Next generation sequencing is a term used to describe a variety of modern sequencing technologies. They allow for sequencing of DNA and RNA more cheaply and quickly than previously used Sanger sequencing and have revolutionized the study of genetics.
The next generation sequencing process involves breaking up of DNA or RNA into multiple pieces whereupon adapters are added and libraries sequenced before they’re reassembled. One of the critical differences is that millions of fragments are sequenced in massive parallel fashion, thus reducing costs and improving speed and accuracy.
The advantage of cost-effectiveness, high sequencing speed, high resolution and accuracy has had a great influence on genomic research. High-throughput sequencing technologies have been applied in many ways already, such as in gene expression profiling, small RNA sequencing, target sequencing and whole genome sequencing.
Improving of sequencing technologies
The human genome project was completed in 2003 after many years and at a significant cost. The need to improve sequencing technologies since then has resulted in the emergence of next generation sequencing.
Different sequencing companies started to develop a variety of high-throughput sequencing methods, such as sequencing by synthesis, single-molecule real-time sequencing and ion torrent sequencing.
It is currently possible to sequence more than 45 genomes a day at a cost of about 1,000 dollars each, showing how costs have been reduced and speed has improved.
Applications of next generation sequencing technologies
Improvements in costs, chemistry, throughput and accessibility have resulted in new, varied technologies to address applications that were not previously possible.
Library preparation, sequencing and data analysis are the three basic steps in next generation sequencing. Library and sample preparation is a time-consuming and labor-intensive part.
Many scientists use automated liquid handling workstations to automate library preparation for next generation sequencing analysis. Aurora Biomed is a company that provides these automated systems.
Some next generation sequencing applications include real-time pathogen DNA monitoring, integrated short-read and long-read sequencing studies and routine clinical DNA sequencing. Massive population-level projects are now possible.
Next generation sequencing can be applied for multi-gene panel tests, whole-genome-sequencing, whole-exome sequencing and cell-free DNA for non-invasive prenatal testing. RNA-sequencing and circulating tumor RNA discovery are other applications.
Targeted exome sequencing is increasing in popularity in oncology for the assessment of the sequence of cancer-related genes. Whole-genome sequences gives a comprehensive view of genetic variation is and ideal for discovery applications.
Other applications are found in the areas of forensics, detection of pathogens, evolutionary biology and transplant rejection. For example, next generation sequencing can effectively analyze DNA from different species in large and complex environmental samples.
Some limitations
Great strides are being made but there are still some limitations. The time required to sequence and analyze data limits the use of next generation sequencing in clinical applications where time is of the essence.
The error rates and cost of long-read sequencing can make routine use prohibitive. Ethical considerations are another possible limitation to the private and public use of genetic data.
Benefits
Benefits of next generation sequencing include:
- Higher sensitivity to detect low-frequency variants
- Comprehensive genome coverage,
- A lower limit of detection and the ability to sequences thousands of genes or gene regions simultaneously.
- Fast turnaround times for high volume samples
High throughput with sample multiplexing
Different approaches are giving researchers tools to understand genomes in greater depth. They are able to perform a wide variety of applications and study biological systems at a level not possible in the past.
The complexity of today’s genomic research demands information beyond the capacity of traditional sequencing technologies and next-generation sequencing has filled the gap.