RNA in chromatin organization and nuclear architecture

LINC01559: roles, mechanisms, and clinical implications in human cancers

Long intergenic non-protein coding RNA 1559 (LINC01559), a long non-coding RNA (lncRNA) located on chromosome 12p13.1, plays a critical role in the progression of various cancers. The aberrant expression of LINC01559 significantly impacts multiple biological processes in tumor cells, including cell proliferation, epithelial-mesenchymal transition (EMT), migration, invasion, angiogenesis, and cellular stemness. Notably, the expression levels of LINC01559 correlate with the pathological features and prognosis of several cancers, such as pancreatic, breast, and gastric cancers, and it may serve as a diagnostic marker for non-small cell lung cancer. Moreover, the expression of LINC01559 is regulated by various mechanisms and can influence cancer initiation and progression through a competing endogenous RNA (ceRNA) network, where it interacts with a cohort of eight different microRNAs (miRNAs). Additionally, LINC01559 may directly interact with downstream proteins, thereby promoting their functions or enhancing their stability. LINC01559 is also implicated in key signaling pathways associated with cancer development, including the PI3 K/AKT, RAS, and autophagy signaling pathways. Furthermore, it has been linked to drug resistance in breast cancer and hepatocellular carcinoma. This review provides a comprehensive assessment of the clinical implications of dysregulated LINC01559 expression across various cancer types, highlighting its crucial functions and underlying molecular mechanisms in tumorigenesis. Additionally, we present in-depth discussions and propose hypotheses regarding the functional roles of LINC01559 in cancer pathogenesis, while outlining potential research avenues for future exploration of this molecular target.

Exploring the interplay between enhancer-promoter interactions and transcription

Enhancers in metazoan genomes are known to activate their target genes across both short and long genomic distances. Recent advances in chromosome conformation capture assays and single-cell imaging have shed light on the underlying chromatin contacts and dynamics. Yet the relationship between 3D physical enhancer-promoter (E-P) interactions and transcriptional activation remains unresolved. In this brief review, we discuss recent studies exploring this relationship across scales: from developmental stages to the minutes surrounding transcriptional activation and from the tissue level to single-allele subcellular dynamics. We discuss how seemingly contradictory observations might be reconciled and contribute to a refined causal relationship between E-P interactions and transcription, with mutual influences.

RNA surveillance by the RNA helicase MTR4 determines volume of mouse oocytes

Oocytes are the largest cell type in multicellular animals. Here, we show that mRNA transporter 4 (MTR4) is indispensable for oocyte growth and functions as part of the RNA surveillance mechanism, which is responsible for nuclear waste RNA clearance. MTR4 ensures the normal post-transcriptional processing of maternal RNAs, their nuclear export to the cytoplasm, and the accumulation of properly processed transcripts. Oocytes with Mtr4 knockout fail to accumulate sufficient and normal transcripts in the cytoplasm and cannot grow to normal sizes. MTR4-dependent RNA surveillance has a previously unrecognized function in maintaining a stable nuclear environment for the establishment of non-canonical histone H3 lysine-4 trimethylation and chromatin reorganization, which is necessary to form a nucleolus-like structure in oocytes. In conclusion, MTR4-dependent RNA surveillance activity is a checkpoint that allows oocytes to grow to a normal size, undergo nuclear and cytoplasmic maturation, and acquire developmental competence.

SVM-LncRNAPro: An SVM-Based Method for Predicting Long Noncoding RNA Promoters

Long non-coding RNAs (lncRNAs) are closely associated with the regulation of gene expression, whose promoters play a crucial role in comprehensively understanding lncRNA regulatory mechanisms, functions and their roles in diseases. Due to limitations of the current techniques, accurately identifying lncRNA promoters remains a challenge. To address this challenge, we propose a support vector machine (SVM)-based method for predicting lncRNA promoters, called SVM-LncRNAPro. This method uses position-specific trinucleotide propensity based on single-strand (PSTNPss) to encode the DNA sequences and employs an SVM as the learning algorithm. The SVM-LncRNAPro achieves state-of-the-art performance with reduced complexity. Additionally, experiments demonstrate that this method exhibits a strong generalisation ability. For the convenience of academic research, we have made the source code of SVM-LncRNAPro publicly available. Researchers can download the code and perform the prediction of the lncRNA promoter via the following link: https://github.com/TG0F7/Prom/tree/master.

Exceptionally long-lived nuclear RNAs

RNA labeled in young mice is detected 2 years later in adult mouse brains.