Genome sequencing is revolutionizing genetic research and healthcare, with the global next-generation sequencing (NGS) market valued at USD 11.57 billion in 2023 and expected to exceed USD 44.69 billion by 2032, growing at a CAGR of 16.20%.
This growth highlights the increasing role of sequencing technologies in understanding diseases and enabling personalized medicine.
Since the 1980s, significant attention has been given to the costs of genome sequencing. The National Human Genome Research Institute (NHGRI) has tracked these costs across its genome sequencing centers, reflecting how advancements in technology have impacted pricing.
As genome sequencing becomes more widely used in clinical applications, understanding these costs has become essential for researchers and clinicians.
In this blog, we’ll explore the process of genome sequencing, the evolution of its costs, and its future impact on genetic research and healthcare.
What is Genome Sequencing?
Genome sequencing is the process of determining the entire DNA sequence of an organism’s genome. The genome is made up of DNA, which contains the biological information required to build and maintain that organism.
In diploid organisms, like humans, nearly every cell contains two copies of their DNA, inherited from both parents, making up chromosomes. The DNA in these chromosomes is composed of four chemical bases: adenine (A), thymine (T), cytosine (C), and guanine (G).
The sequence of these bases encodes the genetic instructions used in the development, functioning, and reproduction of the organism.
For humans, sequencing the genome involves determining the order of the 3 billion bases that make up our DNA.
However, the actual sequencing process cannot be done in one step due to the immense size of the genome. The DNA must first be fragmented into smaller pieces, and each fragment is sequenced individually.
These fragments are then computationally assembled into a full sequence. This method is known as whole-genome sequencing.
Comparative Analysis of WGS and WES
- Whole Genome Sequencing (WGS)
Whole Genome Sequencing (WGS) involves sequencing the entire genome of an organism, covering all regions of DNA, including coding and non-coding regions.
This method provides a comprehensive view of the genetic material and offers insights into protein-coding regions, regulatory sequences, and non-coding regions, which may be involved in disease development.
- Coverage: WGS sequences the entire genome, including the protein-coding regions (exons), regulatory elements (e.g., promoters, enhancers), and non-coding regions (introns, intergenic regions).
- Data Output: The sheer volume of data generated from WGS is immense, with one human genome producing approximately 250,000 pages of data if printed out. This makes the analysis of WGS challenging, as not all of the sequences are fully understood in terms of their function.
- Applications: WGS is primarily used for research purposes due to its high cost and complexity. It is particularly useful in studying genetic diseases where both coding and non-coding regions may play a role in disease development.
- Whole Exome Sequencing (WES)
Whole Exome Sequencing (WES), on the other hand, focuses only on the exons of the genome — the protein-coding regions. These regions account for about 1.5-2% of the human genome but are highly functional because they directly translate into proteins, which play crucial roles in cellular function and disease mechanisms.
- Coverage: WES targets just the exons, excluding introns and intergenic regions. This reduces the complexity of the sequencing process and focuses on the areas of the genome most likely to influence disease.
- Data Output: Since WES sequences only a small portion of the genome (the exons), the data volume is much smaller compared to WGS, making it easier and faster to analyze.
- Applications: WES is often used for diagnosing genetic diseases, particularly those caused by mutations in coding regions. It is more cost-effective than WGS and is widely used in clinical settings and research to identify genetic variants associated with diseases.
Comparative Analysis of WGS and WES
| Aspect | Whole Genome Sequencing (WGS) | Whole Exome Sequencing (WES) |
| Coverage | Full genome (coding + non-coding regions) | Only coding regions (exons) |
| Data Output | Large data (approx. 250,000 pages for human genome) | Smaller data output, easier to manage |
| Cost | High cost due to complexity and large data volume | More cost-effective, cheaper than WGS |
| Applications | Comprehensive analysis of entire genome, useful for research | Focuses on genetic diseases related to protein-coding genes |
| Data Analysis Complexity | High, due to vast amount of data and unstudied non-coding regions | Lower, as the focus is on the functionally critical exons |
Now that we’ve covered the basics, let’s dive into the main topic: How much does genome sequencing cost?
