Cellular gene expression varies in different physiological or pathological conditions. Conventional gene expression analysis assumes that each gene produces a single mRNA, which is not accurate. On average, genes express more than three mRNA isoforms. A particular cell type expresses different mRNA isoforms from a specific gene depending on its developmental or differentiation state. Different isoforms encode distinct proteins or noncoding regulatory RNAs, each with its own unique functions. Pathological states also alter the expression of transcript variants, which can either cause a disease or facilitate recovery. Still, the detection of mRNA isoforms or variants is not preferred to avoid complex analyses. As a result, gene expression studies often fail to identify the actual mRNA isoforms or variants associated with pathophysiology. In this article, we summarize the data on mRNA isoforms and disease-associated variants identified in various physiological and pathological conditions. These findings emphasize the importance of detecting mRNA isoforms for a better understanding of physiological or pathological conditions.

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.

We analyzed the transcriptome 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 to postnatal day (PD) 4.5 wildtype ovaries, 17 differentially expressed epigenetic regulators (DEERs), and 23 differentially expressed transcription factors (DETFs) were detected in PD6.5 wildtype ovaries. Subsequently, compared to PD 6.5 wildtype ovaries, 24 DEERs and 68 DETFs were detected in PD8.5 ovaries. Changes in DEERs and DEFTs resulted in 581 differentially expressed downstream genes (DEDGs) in PD6.5 and 920 DEDGs in wildtype PD8.5 ovaries. The DEERs, DETFs, and DEDGs in wildtype ovaries represented primordial follicle activation (PFA) and development of the first-wave follicles because the second-wave follicles remain dormant during this period. However, the changes in DEERs, DETFs, and DEDGs during this postnatal period were markedly different in Erβ ^KO rat ovaries, which suffered from increased PFA in both waves. Compared to 17 DEERs and 23 DETFs in wildtype, 46 DEERs and 55 DETFs were identified in PD 6.5 Erβ ^KO ovaries. The differences were more remarkable in PD 8.5 Erβ ^KO ovaries; compared to 24 DEERS and 68 DETFs in wildtype, only 8 DEERs and 10 DETFs were detected in Erβ ^KO ovaries. Such dysregulation resulted in altered DEDGs in PD 6.5 (581 vs. 744) and in PD8.5 (920 vs. 191) Erβ ^KO ovaries. These findings also suggest that the number of DEDGs depends directly on the numbers of DEERS and DETFs. In addition to the quantitative differences in DEERs and DETFs between the wildtype and Erβ ^KO ovaries, we detected distinct differences in the identities of the regulators. Our observations indicate that 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.

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.