Molecular mechanistic studies of long ?noncoding? RNAs in mammalian cell differentiation

Project: Research project

Project Details


PROJECT SUMMARY The goal of this study is to determine the molecular mechanisms by which long ?noncoding? RNAs regulate mammalian cells differentiation. Long noncoding RNAs (lncRNAs), defined as RNAs longer than 200nt without functional protein coding capacity, are emerging regulators of gene expression. Genomic studies revealed that many lncRNAs are differentially expressed in a wide variety of biological processes. Although an increasing number of lncRNAs are observed to play important roles under many physiological and pathological conditions, the molecular mechanisms they use to control gene expression are still unknown for a lot of lncRNAs. Thus, mechanistically characterizing functionally important lncRNAs in mammalian cells is of high significance to both RNA molecular biology and potential usage of these RNAs as diagnostic markers and therapeutic targets. Using the terminal differentiation of erythroid cells as a model, our recent studies revealed that lncRNAs can be classified into bona fide lncRNAs and small-polypeptide-encoding ?lncRNAs? based on their functional association with the cellular translational apparatus, the ribosome. Notably, we observed that lncRNAs from each of these two categories play critical roles in this important cell differentiation process. Thus, we plan to mechanistically dissect how bona fide lncRNAs and small-polypeptide-encoding ?lncRNAs? regulate gene expression in mammalian cell differentiation, respectively. The results from this study will not only fill a fundamental knowledge gap in lncRNA biology, the molecular mechanisms of lncRNAs, but also may potentially provide insights for human diseases, as one of the lncRNAs we will study, Dleu2, is frequently deleted in certain human leukemias.
StatusNot started


  • National Institute of General Medical Sciences: $318,000.00


Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.