The central dogma of gene expression considers RNA as the carrier of genetic information from DNA to protein. However, it has become more and more clear that RNA plays more important roles than simply being the information carrier. Recently, whole genome transcriptomic analyses have identified large numbers of dynamically expressed long noncoding RNAs (lncRNAs), many of which are involved in a variety of biological functions. Even so, the functions and molecular mechanisms of most lncRNAs still remain elusive. Therefore, it is necessary to develop computational methods to predict the function of lncRNAs in order to accelerate the study of lncRNAs. Here, we review the recent progress in the identification of lncRNAs, the molecular functions and mechanisms of lncRNAs, and the computational methods for predicting the function of lncRNAs.

Cell metabolism is critical for cancer cell transformation and progression. In this study, we have developed a novel method, named Met-express, that integrates a cancer gene co-expression network with the metabolic network to predict key enzyme-coding genes and metabolites in cancer cell metabolism. Met-express successfully identified a group of key enzyme-coding genes and metabolites in lung, leukemia, and breast cancers. Literature reviews suggest that approximately 33-53% of the predicted genes are either known or suggested anti-cancer drug targets, while 22% of the predicted metabolites are known or high-potential drug compounds in therapeutic use. Furthermore, experimental validations prove that 90% of the selected genes and 70% of metabolites demonstrate the significant anti-cancer phenotypes in cancer cells, implying that they may play important roles in cancer metabolism. Therefore, Met-express is a powerful tool for uncovering novel therapeutic biomarkers.

Although miniature CRISPR-Cas12f systems were recently developed, the editing efficacy and targeting range of derived miniature cytosine and adenine base editors (miniCBEs and miniABEs) have not been comprehensively addressed. Moreover, functional miniCBEs have not yet be established. Here we generate various Cas12f-derived miniCBEs and miniABEs with improved editing activities and diversified targeting scopes. We reveal that miniCBEs generated with traditional cytidine deaminases exhibit wide editing windows and high off-targeting effects. To improve the editing signatures of classical CBEs and derived miniCBEs, we engineer TadA deaminase with mutagenesis screening to generate potent miniCBEs with high precision and minimized off-target effects. We show that newly designed miniCBEs and miniABEs are able to correct pathogenic mutations in cell lines and introduce genetic mutations efficiently via adeno-associated virus delivery in the brain in vivo. Together, this study provides alternative strategies for CBE development, expands the toolkits of miniCBEs and miniABEs and offers promising therapeutic tools for clinical applications.