Rattus norvegicus reference genome evaluation for hippocampus RNA-seq data analysis

Abstract Background: One of the first steps of a usual RNA-seq data analysis workflow consists in quantifying gene expression by aligning the sequencing reads to a reference genome and counting the aligned reads in its annotated regions. Downstream analysis, such as the identification of differentially expressed genes, strongly rely on the quality of this process. In addition to the performance of alignment methods, the choice of reference genome, when several of them are available, may strongly impact this step. Results: Here, we propose to evaluate the effect of widely used \Rn reference genomes consisting of Ensembl and RefSeq annotations of the Rnor\_6.0 assembly and the ones based on the mRatBN7.2 genome assembly recently published by RefSeq, on a classical differential expression workflow. We re-analyzed published RNA-seq datasets from different hippocampal subregions and revealed that the Ensembl and Refseq reference genome based on the mRatBN7.2 assembly provide an improvement of read mapping statistics. We showed that the RefSeq annotations of this assembly make gene expression quantification and differentially expressed gene identification more reliable thanks to overall longer exon length in comparison with Ensembl annotations. Moreover, we identified specific biologically relevant results using RefSeq annotations of the new genome assembly. Conclusion: Overall, the biological interpretation of the differential expression analysis of the analyzed datasets may be dramatically impacted by the choice of reference genome. Therefore, we believe that this choice should be more carefully addressed and that our approach could extend to other tissues and species.