Kevin Vo

Aging in females affects the ovaries before any other organ. This has a significant impact on women’s health. Aging results in the gradual depletion of ovarian follicles and a decline in oocyte quality. Studies have shown that cellular changes within ovaries manifest before the depletion of ovarian follicles. To understand the molecular mechanisms underlying these changes, we conducted a comprehensive analysis of gene expression changes in aging mouse ovaries. When RNA sequencing data from 6-month-old mice were compared to those from 12-month-old mice, we identified numerous differentially expressed genes, as well as transcript variants. Transcript variants arise from alternative transcription start sites (TSSs) and alternative pre-mRNA processing. Therefore, we further analyzed a specific set of regulators for these cellular processes. Our findings indicate that ovarian aging alters the expression of epigenetic regulators (ERs) and transcription factors (TFs) that are involved in alternative TSS usage. Ovarian aging also affects the expression of RNA-binding proteins (RBPs) and spliceosome components (SPs), which are essential for pre-mRNA processing. We noticed that variations in transcript variants were more pronounced than those found through gene expression analysis. While 8% of the known TFs and ERs were differentially expressed at the gene level, this increased to 30% at the transcript variant level. Similarly, 3% of the known RBPs but no known SPs were differentially expressed at the gene level, while this increased to 30% at the transcript variant level. These observations highlight the importance of focusing on transcript variants and their functions in aging research, as they may provide insight into the underlying biological processes involved.

Cellular gene expression varies in different physiological and pathological conditions. Analysis of differential gene expression enables researchers to understand the cellular changes associated with physiological or pathological conditions. During gene expression analyses, researchers calculate the transcripts expressed from a gene under that gene's name, assuming only a single mRNA is expressed by that gene. However, this assumption is biologically inaccurate, but it is often preferred to avoid the complex analyses of isoforms. Most mammalian genes express more than three mRNAs, which encode various proteins or act as noncoding RNAs. We have previously addressed the molecular basis mRNA isoform formation and detection strategies. In this review article, we have discussed the physiological and pathological roles of mRNA isoforms. Any specific cell may express different isoforms of mRNA from a specific gene depending on its differentiation state. Different isoforms can be expressed from a single gene at various stages of development and during aging. The same cell may also express mRNA isoforms related to pathological conditions. Summarized findings highlight the importance of detecting mRNA isoforms over conventional gene identification.

Most eukaryotic genes express more than one mature mRNA, defined as transcript variants. This complex phenomenon arises from various mechanisms, such as using alternative transcription start sites and alternative post-transcriptional processing events. The resulting transcript variants can lead to synthesizing proteins that possess distinct functional domains or may even generate noncoding RNAs, each with unique roles in cellular processes. The generation of these transcript variants is not merely a random occurrence; it is cell-type specific and varies with developmental stages, aging processes, or pathogenesis of diseases. This highlights the biological significance of transcript variants in regulating gene expression and their potential impact on cellular functionality. Despite the biological importance, investigating transcript variants has been hampered by challenges associated with detecting their expression. This review article addresses the advancements in molecular techniques in detecting transcript variants. Traditional methods such as RT-PCR and RT-qPCR can easily detect known transcript variants using primers that target unique exons associated with the variants. Other techniques like RACE-PCR and hybridization-based methods, including Northern blotting, RNase protection assays, and microarrays, have also been utilized to detect transcript variants. Nevertheless, RNA sequencing (RNA-Seq) has emerged as a powerful technique for identifying transcript variants, especially those with previously unknown sequences. The effectiveness of RNA sequencing in transcript variant detection depends on the specific sequencing approach and the precision of data analysis. By understanding the strengths and weaknesses of each laboratory technique, researchers can develop more effective strategies for detecting mRNA transcript variants. This ability will be crucial for our comprehensive understanding of gene regulation and the implications of transcript diversity in various biological contexts.

Gene expression or gene regulation studies often assume one gene expresses one mRNA. However, contrary to the conventional idea, a single gene in mammalian cells can express multiple transcript variants translated into several different proteins. The transcript variants are generated through transcription from alternative start sites and alternative post-transcriptional processing of the precursor mRNA (pre-mRNA). In addition, gene mutations and RNA editing further enhance the diversity of the transcript variants. The transcript variants can encode proteins with various domains, expanding the functional repertoire of a single gene. Some transcript variants may not encode proteins but function as non-coding RNAs and regulate gene expression. The expression level of the transcript variants may vary between cell types or within the same cells under different biological conditions. Transcript variants are characteristic of cell differentiation in a particular tissue, and the variants may play a key role in normal development and aging. Studies also reported that some transcript variants may have roles in disease pathogenesis. The biological significances urge studying the complexity of gene expression at the transcript level. This article updates the molecular basis of transcript variants in mammalian cells, including the formation mechanisms and potential roles in host biology. Gaining insight into the transcript variants will not only identify novel mechanisms of gene regulation but also unravel the role of the variants in health and disease.

We analyzed the transcriptome data of wildtype and estrogen receptor β knockout (Erβ^KO) rat ovaries during the early postnatal period and detected remarkable changes in epigenetic regulators and transcription factors. Compared with postnatal day (PD) 4.5 ovaries, PD 6.5 wildtype ovaries possessed 581 differentially expressed downstream transcripts (DEDTs), including 17 differentially expressed epigenetic regulators (DEERs) and 23 differentially expressed transcription factors (DETFs). Subsequently, compared with PD 6.5 ovaries, PD 8.5 wildtype ovaries showed 920 DEDTs, including 24 DEERs and 68 DETFs. The DEDTs, DEERs, and DETFs in wildtype ovaries represented the gene expression during primordial follicle activation and the gradual development of primary follicles of first-wave origin because the second-wave follicles remained dormant during this developmental period. When we compared the transcriptome data of age-matched Erβ^KO ovaries, we observed that PD 6.5 Erβ^KO ovaries had 744 DEDTs compared with PD 4.5 ovaries, including 46 DEERs and 55 DETFs. The loss of ERβ rapidly activated the primordial follicles of both first- and second-wave origin on PD 6.5 and showed a remarkable increase in DEDTs (744 vs. 581). However, compared with PD 6.5 ovaries, PD 8.5 Erβ^KO ovaries showed only 191 DEDTs, including 8 DEERs and 10 DETFs. This finding suggests that the PD 8.5 Erβ^KO ovaries did not undergo remarkable ovarian follicle activation greater than that had already occurred in PD 6.5 Erβ^KO ovaries. The results also showed that the numbers of DEERs and DETFs were associated with increased changes in DEDTs; the greater the number of DEERs or DETFs, the larger the number of DEDTs. In addition to the quantitative differences in DEERs and DETFs between the wildtype and Erβ^KO ovaries, the differentially expressed regulators showed distinct patterns. We identified that 17 transcripts were tied to follicle assembly, 6 to follicle activation, and 12 to steroidogenesis. Our observations indicate that a loss of ERβ dysregulates the epigenetic regulators and transcription factors in Erβ^KO ovaries, which disrupts the downstream genes in ovarian follicles and increases follicle activation. Further studies are required to clarify if ERβ directly or indirectly regulates DEDTs, including DEERs and DETFs, during the neonatal development of rat ovarian follicles.