RNA is a key molecule in gene expression and its regulation. Therefore, being able to monitor RNA through live-cell imaging would represent an important step toward a better understanding of gene expression regulation. RNA-based fluorogenic modules are extremely promising tools to reach this goal. To this end, two light-up RNA aptamers (Spinach and Mango) display attractive properties but they suffer from a limited brightness. Since previous work in the group demonstrated the possibility to evolve RNA using microfluidic-assisted in vitro compartmentalization (µIVC), this technology appeared to be well suited to improve light-up aptamers properties by an evolution strategy. Therefore, the µIVC procedure was adapted to fluorogenic RNA aptamers to improve their properties (especially the brightness). Finally, using µIVC in tandem with high-throughput sequencing (NGS) allowed further developing the technology into a more integrated and semi-automatized approach in which RNAs and biosensors are selected by µIVC screening and the best variants identified by a bioinformatics process upon NGS analysis. To summarize, this thesis allowed establishing robust µIVC screening workflows for the discovery of novel efficient light-up RNA aptamers as well as metabolites biosensors.