Characterising the Transcriptional and Translational Impact of the Schizophrenia-Associated miR-1271-5p in Neuronal Cells

Extension of mRNA poly(A) tails and 3'UTRs during neuronal differentiation exhibits variable association with post-transcriptional dynamics

Differentiation of neural progenitor cells into mature neuronal phenotypes relies on extensive temporospatial coordination of mRNA expression to support the development of functional brain circuitry. Cleavage and polyadenylation of mRNA has tremendous regulatory capacity through the alteration of mRNA stability and modulation of microRNA (miRNA) function, however the extent of utilization in neuronal development is currently unclear. Here, we employed poly(A) tail sequencing, mRNA sequencing, ribosome profiling and small RNA sequencing to explore the functional relationship between mRNA abundance, translation, poly(A) tail length, alternative polyadenylation (APA) and miRNA expression in an in vitro model of neuronal differentiation. Differential analysis revealed a strong bias towards poly(A) tail and 3'UTR lengthening during differentiation, both of which were positively correlated with changes in mRNA abundance, but not translation. Globally, changes in miRNA expression were predominantly associated with mRNA abundance and translation, however several miRNA-mRNA pairings with potential to regulate poly(A) tail length were identified. Furthermore, 3'UTR lengthening was observed to significantly increase the inclusion of non-conserved miRNA binding sites, potentially enhancing the regulatory capacity of these molecules in mature neuronal cells. Together, our findings suggest poly(A) tail length and APA function as part of a rich post-transcriptional regulatory matrix during neuronal differentiation.

Potential diagnostic biomarkers for schizophrenia

Schizophrenia (SCH) is a complex and severe mental disorder with high prevalence, disability, mortality and carries a heavy disease burden, the lifetime prevalence of SCH is around 0.7%-1.0%, which has a profound impact on the individual and society. In the clinical practice of SCH, key problems such as subjective diagnosis, experiential treatment, and poor overall prognosis are still challenging. In recent years, some exciting discoveries have been made in the research on objective biomarkers of SCH, mainly focusing on genetic susceptibility genes, metabolic indicators, immune indices, brain imaging, electrophysiological characteristics. This review aims to summarize the biomarkers that may be used for the prediction and diagnosis of SCH.

Meta-analysis of transcriptional regulatory networks for lipid metabolism in neural cells from schizophrenia patients based on an open-source intelligence approach

There have been a number of reports about the transcriptional regulatory networks in schizophrenia. However, most of these studies were based on a specific transcription factor or a single dataset, an approach that is inadequate to understand the diverse etiology and underlying common characteristics of schizophrenia. Here we reconstructed and compared the transcriptional regulatory network for lipid metabolism enzymes using 15 public transcriptome datasets of neural cells from schizophrenia patients. Since many of the well-known schizophrenia-related SNPs are in enhancers, we reconstructed a network including enhancer-dependent regulation and found that 53.3 % of the total number of edges (7,577 pairs) involved regulation via enhancers. By examining multiple datasets, we found common and unique transcriptional modes of regulation. Furthermore, enrichment analysis of SNPs that were connected with genes in the transcriptional regulatory networks by eQTL suggested an association with hematological cell counts and some other traits/diseases, whose relationship to schizophrenia was either not or insufficiently reported in previous studies. Based on these results, we suggest that in future studies on schizophrenia, information on genotype, comorbidities and hematological cell counts should be included, along with the transcriptome, for a more detailed genetic stratification and mechanistic exploration of schizophrenia.

Molecular Mechanisms of miR-1271 Dysregulation in Human Cancer

MicroRNA is a small noncoding RNA that plays a role in regulating gene expression. miR-1271 is a tumor suppressor microRNA, which is related to the biological changes of many cancers. miR-1271 is considered a biomarker with a potential prognosis and high therapeutic value in tumors. Besides, the expression of miR-1271 is also regulated by many factors. In this study, we summarize the role of miR-1271 in tumors, focusing on the molecular mechanisms of the target genes of miR-1271. Our review will provide a comprehensive understanding of miR-1271 in tumors, as well as ideas for subsequent tumor research related to miR-1271.