Dataset Information

Human cytomegalovirus genomics and transcriptomics through the lens of next-generation sequencing: revision and future challenges.

ABSTRACT: The human cytomegalovirus (HCMV) genome was sequenced by hierarchical shotgun almost 30 years ago. Over these years, low and high passaged strains have been sequenced, improving, albeit still far from complete, the understanding of the coding potential, expression dynamics and diversity of wild-type HCMV strains. Next-generation sequencing (NGS) platforms have enabled a huge advancement, facilitating the comparison of differentially passaged strains, challenging diagnostics and research based on a single or reduced gene set genotyping. In addition, it allowed to link genetic features to different viral phenotypes as for example, correlating large genomic re-arrangements to viral attenuation or different mutations to antiviral resistance and cell tropism. NGS platforms provided the first high-resolution experiments to HCMV dynamics, allowing the study of intra-host viral population structures and the description of rare transcriptional events. Long-read sequencing has recently become available, helping to identify new genomic re-arrangements, partially accounting for the genetic variability displayed in clinical isolates, as well as, in changing the understanding of the HCMV transcriptome. Better knowledge of the transcriptome resulted in a vast number of new splicing events and alternative transcripts, although most of them still need additional validation. This review summarizes the sequencing efforts reached so far, discussing its approaches and providing a revision and new nuances on HCMV sequence variability in the sequencing field.

SUBMITTER: Marti-Carreras J

PROVIDER: S-EPMC6458973 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Human cytomegalovirus genomics and transcriptomics through the lens of next-generation sequencing: revision and future challenges.

Martí-Carreras Joan J Maes Piet P

Virus genes 20190102 2

The human cytomegalovirus (HCMV) genome was sequenced by hierarchical shotgun almost 30 years ago. Over these years, low and high passaged strains have been sequenced, improving, albeit still far from complete, the understanding of the coding potential, expression dynamics and diversity of wild-type HCMV strains. Next-generation sequencing (NGS) platforms have enabled a huge advancement, facilitating the comparison of differentially passaged strains, challenging diagnostics and research based on ...[more]

PMID: 30604286

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Project description:Next-generation sequencing (NGS) informs many biological questions with unprecedented depth and nucleotide resolution. These assays have created a need for analytical tools that enable users to manipulate data nucleotide-by-nucleotide robustly and easily. Furthermore, because many NGS assays encode information jointly within multiple properties of read alignments - for example, in ribosome profiling, the locations of ribosomes are jointly encoded in alignment coordinates and length - analytical tools are often required to extract the biological meaning from the alignments before analysis. Many assay-specific pipelines exist for this purpose, but there remains a need for user-friendly, generalized, nucleotide-resolution tools that are not limited to specific experimental regimes or analytical workflows.Plastid is a Python library designed specifically for nucleotide-resolution analysis of genomics and NGS data. As such, Plastid is designed to extract assay-specific information from read alignments while retaining generality and extensibility to novel NGS assays. Plastid represents NGS and other biological data as arrays of values associated with genomic or transcriptomic positions, and contains configurable tools to convert data from a variety of sources to such arrays. Plastid also includes numerous tools to manipulate even discontinuous genomic features, such as spliced transcripts, with nucleotide precision. Plastid automatically handles conversion between genomic and feature-centric coordinates, accounting for splicing and strand, freeing users of burdensome accounting. Finally, Plastid's data models use consistent and familiar biological idioms, enabling even beginners to develop sophisticated analytical workflows with minimal effort.Plastid is a versatile toolkit that has been used to analyze data from multiple NGS assays, including RNA-seq, ribosome profiling, and DMS-seq. It forms the genomic engine of our ORF annotation tool, ORF-RATER, and is readily adapted to novel NGS assays. Examples, tutorials, and extensive documentation can be found at https://plastid.readthedocs.io .

Dataset Information

Human cytomegalovirus genomics and transcriptomics through the lens of next-generation sequencing: revision and future challenges.

Publications

Human cytomegalovirus genomics and transcriptomics through the lens of next-generation sequencing: revision and future challenges.

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