies. However, few data are yet available on human primary medulloblastomas. This work aime...Background MicroRNAs （miRNAs） are small noncoding regulatory RNAs whose aberrant expression may be observed in many malignancies. However, few data are yet available on human primary medulloblastomas. This work aimed to identify that whether miRNAs would be aberrantly expressed in tumor tissues compared with non-tumorous cerebellum tissues from same patients, and to explore a possible role during carcinogenesis. Methods A high throughput microRNA microarray was performed in human primary medulloblastoma specimens to investigate differentially expressed miRNAs, and some miRNAs were validated using real-time quantitative RT-PCR method. In addition, the predicted target genes for the most significantly downor up-regulated miRNAs were analyzed by using a newly modified ensemble algorithm. Results Nine miRNA species were differentially expressed in medulloblastoma specimens versus normal non-tumorous cerebellum tissues. Of these, 4 were over expressed and 5 were under expressed. The changes ranged from 0.02-fold to 6.61-fold. These findings were confirmed using real-time quantitative RT-PCR for most significant deregulated miRNAs （miR-17, miR-100, miR-106b, and miR-218） which are novel and have not been previously published. Interestingly, most of the predicted target genes for these miRNAs were involved in medulloblastoma carcinogenesis. Conclusions MJRNAs are differentially expressed between human medulloblastoma and non-tumorous cerebellum tissue. MiRNAs may play a role in the tumorigenesis of medulloblastoma and maybe serve as potential targets for novel therapeutic strategies in future.展开更多
Computational prediction of potential microRNAs （miRNAs） and their target genes was performed to identify the miRNAs and genes associated with temperature response in rice. The data of temperature-responsive miRNAs ...Computational prediction of potential microRNAs （miRNAs） and their target genes was performed to identify the miRNAs and genes associated with temperature response in rice. The data of temperature-responsive miRNAs of Arabidopsis, and miRNAs and the whole genome data of rice were used to predict potential miRNAs in Oryza sativa involved in temperature response. A total of 55 miRNAs were common in both the species, and 27 miRNAs were predicted at the first time in rice. Target genes were searched for these 27 miRNAs in rice genome following stringent criteria. Real time PCR based on expression analysis of nine miRNAs showed that majority of the miRNAs were down regulated under heat stress for rice cultivar Nagina 22. Furthermore, miR169, miR1884 and miR160 showed differential expression in root and shoot tissues of rice. Identification and expression studies of miRNAs during heat stress will advance the understanding of gene regulation under stress in rice.展开更多
The Cancer Genome Arias （TCGA） （http：//cancergenome.nih.gov） is a valuable data resource focused on an increasing number of well-characterized cancer genomes. In part, TCGA provides detailed information about can...The Cancer Genome Arias （TCGA） （http：//cancergenome.nih.gov） is a valuable data resource focused on an increasing number of well-characterized cancer genomes. In part, TCGA provides detailed information about cancer-dependent gene expression changes, including changes in the expression of transcription-regulating microRNAs. We developed a web interface tool MMiRNA-Tar （http：f/bioinfl.indstate.edufMMiRNA-Tar） that can calculate and plot the correlation of expression for mRNA-microRNA pairs across samples or over a time course for a list of pairs under different prediction confidence cutoff criteria. Prediction confidence was estab- lished by requiring that the proposed mRNA-microRNA pair appears in at least one of three target prediction databases： TargetProfiler, TargetScan, or miRanda. We have tested our MMiRNA-Tar tool through analyzing 53 tumor and 11 normal samples of bladder urothelial carcinoma （BLCA） datasets obtained from TCGA and identified 204 microRNAs. These microRNAs were correlated with the mRNAs of five previously-reported bladder cancer risk genes and these selected pairs exhib- ited correlations in opposite direction between the tumor and normal samples based on the cus- tomized cutoff criterion of prediction. Furthermore, we have identified additional 496 genes （830 pairs） potentially targeted by 79 significant microRNAs out of 204 using three cutoff criteria, i.e.,false discovery rate （FDR） 〈 0.1, opposite correlation coefficient between the tumor and normal samples, and predicted by at least one of three target prediction databases. Therefore, MMiRNA- Tar provides researchers a convenient tool to visualize the co-relationship between microRNAs and mRNAs and to predict their targeting relationship. We believe that correlating expression profiles for microRNAs and mRNAs offers a complementary approach for elucidating their interactions.展开更多
