Predictive modeling of oocyte maternal mRNA features of five mammalian species reveals potential shared and species-restricted regulators during maturation

Oocyte maturation is accompanied by changes in abundances of thousands of mRNAs, many degraded and many preferentially stabilized. mRNA stability can be regulated by diverse features including GC content, codon bias, and motifs within the 3' untranslated region (UTR) interacting with RNA binding proteins (RBPs) and miRNAs. Many studies identified factors participating in mRNA splicing, bulk mRNA storage and translational recruitment in mammalian oocytes, but the roles of potentially hundreds of expressed factors, how they regulate cohorts of thousands of mRNAs, and to what extent their functions are conserved across species has not been determined. We performed an extensive in-silico cross-species analysis of features associated with mRNAs of different stability classes during oocyte maturation (stable, moderately degraded, and highly-degraded) for five mammalian species. Using publicly available RNA sequencing data for GV and MII oocyte transcriptomes, we determined that 3'UTR length and synonymous codon usage are positively associated with stability whilst greater GC content is negatively associated with stability. By applying machine learning and feature selection strategies, we identified RBPs and miRNAs that are predictive of mRNA stability, including some across multiple species and others more species-restricted. The results provide new insight into the mechanisms regulating maternal mRNA stabilization or degradation.