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Spatial Isoform Profiling within Individual Tissue Sections
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.ORCID iD: 0000-0001-5941-7220
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

Spatial Transcriptomics has been shown to be a persuasive RNA sequencing

technology for analyzing cellular heterogeneity within tissue sections. The

technology efficiently captures and barcodes 3’ tags of all polyadenylated

transcripts from a tissue section, and thus provides a powerful platform when

performing quantitative spatial gene expression studies. However, the current

protocol does not recover the full-length information of transcripts, and

consequently lack information regarding alternative splice variants. Here, we

introduce a novel protocol for spatial isoform profiling, using Spatial

Transcriptomics barcoded arrays.

National Category
Biological Sciences
Research subject
Biotechnology
Identifiers
URN: urn:nbn:se:kth:diva-235650OAI: oai:DiVA.org:kth-235650DiVA, id: diva2:1252467
Note

QC 20181002

Available from: 2018-10-01 Created: 2018-10-01 Last updated: 2018-10-02Bibliographically approved
In thesis
1. Spatially Resolved Gene Expression Analysis
Open this publication in new window or tab >>Spatially Resolved Gene Expression Analysis
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Spatially resolved transcriptomics has greatly expanded our knowledge of complex multicellular biological systems. To date, several technologies have been developed that combine gene expression data with information about its spatial tissue context. There is as yet no single spatial method superior to all others, and the existing methods have jointly contributed to progress in this field of technology. Some challenges presented by existing protocols include having a limited number of targets, being labor extensive, being tissue-type dependent and having low throughput or limited resolution. Within the scope of this thesis, many aspects of these challenges have been taken into consideration, resulting in a detailed evaluation of a recently developed spatial transcriptome-wide method. This method, termed Spatial Transcriptomics (ST), enables the spatial location of gene activity to be preserved and visually links it to its histological position and anatomical context. Paper I describes all the details of the experimental protocol, which starts when intact tissue sections are placed on barcoded microarrays and finishes with high throughput sequencing. Here, spatially resolved transcriptome-wide data are obtained from both mouse olfactory bulb and breast cancer samples, demonstrating the broad tissue applicability and robustness of the approach. In Paper II, the ST technology is applied to samples of human adult heart, a tissue type that contains large proportions of fibrous tissue and thus makes RNA extraction substantially more challenging. New protocol strategies are optimized in order to generate spatially resolved transcriptome data from heart failure patients. This demonstrates the advantage of using the technology for the identification of lowly expressed biomarkers that have previously been seen to correlate with disease progression in patients suffering heart failure. Paper III shows that, although the ST technology has limited resolution compared to other techniques, it can be combined with single-cell RNA-sequencing and hence allow the spatial positions of individual cells to be recovered. The combined approach is applied to developing human heart tissue and reveals cellular heterogeneity of distinct compartments within the complete organ. Since the ST technology is based on the sequencing of mRNA tags, Paper IV describes a new version of the method, in which spatially resolved analysis of full-length transcripts is being developed. Exploring the spatial distribution of full-length transcripts in tissues enables further insights into alternative splicing and fusion transcripts and possible discoveries of new genes.  

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2018. p. 40
Series
TRITA-CBH-FOU ; 2018:43
Keywords
RNA, RNA-sequencing, transcriptomics, spatial transcriptomics, single cells
National Category
Engineering and Technology
Research subject
Biotechnology
Identifiers
urn:nbn:se:kth:diva-235652 (URN)978-91-7729-965-3 (ISBN)
Public defence
2018-10-26, Gardaulan, Nobels väg 18, Folkhälsomyndigheten, Solna, 10:00 (English)
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Supervisors
Note

QC 20181002

Available from: 2018-10-02 Created: 2018-10-01 Last updated: 2018-10-02Bibliographically approved

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Authority records BETA

Asp, MichaelaBorgström, ErikStuckey, AlexanderCarlberg, KonstantinAndrusivova, ZanetaSalmén, FredrikKäller, MaxStåhl, PatrikLundeberg, Joakim

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Asp, MichaelaBorgström, ErikStuckey, AlexanderCarlberg, KonstantinAndrusivova, ZanetaSalmén, FredrikKäller, MaxStåhl, PatrikLundeberg, Joakim
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Gene TechnologyScience for Life Laboratory, SciLifeLab
Biological Sciences

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