In a first, scientists translated an entire viral genome so a quantum computer could read and analyze it

Scientists say they have uploaded a real genome to a quantum computer for the first time, marking an important step in applying the emerging technology to biology.

The researchers encoded the entire genome of the hepatitis D virus (HDV) onto a system powered by IBM's 156-qubit Heron quantum processing unit. This achievement came during the Quantum for Bio (Q4Bio) challenge, a competitive international research program designed to accelerate quantum computing applications for human health. The goal was to demonstrate that quantum computers could handle real-world genomic data in a format the machines could actually process.

A genome is naturally stored as a long sequence of letters (A, C, G, and T/U), whereas a quantum computer works with quantum states represented by qubits. Simply copying DNA letters into qubits is not enough; the information has to be transformed into a quantum representation that can be prepared, manipulated, and measured by the hardware.

The scientists with the Wellcome Sanger Institute converted the HDV genome into a quantum-compatible format, allowing quantum algorithms to analyze genetic information rather than just theoretical problems.

They said in a statement that they specifically targeted the most complex and variable genomes ‪—‬ tasks that can exceed the current capabilities of classical computers, including artificial intelligence (AI) systems.

Where quantum computing and biology intersect

"When we work with pangenomes, the information is presented in a form of a tangled maze, but we are building quantum algorithms to help find the best path through this maze when regular tools, such as classic computers, just get hopelessly stuck," said leader of the research team, Sergii Strelchuk, an associate professor at the Department of Computer Science at the University of Oxford.

"We’re aiming for a simple but game-changing idea by bringing quantum computing into the world of genomics."

The same researchers already demonstrated four key genomics capabilities on real quantum hardware within the same Q4Bio genomics project. They used data encoding to convert DNA sequences into a quantum-compatible format.

A step called sequence alignment mapped DNA fragments into reference genomes, while a process called pangenome assembly built genomes from multiple individuals' DNA data. They also used, phylogenetic tree construction to map evolutionary relationships among organisms.

The scientists chose HDV because it has a compact genome and is clinically relevant. Although its RNA folds into intricate secondary structures — rather than existing as a simple linear sequence — and it mutates rapidly (like many RNA viruses), HDV has one of the smallest known animal virus genomes — roughly 1,700 nucleotides of circular RNA.

It causes severe blood-borne liver infections through contact with infected bodily fluids, making it an ideal test case that balances complexity with practical biomedical importance, the team said.

Increasingly complex computations

The work also demonstrates that pangenomes — collections of genome sequences from many individuals of the same species — are where quantum computing truly shines. As more genomes join a pangenome, conventional computing resources can be overwhelmed due to combinatorial growth in complexity.

A pangenome is not just a collection of genomes stored side by side but a data structure that captures all the genetic variation across many individuals, strains, or populations. As more genomes are added, the amount of variation that must be represented, compared, and indexed grows rapidly.

Quantum machines may be better able to navigate this computational complexity because they can represent and process many possible genetic patterns at once in a way that might make certain large-scale comparison and search problems in genomics faster (or more efficient) than traditional computers.

In the future, faster and more powerful genomic analysis could let scientists rapidly track infectious diseases, improve their understanding of rare genetic disorders, and pinpoint disease-causing mutations, the team said. Loading the hepatitis D genome onto a quantum computer opens the door to solving biological problems that have been impossible for classical computers to tackle, James McCafferty, chief information officer at the Wellcome Sanger Institute, said in the statement.

Although the accomplishment is promising, practical applications may still be years away, Strelchuk and colleagues on the Q4Bio team said in the statement. The team wants to package these capabilities into a usable service that would allow the wider scientific community to upload data and choose between classical or quantum approaches (or both) to address computational challenges.

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