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Accurate Quantification of Overlapping Herpesvirus Transcripts from RNA Sequencing Data.

Alejandro Casco1, Akansha Gupta1, Mitchell Hayes1

  • 1Department of Oncology, McArdle Laboratory for Cancer Research, University of Wisconsin, Madison, Wisconsin, USA.

Journal of Virology
|October 27, 2021
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Summary

Accurately quantifying overlapping viral transcripts is challenging. New methods like Unique TranScript (UTS) improve Epstein-Barr virus (EBV) gene expression analysis from RNA sequencing data, offering a more accessible alternative to complex techniques.

Keywords:
EBVRNA-seqherpesvirustranscription

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Area of Science:

  • Virology
  • Genomics
  • Bioinformatics

Background:

  • Herpesviruses utilize bidirectional transcription of overlapping genes, complicating accurate gene expression measurement via conventional RNA sequencing (RNA-seq).
  • Existing methods like Unique Coding Sequences (UCDS) for estimating viral gene abundance from RNA-seq have not been rigorously validated.
  • The complexity of overlapping transcripts necessitates improved analytical approaches for accurate viral gene quantification.

Purpose of the Study:

  • To validate the accuracy of the UCDS method for quantifying Epstein-Barr virus (EBV) lytic gene expression from RNA-seq data.
  • To introduce and evaluate the Unique TranScript (UTS) method for improved quantification of overlapping viral transcripts.
  • To compare the performance of UTS and UCDS against conventional RNA-seq analysis and cap analysis of gene expression sequencing (CAGE-seq).

Main Methods:

  • Utilized cap analysis of gene expression sequencing (CAGE-seq) as a gold standard for validating RNA-seq-based quantification methods.
  • Developed the Unique TranScript (UTS) method, which uses empirically determined transcript ends for abundance estimation.
  • Compared read assignment strategies, including conventional methods, UCDS, and UTS, for analyzing EBV lytic gene expression from RNA-seq data.

Main Results:

  • Both UCDS and UTS methods significantly improved the accuracy of quantifying overlapping viral genes compared to conventional RNA-seq analysis.
  • The UTS method demonstrated the highest accuracy in estimating transcript abundance, outperforming UCDS.
  • UTS discards fewer reads than UCDS and is computationally less demanding, making it suitable for laptops and lower sequencing depths.

Conclusions:

  • Conventional RNA-seq analysis methods are insufficient for accurately quantifying overlapping viral transcripts.
  • The UTS method provides a highly accurate and accessible approach for analyzing viral gene expression from RNA-seq data, applicable across herpesviruses.
  • UTS offers a practical alternative to complex, expensive high-throughput sequencing techniques for studying viral transcriptomes.