Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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LncRNA expression profiling for 6 human plasma samples from Coronary Artery Disease patients and non Coronary Artery Disease patients

ABSTRACT: The human LncRNA microarray analysis of the 6 plasma samples from Coronary Artery Disease patients and non Coronary Artery Disease Agilent Feature Extraction software (version 11.0.1.1) was used to analyze acquired array images. Quantile normalization was performed using Expander6 and subsequent data processing was performed using the GeneSpring GX v11.5.1 software package (Agilent Technologies). After low intensity filtering, LncRNAs and mRNAs that at least 2 out of 12 samples have flags in Present or Marginal (“All Targets Value”) were chosen for quantile normalization and further data analysis. Differentially expressed LncRNAs and mRNAs with statistical significance 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 expression pattern among samples.

ORGANISM(S): Homo sapiens

SUBMITTER: yujia yang

PROVIDER: E-GEOD-68506 | 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.

Project description:Background: Long non-coding RNAs (lncRNAs) are an important class of pervasive genes involved in a variety of biological functions. They are aberrantly expressed in many types of diseases. We want to study the lncRNAs profiles in preeclampsia. Preeclampsia has been observed in patients with molar pregnancy where a fetus is absent demonstrating that the placenta is sufficient to cause the condition. So we analyze the lncRNAs profiles in preeclampsia placentas. In this study, we described the lncRNAs profiles in 6 preeclampsia placentas (T) and 5 matched normal pregnancy placentas (N) tissues by microarray. Methodology/Principal Findings: With abundant and varied probes accounting 33,045 LncRNAs in our microarray, the number of lncRNAs that expressed at a certain level could be detected is 28,443. From the data we found there were 738 lncRNAs that differentially expressed (M-bM-^IM-%1.5 fold-change) among preeclampsia placentas compared with matched controls. Up to 18,063 coding transcripts could be detected in placenta samples through 30,215 coding transcripts probes. Coding-non-coding gene co-expression networks (CNC network) were constructed based on the correlation analysis between the differential expressed lncRNAs and mRNAs. According to the GO-Pathway analysis of differential expressed lncRNAs/mRNAs, we choose three lncRNAs to analyze the relationship between lncRNAs and preeclampsia. LOC391533, LOC284100, CEACAMP8 were evaluated by qPCR in 40 of preeclampsia placentas and 40 of controls. The results showed three lncRNAs were aberrantly expressed in preeclampsia placentas compared with controls. Conclusions/Significance: Our study is the first one to determine genome-wide lncRNAs expression patterns in preeclampsia placenta by microarray. The results displayed that clusters of lncRNAs were aberrantly expressed in preeclampsia placenta compared with controls, which revealed that lncRNAs differentially expressed in preeclampsia placenta may exert a partial or key role in preeclampsia development. Misregulation of LOC391533, LOC284100, CEACAMP8 might be associated with preeclampsia. Taken together, this study may provide potential targets for future treatment of preeclampsia and novel insights into preeclampsia biology. LncRNAs/mRNAs profiles in 6 preeclampsia placentas and 5 matched normal pregnancy placentas tissues by microarray using Arraystar v2.0.

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LncRNA expression profiling for 6 human plasma samples from Coronary Artery Disease patients and non Coronary Artery Disease patients

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