Search

The implementation of next-generation sequencing (NGS) in a clinical diagnostic setting opens vast opportunities through the ability to sequence all genes contributing to a certain morbidity simultaneously at a cost and speed that is superior to traditional sequencing approaches. On the other hand, the practical implementation of NGS in a clinical diagnostic setting involves a variety of new challenges, which need to be overcome. Among these are the generation, analysis and storage of unprecedented amounts of data, strict control of sequencing performance, validation of results, interpretation of detected variants and reporting. In the following sections, key aspects of data management and integration will be discussed. In particular, issues of data storage, data analysis using in-house IT infrastructure vs. data analysis employing cloud computing and the need for data integration from different sources will be covered. [ABSTRACT FROM AUTHOR]

Next-generation sequencing (NGS) technologies in clinical diagnostics open vast opportunities through the ability to sequence all genes simultaneously at a cost and speed that is superior to traditional sequencing approaches. On the other hand, the practical implementation of NGS in routine diagnostics involves a variety of challenges, which need to be overcome. Among these are the generation, analysis and storage of large amounts of data, strict control of sequencing performance, validation of results, interpretation of detected variants and reporting. Here, we outline the Multiple Integration and Data Annotation Study, an approach for data integration in clinical diagnostics based on genotype-phenotype correlations. MIDAS aims to accelerate NGS data analysis and to enhance the validity of the results by computer-based variant prioritization using the clinical data of the patient. In this context, we present the MIDAS case reports of one patient with intellectual disability caused by a novel de novo loss-of-function variant in the GATAD2B gene [NM_020699.3: c.1426G>T (p.Glu476*)] identified by trio whole-exome sequencing, as well as two cardiac disease patients with severe phenotype and multiple variants in genes linked to cardiac arrhythmogenic disorders analyzed with multi-gene panel sequencing. Based on the data collected in the MIDAS cohort, the MIDAS software will be tested and optimized. Moreover, the MIDAS software concept can be extended modularly to include further data resources for improved data handling and interpretation in the broad field of diagnostics. [ABSTRACT FROM AUTHOR]

Over the past 6 years, next-generation sequencing (NGS) has been established as a valuable high-throughput method for research in molecular genetics and has successfully been employed in the identification of rare and common genetic variations. Although the high expectations regarding the discovery of new diagnostic targets and an overall reduction of cost have been achieved, technological challenges in instrument handling, robustness of the chemistry, and data analysis need to be overcome. Each workflow and sequencing platform have their particular problems and caveats, which need to be addressed. Regarding NGS, there is a variety of different enrichment methods, sequencing devices, or technologies as well as a multitude of analyzing software products available. In this manuscript, the authors focus on challenges in data analysis when employing different target enrichment methods and the best applications for each of them. [ABSTRACT FROM AUTHOR]

With the introduction of the next generation sequencing (NGS) technologies, remarkable new diagnostic applications have been established in daily routine. Implementation of NGS is challenging in clinical diagnostics, but definite advantages and new diagnostic possibilities make the switch to the technology inevitable. In addition to the higher sequencing capacity, clonal sequencing of single molecules, multiplexing of samples, higher diagnostic sensitivity, workflow miniaturization, and cost benefits are some of the valuable features of the technology. After the recent advances, NGS emerged as a proven alternative for classical Sanger sequencing in the typing of human leukocyte antigens (HLA). By virtue of the clonal amplification of single DNA molecules ambiguous typing results can be avoided. Simultaneously, a higher sample throughput can be achieved by tagging of DNA molecules with multiplex identifiers and pooling of PCR products before sequencing. In our experience, up to 380 samples can be typed for HLA-A, -B, and -DRB1 in high-resolution during every sequencing run. In molecular oncology, NGS shows a markedly increased sensitivity in comparison to the conventional Sanger sequencing and is developing to the standard diagnostic tool in detection of somatic mutations in cancer cells with great impact on personalized treatment of patients. © 2013 S. Karger GmbH, Freiburg [ABSTRACT FROM AUTHOR]

Background: The majority of the 2 million bovine single nucleotide polymorphisms (SNPs) currently available in dbSNP have been identified in a single breed, Hereford cattle, during the bovine genome project. In an attempt to evaluate the variance of a second breed, we have produced a whole genome sequence at low coverage of a single Fleckvieh bull., Results: We generated 24 gigabases of sequence, mainly using 36-bp paired-end reads, resulting in an average 7.4-fold sequence depth. This coverage was sufficient to identify 2.44 million SNPs, 82% of which were previously unknown, and 115,000 small indels. A comparison with the genotypes of the same animal, generated on a 50 k oligonucleotide chip, revealed a detection rate of 74% and 30% for homozygous and heterozygous SNPs, respectively. The false positive rate, as determined by comparison with genotypes determined for 196 randomly selected SNPs, was approximately 1.1%. We further determined the allele frequencies of the 196 SNPs in 48 Fleckvieh and 48 Braunvieh bulls. 95% of the SNPs were polymorphic with an average minor allele frequency of 24.5% and with 83% of the SNPs having a minor allele frequency larger than 5%., Conclusions: This work provides the first single cattle genome by next-generation sequencing. The chosen approach - low to medium coverage re-sequencing - added more than 2 million novel SNPs to the currently publicly available SNP resource, providing a valuable resource for the construction of high density oligonucleotide arrays in the context of genome-wide association studies.