• Record: found
  • Abstract: found
  • Article: found
Is Open Access

KSHV 2.0: A Comprehensive Annotation of the Kaposi's Sarcoma-Associated Herpesvirus Genome Using Next-Generation Sequencing Reveals Novel Genomic and Functional Features

Read this article at

      There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.


      Productive herpesvirus infection requires a profound, time-controlled remodeling of the viral transcriptome and proteome. To gain insights into the genomic architecture and gene expression control in Kaposi's sarcoma-associated herpesvirus (KSHV), we performed a systematic genome-wide survey of viral transcriptional and translational activity throughout the lytic cycle. Using mRNA-sequencing and ribosome profiling, we found that transcripts encoding lytic genes are promptly bound by ribosomes upon lytic reactivation, suggesting their regulation is mainly transcriptional. Our approach also uncovered new genomic features such as ribosome occupancy of viral non-coding RNAs, numerous upstream and small open reading frames (ORFs), and unusual strategies to expand the virus coding repertoire that include alternative splicing, dynamic viral mRNA editing, and the use of alternative translation initiation codons. Furthermore, we provide a refined and expanded annotation of transcription start sites, polyadenylation sites, splice junctions, and initiation/termination codons of known and new viral features in the KSHV genomic space which we have termed KSHV 2.0. Our results represent a comprehensive genome-scale image of gene regulation during lytic KSHV infection that substantially expands our understanding of the genomic architecture and coding capacity of the virus.

      Author Summary

      Kaposi's sarcoma-associated herpesvirus (KSHV) is a cancer-causing agent in immunocompromised patients that establishes long-lasting infections in its hosts. Initially described in 1994 and extensively studied ever since, KSHV molecular biology is understood in broad outline, but many detailed questions are still to be resolved. After almost two decades, specific aspects pertaining to the organization of the KSHV genome as well as the fate of the viral transcripts during the productive stages of infection remain unexplored. Here we use a systematic genome-wide approach to investigate changes in gene and protein expression during the productive stage of infection known as the lytic cycle. We found that the viral genome has a large coding capacity, capable of generating at least 45% more products than initially anticipated by bioinformatic analyses alone, and that it uses multiple strategies to expand its coding capacity well beyond what is determined solely by the DNA sequence of its genome. We also provide an expanded and highly detailed annotation of known and new genomic features in KSHV. We have termed this new architectural and functional annotation KSHV 2.0. Our results indicate that viral genomes are more complex than anticipated, and that they are subject to tight mechanisms of regulation to ensure correct gene expression.

      Related collections

      Most cited references 123

      • Record: found
      • Abstract: found
      • Article: not found

      Fast gapped-read alignment with Bowtie 2.

      As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
        • Record: found
        • Abstract: not found
        • Article: not found

        SignalP 4.0: discriminating signal peptides from transmembrane regions.

          • Record: found
          • Abstract: found
          • Article: not found

          Ribosome profiling of mouse embryonic stem cells reveals the complexity and dynamics of mammalian proteomes.

          The ability to sequence genomes has far outstripped approaches for deciphering the information they encode. Here we present a suite of techniques, based on ribosome profiling (the deep sequencing of ribosome-protected mRNA fragments), to provide genome-wide maps of protein synthesis as well as a pulse-chase strategy for determining rates of translation elongation. We exploit the propensity of harringtonine to cause ribosomes to accumulate at sites of translation initiation together with a machine learning algorithm to define protein products systematically. Analysis of translation in mouse embryonic stem cells reveals thousands of strong pause sites and unannotated translation products. These include amino-terminal extensions and truncations and upstream open reading frames with regulatory potential, initiated at both AUG and non-AUG codons, whose translation changes after differentiation. We also define a class of short, polycistronic ribosome-associated coding RNAs (sprcRNAs) that encode small proteins. Our studies reveal an unanticipated complexity to mammalian proteomes. Copyright © 2011 Elsevier Inc. All rights reserved.

            Author and article information

            [1 ]Novartis Institute for Biomedical Research, Department of Infectious Diseases, Emeryville, California, United States of America
            [2 ]Novartis Vaccines and Diagnostics, Bioinformatics, Emeryville, California, United States of America
            [3 ]Department of Cellular and Molecular Pharmacology, Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, California, United States of America
            University of North Carolina at Chapel Hill, United States of America
            Author notes

            The authors have declared that no competing interests exist.

            Conceived and designed the experiments: CA JSW DG. Performed the experiments: CA NSG ASM MH PB. Analyzed the data: CA BW AM. Contributed reagents/materials/analysis tools: AM ASM NSG. Wrote the paper: CA DG.

            Role: Editor
            PLoS Pathog
            PLoS Pathog
            PLoS Pathogens
            Public Library of Science (San Francisco, USA )
            January 2014
            January 2014
            16 January 2014
            : 10
            : 1

            This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

            Pages: 23
            CA, ASM and AM were supported by a Novartis Presidential Postdoctoral fellowship. NSG was supported by a human frontier science program postdoctoral fellowship. JSW and DG were supported by the Howard Hughes Medical Institute. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
            Research Article
            Computational Biology
            Functional Genomics
            Genome Expression Analysis
            Genome Sequencing
            Sequence Analysis
            Viral Classification
            DNA viruses
            Molecular Cell Biology
            Gene Expression
            DNA transcription
            Protein Translation
            RNA processing

            Infectious disease & Microbiology


            Comment on this article