Dataset Information

Functional and molecular dissection of viral lncRNAs throughout HCMV life cycle

ABSTRACT: Small, compact genomes confer a selective advantage to viruses, yet human cytomegalovirus (HCMV) expresses the long non-coding RNAs (lncRNAs) RNA1.2, RNA2.7, RNA4.9, and RNA5.0. These lncRNAs account for majority of the viral transcriptome, but their functions remain largely unknown. Here, we showed that HCMV lncRNAs, except for RNA5.0, are required throughout the entire viral life cycle. Deletion of each lncRNA resulted in a decrease in viral progeny during lytic replication and failing to efficiently establish latent reservoirs and reactivate. Nanopore direct RNA sequencing of native lncRNA molecules revealed that each lncRNA exhibited a dynamic modification landscape, depending on the state of infection. Global analysis of the lncRNA interactome identified 32, 11, and 89 host factors that specifically bind to RNA1.2, RNA2.7, and RNA4.9, respectively. Moreover, 52 proteins commonly bound to the three lncRNAs were identified, including 11 antiviral immunity-related proteins. Our molecular analyses found that three lncRNAs are modified with N⁶-methyladenosine (m6A) and interact with m6A readers in all infection states. In-depth functional analysis revealed that m6A–mediated lncRNA stabilization as the key mechanism by which lncRNAs are maintained at high levels. Our study lays the groundwork for understanding viral lncRNA–mediated regulation of host-virus interaction throughout the HCMV life cycle.

INSTRUMENT(S): Orbitrap Eclipse

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Skin, Fibroblast

SUBMITTER: Sungwon Lee

LAB HEAD: Kwangseog Ahn

PROVIDER: PXD034587 | Pride | 2022-11-14

REPOSITORIES: Pride

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Publications

Functional and molecular dissection of HCMV long non-coding RNAs.

Lee Sungwon S Kim Hyewon H Hong Ari A Song Jaewon J Lee Sungyul S Kim Myeonghwan M Hwang Sung-Yeon SY Jeong Dongjoon D Kim Jeesoo J Son Ahyeon A Lee Young-Suk YS Kim V Narry VN Kim Jong-Seo JS Chang Hyeshik H Ahn Kwangseog K

Scientific reports 20221111 1

Small, compact genomes confer a selective advantage to viruses, yet human cytomegalovirus (HCMV) expresses the long non-coding RNAs (lncRNAs); RNA1.2, RNA2.7, RNA4.9, and RNA5.0. Little is known about the function of these lncRNAs in the virus life cycle. Here, we dissected the functional and molecular landscape of HCMV lncRNAs. We found that HCMV lncRNAs occupy ~ 30% and 50-60% of total and poly(A)+viral transcriptome, respectively, throughout virus life cycle. RNA1.2, RNA2.7, and RNA4.9, the t ...[more]

