Complex Transcriptional Profiles of the PPP1R12A Gene in Cells of the Circulatory System as Revealed by In Silico Analysis and Reverse Transcription PCR.
Paulo André SaldanhaIsrael Olapeju BolanleTimothy Martin PalmerLeonid Leonidovich NikitenkoFrancisco RiveroPublished in: Cells (2022)
The myosin light chain phosphatase target subunit 1 (MYPT1), encoded by the PPP1R12A gene, is a key component of the myosin light chain phosphatase (MLCP) protein complex. MYPT1 isoforms have been described as products of the cassette-type alternative splicing of exons E13, E14, E22, and E24. Through in silico analysis of the publicly available EST and mRNA databases, we established that PPP1R12A contains 32 exons (6 more than the 26 previously reported), of which 29 are used in 11 protein-coding transcripts. An in silico analysis of publicly available RNAseq data combined with validation by reverse transcription (RT)-PCR allowed us to determine the relative abundance of each transcript in three cell types of the circulatory system where MYPT1 plays important roles: human umbilical vein endothelial cells (HUVEC), human saphenous vein smooth muscle cells (HSVSMC), and platelets. All three cell types express up to 10 transcripts at variable frequencies. HUVECs and HSVSMCs predominantly express the full-length variant (58.3% and 64.3%, respectively) followed by the variant skipping E13 (33.7% and 23.1%, respectively), whereas in platelets the predominant variants are those skipping E14 (51.4%) and E13 (19.9%), followed by the full-length variant (14.4%). Variants including E24 account for 5.4% of transcripts in platelets but are rare (<1%) in HUVECs and HSVSMCs. Complex transcriptional profiles were also found across organs using in silico analysis of RNAseq data from the GTEx project. Our findings provide a platform for future studies investigating the specific (patho)physiological roles of understudied MYPT1 isoforms.
Keyphrases
- endothelial cells
- copy number
- molecular docking
- binding protein
- transcription factor
- single cell
- big data
- electronic health record
- gene expression
- genome wide
- cell therapy
- induced apoptosis
- extracorporeal membrane oxygenation
- protein kinase
- cell cycle arrest
- molecular dynamics simulations
- high glucose
- artificial intelligence
- data analysis
- genome wide identification
- dna methylation
- induced pluripotent stem cells
- current status
- acute coronary syndrome
- microbial community
- coronary artery disease
- antibiotic resistance genes
- deep learning
- cell death
- cell proliferation
- coronary artery bypass