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Quantum Computing Meets Genomics: The Dawn of Hyper-Fast DNA Analysis

A new project brings together leading experts in quantum computing and genomics to create new methods and algorithms for processing biological data. Researchers aim to utilize...

Advanced Genomics DNA Analysis Concept Art

A pioneering collaboration has been set up to focus on using quantum computing to improve genomics. The team will create algorithms to speed up the analysis of pangenomic datasets, which could revolutionize personalized medicine and pathogen management. Credit:

A new project brings together top experts in quantum computing and genomics to develop new methods and algorithms to process biological data.

Researchers plan to utilize quantum computing to accelerate genomics, improving our understanding of DNA and driving progress in personalized medicine

A new collaboration has been formed, uniting an interdisciplinary team with expertise in quantum computing, genomics, and advanced algorithms. They aim to address one of the most complex computational problems in genomic science: building, enhancing, and analyzing pangenomic datasets for large population samples. Their project is at the cutting edge of research in both biomedical science and quantum computing.

The project, which involves researchers based at the University of Cambridge, the Wellcome Sanger Institute, and EMBL’s European Bioinformatics Institute (EMBL-EBI), has been awarded up to US $3.5 million to explore the potential of quantum computing for improvements in human health.

The team aims to develop quantum computing algorithms with the potential to speed up the production and analysis of pangenomes – new representations of DNA sequences that capture population diversity. Their methods will be designed to run on emerging quantum computers. The project is one of 12 selected worldwide for the Wellcome Leap Quantum for Bio (Q4Bio) Supported Challenge Program.

Advancements in Genomics

Since the initial sequencing of the human genome over two decades ago, genomics has revolutionized science and medicine. Less than one percent of the 6.4 billion letters of DNA code differs from one human to the next, but those genetic differences are what make each of us unique. Our genetic code can provide insights into our health, help to diagnose disease, or guide medical treatments.

However, the reference human genome sequence, which most subsequently sequenced human DNA is compared to, is based on data from only a few people, and doesn’t represent human diversity. Scientists have been working to address this problem for over a decade, and in 2023 the first human pangenome reference was produced. A pangenome is a collection of many different genome sequences that capture the genetic diversity in a population. Pangenomes could potentially be produced for all species, including pathogens such as SARS-CoV-2.

Quantum Computing in Genomics

Pangenomics, a new domain of science, requires high levels of computational power. While the current human reference genome structure is linear, pangenome data can be represented and analyzed as a network, called a sequence graph, which stores the shared structure of genetic relationships between many genomes. Comparing subsequent individual genomes to the pangenome then involves mapping a route for their sequences through the graph.

The team's new project aims to create quantum computing methods that can make mapping data to graph nodes and finding routes through the graph much faster.

Quantum technologies are set to change high-performance computing. While classical computers use bits as 0 or 1, quantum computers use qubits which can be 0, 1, or in a mixed state of 0 and 1, thanks to quantum mechanics.

Challenges and Future Prospects

However, the current quantum computer hardware is very sensitive to disturbances and noise, making it difficult to scale up. Despite some exciting experiments, today's quantum computers are still small and limited in computational power. But there are expected to be significant advances in quantum hardware in the next three to five years.

The Wellcome Leap Q4Bio Challenge is based on the idea that new computational methods benefit from developing applications, software, and hardware together, allowing for optimizations with early systems.

Using advanced computational genomics methods as a starting point, the team will create and test new quantum algorithms with real data. They will initially test these algorithms in powerful High Performance Compute environments to simulate expected quantum computing hardware. These tests will start with small DNA sequences and progress to larger sequences like SARS-CoV-2 and eventually the human genome.

Perspectives From the Team

Dr. Sergii Strelchuk, Principal Investigator from the University of Cambridge, stated: "The structure of many challenging problems in computational genomics, especially in pangenomics, makes them suitable for quantum computing speedups. We are working on developing and using quantum algorithms designed for genomic data to gain new insights not possible with classical algorithms."

David Holland, Principal Systems Administrator at the Wellcome Sanger Institute, is creating a High Performance Compute environment to simulate a quantum computer. He mentioned: "We are just beginning to explore quantum computing and pangenomics, and bringing them together is very exciting. There are many opportunities for new advances. We are doing things today to make tomorrow better."

Dr. David Yuan, Project Lead at EMBL-EBI, stated that they are starting from the beginning as they don't know how to represent a pangenome in a quantum computing environment. He compared the project to designing a rocket and training astronauts for the first moon landings. However, they have a strong foundation built on decades of annotated genomic data from researchers worldwide and made available by EMBL-EBI. He emphasized the importance of open data and collaborative science in developing the next generation of tools for the life sciences.

The potential benefits of this work are significant. Comparing a specific human genome to the human pangenome, instead of the existing human reference genome, provides better insights into its unique composition. This will be crucial for advancing personalized medicine. Similar approaches for bacterial and viral genomes will support the tracking and management of pathogen outbreaks.

The Wellcome Leap Quantum for Bio (Q4Bio) Supported Challenge Program is funding this project.

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