The past, present, and future of genome sequencing

Genome sequencing is the process of determining the complete DNA sequence of an organism’s genome, a step-by-step decoding of all the genetic instructions. In humans, that means reading around 3 billion base pairs to reveal everything from disease risk and drug response to ancestry and evolution.

For many years, genome sequencing was largely limited to research settings due to its high cost and technical complexity. Today, however, it is becoming more widely used in clinical and public health contexts. Costs have decreased significantly, and sequencing is increasingly being integrated into healthcare systems for early diagnosis, especially in areas such as rare genetic diseases and cancer.

In 2024, the cost of sequencing a human genome reached around $200 using the latest generation of high-throughput platforms, with some technologies approaching the $100 mark when performed at scale. At the same time, national initiatives are emerging that apply genome sequencing to newborn screening or population health.

This article explores how genome sequencing has evolved over the past few decades, where it currently stands, and how it may continue to shape research and medicine in the coming years.

A brief history of genome sequencing

The journey of genome sequencing began in 1977 with Frederick Sanger’s introduction of the chain-termination method, revolutionizing DNA sequencing by enabling the reading of longer DNA fragments with higher accuracy. This technique laid the groundwork for future genomic research and earned Sanger his second Nobel Prize, this time, shared with Walter Gilbert.

Building on this foundation, the Human Genome Project (HGP) was launched in 1990, aiming to map the entire human genome. After 13 years and an investment exceeding $2 billion, the HGP successfully completed the first human genome sequence in 2003. ​

The early 2000s have seen the emergence of next-generation sequencing (NGS) technologies, which transformed genomic research by significantly reducing sequencing costs and increasing throughput. In 2005, 454 Life Sciences introduced the GS20 platform, pioneering massively parallel sequencing. Not too long after, Illumina’s acquisition of Solexa led to the development of sequencing-by-synthesis technology.

This all contributed to the significant decrease in sequencing costs, from approximately $95 million per genome in 2001 to around $600 by 2023. This cost reduction made genome sequencing more accessible for research and clinical applications.​

While NGS technologies excelled in speed and cost-effectiveness, they often produced short reads, posing challenges in assembling complex genomic regions. This is why long-read sequencing technologies emerged, offering longer read lengths and improved assembly of repetitive regions. Companies like Pacific Biosciences and Oxford Nanopore Technologies have been at the forefront of this innovation.

Additionally, the pursuit of affordable whole-genome sequencing has been a driving force in genomics. In 2014, Illumina announced the HiSeq X Ten system, aiming for the $1,000 genome. By 2023, MGI Tech introduced the DNBSEQ-T20x2 sequencer, claiming to achieve a sub-$100 genome at scale. In 2024, Illumina’s NovaSeq X series further reduced sequencing costs to approximately $200 per genome, bringing the $100 genome within reach.

The forces shaping genome sequencing today

Genome sequencing is no longer dominated by a single technology or provider. The field has become more diverse, with multiple companies developing platforms that vary in speed, cost, and the types of data they generate. While affordability remains a central focus, accuracy, read length, and ease of integration into clinical workflows are also driving innovation and competition.

Illumina remains a central force in the market with its NovaSeq X series, launched in 2023. The new platform builds on the company’s sequencing-by-synthesis technology, but with higher throughput, improved chemistry, and integrated onboard data processing. With a capability of over 20,000 human genomes per year, NovaSeq X has brought the cost per genome down to around $200.

Meanwhile, Illumina is no longer the only one targeting this price point. MGI, a subsidiary of BGI Group, offers a competing platform, the DNBSEQ-T20x2, which claims to deliver whole-genome sequencing at under $100 when used at a large scale. Companies like Ultima Genomics and Element Biosciences are also entering the field with alternative technologies designed to reduce cost barriers. While not yet widely adopted, it does point to an increasingly diverse landscape.

Beyond the race for lower costs, sequencing innovation is also being driven by the need for better resolution of complex genomic regions. Long-read technologies, which can capture structural variants and repetitive elements more effectively than short-read methods, have become increasingly important. Pacific Biosciences’ Revio system is leading this space with high-accuracy long reads suited for clinical research, while Oxford Nanopore continues to push the portability and real-time potential of its nanopore-based sequencers.

As platforms diversify and improve, the types of projects they serve are evolving too. Large-scale genomic initiatives, from population health programs to national newborn screening pilots, are no longer limited by the availability of affordable sequencing. Instead, the challenge is increasingly about downstream analysis and integration into healthcare workflows.

At the same time, the consumer genomics boom of the 2010s has cooled down. Companies like 23andMe have scaled back direct-to-consumer services in response to market saturation and privacy concerns, shifting their business models toward partnerships in drug discovery and research. This reflects a broader trend: genome sequencing is moving away from novelty and into more regulated, clinical, and research-driven contexts.

What happens after the genome is read: Real-world applications

One of the most direct uses of genome sequencing is in the diagnosis of rare genetic conditions. When symptoms are unclear and conventional tests fail to provide answers, sequencing a patient’s genome, or the genomes of an entire family, can help identify the underlying cause. This is particularly relevant in pediatric medicine, where early diagnosis can significantly improve treatment options and long-term outcomes. Whole-genome sequencing has already replaced the traditional diagnostic odyssey for many families by providing a single test that can identify mutations across the entire genome.

