A novel termini analysis theory using HTS data alone for the identification of Enterococcus phage EF4-like genome termini

Background

Enterococcus faecalis and Enterococcus faecium are typical enterococcal bacterial pathogens. Antibiotic resistance means that the identification of novel E. faecalis and E. faecium phages against antibiotic-resistant Enterococcus have an important impact on public health. In this study, the E. faecalis phage IME-EF4, E. faecium phage IME-EFm1, and both their hosts were antibiotic resistant. To characterize the genome termini of these two phages, a termini analysis theory was developed to provide a wealth of terminal sequence information directly, using only high-throughput sequencing (HTS) read frequency statistics.

Results

The complete genome sequences of phages IME-EF4 and IME-EFm1 were determined, and our termini analysis theory was used to determine the genome termini of these two phages. Results showed 9 bp 3′ protruding cohesive ends in both IME-EF4 and IME-EFm1 genomes by analyzing frequencies of HTS reads. For the positive strands of their genomes, the 9 nt 3′ protruding cohesive ends are 5′-TCATCACCG-3′ (IME-EF4) and 5′-GGGTCAGCG-3′ (IME-EFm1). Further experiments confirmed these results. These experiments included mega-primer polymerase chain reaction sequencing, terminal run-off sequencing, and adaptor ligation followed by run-off sequencing.

Conclusion

Using this termini analysis theory, the termini of two newly isolated antibiotic-resistant Enterococcus phages, IME-EF4 and IME-EFm1, were identified as the byproduct of HTS. Molecular biology experiments confirmed the identification. Because it does not require time-consuming wet lab termini analysis experiments, the termini analysis theory is a fast and easy means of identifying phage DNA genome termini using HTS read frequency statistics alone. It may aid understanding of phage DNA packaging.     

SOPRA: Scaffolding algorithm for paired reads via statistical optimization

Background  

High throughput sequencing (HTS) platforms produce gigabases of short read (<100 bp) data per run. While these short reads are adequate for resequencing applications, de novo assembly of moderate size genomes from such reads remains a significant challenge. These limitations could be partially overcome by utilizing mate pair technology, which provides pairs of short reads separated by a known distance along the genome.     

QSRA – a quality-value guided de novo short read assembler

Background  

New rapid high-throughput sequencing technologies have sparked the creation of a new class of assembler. Since all high-throughput sequencing platforms incorporate errors in their output, short-read assemblers must be designed to account for this error while utilizing all available data.     

Experience of a multidisciplinary task force with exome sequencing for Mendelian disorders

Background

In order to optimally integrate the use of high-throughput sequencing (HTS) as a tool in clinical diagnostics of likely monogenic disorders, we have created a multidisciplinary “Genome Clinic Task Force” at the University Hospitals of Geneva, which is composed of clinical and molecular geneticists, bioinformaticians, technicians, bioethicists, and a coordinator.

Methods and results

We have implemented whole exome sequencing (WES) with subsequent targeted bioinformatics analysis of gene lists for specific disorders. Clinical cases of heterogeneous Mendelian disorders that could potentially benefit from HTS are presented and discussed during the sessions of the task force. Debate concerning the interpretation of identified variants and the content of the final report constitutes a major part of the task force’s work. Furthermore, issues related to bioethics, genetic counseling, quality control, and reimbursement are also addressed.

Conclusions

This multidisciplinary task force has enabled us to create a platform for regular exchanges between all involved experts in order to deal with the multiple complex issues related to HTS in clinical practice and to continuously improve the diagnostic use of HTS. In addition, this task force was instrumental to formally approve the reimbursement of HTS for molecular diagnosis of Mendelian disorders in Switzerland.

     

Genome-wide SNP identification by high-throughput sequencing and selective mapping allows sequence assembly positioning using a framework genetic linkage map

Background  

Determining the position and order of contigs and scaffolds from a genome assembly within an organism's genome remains a technical challenge in a majority of sequencing projects. In order to exploit contemporary technologies for DNA sequencing, we developed a strategy for whole genome single nucleotide polymorphism sequencing allowing the positioning of sequence contigs onto a linkage map using the bin mapping method.     

Finding sRNA generative locales from high-throughput sequencing data with NiBLS

Background  

Next-generation sequencing technologies allow researchers to obtain millions of sequence reads in a single experiment. One important use of the technology is the sequencing of small non-coding regulatory RNAs and the identification of the genomic locales from which they originate. Currently, there is a paucity of methods for finding small RNA generative locales.     

M-GCAT: interactively and efficiently constructing large-scale multiple genome comparison frameworks in closely related species

Background  

Due to recent advances in whole genome shotgun sequencing and assembly technologies, the financial cost of decoding an organism's DNA has been drastically reduced, resulting in a recent explosion of genomic sequencing projects. This increase in related genomic data will allow for in depth studies of evolution in closely related species through multiple whole genome comparisons.     

