aiqbench analysis
This study applies quantum annealing to model the 3D folding of chromatin domains by embedding an epigenetic Ising model onto D-Wave hardware. By overcoming classical sampling limitations caused by high frustration, it successfully reproduces key statistical features of Topologically Associating Domains without reconstructing exact distributions. The work establishes a viable pathway for using quantum processors to explore complex biological architectures that are intractable for current classical methods.
Intermediate State Formation of Topologically Associated Chromatin Domains using Quantum Annealing
arXiv:2505.23289v2 Announce Type: replace Abstract: Topologically Associating Chromatin Domains are spatially distinct chromatin regions that regulate transcription by segregating active and inactive genomic elements. Empirical studies show that their formation correlates with local patterns of epigenetic markers, yet the precise mechanisms linking 1D epigenetic landscapes to 3D chromatin folding remain unclear. Recent models represent chromatin as a spin system, where nucleosomes are treated as discrete-state variables coupled by interaction strengths derived from genomic and epigenetic data. Classical samplers struggle with these models due to high frustration and dense couplings. Here, we present a quantum annealing (QA) approach to efficiently sample chromatin states, embedding an epigenetic Ising model into the topology of D-Wave quantum processors. Rather than reconstructing exact TAD size distributions or insulation scores, our method reproduces statistical features, such as mean marker incidences and intra-/inter-nucleosome correlations, while generating configurations that exhibit TAD-like structural motifs. These results demonstrate QA as an alternative to explore the chromatin architecture and provide a foundation in epigenetic modeling.
Abstract:Topologically Associating Chromatin Domains are spatially distinct chromatin regions that regulate transcription by segregating active and inactive genomic elements. Empirical studies show that their formation correlates with local patterns of epigenetic markers, yet the precise mechanisms linking 1D epigenetic landscapes to 3D chromatin folding remain unclear. Recent models represent chromatin as a spin system, where nucleosomes are treated as discrete-state variables coupled by interaction strengths derived from genomic and epigenetic data. Classical samplers struggle with these models due to high frustration and dense couplings. Here, we present a quantum annealing (QA) approach to efficiently sample chromatin states, embedding an epigenetic Ising model into the topology of D-Wave quantum processors. Rather than reconstructing exact TAD size distributions or insulation scores, our method reproduces statistical features, such as mean marker incidences and intra-/inter-nucleosome correlations, while generating configurations that exhibit TAD-like structural motifs. These results demonstrate QA as an alternative to explore the chromatin architecture and provide a foundation in epigenetic modeling.
Quantum Physics (quant-ph); Soft Condensed Matter (cond-mat.soft); Biological Physics (physics.bio-ph); Genomics (q-bio.GN)
arXiv:2505.23289 [quant-ph]
(or arXiv:2505.23289v2 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2505.23289 Focus to learn more arXiv-issued DOI via DataCite
https://doi.org/10.1038/s41598-026-55306-1 Focus to learn more DOI(s) linking to related resources
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