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Computational analysis of ribonomics datasets identifies long non-coding RNA targets of ?-herpesviral miRNAs.

ABSTRACT: Ribonomics experiments involving crosslinking and immuno-precipitation (CLIP) of Ago proteins have expanded the understanding of the miRNA targetome of several organisms. These techniques, collectively referred to as CLIP-seq, have been applied to identifying the mRNA targets of miRNAs expressed by Kaposi's Sarcoma-associated herpes virus (KSHV) and Epstein-Barr virus (EBV). However, these studies focused on identifying only those RNA targets of KSHV and EBV miRNAs that are known to encode proteins. Recent studies have demonstrated that long non-coding RNAs (lncRNAs) are also targeted by miRNAs. In this study, we performed a systematic re-analysis of published datasets from KSHV- and EBV-driven cancers. We used CLIP-seq data from lymphoma cells or EBV-transformed B cells, and a crosslinking, ligation and sequencing of hybrids dataset from KSHV-infected endothelial cells, to identify novel lncRNA targets of viral miRNAs. Here, we catalog the lncRNA targetome of KSHV and EBV miRNAs, and provide a detailed in silico analysis of lncRNA-miRNA binding interactions. Viral miRNAs target several hundred lncRNAs, including a subset previously shown to be aberrantly expressed in human malignancies. In addition, we identified thousands of lncRNAs to be putative targets of human miRNAs, suggesting that miRNA-lncRNA interactions broadly contribute to the regulation of gene expression.

SUBMITTER: Sethuraman S

PROVIDER: S-EPMC6144796 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Computational analysis of ribonomics datasets identifies long non-coding RNA targets of γ-herpesviral miRNAs.

Sethuraman Sunantha S Thomas Merin M Gay Lauren A LA Renne Rolf R

Nucleic acids research 20180901 16

Ribonomics experiments involving crosslinking and immuno-precipitation (CLIP) of Ago proteins have expanded the understanding of the miRNA targetome of several organisms. These techniques, collectively referred to as CLIP-seq, have been applied to identifying the mRNA targets of miRNAs expressed by Kaposi's Sarcoma-associated herpes virus (KSHV) and Epstein-Barr virus (EBV). However, these studies focused on identifying only those RNA targets of KSHV and EBV miRNAs that are known to encode prote ...[more]

PMID: 29846699

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Project description:The human malaria parasite Plasmodium falciparum has a complex and multi-stage life cycle that requires extensive and precise gene regulation to allow invasion and hijacking of host cells, transmission, and immune escape. To date, the regulatory elements orchestrating these critical parasite processes remain largely unknown. Yet it is becoming increasingly clear that long non-coding RNAs (lncRNAs) could represent a missing regulatory layer across a broad range of organisms.To investigate the regulatory capacity of lncRNA in P. falciparum, we harvested fifteen samples from two time-courses. Our sample set profiled 56 h of P. falciparum blood stage development. We then developed and validated strand-specific, non-polyA-selected RNA sequencing methods, and pursued the first assembly of P. falciparum strand-specific transcript structures from RNA sequencing data. This approach enabled the annotation of over one thousand lncRNA transcript models and their comprehensive global analysis: coding prediction, periodicity, stage-specificity, correlation, GC content, length, location relative to annotated transcripts, and splicing. We validated the complete splicing structure of three lncRNAs with compelling properties. Non-polyA-selected deep sequencing also enabled the prediction of hundreds of intriguing P. falciparum circular RNAs, six of which we validated experimentally.We found that a subset of lncRNAs, including all subtelomeric lncRNAs, strongly peaked in expression during invasion. By contrast, antisense transcript levels significantly dropped during invasion. As compared to neighboring mRNAs, the expression of antisense-sense pairs was significantly anti-correlated during blood stage development, indicating transcriptional interference. We also validated that P. falciparum produces circRNAs, which is notable given the lack of RNA interference in the organism, and discovered that a highly expressed, five-exon antisense RNA is poised to regulate P. falciparum gametocyte development 1 (PfGDV1), a gene required for early sexual commitment events.

Project description:BackgroundHeterogeneity in colorectal cancer (CRC) patients provides novel strategies in clinical decision-making. Identifying distinctive subgroups in patients can improve the screening of CRC and reduce the cost of tests. Metabolism-related long non-coding RNA (lncRNA) can help detection of tumorigenesis and development for CRC patients.MethodsRNA sequencing and clinical data of CRC patients which extracted and integrated from public databases including The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were set as training cohort and validation cohort. Metabolism-related genes were acquired from Kyoto Encyclopedia of Genes and Genomes (KEGG) and the metabolism-related lncRNAs were filtered using correlation analysis. The risk score was calculated based on lncRNAs with prognostic value and verified through survival curve, receiver operating characteristic (ROC) curve and risk curve. Prognostic factors of CRC patients were also analyzed. Nomogram was constructed based on the results of cox regression analyses. The different immune status was observed in the single sample Gene Set Enrichment Analysis (ssGSEA).ResultsThe training cohort and the validation cohort enrolled 432 and 547 CRC patients respectively. A total of 23 metabolism-related lncRNAs with prognostic value were screened out and 10 of which were significantly differentially expressed between tumour and normal tissues. Finally, 8 lncRNAs were used to establish a risk score (DICER1-AS1, PCAT6, GAS5, PRR7-AS1, MCM3AP-AS1, GAS6-AS1, LINC01082 and ADIRF-AS1). Patients were divided into high-risk and low-risk groups according to the median of risk scores in training cohort and the survival curves indicated that the survival prognosis was significantly different. The area under curve (AUC) of the ROC curve in two cohorts were both greater than 0.6. The age, tumour stage and risk score were selected as independent factors and used to construct a nomogram to predict CRC patients' survival rate with the c-index of 0.806. The ssGSEA indicated that the risk score was associated with immune cells and functions.ConclusionsOur systematic study established a metabolism-related lncRNA signature to predict outcomes of CRC patients which may contribute to individual prevention and treatment.

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Computational analysis of ribonomics datasets identifies long non-coding RNA targets of ?-herpesviral miRNAs.

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Computational analysis of ribonomics datasets identifies long non-coding RNA targets of γ-herpesviral miRNAs.

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