PanGEA: Identification of allele specific gene expression using the 454 technology

Background  

Next generation sequencing technologies hold great potential for many biological questions. While mainly used for genomic sequencing, they are also very promising for gene expression profiling. Sequencing of cDNA does not only provide an estimate of the absolute expression level, it can also be used for the identification of allele specific gene expression.     

Phylogenetic comparative assembly

Background  

Recent high throughput sequencing technologies are capable of generating a huge amount of data for bacterial genome sequencing projects. Although current sequence assemblers successfully merge the overlapping reads, often several contigs remain which cannot be assembled any further. It is still costly and time consuming to close all the gaps in order to acquire the whole genomic sequence.     

Pysim-sv: a package for simulating structural variation data with GC-biases

Background

Structural variations (SVs) are wide-spread in human genomes and may have important implications in disease-related and evolutionary studies. High-throughput sequencing (HTS) has become a major platform for SV detection and simulation serves as a powerful and cost-effective approach for benchmarking SV detection algorithms. Accurate performance assessment by simulation requires the simulator capable of generating simulation data with all important features of real data, such GC biases in HTS data and various complexities in tumor data. However, no available package has systematically addressed all issues in data simulation for SV benchmarking.

Results

Pysim-sv is a package for simulating HTS data to evaluate performance of SV detection algorithms. Pysim-sv can introduce a wide spectrum of germline and somatic genomic variations. The package contains functionalities to simulate tumor data with aneuploidy and heterogeneous subclones, which is very useful in assessing algorithm performance in tumor studies. Furthermore, Pysim-sv can introduce GC-bias, the most important and prevalent bias in HTS data, in the simulated HTS data.

Conclusions

Pysim-sv provides an unbiased toolkit for evaluating HTS-based SV detection algorithms.

     

rSW-seq: Algorithm for detection of copy number alterations in deep sequencing data

Background  

Recent advances in sequencing technologies have enabled generation of large-scale genome sequencing data. These data can be used to characterize a variety of genomic features, including the DNA copy number profile of a cancer genome. A robust and reliable method for screening chromosomal alterations would allow a detailed characterization of the cancer genome with unprecedented accuracy.     

Human papillomavirus detection using the Abbott RealTi<Emphasis Type="Italic">m</Emphasis>e high-risk HPV tests compared with conventional nested PCR coupled to high-throughput sequencing of amplification products in cervical smear specimens from a Gabonese female population

Background

Cervical cancer is the fourth most common malignancy in women worldwide. However, screening with human papillomavirus (HPV) molecular tests holds promise for reducing cervical cancer incidence and mortality in low- and middle-income countries. The performance of the Abbott RealTime High-Risk HPV test (AbRT) was evaluated in 83 cervical smear specimens and compared with a conventional nested PCR coupled to high-throughput sequencing (HTS) to identify the amplicons.

Results

The AbRT assay detected at least one HPV genotype in 44.57% of women regardless of the grade of cervical abnormalities. Except for one case, good concordance was observed for the genotypes detected with the AbRT assay in the high-risk HPV category determined with HTS of the amplicon generated by conventional nested PCR.

Conclusions

The AbRT test is an easy and reliable molecular tool and was as sensitive as conventional nested PCR in cervical smear specimens for detection HPVs associated with high-grade lesions. Moreover, sequencing amplicons using an HTS approach effectively identified the genotype of the hrHPV identified with the AbRT test.

     

Systematic cross-validation of 454 sequencing and pyrosequencing for the exact quantification of DNA methylation patterns with single CpG resolution

Background  

New high-throughput sequencing technologies promise a very sensitive and high-resolution analysis of DNA methylation patterns in quantitative terms. However, a detailed and comprehensive comparison with existing validated DNA methylation analysis methods is not yet available. Therefore, a systematic cross-validation of 454 sequencing and conventional pyrosequencing, both of which offer exact quantification of methylation levels with a single CpG dinucleotide resolution, was performed.     

Ultra-high throughput sequencing-based small RNA discovery and discrete statistical biomarker analysis in a collection of cervical tumours and matched controls

Background  

Ultra-high throughput sequencing technologies provide opportunities both for discovery of novel molecular species and for detailed comparisons of gene expression patterns. Small RNA populations are particularly well suited to this analysis, as many different small RNAs can be completely sequenced in a single instrument run.     

A database and API for variation,dense genotyping and resequencing data

Background  

Advances in sequencing and genotyping technologies are leading to the widespread availability of multi-species variation data, dense genotype data and large-scale resequencing projects. The 1000 Genomes Project and similar efforts in other species are challenging the methods previously used for storage and manipulation of such data necessitating the redesign of existing genome-wide bioinformatics resources.