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The spatial landscape of gene expression isoforms in tissue sections

In situ capturing technologies add tissue context to gene expression data, with the potential of providing a greater understanding of complex biological systems. However, splicing variants and full-length sequence heterogeneity cannot be characterized at spatial resolution with current transcriptome...

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Autores principales: Lebrigand, Kevin, Bergenstråhle, Joseph, Thrane, Kim, Mollbrink, Annelie, Meletis, Konstantinos, Barbry, Pascal, Waldmann, Rainer, Lundeberg, Joakim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10164556/
https://www.ncbi.nlm.nih.gov/pubmed/36928528
http://dx.doi.org/10.1093/nar/gkad169
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author Lebrigand, Kevin
Bergenstråhle, Joseph
Thrane, Kim
Mollbrink, Annelie
Meletis, Konstantinos
Barbry, Pascal
Waldmann, Rainer
Lundeberg, Joakim
author_facet Lebrigand, Kevin
Bergenstråhle, Joseph
Thrane, Kim
Mollbrink, Annelie
Meletis, Konstantinos
Barbry, Pascal
Waldmann, Rainer
Lundeberg, Joakim
author_sort Lebrigand, Kevin
collection PubMed
description In situ capturing technologies add tissue context to gene expression data, with the potential of providing a greater understanding of complex biological systems. However, splicing variants and full-length sequence heterogeneity cannot be characterized at spatial resolution with current transcriptome profiling methods. To that end, we introduce spatial isoform transcriptomics (SiT), an explorative method for characterizing spatial isoform variation and sequence heterogeneity using long-read sequencing. We show in mouse brain how SiT can be used to profile isoform expression and sequence heterogeneity in different areas of the tissue. SiT reveals regional isoform switching of Plp1 gene between different layers of the olfactory bulb, and the use of external single-cell data allows the nomination of cell types expressing each isoform. Furthermore, SiT identifies differential isoform usage for several major genes implicated in brain function (Snap25, Bin1, Gnas) that are independently validated by in situ sequencing. SiT also provides for the first time an in-depth A-to-I RNA editing map of the adult mouse brain. Data exploration can be performed through an online resource (https://www.isomics.eu), where isoform expression and RNA editing can be visualized in a spatial context.
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spelling pubmed-101645562023-05-08 The spatial landscape of gene expression isoforms in tissue sections Lebrigand, Kevin Bergenstråhle, Joseph Thrane, Kim Mollbrink, Annelie Meletis, Konstantinos Barbry, Pascal Waldmann, Rainer Lundeberg, Joakim Nucleic Acids Res Methods Online In situ capturing technologies add tissue context to gene expression data, with the potential of providing a greater understanding of complex biological systems. However, splicing variants and full-length sequence heterogeneity cannot be characterized at spatial resolution with current transcriptome profiling methods. To that end, we introduce spatial isoform transcriptomics (SiT), an explorative method for characterizing spatial isoform variation and sequence heterogeneity using long-read sequencing. We show in mouse brain how SiT can be used to profile isoform expression and sequence heterogeneity in different areas of the tissue. SiT reveals regional isoform switching of Plp1 gene between different layers of the olfactory bulb, and the use of external single-cell data allows the nomination of cell types expressing each isoform. Furthermore, SiT identifies differential isoform usage for several major genes implicated in brain function (Snap25, Bin1, Gnas) that are independently validated by in situ sequencing. SiT also provides for the first time an in-depth A-to-I RNA editing map of the adult mouse brain. Data exploration can be performed through an online resource (https://www.isomics.eu), where isoform expression and RNA editing can be visualized in a spatial context. Oxford University Press 2023-03-17 /pmc/articles/PMC10164556/ /pubmed/36928528 http://dx.doi.org/10.1093/nar/gkad169 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Methods Online
Lebrigand, Kevin
Bergenstråhle, Joseph
Thrane, Kim
Mollbrink, Annelie
Meletis, Konstantinos
Barbry, Pascal
Waldmann, Rainer
Lundeberg, Joakim
The spatial landscape of gene expression isoforms in tissue sections
title The spatial landscape of gene expression isoforms in tissue sections
title_full The spatial landscape of gene expression isoforms in tissue sections
title_fullStr The spatial landscape of gene expression isoforms in tissue sections
title_full_unstemmed The spatial landscape of gene expression isoforms in tissue sections
title_short The spatial landscape of gene expression isoforms in tissue sections
title_sort spatial landscape of gene expression isoforms in tissue sections
topic Methods Online
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10164556/
https://www.ncbi.nlm.nih.gov/pubmed/36928528
http://dx.doi.org/10.1093/nar/gkad169
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