PMID: 36369338

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Project description:LncRNA expression profiling for liver tissues of mice fed for a normal diet (NFD, 3mice) and a high-fat diet (HFD, 3mice) Summary: An abstract of the experiment and the data analysis. Experiment Workflow: A workflow of the experiment and the data analysis. Project Description: Sample and experiment information. Array Information: Mouse 8 x 60K LncRNA expression array information. Summary Table of Files for Data Delivery: Contains summary table of files for data delivery and the recommended software programs for viewing the data. Data Analysis for LncRNAs 1. Raw LncRNA data normalization and low intensity filtering: Raw signal intensities were normalized in quantile method by GeneSpring GX v11.5.1, and low intensity LncRNAs were filtered (LncRNAs that at least 6 out of 9 samples have flags in Present or Marginal were chosen for further analysis, these LncRNAs can be found from the LncRNA Expression Profiling Data.xls file). 2. Quality assessment of LncRNA data after filtering: Contains Box Plot and Scatter Plot for LncRNAs after filtering (This data can be found from the LncRNA Expression Profiling Data.xls file). 3. Differentially expressed LncRNAs screening: Contains differentially expressed genes with statistical significance that passed Volcano Plot filtering (Fold Change >= 2.0, P-value <= 0.05) (This data can be found from the Differentially Expressed LncRNAs.xls file). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of Differentially Expressed LncRNAs (The heat map can be found from the LncRNA Expression Profiling Data.xls file). Data Analysis for mRNAs 1. Raw mRNA data normalization and low intensity filtering: Raw signal intensities were normalized in quantile method by GeneSpring GX v11.5.1, and low intensity mRNAs were filtered (mRNAs that at least 6 out of 9 samples have flags in Present or Marginal were chosen for further analysis, these mRNAs can be found from the mRNA Expression Profiling Data.xls file). 2. Quality assessment of mRNA data after filtering: Contains Box Plot and Scatter Plot for mRNAs after filtering (This data can be found from the mRNA Expression Profiling Data.xls file). 3. Differentially expressed mRNAs screening: Contains differentially expressed genes with statistical significance that passed Volcano Plot filtering (Fold Change >= 2.0, P-value <= 0.05) (This data can be found from the Differentially Expressed mRNAs.xls file). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of Differentially Expressed mRNAs (The heat map can be found from the mRNA Expression Profiling Data.xls file). 5. Pathway analysis: Pathway analysis of the differentially expressed mRNAs. 6. GO analysis: GO term analysis of the differentially expressed mRNAs. LncRNA Classification and Subgroup Analysis 1. Rinn lincRNAs profiling: Contains profiling data of all lincRNAs based on John Rinn's papers (This data can be found from the Rinn lincRNAs profiling.xls file). 2. LincRNAs nearby coding gene data table: Contains the differentially expressed lincRNAs and nearby coding gene pairs (distance < 300 kb) (This data can be found from the LincRNAs nearby coding gene data table.xls file). Sample RNA Quality Control: Sample quality control data file from NanoDrop ND-1000 spectrophotometer and standard denaturing agarose gel electrophoresis. Methods: A brief introduction of methods for sample preparation, microarray design, experiment, and data analysis.

Project description:Long non-coding RNAs (lncRNAs) are generally defined as RNA transcripts longer than 200 nucleotides that are not translated into proteins. Recently, many small open reading frames (smORFs) embedded in lncRNA scripts have been verified to be able to encode functional polypeptides (namely lncRNA-SEPs here). Although collaborative analysis by advanced genomics, bioinformatics and proteomics largely drives SEPs discovery, the poor predictability, diminutive size and low abundance still challenge systematic identification of SEPs from different biological samples. Here, we took advantage of the NONCODE database that deposited with the most complete collection and annotation of lncRNA transcripts from different species to build a database that to maximally collect all putative small ORFs from human and mouse lncRNA transcripts. Two effective and complementary polypeptides enrichment strategies (30 kDa MWCO filter and C8 SPE column) were also integrated to further improve the discovery of novel lncRNA-SEPs. These efforts led to the discovery of 362 lncRNA-SEPs from 8 human cell lines and 238 lncRNA-SEPs from 3 mouse cell lines and 8 mouse tissues. 18 out of these lncRNA-SEPs were verified experimentally by multiple technologies including in vitro expression, immunoblotting and parallel reaction monitoring-based mass spectrometry (PRM-MS) in 293T cells. Further bioinformatic analysis reveals that the physical and chemical properties of these novel lncRNA-SEPs, such as amino acid composition and codon usage, are varied from canonical proteins. Intriguingly, nearly 70% of the identified lncRNA-SEPs were found to be initiated with non-AUG start codons. Collectively, the efficient workflows presented in this study enables us identify 600 novel lncRNA-SPEs from multiple cell lines and tissues, which should represent the largest number of MS-detected lncRNA-encoding SEPs ever reported to date. These novel lncRNA-SEPs not only could provide new clues for the annotation of the noncoding elements in the genome, but also could serve as a valuable resource for the functional characterization of individual lncRNA-SEPs.

Dataset Information

Functional and molecular dissection of viral lncRNAs throughout HCMV life cycle

Publications

Functional and molecular dissection of HCMV long non-coding RNAs.

Similar Datasets

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