Next-Generation Sequencing Technologies
Next-generation sequencing (NGS), also called high-throughput or massively parallel sequencing, refers to the platforms that read millions to billions of DNA fragments simultaneously, displacing the one-read-at-a-time Sanger method. These technologies dropped the cost of sequencing by orders of magnitude and made whole-genome, exome, and transcriptome studies routine.
Definition
Next-generation sequencing technologies are platforms that determine nucleotide sequence by reading very large numbers of DNA fragments in parallel, producing high-throughput data at low per-base cost, in contrast to the sequential electrophoretic reading of Sanger sequencing.
Scope
The entry surveys the families of high-throughput platforms, including short-read sequencing-by-synthesis and long-read single-molecule approaches such as nanopore and single-molecule real-time sequencing, the read-length versus accuracy trade-offs that distinguish them, and their impact on the scale of genomics. It is a methodological overview, not a comparison for purchasing or clinical-testing decisions.
Core questions
- What distinguishes next-generation sequencing from earlier Sanger sequencing?
- How do short-read and long-read platforms differ in read length, accuracy, and applications?
- How did high-throughput sequencing change the scale and cost of genomics?
Key concepts
- Massively parallel sequencing
- Sequencing by synthesis
- Short-read versus long-read platforms
- Single-molecule real-time sequencing
- Nanopore sequencing
- Read length and per-base accuracy trade-off
- Cost per base
Mechanisms
High-throughput platforms immobilise and read enormous numbers of DNA fragments at once. Short-read sequencing-by-synthesis detects each base as it is incorporated, often using reversible terminators, yielding short but highly accurate reads. Long-read approaches read single molecules in real time or as they pass through a nanopore, producing much longer reads that span repetitive and structurally complex regions at the cost of somewhat higher per-base error. The choice between platforms reflects a trade-off among read length, accuracy, throughput, and cost that depends on the analytical goal.
Clinical relevance
Next-generation sequencing is the workhorse of modern genomic research and clinical genomics, enabling everything from variant detection to pathogen and cancer genomics. This entry describes the technologies and their trade-offs as reference material and does not recommend any particular platform or test for individual use.
Evidence & guidelines
The field is documented through influential reviews tracing platform evolution: Metzker (2010), Reuter et al. (2015), and Goodwin et al. (2016) for the broad landscape, and Wang et al. (2021) for nanopore sequencing specifically; Bentley et al. (2008) is a foundational short-read primary report.
History
After Sanger sequencing dominated for three decades, commercial massively parallel platforms emerged in the mid-2000s, with reversible-terminator short-read sequencing demonstrated at whole-genome scale in 2008. Over the following decade throughput rose and costs fell sharply, while single-molecule long-read platforms (single-molecule real-time and nanopore sequencing) matured to address the read-length limitations of short reads.
Key figures
- Michael Metzker
- Michael Snyder
- W. Richard McCombie
- David Bentley
Related topics
Seminal works
- metzker-2009
- goodwin-2016
- wang-2021
Frequently asked questions
- What does next-generation sequencing add over Sanger sequencing?
- It reads millions to billions of fragments in parallel rather than one at a time, increasing throughput by many orders of magnitude and lowering cost, which makes whole-genome and population-scale studies practical.
- What is the main trade-off between short-read and long-read sequencing?
- Short reads are typically highly accurate but too short to span long repeats, while long reads cover repetitive and structurally complex regions but have historically carried higher per-base error rates.