Key Principles and Clinical Applications of "Next-Generation" DNA Sequencing
ABSTRACT Demand for fast, inexpensive, and accurate DNA sequencing data has led to the birth and dominance of a new generation of sequencing technologies. So-called "next-generation" sequencing technologies enable rapid generation of data by sequencing massive amounts of DNA in parallel using diverse methodologies which overcome the limitations of Sanger sequencing methods used to sequence the first human genome. Despite opening new frontiers of genomics research, the fundamental shift away from the Sanger sequencing that next-generation technologies has created has also left many unaware of the capabilities and applications of these new technologies, especially those in the clinical realm. Moreover, the brisk evolution of sequencing technologies has flooded the market with commercially available sequencing platforms, whose unique chemistries and diverse applications stand as another obstacle restricting the potential of next-generation sequencing. This review serves to provide a primer on next-generation sequencing technologies for clinical researchers and physician scientists. We provide an overview of the capabilities and clinical applications of DNA sequencing technologies to raise awareness among researchers about the power of these novel genomic tools. In addition, we discuss that key sequencing principles provide a comparison between existing and near-term technologies and outline key advantages and disadvantages between different sequencing platforms to help researchers choose an appropriate platform for their research interests.
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ABSTRACT: Most patients who undergo surgery or experience a traumatic injury suffer from acute pain that subsides once tissues heal. Nevertheless, the pain remains in 15-30% of patients, sometimes for life, and this chronic post-surgical pain (CPSP) can result in suffering, depression, anxiety, sleep disturbance, physical incapacitation, and an economic burden. The incorporation of genetic knowledge is expected to lead to the development of more effective means to prevent and manage CPSP using tools of personalized pain medicine. The purpose of this review article is to provide an update on the current state of CPSP genetics and its future potential. The large variability in CPSP amongst patients undergoing similar surgery suggests that individual factors are significant contributors to CPSP, raising the possibility that CPSP is influenced by genetic determinants. Heritability estimates suggest that about half of the variance in CPSP levels is attributable to genetic variation. These estimates suggest that identifying the genetic underpinnings of CPSP may lead to significant improvements in treatment. Analyzing patients' DNA sequences, blood and salivary pain biomarkers, as well as their analgesic responses to medications will facilitate developing insights into CPSP pathophysiology and inform predictive algorithms to determine a patient's likelihood of developing CPSP even prior to surgery. These algorithms could facilitate effective treatment regimens that will protect against the transition to chronicity in traumatically injured patients or those scheduled for surgery and lead to better therapy for patients who have already developed CPSP. Pharmacogenomic technologies and strategies provide an opportunity to expand our knowledge in CPSP treatment that may manifest in a personalized approach to diagnosis, prevention, and therapy. Capitalizing on this genomic knowledge will necessitate the analysis of many tens of thousands of study patients. This will require an international coordinated effort to which anesthesiologists and surgeons can contribute substantially.Canadian Journal of Anaesthesia 12/2014; 62(3). DOI:10.1007/s12630-014-0287-6 · 2.50 Impact Factor
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ABSTRACT: Next-generation sequencing (NGS) technologies have played a central role in the genetic revolution. These technologies, especially whole-exome sequencing, have become the primary tool of geneticists to identify the causative DNA variants in Mendelian disorders, including hereditary deafness. Current research estimates that 1% of all human genes have a function in hearing. To date, mutations in over 80 genes have been reported to cause nonsyndromic hearing loss (NSHL). Strikingly, more than a quarter of all known genes related to NSHL were discovered in the past 5 years via NGS technologies. In this article, we review recent developments in the usage of NGS for hereditary deafness, with an emphasis on whole-exome sequencing.Genetics Research 01/2015; 97:e4. DOI:10.1017/S001667231500004X · 2.20 Impact Factor
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ABSTRACT: Unbiased metagenomic sequencing holds significant potential as a diagnostic tool for the simultaneous detection of any previously genetically described viral nucleic acids in clinical samples. Viral genome sequences can also inform on likely phenotypes including drug susceptibility or neutralization serotypes. In this study, different variables of the laboratory methods often used to generate viral metagenomics libraries on the efficiency of viral detection and virus genome coverage were compared. A biological reagent consisting of 25 different human RNA and DNA viral pathogens was used to estimate the effect of filtration and nuclease digestion, DNA/RNA extraction methods, pre-amplification and the use of different library preparation kits on the detection of viral nucleic acids. Filtration and nuclease treatment led to slight decreases in the percentage of viral sequence reads and number of viruses detected. For nucleic acid extractions silica spin columns improved viral sequence recovery relative to magnetic beads and Trizol extraction. Pre-amplification using random RT-PCR while generating more viral sequence reads resulted in detection of fewer viruses, more overlapping sequences, and lower genome coverage. The ScriptSeq library preparation method retrieved more viruses and a greater fraction of their genomes than the TruSeq and Nextera methods. Viral metagenomics sequencing was able to simultaneously detect up to 22 different viruses in the biological reagent analyzed including all those detected by qPCR. Further optimization will be required for the detection of viruses in biologically more complex samples such as tissues, blood, or feces. Copyright © 2014. Published by Elsevier B.V.Journal of Virological Methods 12/2014; 213. DOI:10.1016/j.jviromet.2014.12.002 · 1.88 Impact Factor