Generating three-dimensional genome structures with a variational quantum algorithm

Abstract

Chromosome conformation capture (3C) experiments have revealed the underlying spatial interactions that govern three-dimensional (3D) genome organization and topology. Detecting 3D contacts between genomic loci considerably enhances our understanding of fundamental regulatory processes. Modeling 3D structures from experimental contact matrices can further contextualize the relationship between 3D genome organization and regulation. While classical algorithms have been successful in reconstructing genomic conformations, we investigate the prospect of quantum computation to aid in modeling the conformational space. In this context, we propose a novel variational quantum algorithm to model the distribution of 3D genomic structures from experimental contact data. Through rigorous evaluations, we demonstrate the capability of our algorithm to sample ensembles of viable 3D conformations that agree well with experimental and simulated contact data. Furthermore, we extend our methodology to model the conformational space of a single cell or a population of cells. In the advent of sufficient quantum utility, the insights gained from this study can serve as a foundation for investigating high-resolution, large-scale ensembles of genomic conformations through generative variational quantum algorithms.