Search Results for: lncrna hong kong
Inheritable and Precise Large Genomic Deletions of Non-Coding RNA Genes in Zebrafish Using TALENs
Transcription activator-like effector nucleases (TALENs) have so far been applied to disrupt protein-coding genes which constitute only 2–3% of the genome in animals. The majority (70–90%) of the animal genome is actually transcribed as non-coding RNAs (ncRNAs), yet the lack of efficient tools to knockout ncRNA genes hinders studies on their in vivo functions.
Here a team led by researchers at The Chinese University of Hong Kong have developed novel strategies using TALENs to achieve precise and inheritable large genomic deletions and knockout of ncRNA genes in zebrafish. They have demonstrated that individual miRNA genes could be disrupted using one pair of TALENs, whereas large microRNA (miRNA) gene clusters and long non-coding RNA (lncRNA) genes could be precisely deleted using two pairs of TALENs. They have generated large genomic deletions of two miRNA clusters (the 1.2 kb miR-17-92 cluster and the 79.8 kb miR-430 cluster) and one long non-coding RNA (lncRNA) gene (the 9.0 kb malat1), and the deletions are transmitted through the germline. Taken together, these results establish TALENs as a robust tool to engineer large genomic deletions and knockout of ncRNA genes, thus opening up new avenues in the application of TALENs to study the genome in vivo.
- Liu Y, Luo D, Zhao H, Zhu Z, Hu W, et al. (2013) Inheritable and Precise Large Genomic Deletions of Non-Coding RNA Genes in Zebrafish Using TALENs. PLoS ONE 8(10), e76387. [article]
Incoming search terms:
- lncRNA Hong Kong
A long non-coding RNA signature in glioblastoma multiforme predicts survival
Long non-coding RNAs (lncRNAs) represent the leading edge of cancer research, and have been implicated in cancer biogenesis and prognosis. Researchers at The University of Hong Kong aimed to identify lncRNA signatures that have prognostic values in glioblastoma multiforme (GBM). Using a lncRNA-mining approach, they performed lncRNA expression profiling in 213 GBM tumors from The Cancer Genome Atlas (TCGA), randomly divided into a training (n=107) and a testing set (n=106). They analyzed the associations between lncRNA signatures and clinical outcome in the training set, and validated the findings in the testing set. The researchers also validated the identified lncRNA signature in another two independent GBM data sets from Gene Expression Omnibus (GEO), which contained specimens from 68 and 101 patients, respectively. They identified a set of six lncRNAs that were significantly associated with the overall survival in the training set (P≤0.01). Based on this six-lncRNA signature, the training-set patients could be classified into high-risk and low-risk subgroups with significantly different survival (HR=2.13, 95% CI=1.38-3.29; P=0.001). The prognostic value of this six-lncRNA signature was confirmed in the testing set and the two independent data sets. Further analysis revealed that the prognostic value of this signature was independent of age and O-6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. The identification of the prognostic lncRNAs indicates the potential roles of lncRNAs in GBM pathogenesis. This six-lncRNA signature may have clinical implications in the subclassification of GBM.
- Zhang XQ, Sun S, Lam KF, Kiang KM, Pu JK, Ho AS, Lui WM, Fung CF, Wong TS, Leung GK. (2013) A long non-coding RNA signature in glioblastoma multiforme predicts survival. Neurobiol Dis [Epub ahead of print]. [abstract]
Incoming search terms:
- lncRNA classification