Non-Invasive Prenatal Testing (NIPT)
Carlos Simón, Carmen Rubio in Handbook of Genetic Diagnostic Technologies in Reproductive Medicine, 2022
Widespread adoption of NIPT is likely to continue, leading to a dramatic reduction in invasive sampling for prenatal genetic diagnostic tests. From a technical point of view, non-invasive deep sequencing of the fetal genome may serve as a universal screening or even diagnostic test to detect genetic diseases in a fetus (1). However, whether it should be routinely offered to pregnant women without a known risk is a complex issue requiring ethical and socio-economical discussions. Regardless, genome-wide profiling will improve overall pregnancy management. A workflow for the follow-up of NIPT results is proposed in Figure 26.4 (47). Despite technological advances in NIPT for monogenic diseases, widespread clinical uptake will remain hindered by the rarity of individual genetic diseases and the subsequent need for individual, customized development.
An approach to pathogen discovery for viral infections of the nervous system
Avindra Nath, Joseph R. Berger in Clinical Neurovirology, 2020
The depth of sequencing employed is dependent on the study design and the sequencing platform engaged. There are several sequencing platforms that have varying maximum reads per run, ranging from 4 million to now 20 billion with the new Illumina NovaSeq machine. A metagenomic sample comprising a milieu of host and non-host DNA will be sequenced with a similar ratio to the sample composition. Therefore, host DNA will constitute the bulk of the sequencing reads, approximately 90%–98% of total reads in CSF. If human DNA is removed, or a specific organism is isolated or selected prior to sequencing, then the total reads per sequencing run will be re-distributed to this smaller subset, providing more reads per organism and therefore deeper coverage. The depth of coverage describes the number of times the genome has been sequenced at a particular point. Metagenomics will generally require a depth of approximately 5–10 million reads per sample. Deep sequencing of a sample may require more than 20 million reads per sample [42].
Drug-Resistant Tuberculosis
Lloyd N. Friedman, Martin Dedicoat, Peter D. O. Davies in Clinical Tuberculosis, 2020
An alternative to WGS is targeted next-generation deep sequencing.110,111 This method allows variants to be detected in minor M. tuberculosis populations, termed heteroresistance. This has allowed researchers to find resistance at a frequency below the classical 1% proportion method. It is envisaged that targeted deep sequencing may be a replacement for culture-based DST. It also has the potential to identify resistance earlier, thereby allowing researchers to get a greater understanding of the biology of the evolution of drug resistance. An added advantage is the potential for clinical decisions to be made earlier and for treatment regimens to be individualized based on the comprehensive drug resistance profile of the M. tuberculosis isolate infecting the patient, but exactly how this should be implemented remains unclear.110,112 However, the limited number of genetic targets being evaluated currently precludes targeted deep sequencing as a method to study the epidemiology of DR-TB.
The potential of circulating cell free RNA as a biomarker in cancer
Published in Expert Review of Molecular Diagnostics, 2019
Ka Wan Emily Cheung, Sin-yu Rachel Choi, Lok Ting Claire Lee, Nga Lam Ella Lee, Hin Fung Tsang, Yin Tung Cheng, William Chi Shing Cho, Elaine Yue Ling Wong, Sze Chuen Cesar Wong
Profiling of expressed miRNAs can be performed by means of deep sequencing in NGS. Deep sequencing is a massive parallel sequencing technique. This sequencing analysis is advantageous in increased range, complexity, improved sensitivity and accuracy of the results by sequencing a genomic region multiple times, in the scale of hundreds or thousands of times. The analysis starts with a reverse-transcribed RNA (a small RNA-cDNA) as the material and followed by amplification and deep sequencing. Any detected short reads are then mapped to the reference genome. The abundance of known miRNAs and their expression levels can be quantified by read density or accumulated reads numbers [170]. Meanwhile, it enables the detection of novel miRNAs and splicing variants (isomiRs), the alternative processing versions of predominant miRNAs. The limitations of deep sequencing mainly dealt with technical problems, such as sequence-specific biases due to enzymatic ligation, relatively high cost and demanding manpower. In line with this, targeted sequencing for plasma mRNA is more feasible for clinical applications [173]. An overview of the detections of ccfRNAs is summarized in Figure 4.
Molecular characterisation of emerging pathogens of unexplained infectious disease syndromes
Published in Expert Review of Molecular Diagnostics, 2019
Xin Li, Susanna K. P. Lau, Patrick C. Y. Woo
Traditionally, emerging pathogens associated with these unexplained infectious disease syndromes were investigated by culturing the microorganisms and/or directly visualizing them under microscopy. With the advancement of molecular technologies, direct amplification and sequencing of genes and even viral genomes from clinical specimens become possible. The use of deep sequencing has also facilitated genome sequencing and downstream characterization of the microbes. In this article, we reviewed the application of molecular tools in the discovery of emerging pathogens associated with unexplained infectious disease syndromes presented as outbreaks or unexplained cases of pneumonia, gastroenteritis, etc., that we see in our daily practice. Representative examples of molecular characterization of emerging pathogens causing unexplained infectious disease syndrome will be discussed. Details of the molecular technologies will not be covered in this review.
Genetic screening as an adjunct to universal newborn hearing screening: literature review and implications for non-congenital pre-lingual hearing loss
Published in International Journal of Audiology, 2019
Christine D’Aguillo, Sara Bressler, Denise Yan, Rahul Mittal, Robert Fifer, Susan H. Blanton, Xuezhong Liu
The critical difference between Sanger sequencing or single mutation testing and NGS is sequencing volume. While the Sanger method only sequences a single DNA fragment at a time, NGS is massively parallel, sequencing millions of fragments simultaneously per run. This high-throughput process translates into sequencing hundreds of genes at one time. NGS offers greater discovery power to detect novel or rare variants with deep sequencing. The benefits of Sanger sequencing include fast, cost-effective sequencing for low numbers of targets (1–20 targets) whereas NGS has higher sequencing depth enabling higher sensitivity (down to 1%), faster turnaround time for high sample volumes, comprehensive genomic coverage, higher throughput with sample multiplexing, higher mutation resolution and more data produced with the same amount of input DNA. It is not without its drawbacks, however. These include shorter reads, difficulty in detection certain types of variation (e.g. repeat expansions), and some areas of the genome which are resistant to NGS.
Related Knowledge Centers
- DNA Sequencing
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