Resolving Conflicting microRNA Target Outcomes: Single-Cell Dual-Transcriptome Profiling of miRNA-Target Pairs

Conflicting results abound regarding whether a given miRNA represses, stabilizes, or sometimes even activates specific targets, as seen in studies like Wardana et al. (2022) and Lou et al. (2018). Bulk assays often obscure cell-to-cell variability and context dependency. Inspired by Liu & Shomron (2022) and Velut et al. (2025), this idea suggests leveraging emerging single-cell co-sequencing platforms to simultaneously measure both miRNA and mRNA in the same cell. By designing experiments that perturb specific miRNAs and then profile the outcomes at single-cell resolution, we can tease apart heterogeneity, buffering effects, and conflicting regulatory outcomes within complex tissues or tumors. This approach could explain paradoxical findings in the literature and inform more precise miRNA-based therapies.

References:

1. MicroRNA Gene Signature for Predicting Mechanisms in Nasopharyngeal Carcinoma: A Case Study on the Potential Application of Circulating Biomarkers.. Tirta Wardana, R. Oktriani, Cita Herawati Murjayanto, D. U. Putri, S. Anwar, T. Aryandono, S. Haryana (2022). MicroRNA.
2. Mechanisms of microRNA-mediated gene regulation in unicellular model alga Chlamydomonas reinhardtii. Sulin Lou, Ting Sun, Hui Li, Zhangli Hu (2018). Biotechnology for Biofuels.
3. Analysis of MicroRNA Regulation and Gene Expression Variability in Single Cell Data. Wendao Liu, N. Shomron (2022). Journal of Personalized Medicine.
4. Benchmarking microRNA Target Prediction Algorithms Using Single-Cell Co-Sequencing Data. Louise Velut, Laura Fancello, Nadia Cherradi, Laurent Guyon (2025). bioRxiv.