Leveraging advances in hardware and probes, we have combined innovations in optics and algorithms to allow automated single-molecule-based super-resolution imaging at unprecedented throughput. This approach allows us to obtain nanoscale information from large cell populations, bridging the gap between imaging and indirect ensemble methods.

Fine-tuning gene expression is crucial for generating quantitative phenotypic changes and crop improvement. Using CRISPR–Cas base editing and prime editing, we engineered upstream open reading frames — eukaryotic translational control elements — in rice to incrementally downregulate translation to predictable and desired levels.

Sequencing individual cells in a sample enables scientists to infer the unique characteristics of important subsets. Single-cell sequencing methods that rely on microfluidics for cell barcoding are limited in speed, scale and flexibility. We developed a technique that uses particle-templated emulsification instead of microfluidics and can process millions of cells within minutes.

We developed TACCO, a versatile and efficient computational annotation framework, leveraging growing single-cell and spatial omics data to identify cell types and states, decipher molecular and cellular tissue structure, and resolve differentiation trajectories.