High-throughput sequencing of RNA molecules has enabled the quantitative analysis of gene expression at the expense of storage space and processing power. To alleviate these prob- lems, lossy compression methods of the quality scores associated to RNA sequencing data have recently been proposed, and the evaluation of their impact on downstream analyses is gaining attention. In this context, this work presents a first assessment of the impact of lossily compressed quality scores in RNA sequencing data on the performance of some of the most recent tools used for differential gene expression.