Spatial Isoform Profiling within Individual Tissue Sections
Michaela Asp1, Alex Stuckey1, Konstantin Carlberg1, Joel Gruselius2, Sebastian Johansson3, Erik Borgström2, Fredrik Salmén1, Sanja Vickovic1, Max Käller1, Patrik L. Ståhl1, Joakim Lundeberg1
1Division of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Stockholm, Sweden; 2Department of Biosciences and Nutrition, Karolinska Institutet, Stockholm, Sweden; 3Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden
Massively parallel cDNA sequencing has rapidly evolved from the traditional bulk analysis towards both single cell and spatially resolved gene expression analyses within tissue sections. This has broadened our understanding of biological systems, as bulk studies can only provide average measurements of gene activity. Today, individual single cells can be characterized in a high throughput manner and complete transcriptomes can be reconstructed. Spatial transcriptomics captures transcript tags and offers an efficient approach for quantitative gene expression studies, due to retaining spatial information about the tissue context. The tagged approach however restricts deeper investigations concerning alternative splicing, fusion transcripts and possible discoveries of new genes, which typically requires information from the full-length transcript to be present. Here we present a new strategy that allows a global view of spatially resolved full-length transcriptomes by using spatial transcriptomics positionally barcoded microarrays, in combination with full-length transcript information and cDNA sequencing.
Full-length cDNA from individual tissue sections are synthesized directly on the microarray surface based on the Smart-seq2 technology1. Next, full-length cDNA with positional barcodes are released from the surface and amplified in a single pool. The cDNA library is then prepared so that the full-length information is retained when sequencing. By combing the positional barcodes from the microarray with the full-length constructs, we are then able to examine spatially resolved full-length transcripts for the determination of complete transcript structures.
1.Picelli, S. et al. Full-length RNA-seq from single cells using Smart-seq2. Nat. Protoc.9, 171–81 (2014).
Credits: None available.
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