Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

RNA-Seq based characterization of long non-coding RNA involved in respiratory viruses pathogenesis

ABSTRACT: We aimed at systematically inferring the regulatory functions of host lncRNAs in response to influenza A virus (IAV) and severe acute respiratory syndrome coronavirus (SARS-CoV) in the mouse model, using a ‘guilt-by-association’ approach which relies on finding which lncRNAs have similar expression profiles to protein-coding genes of known function. To build a large panel of diverse host responses to viral infection, we took advantage of the genetic diversity present in the 8 founder strains of the Collaborative Cross (CC) mouse resource. Extensive pulmonary host-response profiling was performed on mock and viral-infected lungs at 2 and 4 days post-infection using total RNA-Seq. Overall lncRNAs accounted for about 40% of total genes differentially expressed upon infections (5,329 DE lncRNAs). To predict the functions of these lncRNAs, we constructed a co-expression network using the weighted correlation network analysis (WGCNA) and identified modules of co-expressed genes. Several lncRNAs were identified as belonging to gene modules associated with viral replication or weight loss, and enriched in various infection-related biological processes such as immune response. In addition, each lncRNA was individually annotated using ranked list of DE genes based on signed correlation with each LncRNA. We predicted that a few lncRNAs may be implicated in more than 50 biological processes or pathways. Finally, we identified the lncRNAs that were positively or negatively correlated with all their neighbors and may have cis enhancer or inhibitor effects. We validated our prediction by examining additional RNASeq dataset of mice treated with IFN-alpha. Altogether, these results provide a broad categorization of lncRNA functions and identify subsets of lncRNAs with potential key roles for respiratory virus pathogenesis. These data are fully accessible through The MOuse NOn-Code Lung database (MONOCLdb) http://monocldb.viromics.washington.edu/ At 2 or 4 days post infection, Collaborative Cross founders mice (n=2-3 for infected conditions, n=2 for mocks) were euthanized and lungs were used for total RNA-Seq.

ORGANISM(S): Mus musculus

SUBMITTER: Michael Katze

PROVIDER: E-GEOD-52405 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Genomic profiling of collaborative cross founder mice infected with respiratory viruses reveals novel transcripts and infection-related strain-specific gene and isoform expression.

Xiong Hao H Morrison Juliet J Ferris Martin T MT Gralinski Lisa E LE Whitmore Alan C AC Green Richard R Thomas Matthew J MJ Tisoncik-Go Jennifer J Schroth Gary P GP Pardo-Manuel de Villena Fernando F Baric Ralph S RS Heise Mark T MT Peng Xinxia X Katze Michael G MG

G3 (Bethesda, Md.) 20140605 8

Genetic variation between diverse mouse species is well-characterized, yet existing knowledge of the mouse transcriptome comes largely from one mouse strain (C57BL/6J). As such, it is unlikely to reflect the transcriptional complexity of the mouse species. Gene transcription is dynamic and condition-specific; therefore, to better understand the mouse transcriptional response to respiratory virus infection, we infected the eight founder strains of the Collaborative Cross with either influenza A v ...[more]

PMID: 24902603

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Project description:Recent studies show that long non-coding RNAs (lncRNAs) play crucial roles in human cancers. However, functional lncRNAs and their downstream mechanisms are largely unknown in the molecular pathogenesis of intrahepatic cholangiocarcinoma (ICC) and its progression. In the present study, we performed transcriptomic profiling of five ICC and paired adjacent noncancerous tissues (N) using lncRNA and mRNA microarrays to identify relevant biomarkers in ICC. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate the microarray results. We sought correlations between the expression levels of lncRNAs and those of target genes. Clinicopathological characteristics and overall survival were compared using the t-test and the Kaplan–Meier method, respectively. A total of 3,054 and 2,111 lncRNAs were significantly up- and down-regulated(fold change?2, p?0.05) in ICC tissues compared to the adjacent NT samples. Bioinformatic analysis indicated that most such genes were related to carcinogenesis, hepatic system disease, and signal transduction. Positive correlations were evident between four pairs of lncRNAs and target mRNAs (RNA43085 and SULF1, RNA47504 and KDM8, RNA58630 and PCSK6, and RNA40057 and CYP2D6). In addition, some lncRNAs and mRNAs were significantly associated with clinicopathological characteristics. The cumulative overall survival rate was significantly associated with low-level expression of CYP2D6 (p=0.005) and PCSK6 (p=0.038). And patients with high expression levels of CYP2D6 and RNA40057 have significant better prognosis (p=0.014). Our results suggested that lncRNA expression profile in ICC tissues is profoundly different from that in NT samples. The lncRNA signature could be used as a biomarker for the prognosis of patients with ICC. Furthermore, the combination of lncRNA and mRNA can reliably predict the survival. The lncRNA expression profiles of cancer and adjacent normal tissues form 5 ICC patients were studied by microarray and an combination of lncRNA and mRNA could be used as a biomarker for the prognosis of patients with ICC

Dataset Information

RNA-Seq based characterization of long non-coding RNA involved in respiratory viruses pathogenesis

Publications

Genomic profiling of collaborative cross founder mice infected with respiratory viruses reveals novel transcripts and infection-related strain-specific gene and isoform expression.

Similar Datasets

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