An Introduction to Next-Generation Sequencing
At the 2015 American Association of Clinical Chemistry Annual Meeting, Linnea Baudhuin, Ph.D., Co-Director of the Mayo Clinic’s Next-Generation Sequencing Core Laboratory, moderated and co-presented a workshop on next-generation sequencing (NGS). The workshop provided an introduction to NGS and details related to the emerging laboratory approach. Additional panelists included:
- John Logan Black, M.D., Mayo Clinic
- Christina Lockwood, University of Washington
- Eric Duncavage, University of Washington
While the hour and half presentation went into great detail, this blog post will highlight the basics of next-generation sequencing.
Next-generation sequencing builds on Sanger sequencing, which has been widely used since 1975 and was used to sequence the human genome for the first time.
While the most popular name for the testing approach is next-generation sequencing, it is also referred to as:
- Massively parallel sequencing
- High-throughput sequencing
- Second-generation sequencing
- Third-generation sequencing
- Single molecule sequencing
A Range of Possibilities
While the applications of next generation sequencing appear to be limitless, the most common approaches mainly focus on whole-exome sequencing and targeted sequencing to look at certain genes or genomic regions. The major applications for next generation sequencing include somatic, inherited disorders, non-invasive prenatal testing, and microbe identification.
Theoretically, next-generation sequencing has several benefits, such as:
- Enables much more comprehensive testing approaches.
- Allows laboratories to generate higher “hit” rates for diagnostic and/or actionable mutations.
- Drives clinical trial data generation and future discoveries.
- Template preparation for either DNA or RNA
- Massively parallel sequencing using clonal amplification and imaging or other detection methods
- Data analysis, including genome assemble, align with comparison sequence, and interpretation
- All next-generation sequencing tests are laboratory-developed tests, inviting a high level of review, validation, verification, and regulations.
- Interpretation is very challenging, due to the massive amount of data generated along with insufficient clinical databases to reference.
- Turnaround time is not as rapid as the industry would like it, with some tests taking up to three months.
- Not universally accepted by payers.
- Sequencing files are big, in most cases several terabytes, and data analysis is slow due to computation limitations.