Yuxi Ke

All Publications

• High-throughput DNA melt measurements enable improved models of DNA folding thermodynamics. Nature communications Ke, Y., Sharma, E., Wayment-Steele, H. K., Becker, W. R., Ho, A., Marklund, E., Greenleaf, W. J. 2025; 16 (1): 5572

  Abstract

  DNA folding thermodynamics are central to many biological processes and biotechnological applications involving base-pairing. Current methods for predicting stability from DNA sequence use nearest-neighbor models that struggle to accurately capture the diverse sequence dependence of secondary structural motifsbeyond Watson-Crick base pairs, likely due to insufficient experimental data. In this work, we introduce a massively parallel method, Array Melt, that uses fluorescence-based quenching signals to measure the equilibrium stability of millions of DNA hairpins simultaneously on a repurposed Illumina sequencing flow cell. By leveraging this dataset of 27,732 sequences with two-state melting behaviors, we derive a NUPACK-compatible model (dna24), a rich parameter model that exhibits higher accuracy, and a graph neural network (GNN) model that identifies relevant interactions within DNA beyond nearest neighbors. All models show improved accuracy in predicting DNA folding thermodynamics, enabling more effective in silico design of qPCR primers, oligo hybridization probes, and DNA origami.

  View details for DOI 10.1038/s41467-025-60455-4

  View details for PubMedID 40593545

• High-throughput biochemistry in RNA sequence space: predicting structure and function. Nature reviews. Genetics Marklund, E., Ke, Y., Greenleaf, W. J. 2023

  Abstract

  RNAs are central to fundamental biological processes in all known organisms. The set of possible intramolecular interactions of RNA nucleotides defines the range of alternative structural conformations of a specific RNA that can coexist, and these structures enable functional catalytic properties of RNAs and/or their productive intermolecular interactions with other RNAs or proteins. However, the immense combinatorial space of potential RNA sequences has precluded predictive mapping between RNA sequence and molecular structure and function. Recent advances in high-throughput approaches in vitro have enabled quantitative thermodynamic and kinetic measurements of RNA-RNA and RNA-protein interactions, across hundreds of thousands of sequence variations. In this Review, we explore these techniques, how they can be used to understand RNA function and how they might form the foundations of an accurate model to predict the structure and function of an RNA directly from its nucleotide sequence. The experimental techniques and modelling frameworks discussed here are also highly relevant for the sampling of sequence-structure-function space of DNAs and proteins.

  View details for DOI 10.1038/s41576-022-00567-5

  View details for PubMedID 36635406