Transcriptome of interstitial cells of Cajal reveals unique and selective gene signatures.
Moon Young LeeSe Eun HaChanjae ParkPaul J ParkRobert FuchsLai WeiBrian G JorgensenDoug RedelmanSean M WardKenton M SandersSeungil RoPublished in: PloS one (2017)
Transcriptome-scale data can reveal essential clues into understanding the underlying molecular mechanisms behind specific cellular functions and biological processes. Transcriptomics is a continually growing field of research utilized in biomarker discovery. The transcriptomic profile of interstitial cells of Cajal (ICC), which serve as slow-wave electrical pacemakers for gastrointestinal (GI) smooth muscle, has yet to be uncovered. Using copGFP-labeled ICC mice and flow cytometry, we isolated ICC populations from the murine small intestine and colon and obtained their transcriptomes. In analyzing the transcriptome, we identified a unique set of ICC-restricted markers including transcription factors, epigenetic enzymes/regulators, growth factors, receptors, protein kinases/phosphatases, and ion channels/transporters. This analysis provides new and unique insights into the cellular and biological functions of ICC in GI physiology. Additionally, we constructed an interactive ICC genome browser (http://med.unr.edu/physio/transcriptome) based on the UCSC genome database. To our knowledge, this is the first online resource that provides a comprehensive library of all known genetic transcripts expressed in primary ICC. Our genome browser offers a new perspective into the alternative expression of genes in ICC and provides a valuable reference for future functional studies.
Keyphrases
- genome wide
- single cell
- dna methylation
- rna seq
- induced apoptosis
- smooth muscle
- copy number
- gene expression
- flow cytometry
- transcription factor
- high throughput
- cell cycle arrest
- healthcare
- oxidative stress
- poor prognosis
- computed tomography
- cell proliferation
- endoplasmic reticulum stress
- type diabetes
- social media
- signaling pathway
- machine learning
- metabolic syndrome
- current status
- adipose tissue
- health information
- deep learning
- emergency department
- wild type