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Next-generation sequencing reveals HIV-1-mediated suppression of T cell activation and RNA processing and regulation of noncoding RNA expression in a CD4+ T cell line.

ABSTRACT: UNLABELLED:Next-generation sequencing (NGS) enables the highly sensitive measurement of whole transcriptomes. We report the first application to our knowledge of this technology to the analysis of RNA from a CD4+ T cell line infected with intact HIV. We sequenced the total mRNA from infected cells and detected differences in the expression of both host and viral mRNA. Viral reads represented a large portion of the total mapped sequencing reads: approximately 20% at 12 h postinfection (hpi) and 40% at 24 hpi. We also detected a small but significant suppression of T cell activation-related genes at 12 hpi. This suppression persisted and expanded by 24 hpi, providing new possible markers of virus-induced T cell cytopathology. By 24 hpi, the expression of over 50% of detectable host loci was also altered, indicating widespread alteration of host processes, including RNA processing, splicing, and transport to an extent not previously reported. In addition, next-generation sequencing provided insights into alternative viral RNA splice events and the expression of noncoding RNAs, including microRNA host genes. IMPORTANCE:Recent advances in sequencing technology now allow the measurement of effectively all the RNA in a cell. This approach is especially useful for studying models of virus infection, as it allows the simultaneous measurement of both host and viral RNA. Using next-generation sequencing (NGS), we measured changes in total mRNA from a HIV-infected T cell line. To our knowledge, this is the first application of this technology to the investigation of HIV-host interactions involving intact HIV. We directly measured the amount of viral mRNA in infected cells and detected novel viral RNA splice variants and changes in the host expression of noncoding RNA species. We also detected small changes in T cell activation and other host processes during the early stages of viral replication that increased near the peak of viral replication, providing new candidate biomarkers of T cell death.

SUBMITTER: Chang ST

PROVIDER: S-EPMC3175625 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Next-generation sequencing reveals HIV-1-mediated suppression of T cell activation and RNA processing and regulation of noncoding RNA expression in a CD4+ T cell line.

Chang Stewart T ST Sova Pavel P Peng Xinxia X Weiss Jeffrey J Law G Lynn GL Palermo Robert E RE Katze Michael G MG

mBio 20110920 5

<h4>Unlabelled</h4>Next-generation sequencing (NGS) enables the highly sensitive measurement of whole transcriptomes. We report the first application to our knowledge of this technology to the analysis of RNA from a CD4+ T cell line infected with intact HIV. We sequenced the total mRNA from infected cells and detected differences in the expression of both host and viral mRNA. Viral reads represented a large portion of the total mapped sequencing reads: approximately 20% at 12 h postinfection (hp ...[more]

PMID: 21933919

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Project description:BACKGROUND:When compared to Sanger sequencing technology, next-generation sequencing (NGS) technologies are hindered by shorter sequence read length, higher base-call error rate, non-uniform coverage, and platform-specific sequencing artifacts. These characteristics lower the quality of their downstream analyses, e.g. de novo and reference-based assembly, by introducing sequencing artifacts and errors that may contribute to incorrect interpretation of data. Although many tools have been developed for quality control and pre-processing of NGS data, none of them provide flexible and comprehensive trimming options in conjunction with parallel processing to expedite pre-processing of large NGS datasets. METHODS:We developed ngsShoRT (next-generation sequencing Short Reads Trimmer), a flexible and comprehensive open-source software package written in Perl that provides a set of algorithms commonly used for pre-processing NGS short read sequences. We compared the features and performance of ngsShoRT with existing tools: CutAdapt, NGS QC Toolkit and Trimmomatic. We also compared the effects of using pre-processed short read sequences generated by different algorithms on de novo and reference-based assembly for three different genomes: Caenorhabditis elegans, Saccharomyces cerevisiae S288c, and Escherichia coli O157 H7. RESULTS:Several combinations of ngsShoRT algorithms were tested on publicly available Illumina GA II, HiSeq 2000, and MiSeq eukaryotic and bacteria genomic short read sequences with the focus on removing sequencing artifacts and low-quality reads and/or bases. Our results show that across three organisms and three sequencing platforms, trimming improved the mean quality scores of trimmed sequences. Using trimmed sequences for de novo and reference-based assembly improved assembly quality as well as assembler performance. In general, ngsShoRT outperformed comparable trimming tools in terms of trimming speed and improvement of de novo and reference-based assembly as measured by assembly contiguity and correctness. CONCLUSIONS:Trimming of short read sequences can improve the quality of de novo and reference-based assembly and assembler performance. The parallel processing capability of ngsShoRT reduces trimming time and improves the memory efficiency when dealing with large datasets. We recommend combining sequencing artifacts removal, and quality score based read filtering and base trimming as the most consistent method for improving sequence quality and downstream assemblies. ngsShoRT source code, user guide and tutorial are available at http://research.bioinformatics.udel.edu/genomics/ngsShoRT/. ngsShoRT can be incorporated as a pre-processing step in genome and transcriptome assembly projects.

Dataset Information

Next-generation sequencing reveals HIV-1-mediated suppression of T cell activation and RNA processing and regulation of noncoding RNA expression in a CD4+ T cell line.

Publications

Next-generation sequencing reveals HIV-1-mediated suppression of T cell activation and RNA processing and regulation of noncoding RNA expression in a CD4+ T cell line.

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