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Genomic and functional characteristics of human cytomegalovirus revealed by next-generation sequencing.

ABSTRACT: The complete genome of human cytomegalovirus (HCMV) was elucidated almost 25 years ago using a traditional cloning and Sanger sequencing approach. Analysis of the genetic content of additional laboratory and clinical isolates has lead to a better, albeit still incomplete, definition of the coding potential and diversity of wild-type HCMV strains. The introduction of a new generation of massively parallel sequencing technologies, collectively called next-generation sequencing, has profoundly increased the throughput and resolution of the genomics field. These increased possibilities are already leading to a better understanding of the circulating diversity of HCMV clinical isolates. The higher resolution of next-generation sequencing provides new opportunities in the study of intrahost viral population structures. Furthermore, deep sequencing enables novel diagnostic applications for sensitive drug resistance mutation detection. RNA-seq applications have changed the picture of the HCMV transcriptome, which resulted in proof of a vast amount of splicing events and alternative transcripts. This review discusses the application of next-generation sequencing technologies, which has provided a clearer picture of the intricate nature of the HCMV genome. The continuing development and application of novel sequencing technologies will further augment our understanding of this ubiquitous, but elusive, herpesvirus.

SUBMITTER: Sijmons S

PROVIDER: S-EPMC3970138 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Genomic and functional characteristics of human cytomegalovirus revealed by next-generation sequencing.

Sijmons Steven S Van Ranst Marc M Maes Piet P

Viruses 20140305 3

The complete genome of human cytomegalovirus (HCMV) was elucidated almost 25 years ago using a traditional cloning and Sanger sequencing approach. Analysis of the genetic content of additional laboratory and clinical isolates has lead to a better, albeit still incomplete, definition of the coding potential and diversity of wild-type HCMV strains. The introduction of a new generation of massively parallel sequencing technologies, collectively called next-generation sequencing, has profoundly incr ...[more]

PMID: 24603756

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Project description:BackgroundIn recent years more than 20 assemblers have been proposed to tackle the hard task of assembling NGS data. A common heuristic when assembling a genome is to use several assemblers and then select the best assembly according to some criteria. However, recent results clearly show that some assemblers lead to better statistics than others on specific regions but are outperformed on other regions or on different evaluation measures. To limit these problems we developed GAM-NGS (Genomic Assemblies Merger for Next Generation Sequencing), whose primary goal is to merge two or more assemblies in order to enhance contiguity and correctness of both. GAM-NGS does not rely on global alignment: regions of the two assemblies representing the same genomic locus (called blocks) are identified through reads' alignments and stored in a weighted graph. The merging phase is carried out with the help of this weighted graph that allows an optimal resolution of local problematic regions.ResultsGAM-NGS has been tested on six different datasets and compared to other assembly reconciliation tools. The availability of a reference sequence for three of them allowed us to show how GAM-NGS is a tool able to output an improved reliable set of sequences. GAM-NGS is also a very efficient tool able to merge assemblies using substantially less computational resources than comparable tools. In order to achieve such goals, GAM-NGS avoids global alignment between contigs, making its strategy unique among other assembly reconciliation tools.ConclusionsThe difficulty to obtain correct and reliable assemblies using a single assembler is forcing the introduction of new algorithms able to enhance de novo assemblies. GAM-NGS is a tool able to merge two or more assemblies in order to improve contiguity and correctness. It can be used on all NGS-based assembly projects and it shows its full potential with multi-library Illumina-based projects. With more than 20 available assemblers it is hard to select the best tool. In this context we propose a tool that improves assemblies (and, as a by-product, perhaps even assemblers) by merging them and selecting the generating that is most likely to be correct.

Project description:Human pathogens can survive and grow in hot springs. For water quality assessment, Escherichia coli or Enterococci are the main thermotolerant enteric bacteria commonly used to estimate the load of pathogenic bacteria in water. However, most of the environmental bacteria are unculturable thus culture methods may cause bias in detection of most pathogens. Illumina sequencing can provide a more comprehensive and accurate insight into environmental bacterial pathogens, which can be used to develop better risk assessment methods and promote public health awareness. In this study, high-throughput Illumina sequencing was used to identify bacterial pathogens from five hot springs; Maiwooi, Akwar, Garbanabra, Elegedi and Gelti, in Eritrea. Water samples were collected from the five hot springs. Total community DNA was extracted from samples using the phenol-chloroform method. The 16S rRNA gene variable region (V4-V7) of the extracted DNA was amplified and library construction done according to Illumina sequencing protocol. The sequence reads (length >200 bp) from Illumina sequencing libraries ranged from 22,091 sequences in the wet sediment sample from Garbanabra to 155,789 sequences in the mat sample from Elegedi. Taxonomy was assigned to each OTU using BLASTn against a curated database derived from GreenGenes, RDPII, SILVA SSU Reference 119 and NCBI. The proportion of potential pathogens from the water samples was highest in Maiwooi (17.8%), followed by Gelti (16.7%), Akwar (13.6%) and Garbanabra (10.9%). Although the numbers of DNA sequence reads from Illumina sequencing were very high for the Elegedi (104,328), corresponding proportion of potential pathogens very low (3.6%). Most of the potential pathogenic bacterial sequences identified were from Proteobacteria and Firmicutes. Legionella and Clostridium were the most common detected genera with different species. Most of the potential pathogens were detected from the water samples. However, sequences belonging to Clostridium were observed more abundantly from the mat samples. This study employed high-throughput sequencing technologies to determine the presence of pathogenic bacteria in the five hot springs in Eritrea.

Dataset Information

Genomic and functional characteristics of human cytomegalovirus revealed by next-generation sequencing.

Publications

Genomic and functional characteristics of human cytomegalovirus revealed by next-generation sequencing.

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