Quantitative Analysis of Wild Type and CTGF-/- Retinal Transcriptomes During Postnatal Vascular Development

Purpose: The goal of this study is to compare the retinal transcriptomes of wild-type and CTGF-/- mice during postnatal development of the retinal vasculature. Results: The results from principal component analysis (PCA) showed a distinguishable gene expression profiling among the samples. The expression level (FPKM value) of known genes and transcripts were calculated using ballgown through the transcript abundances estimated with StringTie. The number of identified genes and transcripts per group was calculated based on the mean of FPKM in group > 0.5. We have identified 24,818 transcripts for 12946 gene count in WT mouse retinas and 24708 transcripts for 12852 gene count in knockout mouse retinas. The significantly enriched GO terms of the differentially expressed genes include those involved in protein, lipid and DNA metabolism, neurogenesis and signal transduction and gene regulation. Overall design: Methods: Retinal mRNA profiles of 7-day-old wild-type (WT) and connective tissue growth factor-deficient (CTGF-/-) mice (obtained using inducible Cre/lox system) were generated by deep sequencing, in triplicate. Total RNA from each sample was enriched by oligo (dT) magnetic beads to remove rRNA. RNA-seq libraries were prepared using KAPA Stranded RNA-Seq Library Prep Kit (Illumina). The completed libraries were qualified with Agilent 2100 Bioanalyzer and quantified by absolute quantification qPCR method. To sequence the libraries on the Illumina HiSeq 4000 instrument, the barcoded libraries were mixed, denatured to single stranded DNA in NaOH, captured on Illumina flow cell, amplified in situ, and subsequently sequenced for 150 cycles for both ends on Illumina HiSeq instrument. Image analysis and base calling were performed using Solexa pipeline v1.8 (Off-Line Base Caller software, v1.8). Sequence quality was examined using the FastQC software. The trimmed reads (trimmed 5', 3'-adaptor bases using cutadapt) were aligned to reference genome using Hisat2 software. The transcript abundance for each sample was estimated with StringTie, and the FPKM value for gene and transcript level was calculated with R package Ballgown. The differentially expressed genes and transcripts were filtered using R package Ballgown. The novel genes and transcripts were predicted from assembled results by comparing to the reference annotation using StringTie and Ballgown, then use CPAT to assess the coding potential of those sequences.