Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Dicer-microRNA-Myc circuit promotes transcription of hundreds of long noncoding RNAs

ABSTRACT: Long noncoding RNAs (lncRNAs) are important regulators of cell fate, and their mis-expression has been implicated in many diseases. While distinct polymerases generate messenger vs. noncoding ribosomal or tRNAs3, little is known about distinct mechanisms controlling lncRNA expression. Here we show that transcription of lncRNAs is quantitatively different from that of messenger RNAs (mRNAs)--as revealed by deficiency of Dicer (Dcr), a key ribonuclease that generates microRNAs (miRNAs). Loss of Dcr in mouse embryonic stem cells (mESCs) led surprisingly to decreased level of the majority of lncRNAs. The canonical Dgcr8-Dcr-miRNA pathway is required for robust lncRNA expression, at the level of transcriptional initiation and elongation of lncRNA genes rather than at the level of their stability. cMyc, an oncogenic transcription factor, whose expression is indirectly regulated by Dcr-miRNA in mESCs, is partly responsible for lncRNA transcription. Loss of cMyc led to a more dramatic decrease of lncRNAs than mRNAs, and cMyc overexpression rescues lncRNA expression in Dcr KO cells. A quantitative metric of “mRNA-lncRNA decoupling” revealed that Dcr and cMyc differentially regulate lncRNAs vs. mRNAs in diverse cell types and in vivo, as evidenced by hundreds of microarray experiments. Thus, Dcr and cMyc may allow numerous lncRNAs to be activated or deactivated as a class, implicating lncRNAs to potential regulatory roles in development and disease states where Dcr and cMyc have been associated with. RNA was sequenced from WT and Dcr KO mESCs and the expression of lncRNAs and mRNAs are compared between WT and Dcr KO mESCs.

ORGANISM(S): Mus musculus

SUBMITTER: Kun Qu

PROVIDER: E-GEOD-55338 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Acute myeloid leukemia (AML) is the most common form of acute leukemia in adults and the second most common form of leukemia in children. Multiple lncRNAs participate in normal and may be implicated in malignant hematopoiesis associated with blood cell cancers, such as leukemia. Currently, the expression profile of lncRNAs in pediatric AML is unclear. In this study, we evaluated the lncRNA expression profile in the tissue of three pediatric AML patients with lncRNA microarray techniques. In order to gain insight into the function of targets of lncRNAs, GO term and KEGG pathway annotation were applied to the target gene pool. qPCR was performed to evaluate the expression patterns of dys-regulated lncRNAs. Bone marrow specimens were obtained at the time of diagnosis during routine clinical assessment of 3 pediatric patients with AML, who presented at the Department of Hematology and Oncology, Children's Hospital of Soochow University between 2000 and 2011. Additionally, bone marrow samples from 3 healthy donors were analyzed as controls. Human LncRNA Array analysis was performed by KangChen Bio-tech, Shanghai P.R. China. Total RNA from each sample was quantified by the NanoDrop ND-1000 and RNA integrity was assessed by standard denaturing agarose gel electrophoresis. For microarray analysis, Agilent Array platform was employed. The sample preparation and microarray hybridization were performed based on the manufacturerâs standard protocols with minor modifications. Briefly, mRNA was purified from total RNA after removal of rRNA (mRNA-ONLYâ¢ Eukaryotic mRNA Isolation Kit, Epicentre). Then, each sample was amplified and transcribed into fluorescent cRNA along the entire length of the transcripts without 3â bias utilizing a random priming method. The labeled cRNAs were hybridized onto the Human LncRNA Array v2.0 (8 x 60K, Arraystar). After having washed the slides, the arrays were scanned by the Agilent Scanner G2505C. Agilent Feature Extraction software (version 11.0.1.1) was used to analyze acquired array images. Quantile normalization and subsequent data processing were performed using the GeneSpring GX v12.0 software package (Agilent Technologies). After quantile normalization of the raw data, LncRNAs and mRNAs that at least 4 out of 6 samples have flags in Present or Marginal (âAll Targets Valueâ) were chosen for further data analysis. Differentially expressed LncRNAs and mRNAs with statistical significance between the two groups were identified through Volcano Plot filtering. Pathway analysis and GO analysis were applied to determine the roles of these differentially expressed mRNAs played in these biological pathways or GO terms. Finally, Hierarchical Clustering was performed to show the distinguishable LncRNAs and mRNAs expression pattern among samples.

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Dicer-microRNA-Myc circuit promotes transcription of hundreds of long noncoding RNAs

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