Full-length transcriptomic profiling reveals age-associated isoform remodeling and altered coding potential in the mouse ovary.

Abstract

Ovarian aging, marked by a progressive diminution of oocyte quality and quantity, is a major contributor to declining female fertility and age-related reproductive disorders. However, transcript-level changes underlying this process remain incompletely understood. In this study, we applied Oxford Nanopore long-read RNA sequencing to profile full-length transcripts from granulosa cells and oocytes of young (6-8 weeks) and aged (10 months) mice, complemented by Illumina short-read sequencing for orthogonal support. We performed transcript annotation, differential expression analysis, alternative polyadenylation (APA) analysis, and weighted gene co-expression network analysis (WGCNA) to investigate age-associated transcriptomic changes. Comprehensive annotation classified 130,730 high-confidence transcripts, including over 100,000 putative novel isoforms, and revealed that aging was associated with a shift toward isoforms with lower predicted coding potential. Exploratory enrichment analysis suggested that transcripts with lower predicted coding potential were associated with biological processes such as protein synthesis and chromosome segregation. APA analysis identified age-associated 3'UTR shortening. Transcript-level differential expression and isoform-switching analysis uncovered 795 significant switching events across both cell types, frequently associated with predicted open reading frame changes and potential protein-domain loss. Exploratory WGCNA highlighted modules associated with aging and cell-type specificity, including an Esr1-derived hub transcript, TALONT000180938, from a gene previously linked to ovarian function and disease. Many disease-associated genes exhibited cell-type-specific isoform usage, with several novel isoforms undetectable at the gene level. Our results indicate that long-read sequencing improves isoform-level resolution of ovarian transcriptomic diversity and identifies candidate aging-associated transcript alterations that may be relevant to reproductive decline.