Highly resolved spatial transcriptomics for detection of rare events in cells
Groiss, S.; Pabst, D.; Faber, C.; Meier, A.; Bogdoll, A.; Unger, C.; Nilges, B.; Strauss, S.; Foederl-Hoebenreich, E.; Hardt, M.; Geipel, A.; Reinecke, F.; Korfhage, C.; Zatloukal, K.
Show abstract
Single-cell spatial transcriptomics technologies leveraged the potential to transcriptionally landscape sophisticated reactions in cells. Current methods to delineate such complex interplay lack the flexibility in rapid target adaptation and are particularly restricted in detecting rare transcripts. We developed a multiplex single-cell RNA In-situ hybridization technique, called Molecular Cartography (MC) that can be easily tailored to specific applications and, by providing unprecedented sensitivity, specificity and resolution, is particularly suitable in tracing rare events at a subcellular level. Using a SARS-CoV-2 infection model, MC allows the discernment of single events in host-pathogen interactions, dissects primary from secondary responses, and illustrates differences in antiviral signaling pathways affected by SARS-CoV-2, simultaneously in various cell types.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- Nanopore ReCappable Sequencing maps SARS-CoV-2 5' capping sites and provides new insights into the structure of sgRNAs 96%
- Timed chromatin invasion during mitosis governs prototype foamy virus integration site selection and infectivity 95%
- Visualizing the transcription and replication of influenza A viral RNAs in cells by multiple direct RNA padlock probing and in-situ sequencing (mudRapp-seq) 95%
Similar papers in this journal
- Dual RNA-Seq analysis of SARS-CoV-2 correlates specific human transcriptional response pathways directly to viral expression 95%
- FT-GO: a multiplex fluorescent tyramide signal amplification system for histochemical analysis 95%
- A minimal-complexity light-sheet microscope maps network activity in 3D neuronal systems 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.