Accurate Quantification of Overlapping Herpesvirus Transcripts from RNA Sequencing Data

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.