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QuASeR: Quantum Accelerated de novo DNA sequence reconstruction.

Aritra Sarkar1, Zaid Al-Ars1, Koen Bertels2

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We introduce QuASeR, a novel quantum computation method for DNA sequence reconstruction using de novo assembly. This tool aids genomics research by enabling efficient DNA sequence assembly on quantum platforms.

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Area of Science:

  • Bioinformatics
  • Quantum Computing
  • Genomics

Background:

  • De novo assembly is crucial for reconstructing genomes from short DNA reads.
  • Current assembly methods face challenges with scalability and accuracy.
  • Quantum computing offers potential for novel computational approaches in bioinformatics.

Purpose of the Study:

  • To present QuASeR, a reference-free DNA sequence reconstruction implementation.
  • To demonstrate the application of quantum computation for de novo DNA assembly.
  • To provide a self-contained explanation for genomics researchers and quantum developers.

Main Methods:

  • Modeling DNA sequence reconstruction using quantum computation.
  • Implementing the algorithm using four key steps: Traveling Salesperson Problem (TSP), Quadratic Unconstrained Binary Optimization (QUBO), Hamiltonians, and Quantum Approximate Optimization Algorithm (QAOA).
  • Executing the algorithm on gate-based quantum simulators, D-Wave quantum annealing simulators, and hardware.

Main Results:

  • Successful reconstruction of DNA sequences from DNA reads using QuASeR.
  • Demonstration of proof-of-concept for each implementation step.
  • Analysis of performance on both quantum simulators and hardware.

Conclusions:

  • QuASeR represents the first quantum computation model for reference-free DNA sequence reconstruction.
  • The study highlights the potential and limitations of current quantum systems for bioinformatics applications.
  • The open-source implementation facilitates further research and development in quantum bioinformatics.