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The spatial landscape of gene expression isoforms in tissue sections
- Publication Year :
- 2020
- Publisher :
- HAL CCSD, 2020.
-
Abstract
- 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 fulllength 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. 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 use of external single cell data allowed to nominate cell types expressing each isoform. Furthermore, SiT identifies differential isoform usage for several major genes implicated in brain function (Snap25, Bin1, Gnas) that we 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.
- Subjects :
- Gene isoform
In situ
0303 health sciences
[SDV]Life Sciences [q-bio]
Context (language use)
Computational biology
Biology
Transcriptome
03 medical and health sciences
0302 clinical medicine
Tissue sections
Gene expression
RNA splicing
Genetics
030217 neurology & neurosurgery
030304 developmental biology
Sequence (medicine)
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....fff08fbaef4cdf2cd9b21123f4c0d539