High-resolution human cytomegalovirus transcriptome

Gatherer, Derek and Seirafian, Sepehr and Cunningham, Charles and Holton, Mary and Dargan, Derrick J. and Baluchova, Katarina and Hector, Ralph D. and Galbraith, Julie and Herzyk, Pawel and Wilkinson, Gavin W. G. and Davison, Andrew J. (2011) High-resolution human cytomegalovirus transcriptome. Proceedings of the National Academy of Sciences of the United States of America, 108 (49). pp. 19755-19760. ISSN 0027-8424

Abstract

Deep sequencing was used to bring high resolution to the human cytomegalovirus (HCMV) transcriptome at the stage when infectious virion production is under way, and major findings were confirmed by extensive experimentation using conventional techniques. The majority (65.1%) of polyadenylated viral RNA transcription is committed to producing four noncoding transcripts (RNA2.7, RNA1.2, RNA4.9, and RNA5.0) that do not substantially overlap designated protein-coding regions. Additional noncoding RNAs that are transcribed antisense to protein-coding regions map throughout the genome and account for 8.7% of transcription from these regions. RNA splicing is more common than recognized previously, which was evidenced by the identification of 229 potential donor and 132 acceptor sites, and it affects 58 protein-coding genes. The great majority (94) of 96 splice junctions most abundantly represented in the deep-sequencing data was confirmed by RT-PCR or RACE or supported by involvement in alternative splicing. Alternative splicing is frequent and particularly evident in four genes (RL8A, UL74A, UL124, and UL150A) that are transcribed by splicing from any one of many upstream exons. The analysis also resulted in the annotation of four previously unrecognized protein-coding regions (RL8A, RL9A, UL150A, and US33A), and expression of the UL150A protein was shown in the context of HCMV infection. The overall conclusion, that HCMV transcription is complex and multifaceted, has implications for the potential sophistication of virus functionality during infection. The study also illustrates the key contribution that deep sequencing can make to the genomics of nuclear DNA viruses.