This research presents FAScore, a novel machine-learning model designed to identify functional alternative splicing (AS) events during the development of blood cells across various species. By integrating 19 features, including evolutionary conservation, protein structure, and dynamic expression patterns, the study successfully predicts which specific genetic segments are critical for hematopoietic lineage commitment. The authors validated their model by discovering four previously unknown splicing events, specifically highlighting how exon 15 of TBC1D23 is essential for erythropoiesis in both mice and zebrafish. Their findings reveal that skipping this specific exon alters the SUMOylation of HDAC1, a process that ultimately impairs the maturation of red blood cells. Overall, this work establishes a comprehensive computational framework and a research paradigm for studying the functional impact of transcript diversity in complex biological systems.

References:

• Hu X, Wang J, Chen L, et al. The functional landscape of alternative splicing in hematopoietic lineage commitment[J]. Nature Communications, 2026.