To fully understand the current pricing, it’s important to first take a look at the history and evolution of genome sequencing.
Historical Cost of Genome Sequencing
Understanding the historical costs of genome sequencing gives us perspective on how far we’ve come and why current prices are much more affordable.
- How Much Did it Cost During the Human Genome Project?
The Human Genome Project (HGP) was a groundbreaking scientific endeavor that produced a reference sequence of the human genome. This sequence was generated by sequencing a representative version of all parts of the human chromosomes, totaling about 3 billion bases.
However, it was not derived from a single individual’s genome but served as a reference for understanding human genetic variation.
The HGP initially focused on mapping the genome to create a framework for organizing and sequencing the DNA.
This mapping phase was essential but expensive, with the cost of producing the first ‘draft’ human genome sequence estimated at $300 million worldwide. The final ‘finished’ sequence, which was achieved by 2003, came at an additional cost of around $150 million.
In total, the cost of the Human Genome Project, including mapping, sequencing, and other research activities, is estimated to have been in the range of $500 million to $1 billion. While this was an astronomical cost at the time, it was a necessary investment to lay the groundwork for future genome sequencing technologies.
- How Much Did it Cost in 2006?
After the completion of the Human Genome Project (HGP), the focus shifted toward sequencing individual human genomes, which involves sequencing approximately 6 billion bases of DNA, compared to the 3 billion bases of the reference human genome. By 2006, significant progress had been made in reducing the cost of genome sequencing.
The cost to produce a high-quality draft human genome sequence had dropped to around $14 million by 2006. If a finished genome sequence had been generated, it would have cost between $20 million to $25 million. Although this was still expensive, it was a significant decrease from the cost of generating the first reference genome during the HGP.
- How Much Did It Cost in 2016?
By 2016, the advent of next-generation sequencing (NGS) revolutionized the field, significantly lowering the costs of genome sequencing. Most sequencing methods in 2015 involved producing a draft sequence, which cataloged sequence variants without finishing the sequence.
The cost for a draft human genome sequence in 2015 had dropped to around $4,000, and by the end of the year, it had fallen to less than $1,500.
At the same time, whole-exome sequencing (WES), which focuses on the coding regions of the genome, was available for under $1,000.
The widespread availability of commercial sequencing services further contributed to the competitive pricing, although differences in what was included in the pricing (e.g., reagents, equipment, data analysis) made direct comparisons between academic and commercial services more complex.
Now that we know how the cost of genome sequencing has been coming down, it will make more sense to discuss how much it costs now.
Current Costs and Commercial Developments
Since the advent of Next-Generation Sequencing (NGS) in 2004, the cost of sequencing a human genome has dropped significantly — from $1 million in 2007 to approximately $600 today.
Illumina, a leading player in the sequencing market, is set to further reduce costs with its NovaSeq X series, which promises to lower the cost to just $200 per genome while also boosting sequencing speed and throughput.
In 2023, commercial laboratories could sequence an entire human genome in just a few hours for around $500, making genome sequencing more accessible and affordable than ever before.
To highlight the progress, these cost reductions align with Moore’s Law, which predicts the doubling of compute power every two years. Sequencing technologies that align with this trend have revolutionized genomic research and diagnostics, making significant strides in cost-efficiency.
Bonus Information:
- Cancer case sequencing costs around £6,841 (including matched tumor and germline samples).
- Rare disease sequencing costs about £7,050 (for three samples).
- Consumables account for 68-72% of the total cost, with equipment and staff costs varying based on the type of sequencing (higher for rare disease cases, and consumables slightly more costly for cancer cases).
Of course, with the declining costs of genome sequencing, there have to be crucial implications.
Implications of Cost Reduction
The reduction in genome sequencing costs has profound implications, especially for diagnosing rare diseases and advancing genomic medicine. Clinicians face challenges in diagnosing rare diseases, often leading to substantial healthcare expenditures.
