Transcriptomic profiling of Phactr1 overexpression in human endothelial cells

Phactr-1 is an actin and protein phosphatase 1 (PP1) binding protein which is reported to be highly expressed in brain and controls PP1 activity and F-actin remodelling. Genome-wide association studies (GWASs) implicate the Phactr-1 locus (6p24) as a risk factor for five vascular diseases, including coronary artery disease, migraine headache, cervical artery dissection, fibromuscular dysplasia, and hypertension, with its mechanism of action being incompletely understood. To depict how Phactr1 regulates endothelial cell function, we performed transcriptomic profiling of human umbilical vein endothelial cells (HUVECs) infected with Phactr1 adenovirus. We documented that Phactr1 overexpression triggers multiple aspects of endothelial dysfunction, thus providing a mechanistic basis for Phactr1 mediated disease-relevant vascular functions. Human umbilical vein endothelial cells (HUVECs) were seeded in 0.1% gelatin-coated dishes the day before experiment. The next day, cells were treated with Phactr1 Adenovirus (2.5×10E10 pfu/ml, WZ Biosciences) or control adenovirus for 24 hours. After treatment, total RNA was isolated using the RNA-Easy Mini Plus kit (QIAGEN). RNA libraries were prepared for sequencing using rRNA Removal Library Construction Protocol. Briefly, take a certain amount of total RNA samples, and remove rRNA by using RNase H or Ribo-Zero method, then fragment the RNA. Obtain the first and second strands of cDNA by reverse transcription. Then add adapters at both ends of the cDNA for PCR amplification to obtain the cDNA library. The library was amplified with phi29 to make DNA nanoball (DNB) which have more than 300 copies of one molecular. The DNBs were load into the patterned nanoarray and single end 50 (pair end 100) bases reads were generated in the way of combinatorial Probe-Anchor Synthesis (cPAS). The sequencing data was filtered with SOAPnuke (v1.5.2), afterwards clean reads were obtained and stored in FASTQ format. The clean reads were mapped to the reference genome using HISAT2 (v2.0.4). Bowtie2 (v2.2.5) was applied to align the clean reads to the gene set, a database built by BGI (Beijing Genomic Institute in ShenZhen), then expression level of gene was calculated by RSEM (v1.2.12).