Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Spatial detection of fetal marker genes expressed at low level in adult human heart tissue
KTH, School of Biotechnology (BIO), Gene Technology.
KTH, School of Biotechnology (BIO), Gene Technology.
KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0003-0985-9885
Show others and affiliations
2017 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 7, article id 12941Article in journal (Refereed) Published
Abstract [en]

Heart failure is a major health problem linked to poor quality of life and high mortality rates. Hence, novel biomarkers, such as fetal marker genes with low expression levels, could potentially differentiate disease states in order to improve therapy. In many studies on heart failure, cardiac biopsies have been analyzed as uniform pieces of tissue with bulk techniques, but this homogenization approach can mask medically relevant phenotypes occurring only in isolated parts of the tissue. This study examines such spatial variations within and between regions of cardiac biopsies. In contrast to standard RNA sequencing, this approach provides a spatially resolved transcriptome- and tissue-wide perspective of the adult human heart, and enables detection of fetal marker genes expressed by minor subpopulations of cells within the tissue. Analysis of patients with heart failure, with preserved ejection fraction, demonstrated spatially divergent expression of fetal genes in cardiac biopsies.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP , 2017. Vol. 7, article id 12941
National Category
Genetics
Identifiers
URN: urn:nbn:se:kth:diva-217038DOI: 10.1038/s41598-017-13462-5ISI: 000412781300009PubMedID: 29021611Scopus ID: 2-s2.0-85031126431OAI: oai:DiVA.org:kth-217038DiVA, id: diva2:1154191
Note

QC 20171101

Available from: 2017-11-01 Created: 2017-11-01 Last updated: 2018-10-01Bibliographically 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)
Opponent
Supervisors
Note

QC 20181002

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

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMedScopus

Authority records BETA

Asp, MichaelaVickovic, SanjaLundeberg, Joakim

Search in DiVA

By author/editor
Asp, MichaelaSalmen, FredrikVickovic, SanjaLundeberg, Joakim
By organisation
Gene TechnologyScience for Life Laboratory, SciLifeLab
In the same journal
Scientific Reports
Genetics

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 111 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf