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Massively parallel sequencing

Massively parallel sequencing is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Massively parallel sequencing rather than just read about it. In short: Massively parallel sequencing (MPS) is any of several high-throughput approaches to DNA sequencing using the concept of massively parallel processing; it is also called next-generation sequencing (NGS) or second-generation sequencing. Some of these technologies emerged between 1993 and 1998 and have been commercially available since 2005.

Massively parallel sequencing — main illustration
Massively parallel sequencing — illustration

Key takeaways

  • Massively parallel sequencing belongs to science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Massively parallel sequencing to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Massively parallel sequencing from memory before moving on to harder problems.

Reference excerpt

Massively parallel sequencing (MPS) is any of several high-throughput approaches to DNA sequencing using the concept of massively parallel processing; it is also called next-generation sequencing (NGS) or second-generation sequencing. Some of these technologies emerged between 1993 and 1998 and have been commercially available since 2005. These technologies use miniaturized and parallelized platforms for sequencing of 1 million to 43 billion short reads (50 to 400 bases each) per instrument run. Many NGS platforms differ in engineering configurations and sequencing chemistry. They share the technical paradigm of massively parallel sequencing via spatially separated, clonally amplified DNA templates or single DNA molecules in a flow cell. This design is very different from that of Sanger sequencing—also known as capillary sequencing or first-generation sequencing—which is based on electrophoretic separation of chain-termination products produced in individual sequencing reactions. This methodology allows sequencing to be completed on a larger scale.

History In the 1990s, Applied Biosystems dominated DNA sequencing technology with their automated capillary electrophoresis Sanger sequencing machines. However, the early 2000s saw many new companies entering the market, driven by the goal of reducing genome sequencing costs below $1000 following the enthusiasm generated by the Human Genome Project. Many of these new methods were first developed with support from the National Institutes of Health (NIH) funding under the 'Technology Development for the $1,000 Genome' program, launched during Francis Collins’ tenure as director of the National Human Genome Research Institute. The first next-generation sequencers were based on pyrosequencing, originally developed by Pyrosequencing AB and later commercialized by 454 Life Sciences. In 2003, 454 Life Sciences launched the GS20, the first NGS DNA sequencer. This system provided reads approximately 400–500 bp long with 99% accuracy, enabling sequencing of about 25 million bases in a four-hour run at significantly lower costs compared to Sanger sequencing. The sequencing machines developed by 454 represented a paradigm shift by enabling the mass parallelisation of sequencing reactions, which significantly boosted the amount of DNA sequenced per run, making 454 Life Sciences the first major success in commercial NGS technology. Also in 2003, Solexa began developing a competing method known as Sequencing by Synthesis (SBS). In 2004, Solexa acquired colony sequencing (bridge amplification) technology from Manteia, producing densely clustered DNA fragments ("polonies") immobilized on flow cells. These dense clusters generated stronger fluorescent signals, improving accuracy and reducing optical costs. In 2005, Solexa integrated an engineered DNA polymerase and reversible terminator nucleotides, allowing repeated cycles of sequencing and imaging. The first commercial sequencer based on this technology, Genome Analyzer, was launched in 2006, providing shorter reads (about 35 bp) but higher throughput (up to 1 Gbp per run) and paired-end sequencing capability, in which both ends of a DNA fragment are sequenced. in 2007, 454 Life Sciences was acquired by Roche and Solexa by Illumina, the same year Applied Biosystems introduced SOLiD, a ligation-based sequencing platform. However, SOLiD encountered issues sequencing palindromic regions and was eventually discontinued. In 2011, Ion Torrent introduced another alternative, measuring proton (pH) changes during nucleotide incorporation using semiconductor-based sensors. Ion Torrent systems rapidly produced 100 bp reads but frequently struggled with accurately sequencing homopolymers, ultimately leading to their abandonment. Due to limitations in competing methods, Illumina’s SBS technology eventually dominated the sequencing market. By 2012, expectations that 454 would gain a substantial share of the sequencing market had not been realized, and Roche’s 2007 acquisition was increasingly viewed as underperforming; that same year, Roche made an unsuccessful attempt to acquire Illumina. In October 2013, Roche announced that it would shut down 454, and stop supporting the platform by mid-2016. By 2014, Illumina controlled approximately 70% of DNA sequencer sales and generated over 90% of sequencing data. That year, Illumina introduced the HiSeq X Ten platform, significantly increasing throughput and claiming the long-targeted goal of sequencing human genomes at roughly $1000 each. Illumina surpassed this milestone in 2017 with the release of NovaSeq, a system capable of generating over 3000 Gbp per run. Ongoing growth in demand for sequencing data, along with the 2023 expiration of several key Illumina patents, has encouraged a wave of short-read sequencing competitors, each bringing distinct chemistries, flow-cell designs, throughput levels, and cost structures. By the early 2020s, Illumina's sequencing-by-synthesis platforms remained dominant; a 2023 overview estimated that more than 90% of the world's sequencing data in 2022 had been generated on Illumina instruments. Competitors included MGI Tech, whose DNBSEQ platforms use DNA nanoballs rather than Illumina-style bridge amplification, and Ultima Genomics, which developed a production-scale platform using a spinning-disc flow cell. Singular Genomics introduced the G4 Sequencing Platform in late 2021, Element Biosciences followed by announcing AVITI Sequencing in March 2022, and PacBio later entered the short-read space with its Onso benchtop platform, unveiled in October 2022. Illumina's NovaSeq X series began shipping in 2023 and used a redesigned flow cell, updated sequencing chemistry, and upgraded optics. Illumina stated that the system could generate up to three times as much data per run as the previous NovaSeq 6000 and reduce the cost of sequencing a human genome to about US$200 when fully utilized. PacBio's involvement in the short-read market was short-lived: after launching the Onso short-read platform in 2023, the company completed the sale of select intellectual property and other assets related to its short-read sequencing technology to Illumina in January 2026.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Massively parallel sequencing

Start with the simplest possible case. Write down what Massively parallel sequencing claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Massively parallel sequencing before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Massively parallel sequencing ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Massively parallel sequencing

In research
Massively parallel sequencing appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Massively parallel sequencing in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Massively parallel sequencing is common in secondary-school and first-year university syllabi. It links to neighbouring topics DNA sequencing methods, so understanding it makes those chapters shorter.
In everyday life
Look for Massively parallel sequencing outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Massively parallel sequencing in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Massively parallel sequencing means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Massively parallel sequencing out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Massively parallel sequencing in simple terms?

Massively parallel sequencing (MPS) is any of several high-throughput approaches to DNA sequencing using the concept of massively parallel processing; it is also called next-generation sequencing (NGS) or second-generation sequencing. Some of these technologies emerged between 1993 and 1998 and hav…

Why does Massively parallel sequencing matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Massively parallel sequencing?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Massively parallel sequencing.

Tags

  • DNA sequencing methods

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