目的:通过筛选mRNA(Clariom^(TM) S Assay)芯片及miRNA芯片的显著差异性基因,预测microRNA相关靶基因,探究丹苘软胶囊改善肝细胞脂肪代谢的调控机制。方法:提取丹苘软胶囊灌胃SD大鼠的含药血清,并对BRL大鼠肝细胞取对数生长期细胞进行实...目的:通过筛选mRNA(Clariom^(TM) S Assay)芯片及miRNA芯片的显著差异性基因,预测microRNA相关靶基因,探究丹苘软胶囊改善肝细胞脂肪代谢的调控机制。方法:提取丹苘软胶囊灌胃SD大鼠的含药血清,并对BRL大鼠肝细胞取对数生长期细胞进行实验,以阴性对照血清做对照,提取细胞总RNAs,采用Clariom S表达谱芯片及microRNA芯片检测细胞mRNA及miRNA的表达水平。运用生物信息学方法预测miRNA的靶基因,对脂肪代谢相关基因进行富集分析和通路分析。结果:经筛选和预测得到5629个预测靶基因参与20种生物学过程,7种细胞成分,有20种分子作用,神经营养素信号通路、丙型肝炎、PI3K-Akt信号通路被富集;rno-miR-26b-5p、rno-miR-129b-5p、rno-miR-21b-5p为调控网络中心;IPA数据库共检出31个与实验有关的脂肪代谢基因。结论:丹苘软胶囊在治疗非酒精性脂肪肝(nonalcoholic fatty liver disease,NAFLD)的机制可能与rno-miR-26b-5p、rno-miR-129b-5p、rno-miR-21b-5p,神经营养素信号通路、丙型肝炎、PI3K-Akt信号通路相关性较高。展开更多
文摘Background MicroRNAs （miRNAs） are small noncoding regulatory RNAs whose aberrant expression may be observed in many malignancies. However, few data are yet available on human primary medulloblastomas. This work aimed to identify that whether miRNAs would be aberrantly expressed in tumor tissues compared with non-tumorous cerebellum tissues from same patients, and to explore a possible role during carcinogenesis. Methods A high throughput microRNA microarray was performed in human primary medulloblastoma specimens to investigate differentially expressed miRNAs, and some miRNAs were validated using real-time quantitative RT-PCR method. In addition, the predicted target genes for the most significantly downor up-regulated miRNAs were analyzed by using a newly modified ensemble algorithm. Results Nine miRNA species were differentially expressed in medulloblastoma specimens versus normal non-tumorous cerebellum tissues. Of these, 4 were over expressed and 5 were under expressed. The changes ranged from 0.02-fold to 6.61-fold. These findings were confirmed using real-time quantitative RT-PCR for most significant deregulated miRNAs （miR-17, miR-100, miR-106b, and miR-218） which are novel and have not been previously published. Interestingly, most of the predicted target genes for these miRNAs were involved in medulloblastoma carcinogenesis. Conclusions MJRNAs are differentially expressed between human medulloblastoma and non-tumorous cerebellum tissue. MiRNAs may play a role in the tumorigenesis of medulloblastoma and maybe serve as potential targets for novel therapeutic strategies in future.
基金Financial support received from NICRA (National Initiative of Climate and Resilient Agriculture) project is acknowledged.
文摘Computational prediction of potential microRNAs （miRNAs） and their target genes was performed to identify the miRNAs and genes associated with temperature response in rice. The data of temperature-responsive miRNAs of Arabidopsis, and miRNAs and the whole genome data of rice were used to predict potential miRNAs in Oryza sativa involved in temperature response. A total of 55 miRNAs were common in both the species, and 27 miRNAs were predicted at the first time in rice. Target genes were searched for these 27 miRNAs in rice genome following stringent criteria. Real time PCR based on expression analysis of nine miRNAs showed that majority of the miRNAs were down regulated under heat stress for rice cultivar Nagina 22. Furthermore, miR169, miR1884 and miR160 showed differential expression in root and shoot tissues of rice. Identification and expression studies of miRNAs during heat stress will advance the understanding of gene regulation under stress in rice.
基金supported by the startup funds of Indiana State University,USA to YB
文摘The Cancer Genome Arias （TCGA） （http：//cancergenome.nih.gov） is a valuable data resource focused on an increasing number of well-characterized cancer genomes. In part, TCGA provides detailed information about cancer-dependent gene expression changes, including changes in the expression of transcription-regulating microRNAs. We developed a web interface tool MMiRNA-Tar （http：f/bioinfl.indstate.edufMMiRNA-Tar） that can calculate and plot the correlation of expression for mRNA-microRNA pairs across samples or over a time course for a list of pairs under different prediction confidence cutoff criteria. Prediction confidence was estab- lished by requiring that the proposed mRNA-microRNA pair appears in at least one of three target prediction databases： TargetProfiler, TargetScan, or miRanda. We have tested our MMiRNA-Tar tool through analyzing 53 tumor and 11 normal samples of bladder urothelial carcinoma （BLCA） datasets obtained from TCGA and identified 204 microRNAs. These microRNAs were correlated with the mRNAs of five previously-reported bladder cancer risk genes and these selected pairs exhib- ited correlations in opposite direction between the tumor and normal samples based on the cus- tomized cutoff criterion of prediction. Furthermore, we have identified additional 496 genes （830 pairs） potentially targeted by 79 significant microRNAs out of 204 using three cutoff criteria, i.e.,false discovery rate （FDR） 〈 0.1, opposite correlation coefficient between the tumor and normal samples, and predicted by at least one of three target prediction databases. Therefore, MMiRNA- Tar provides researchers a convenient tool to visualize the co-relationship between microRNAs and mRNAs and to predict their targeting relationship. We believe that correlating expression profiles for microRNAs and mRNAs offers a complementary approach for elucidating their interactions.
