CCB Colloquium: Joakim Lunderberg

Date & Time

Title: Molecular maps in tissue and disease by data-driven analysis of spatially resolved transcriptomes in situ.

Abstract: RNA-sequencing offers the possibility to analyze the expression of all genes in a sample. However, the spatial information of gene expression is lost. In the pioneering work, a method was described that allowed studies of gene expression in tissue sections using RNA-sequencing to uncover transcriptional patterns in situ (Ståhl et al, Science, 2016). The basic concept is remarkably simple; by placing tissue sections on arrayed reverse transcription oligonucleotides with positional barcodes, cDNA for RNA-sequencing can be generated with maintained positional information within the tissue. The quality of the obtained cDNA libraries is as high as with the best protocols for homogenized tissue. Applying this strategy has been demonstrated to work remarkably well and allows visualizing and quantifying the transcriptome in regular histological tissue sections, i.e. tissue domains can be matched to precise gene expression patterns. Furthermore, data-driven methods can be applied to discover in an unsupervised manner transcriptomic patterns in space. Such patterns correspond to cell-types, microenvironments, or tissue components that allows for novel avenues of research.

About the Speaker

Professor Joakim Lundeberg heads the Department of Gene Technology, KTH Royal Institute of Technology and focus on molecular technology development. His research group is since May 2010 located at the Science for Life Laboratory (SciLifeLab), a national center for molecular biosciences with a focus on health and environmental research. The center combines frontline technical expertise with advanced knowledge of translational medicine and molecular bioscience. The current research focus of JL relates to spatially resolved gene expression studies in situ, Spatial Transcriptomics.

November 5, 2019

Joakim Lunderberg: Molecular maps in tissue and disease by data-driven analysis of spatially resolved transcriptomes in situ.

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