Abstract

The transcriptome of the Kaposi’s sarcoma-associated herpesvirus (KSHV/HHV8) after primary latent infection of human blood (BEC), lymphatic (LEC) and immortalized (TIME) endothelial cells was analyzed using RNAseq, and compared to long-term latency in BCBL-1 lymphoma cells. Naturally expressed transcripts were obtained without artificial induction, and a comprehensive annotation of the KSHV genome was determined. A set of unique coding sequence (UCDS) features and a process to resolve overlapping transcripts were developed to accurately quantitate transcript levels from specific promoters. Similar patterns of KSHV expression were detected in BCBL-1 cells undergoing long-term latent infections and in primary latent infections of both BEC and LEC cultures. High expression levels of poly-adenylated nuclear (PAN) RNA and spliced and unspliced transcripts encoding the K12 Kaposin B/C complex and associated microRNA region were detected, with an elevated expression of a large set of lytic genes in all latently infected cultures. Quantitation of non-overlapping regions of transcripts across the complete KSHV genome enabled for the first time accurate evaluation of the KSHV transcriptome associated with viral latency in different cell types. Hierarchical clustering applied to a gene correlation matrix identified modules of co-regulated genes with similar correlation profiles, which corresponded with biological and functional similarities of the encoded gene products. Gene modules were differentially upregulated during latency in specific cell types indicating a role for cellular factors associated with differentiated and/or proliferative states of the host cell to influence viral gene expression.

Highlights

  • Deep sequencing of RNA transcripts (RNA-seq) has been used to examine the global cellular transcriptome at high resolution [1]

  • The NCBI reference sequence (RefSeq) for the Kaposi’s sarcoma-associated herpesvirus (KSHV) genome was previously determined from overlapping cosmids from KSHV strain “GK18” present in a patient with a case of classic Kaposi’s sarcoma and contains 137,168 nucleotides (NC_009333)

  • The RNA reads from the BCBL-1, lymphatic endothelial cells (LEC), blood endothelial cells (BEC), TIME and Vero infections mapping to the complete KSHV genome (NC_009333) were visualized using the Integrated Genome Viewer (IGV)

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Summary

Introduction

Deep sequencing of RNA transcripts (RNA-seq) has been used to examine the global cellular transcriptome at high resolution [1]. In order to examine the pattern of KSHV gene expression at high resolution during the conventional latent KSHV infection in vitro, we utilized RNA-seq analysis to quantitate KSHV RNA transcripts in long-term latent infections in BCBL-1 PEL cells and compared this to primary latent infections in Vero monkey epithelial cells and human blood (BEC), lymphatic (LEC) and immortalized (TIME) endothelial cell cultures, 48 h post infection. We have utilized this RNA-seq data to identify and characterize typical KSHV gene transcripts. A detailed and comprehensive annotation of the KSHV genome was determined from the RNA-seq data and a simplified unique coding sequence (UCDS) GFF was developed to accurately quantitate gene transcripts from the complex KSHV genome structure

Results
Comparison of Conventional Latency in KSHV-Infected Cell Lines
Characterization ofofa aconventional primarylatent latentKaposi’s
RNA-seq Analysis of KSHV Latent Transcriptomes
RNA-seq analysis of KSHV
Quantitation of RNA Transcripts Using Unique UCDS Features
Quantitation of RNA Transcripts Is Confounded by Overlapping Transcripts
Methods
Quantitation
Materials and Methods
Gene Expression in the Divergent Locus B and PAN Region
Quantitation of reads mapping to the lytic PAN
Quantitation of reads mapping
This transcript classical
2.10. Characterization ORF57 Alternate Splicing
2.11. Characterization of vIRF Alternate Splicing
2.13. Quantitation of Transcripts in the ORFK12-73 Latency Region
2.14. Antisense Transcripts
2.15. Hierarchical Clustering of RNA Reads
2.16. Hierarchical Clustering of the Matrix of Gene-Gene Expression Correlations
Discussion
Cell Lines
Immunological Reagents
KSHV Infection
Immunofluorescence Assays
RNA-Sequencing
Data Analysis
Full Text
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