Plate IV.81 · Publications

Im-seq: Multimodal droplet barcoding enables high-throughput linking of single-cell imaging and gene expression

Preprint in bioRxiv, 1 September 2025.

PreprintOpen accessResearch area: Single Cell RNA, Gene Expression

Authors

  1. Catherine K Xu
  2. Georg Meisl
  3. Nikita Moshkov
  4. Niklas A Schmacke
  5. Karolis Goda
  6. Alexey Shkarin
  7. Maximilian F Schlögel
  8. Sandra Diebold
  9. Christine Schweitzer
  10. Arif Ekici
  11. Tuomas PJ Knowles
  12. Fabian J Theis
  13. Linas Mazutis
  14. Jochen Guck

Abstract

Understanding sequence-phenotype relationships in biology requires large-scale datasets that provide one-to-one mapping of sequence to phenotype. Here, we address this challenge by introducing multimodal droplet barcoding, enabling individual microfluidic droplets to be tracked across both optical and sequencing measurements. We demonstrate the power of this approach through multimodal single-cell analysis. We pair imaging with gene expression profiling of individual cells, identifying genes that correlate with phenotypic features.

Cite

@misc{xu2025im,
  title = {{Im-seq: Multimodal droplet barcoding enables high-throughput linking of single-cell imaging and gene expression}},
  author = {Xu, Catherine K and Meisl, Georg and Moshkov, Nikita and Schmacke, Niklas A and Goda, Karolis and Shkarin, Alexey and Schlögel, Maximilian F and Diebold, Sandra and Schweitzer, Christine and Ekici, Arif and Knowles, Tuomas PJ and Theis, Fabian J and Mazutis, Linas and Guck, Jochen},
  howpublished = {bioRxiv},
  publisher = {openRxiv},
  year = {2025},
  month = sep,
  doi = {10.1101/2025.09.01.672798},
  url = {https://doi.org/10.1101/2025.09.01.672798},
  note = {Preprint}
}
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