One of the steps in DNA sample preparation that is often overlooked when moving from manual to automated methods, is the quantification and normalization of nucleic acid samples that are destined for downstream analysis in different techniques and applications such as genotyping and NGS.
Next-generation sequencing (NGS*) has revolutionized genomic research, allowing entire genomes to be sequenced in a single day. This has led to massive advances in the diagnosis, prognosis and treatment of disease, answering genetic questions from a wide spectrum of applications and biological systems. Today, NGS is an essential tool for any biologist. Ultra-high throughput NGS solutions have a wide range of applications and are fully scalable—from rapid SNP genotyping of a single individual, to whole genome sequencing (WGS) of entire populations. The explosive demand for NGS often creates pressures upstream to process many more samples and prepare high quality DNA to feed into library prep and analysis. In this article we explore the ideal DNA requirements for NGS and look at some of the most critical parameters for developing an automated nucleic acid extraction workflow.
With the advent of next-generation sequencing (NGS), the field of metagenomics has exploded in recent years, as scientists are now able to study microbes as communities instead of individual organisms. This has revolutionized our understanding of the relationships between microbiota, human health, and the environment.
The drive to make healthcare more targeted and more personalized has accelerated the application of increasingly sophisticated technologies, such as next generation sequencing (NGS). The result has been the introduction of some NGS-based tests to be used to direct targeted therapies to the right patient. The power is great, but the challenges are many, including how to standardize for routine use.
You may be convinced that your academic research laboratory is humming along just fine and cannot benefit from, take the time to consider, and perhaps most of all, afford adding automation to your workflow.
If you’ve decided to take advantage of next generation sequencing (NGS) for HLA typing, your timing couldn’t be better. With the recent introduction of more affordable bench-top sequencers and targeted HLA sequencing panels, NGS is more accessible than ever. Of course, integration of a new technology into a busy lab takes careful planning to avoid teething problems, so now is the time to consider the impact an NGS system will have on your lab, and what you can do to make the transition as smooth as possible.
With multiple tests to perform on a tiny volume, samples are getting more precious. And as Next Generation Sequencing pushes the envelope on cost and throughput, scientists are looking for ways of reducing reagent volumes without compromising on quality. Tecan has a tip.
For patients in need of vital transplants, fast and accurate tissue typing can mean earlier treatment and a better chance of survival. Next generation sequencing (NGS) is revolutionizing human leukocyte antigen (HLA) typing by providing allele-level resolution in a single high-throughput step.
They don’t take up much room in your DNA – a mere 4 megabases on the short arm of Chromosome 6 – but Human Leukocyte Antigen (HLA) genes play a defining role in whether you will develop an autoimmune disorder, fend off an infectious disease, or have an adverse reaction to potentially life-saving treatments.
Next-generation sequencing (NGS) is poised to become a decisive tool in diagnostic, therapeutic, and prognostic applications in oncology. In the first part of this two-part series, we saw that sequencing tumor-derived DNA alone can risk incorrect diagnosis by misinterpreting somatic alterations as being tumor-specific. This pinpoints the need to sequence normal tissue in parallel to map out the somatic alterations already present in the patient, which clearly has implications for the future of NGS-based diagnosis and workflows in the clinical laboratory.
Massively parallel sequencing has rapidly become a must-have tool of the trade in molecular biology and drug discovery research. In recent years, the cost of next-generation sequencing (NGS) has declined exponentially, while throughput, accuracy, and read lengths have soared, and multiple regulatory-compliant sequencing technologies have achieved commercial success.