Integrative modelling of cellular assemblies

A wide variety of experimental techniques can be used for understanding the precise molecular mechanisms underlying the activities of cellular assemblies. The inherent limitations of a single experimental technique often requires integration of data from complementary approaches to gain sufficient insights into the assembly structure and function. Here, we review popular computational approaches for integrative modelling of cellular assemblies, including protein complexes and genomic assemblies. We provide recent examples of integrative models generated for such assemblies by different experimental techniques, especially including data from 3D electron microscopy (3D-EM) and chromosome conformation capture experiments, respectively. We highlight general concepts in integrative modelling and discuss the need for careful formulation and merging of different types of information

Evaluating RNA Structural Flexibility: Viruses Lead the Way.

Our understanding of RNA structure has lagged behind that of proteins and most other biological polymers, largely because of its ability to adopt multiple, and often very different, functional conformations within a single molecule. Flexibility and multifunctionality appear to be its hallmarks. Conventional biochemical and biophysical techniques all have limitations in solving RNA structure and to address this in recent years we have seen the emergence of a wide diversity of techniques applied to RNA structural analysis and an accompanying appreciation of its ubiquity and versatility. Viral RNA is a particularly productive area to study in that this economy of function within a single molecule admirably suits the minimalist lifestyle of viruses. Here, we review the major techniques that are being used to elucidate RNA conformational flexibility and exemplify how the structure and function are, as in all biology, tightly linked

Methods for comprehensive experimental identification of RNA-protein interactions

The importance of RNA-protein interactions in controlling mRNA regulation and non-coding RNA function is increasingly appreciated. A variety of methods exist to comprehensively define RNA-protein interactions. We describe these methods and the considerations required for designing and interpreting these experiments

CLIP and complementary methods

RNA molecules start assembling into ribonucleoprotein (RNP) complexes during transcription. Dynamic RNP assembly, largely directed by cis-acting elements on the RNA, coordinates all processes in which the RNA is involved. To identify the sites bound by a specific RNA-binding protein on endogenous RNAs, cross-linking and immunoprecipitation (CLIP) and complementary, proximity-based methods have been developed. In this Primer, we discuss the main variants of these protein-centric methods and the strategies for their optimization and quality assessment, as well as RNA-centric methods that identify the protein partners of a specific RNA. We summarize the main challenges of computational CLIP data analysis, how to handle various sources of background and how to identify functionally relevant binding regions. We outline the various applications of CLIP and available databases for data sharing. We discuss the prospect of integrating data obtained by CLIP with complementary methods to gain a comprehensive view of RNP assembly and remodelling, unravel the spatial and temporal dynamics of RNPs in specific cell types and subcellular compartments and understand how defects in RNPs can lead to disease. Finally, we present open questions in the field and give directions for further development and applications

Development of chemical tools for imaging RNA and studying RNA and protein interactions

Tools for study of RNA are divided into two groups: RNA imaging and RNA crosslinking (Chapter 1). RNA imaging denotes visualization of target RNA by labelling it with fluorophores. RNA crosslinking refers to investigating the function of target RNA by capturing bio-macromolecules the RNA interacts with. In consideration of low abundance of some RNAs in living cells, in chapter 2, we have synthesized a new RNA probe based on previously reported aptamers. which reduces background signal to a large extent. We realized imaging of the RNA aptamer in mammalian cells, and the fluorescence obtained from newly constructed probe was apparently brighter.In chapter 3, we developed two psoralen based length tunable crosslinkers (AMT-NHS and AMT dimer) for studying RNA-RNA interactions or RNA-protein interactions. We have synthesized the crosslinkers and verified in vitro experiment that RNA-RNA interactions could be effectively captured by the AMT dimer, and RNA-protein interactions could be effectively tracked by AMT-NHS. In chapter 4, we proved that AMT-NHS could be applied to study RNA-protein interactions in living cells. We also proved that AMT-NHS CLIP is a stable and efficient method for studying RNA-protein interactions, it captured a large portion of interactions that traditional CLIP method may miss.In chapter 5, we have synthesized and incorporated an unnatural photoactivatable amino acid into a protein on a specific site by expanding genetic code, which paves the way to develop a novel and powerful CLIP method to capture more comprehensively RNA-protein interactions

Epitranscriptomic code and its alterations in human disease

Innovations in epitranscriptomics have resulted in the identification of more than 160 RNA modifications to date. These developments, together with the recent discovery of writers, readers, and erasers of modifications occurring across a wide range of RNAs and tissue types, have led to a surge in integrative approaches for transcriptome-wide mapping of modifications and protein-RNA interaction profiles of epitranscriptome players. RNA modification maps and crosstalk between them have begun to elucidate the role of modifications as signaling switches, entertaining the notion of an epitranscriptomic code as a driver of the post-transcriptional fate of RNA. Emerging single-molecule sequencing technologies and development of antibodies specific to various RNA modifications could enable charting of transcript-specific epitranscriptomic marks across cell types and their alterations in disease