Single Molecule-Based fliFISH Validates Radial and Heterogeneous Gene Expression Patterns in Pancreatic Islet β-Cells.
Fangjia LiDehong HuCailin DieterCharles AnsongLori SusselGalya OrrPublished in: Diabetes (2021)
Single-cell RNA-sequencing (scRNA-Seq) technologies have greatly enhanced our understanding of islet cell transcriptomes and have revealed the existence of β-cell heterogeneity. However, comparison of scRNA-Seq data sets from different groups have highlighted inconsistencies in gene expression patterns, primarily due to variable detection of lower abundance transcripts. Furthermore, such analyses are unable to uncover the spatial organization of heterogeneous gene expression. In this study, we used fluctuation localization imaging-based fluorescence in situ hybridization (fliFISH) to quantify transcripts in single cells in mouse pancreatic islet sections. We compared the expression patterns of Insulin 2 (Ins2) with Mafa and Ucn3, two genes expressed in β-cells as they mature, as well as Rgs4, a factor with variably reported expression in the islet. This approach accurately quantified transcripts across a wide range of expression levels, from single copies to >100 copies/cell in one islet. Importantly, fliFISH allowed evaluation of transcript heterogeneity in the spatial context of an intact islet. These studies confirm the existence of a high degree of heterogeneous gene expression levels within the islet and highlight relative and radial expression patterns that likely reflect distinct β-cell maturation states along the radial axis of the islet.
Keyphrases
- single cell
- gene expression
- rna seq
- poor prognosis
- single molecule
- induced apoptosis
- high throughput
- cell cycle arrest
- high resolution
- type diabetes
- oxidative stress
- cell therapy
- genome wide
- atomic force microscopy
- stem cells
- cell proliferation
- endoplasmic reticulum stress
- signaling pathway
- adipose tissue
- skeletal muscle
- mesenchymal stem cells
- mass spectrometry
- cell death
- weight loss
- sensitive detection
- photodynamic therapy
- microbial community
- insulin resistance
- data analysis
- real time pcr