Project description:Preeclampsia is usually considered as a placental basis of diseases, as there are many differently expressed proteins or pathogenic proteins expressed in the placenta. Owing to the important role of post-transcriptional gene regulation in phenotypes and functions of cells, non-coding ribonucleic acid (ncRNA) molecules contributed to the regulation. We collected 7 placental samples from 3 preeclampsia patients and 4 normal women, focused on the basal plate of placenta, as it is the direct connection of mother and fetal, and adopted SBC human ceRNA array V1.0(4×180K)and human miRNA microarray (8*60 K). The results revealed that expressions of 2840 lncRNAs, 1093 mRNAs, 4282 circRNAs and 4 miRNAs were different between preeclampsia and normal placentas. The functions of differentially expressed lncRNAs and co-expressed potential targeting genes were predicted by analyzing Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathway analysis. Furthermore, we analyzed and find the co-expression and interaction patterns of different RNAs and possible ceRNA mechanism. The present study provided a systematic perspective on the potential function of non-coding RNAs (ncRNAs) in the pathogenesis of preeclampsia.
Project description:Preeclampsia is usually considered as a placental basis of diseases, as there are many differently expressed proteins or pathogenic proteins expressed in the placenta. Owing to the important role of post-transcriptional gene regulation in phenotypes and functions of cells, non-coding ribonucleic acid (ncRNA) molecules contributed to the regulation. We collected 7 placental samples from 3 preeclampsia patients and 4 normal women, focused on the basal plate of placenta, as it is the direct connection of mother and fetal, and adopted SBC human ceRNA array V1.0(4×180K)and human miRNA microarray (8*60 K). The results revealed that expressions of 2840 lncRNAs, 1093 mRNAs, 4282 circRNAs and 4 miRNAs were different between preeclampsia and normal placentas. The functions of differentially expressed lncRNAs and co-expressed potential targeting genes were predicted by analyzing Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathway analysis. Furthermore, we analyzed and find the co-expression and interaction patterns of different RNAs and possible ceRNA mechanism. The present study provided a systematic perspective on the potential function of non-coding RNAs (ncRNAs) in the pathogenesis of preeclampsia.
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.
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 (≥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.
Project description:To investigate the differentially expressed lncRNAs and mRNAs in human placenta between normal pregnancy and preeclampsia, we performed the human LncRNA microarray analysis of 8 samples from clinical patients.
Project description:The maintenance of coordinated powerful episodic contractions of the uterus is the crucial factor for normal labor. The uterine contractility is gradually enhanced with the progression of labor, which is related to the gene expression of myometrium, competing endogenous RNA (ceRNA) can also regulate the gene expression. To better understand the role of ceRNA network in labor, transcriptome sequencing was performed on the myometrium of 17 parturients at different labor duration. Furthermore, an correlated analysis was performed to identify mRNA, long non-coding RNA (lncRNA), circular RNA (circRNA), and microRNA (miRNA) which correlated with their expression levels and labor duration. Then, targeting relationships between mRNAs, lncRNAs, circRNAs and miRNAs were predicted, and the ceRNA regulatory network was established.This analysis identified 934 RNAs positively correlated with labor duration (859 mRNAs, 28 lncRNAs, 45 circRNAs, and 2 miRNAs) and 153 RNAs negatively correlated with labor duration (122 mRNAs, 28 lncRNAs, and 3 miRNAs).
Project description:The maintenance of coordinated powerful episodic contractions of the uterus is the crucial factor for normal labor. The uterine contractility is gradually enhanced with the progression of labor, which is related to the gene expression of myometrium, competing endogenous RNA (ceRNA) can also regulate the gene expression. To better understand the role of ceRNA network in labor, transcriptome sequencing was performed on the myometrium of 17 parturients at different labor duration. Furthermore, an correlated analysis was performed to identify mRNA, long non-coding RNA (lncRNA), circular RNA (circRNA), and microRNA (miRNA) which correlated with their expression levels and labor duration. Then, targeting relationships between mRNAs, lncRNAs, circRNAs and miRNAs were predicted, and the ceRNA regulatory network was established.This analysis identified 934 RNAs positively correlated with labor duration (859 mRNAs, 28 lncRNAs, 45 circRNAs, and 2 miRNAs) and 153 RNAs negatively correlated with labor duration (122 mRNAs, 28 lncRNAs, and 3 miRNAs).
Project description:Cross-talk between competitive endogenous RNAs (ceRNAs) may play a critical role in revealing potential mechanisms of tumor development and physiology. Glioblastoma is the most common type of malignant primary brain tumor, and the mechanisms of tumor genesis and development in glioblastoma are unclear. Here, to investigate the role of non-coding RNAs and the ceRNA network in glioblastoma, we performed paired-end RNA sequencing and microarray analyses to obtain the expression profiles of mRNAs, lncRNAs circRNAs and miRNAs. We identified that the expression of 501 lncRNAs, 1789 mRNAs, 2038 circRNAs and 143 miRNAs were often altered between glioblastoma and matched normal brain tissue. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed on these differentially expressed mRNAs and miRNA-mediated target genes of lncRNAs and circRNAs. Furthermore, we used a multi-step computational framework and several bioinformatics methods to construct a ceRNA network combining mRNAs, miRNAs, lncRNAs and circRNA, based on co-expression analysis between the differentially expressed RNAs. We identified that plenty of lncRNAs, CircRNAs and their downstream target genes in the ceRNA network are related to glutamatergic synapse, suggesting that glutamate metabolism is involved in glioma biological functions. Our results will accelerate the understanding of tumorigenesis, cancer progression and even therapeutic targeting in glioblastoma. We hope to inspire researchers to study the role of non-coding RNAs in glioblastoma.