Cancer treatment is another area where genome sequencing helps. In oncology, it allows the identification of genetic mutations that drive cancer growth, some of which are targetable with specific therapies. For example, BRCA1 and BRCA2 mutations – most commonly associated with breast and ovarian cancers – can inform the use of PARP inhibitors, which are more effective in patients with these mutations. More broadly, sequencing can help guide treatment selection, predict response to therapy, and detect emerging resistance, especially as liquid biopsy techniques mature.

Sequencing is also being used proactively. In the U.K., the NHS has launched a pilot project to sequence the genomes of 100,000 newborns through the Generation Study, aiming to identify over 200 rare but actionable conditions early in life. Such programs represent a shift toward preventive medicine, where early genomic information can inform long-term health management. Beyond rare diseases, genome sequencing is also being explored to assess inherited risk for common conditions, such as cardiovascular disease.

At the population level, initiatives like the U.K. Biobank and the U.S. All of Us Research Program are sequencing genomes to better understand the genetic basis of health and disease. These projects combine genomic data with lifestyle and health information to uncover associations that would be difficult to detect at smaller scales. It also aims to address the lack of diversity in genetic datasets, which has historically limited the applicability of genomic findings across populations.

The price of knowing: Privacy, consent, and genetic risk

Data is always a sensitive topic. As genome sequencing becomes more integrated into healthcare and research, questions about how this data is used, stored, and protected are becoming increasingly important. The ethical and regulatory frameworks that govern genomic data are still evolving, and are rarely keeping pace with the technology.

Genome sequencing can reveal much more than the specific information being sought. In clinical settings, this raises the question of how to handle incidental findings, unexpected results that may indicate a risk for unrelated health conditions. Should patients always be informed? What if no preventive treatment is available? These questions have prompted debates about the boundaries of informed consent and the right not to know. 

The “right not to know” is a principle grounded in respect for individual autonomy, allowing people to remain unaware of certain genetic information if they choose. This right is recognized in various international declarations, such as the European Convention on Human Rights and Biomedicine, which states that individuals have the right to know any information collected about their health, but also the right not to be informed if they so wish.

However, this right is not absolute and has been the subject of ongoing debate. Some argue that disclosing incidental findings, particularly those that are actionable, aligns with the healthcare provider’s duty to prevent harm. Others think that unsolicited information can cause psychological distress, especially when the clinical significance is uncertain.

Professional guidelines attempt to navigate this complex landscape. For instance, the American College of Medical Genetics and Genomics (ACMG) recommends that certain pathogenic variants, which are deemed medically actionable, should be reported regardless of the patient’s preferences. This approach has sparked discussions about balancing the benefits of disclosure with respect for patient autonomy.

There are also concerns about how genomic data might be used beyond healthcare. In some countries, laws such as the Genetic Information Nondiscrimination Act (GINA) in the U.S. prohibit the use of genetic information in employment or health insurance decisions. However, gaps remain, particularly around life insurance, long-term care, or disability insurance. As genomic data becomes more widespread, the risk of misuse, whether intentional or not, continues to draw attention from policymakers and patient advocacy groups.

Another open question is who owns genomic data. Patients often contribute their DNA to research or clinical programs without always having clarity on what happens next. Can the data be reused in future studies? Shared with commercial partners? While many research initiatives anonymize genomic datasets, concerns persist about re-identification and secondary uses. 

Genomic data is not only sensitive, it is also permanent; unlike a credit card number, it cannot be changed if leaked. This makes data breaches particularly concerning. Initiatives such as the Global Alliance for Genomics and Health (GA4GH) have proposed international standards, but implementation varies widely.

Finally, a growing number of researchers and policymakers have highlighted the underrepresentation of certain populations in genomic databases. The majority of sequencing data still comes from people of European descent, which limits the accuracy and relevance of findings for other populations. Without greater diversity, genome sequencing runs the risk of reinforcing existing health bias and disparities rather than reducing them.

What’s next for genome sequencing

The milestone of sequencing a human genome for approximately $100 has been achieved. Companies like Ultima Genomics have introduced platforms such as the UG 100, which offer whole-genome sequencing at this reduced cost, significantly lowering the barrier to entry for large-scale genomic projects. It seems the race to the cheapest genome sequencing is close to its end, and competitors will either have to find a way to align with these costs or find another way to differentiate themselves. 

Advancements in sequencing technology are enabling real-time genomic analysis. Portable devices, like Oxford Nanopore’s MinION, allow for immediate sequencing results, which is particularly beneficial in clinical diagnostics and infectious disease surveillance. 

The future of precision medicine lies in the integration of multi-omics data, combining genomics with transcriptomics, proteomics, metabolomics, and other data types.​ As sequencing becomes cheaper and more accessible, its role in preventive medicine is also bound to become more important.

Yet, there are still some challenges to address. Ethics, privacy, and consent are questions that will need time to be settled by regulations. The vast amount of data to analyse and integrate into clinical practice is a more concrete hurdle that artificial intelligence (AI) might help with considerably.