ABSTRACT: Purpose: The goal of the present study is to provide an independent assessment of the retinal transcriptome signatures of the C57BL/6J (B6) and DBA/2J (D2) mice and to enhance existing microarray datasets for accurately defining the allelic differences in the BXD recombinant inbred strains. Methods: Retinas from both B6 and D2 mice (3 of each) were used for the RNA-seq analysis. Transcriptome features were examined for both strains. Differentially expressed genes between the 2 strains were identified and bioinformatic analysis was performed to analyze the transcriptome differences between B6 and D2 strains, including Gene ontology (GO) analysis, Phenotype and Reactome enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The RNA-seq data were then directly compared with one of the microarray datasets (DoD Retina Normal Affy MoGene 2.0 ST RMA Gene Level Microarray Database) hosted on GeneNetwork (www.genenetwork.org). Results: RNA-seq provided an in-depth analysis of the transcriptome of the B6 and D2 retina with a total of more than 30,000,000 reads per sample. Over 70% of the reads were uniquely mapped, resulting in a total of 18,100 gene counts for all 6 samples. 1,665 genes were differentially expressed, with 858 of these more highly expressed in B6 and 807 more highly expressed in D2. Several molecular pathways were differentially active between the two strains, including the retinoic acid metabolic process, endoplasmic reticulum lumen, extracellular matrix organization, and PI3K-Akt signaling pathway. The most enriched KEGG pathways were the pentose and glucuronate interconversions pathway, the cytochrome P450 pathway, protein digestion and absorption pathway and the ECM-receptor interaction pathway. Each of these pathways had a more than 4-fold enrichment. The DoD normal retina microarray database provided expression profiling for 26,191 annotated transcripts for B6 mouse, D2 mouse and 53 BXD strains. A total of 13,793 genes in this microarray dataset were comparable to the RNA-seq dataset. For both B6 and D2, the RNA-seq data and microarray data were highly correlated with each other (Pearson's r = 0.780 for B6 and 0.784 for D2). Our results suggest that the microarray dataset can reliably detect differentially expressed genes between the B6 and D2 retinas, with a positive predictive value of 45.6%, and a negative predictive value of 93.6%. Examples of true positive and false positive genes are provided. Conclusions: Retinal transcriptome features of B6 and D2 mouse strains provide a useful reference for a better understanding of the mouse retina. Generally, the microarray database presented on GeneNetwork shows good agreement with the RNA-seq data, while we note that any allelic difference between B6 and D2 should be verified with the latter.