However, Next-Generation Sequencing (NGS) has revolutionized the diagnostic process, not only improving workflows but also enabling the decoding of new disease-related genes.
NGS dominated the rare disease genetic testing market, with a 35.4% market share in 2021. This growth is driven by the increasing use of Whole Exome Sequencing (WES) and the introduction of Whole Genome Sequencing (WGS), which collectively enhance diagnostic accuracy and affordability.
- Technological Advancements in Genomic Medicine
In 2024, several key technological developments are expected to further transform the landscape of genome sequencing:
- Artificial Intelligence (AI) and Machine Learning: AI-powered tools are improving the precision and speed of genetic variant identification, offering more accurate diagnostic interpretations.
- CRISPR-Based Sequencing: CRISPR, while widely used for gene editing, is being explored for sequencing enrichment applications — an area still under development but with high potential.
- Personalized Medicine: As genetic testing becomes more accessible, personalized medicine—where treatments are tailored based on an individual’s genetic profile—is gaining traction. This trend is expected to drive increased demand for Whole Genome Sequencing (WGS), allowing for more targeted treatments.
As sequencing costs decrease, NGS technology is also becoming more widely available in low- and middle-income regions, making precision medicine and diagnostic tools accessible to a broader population. This trend is improving healthcare outcomes on a global scale.
- Investment in Large-Scale Sequencing Initiatives
Governments and international organizations are investing heavily in large-scale genomic initiatives. For example, the UK’s 100,000 Genomes Project is creating a national genomic database that will transform disease understanding and lead to more personalized treatment strategies across various populations.
- Sequencing Tumors for Cancer Treatment
A rapidly growing use of sequencing is tumor sequencing to inform cancer treatment. Tumor sequencing helps detect specific variants in cancer cells, allowing for more tailored treatment plans.
Replacing multiple single-gene tests (like EGFR, KRAS, BRAF, ALK) with comprehensive tumor sequencing can provide more clinically valuable information at a potentially lower cost than performing several separate tests.
In colorectal and lung cancer treatment, tumor sequencing can replace single-gene tests that cost $200-$1,400 each, providing broader insights into the cancer’s genetic makeup and potentially improving treatment outcomes.
While tumor sequencing may offer clinically useful data at comparable or lower costs, it’s important to consider the impact of incidental findings.
For example, germline sequencing may uncover inherited genetic mutations that could affect both the patient’s cancer treatment and their family members’ health. This requires careful consideration of both the direct and indirect benefits of tumor sequencing.
- Screening for Future Health Risks
Genomic sequencing also offers the potential to identify health risks in individuals who are unaware of their predispositions, such as Lynch syndrome. This syndrome is often undiagnosed in many individuals, and genetic testing could identify those at risk. However, Lynch syndrome screening in the general population currently incurs high costs.
If whole-exome/genome sequencing became more affordable, more individuals could benefit from identifying Lynch syndrome and participating in cascade testing with their relatives.
While early detection of such conditions can improve clinical outcomes, the costs associated with population-wide screening for Lynch syndrome may not always provide cost savings, making it essential to weigh the benefits against the financial implications.
Conclusion
In 2025, with continued advancements in sequencing technologies and a significant reduction in costs, genetic testing is becoming more accessible than ever.
This progress will not only benefit patients with rare diseases but also pave the way for widespread adoption of precision medicine, providing personalized healthcare to millions worldwide.
Despite the massive increase in genomic data, the challenge remains to extract meaningful insights that can improve diagnoses and deepen our understanding of human biology.
While this blog focuses on genome sequencing, transcriptomic analysis through RNA sequencing offers complementary insights — especially in understanding gene expression and regulatory mechanisms in disease. Biostate AI specializes in affordable total RNA-Seq, supporting researchers working with challenging samples or rare transcripts.
At Biostate AI, we are committed to supporting researchers in navigating this complex data. Our affordable total RNA sequencing services help uncover critical genetic insights, even from challenging specimens like FFPE tissue or small blood samples, enabling researchers to gain a deeper understanding of complex conditions.
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