PAL-AI reveals genetic determinants that control poly(A)-tail length during oocyte maturation, with relevance to human fertility.

ABSTRACT: In oocytes of mammals and other animals, gene regulation is mediated primarily through changes in poly(A)-tail length. Here, we introduce PAL-AI, an integrated neural network machine-learning model that accurately predicts tail-length changes in maturing oocytes of frogs and mammals. We show that PAL-AI learned known and previously unknown sequence elements and their contextual features that control poly(A)-tail length, enabling it to predict tail-length changes resulting from 3'-untranslated region single-nucleotide substitutions. It also predicted tail-length-mediated translational changes, allowing us to nominate genes important for oocyte maturation. When comparing predicted tail-length changes in human oocytes with genomic datasets of the All of Us Research Program and gnomAD, we foun

SUBMITTER: Xiang K 

PROVIDER: S-EPMC12316995 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature