RNA sequencing data from analysing RNA extracted from male mouse aortas taken from Brn-3b/POU4F2 mutants (constitutive) and compared with age and sex-matched, wild-type littermate controls.
Tissue-specific transcription factors (TF) act as important master regulators that control the expression of multiple target genes and thereby control cell fate and function, in a tissue-specific manner. Studies carried out using mutant mice in which the Brn-3b/POU4F2 TF was constitutively deleted (Brn-3b KO mutant mice) show that loss of this transcription factor caused significant morphological and structural changes in blood vessels such as the aorta and this was linked to abnormal contractile function.Therefore, the aim of this study was to identify target genes regulated by the POU4F2 also called Brn 3b transcription factor in controlling vascular integrity and function. This was achieved using RNA sequencing to analyse for genes that were differentially regulated in the aorta of Brn 3b KO mouse mutants in which the Brn-3b gene was constitutively deleted when compared with age- and sex- matched littermate controls.Data from these studies have identified essential roles for the Brn-3b transcription factor in regulating genes associated with calcium signalling, vascular contractility, Sarco endoplasmic reticulum (S/ER) stress and inflammatory genes.Experimental Design:For these studies, highly purified mRNA extracted from 3 Brn-3b KO aortas and wild-type littermate controls were used for RNA-dependent cDNA synthesis and first strand library preparation, prior to sequencing on the Illumina NextSeq 500 instrument (, San Diego, US) using paired end run.De-multiplexed data was converted to Fastq files using Illumina bcl2fastq Conversion Software v2.19, aligned with the reference genome using STAR (v2.5b), deduplicated using Picard Tools v2.7.1) and transcript reads were counted by FeatureCounts (v1.4.6p5).Ensembl ID for each gene was determined using gProfiler and this data was then used for normalisation, modelling and differential expression analysis using the iDEP.93 software platform, which connects multiple R/Bioconductor packages with annotation and pathway databases to provide comprehensive analysis of RNA sequencing data. Principal component analysis identified one outlier WT sample, which was taken into consideration in subsequent analyses as explained in the publication.