5 research outputs found
RNA Framework for Assaying the Structure of RNAs by High-Throughput Sequencing
RNA structure is a key player in regulating a plethora of biological processes. A large part of the functions carried out by RNA is mediated by its structure. To this end, in the last decade big effort has been put in the development of new RNA probing methods based on Next-Generation Sequencing (NGS), aimed at the rapid transcriptome-scale interrogation of RNA structures. In this chapter we describe RNA Framework, the to date most comprehensive toolkit for the analysis of NGS-based RNA structure probing experiments. By using two published datasets, we here illustrate how to use the different components of the RNA Framework and how to choose the analysis parameters according to the experimental setup.</p
A novel SHAPE reagent enables the analysis of RNA structure in living cells with unprecedented accuracy
Due to the mounting evidence that RNA structure plays a critical role in regulating almost any physiological as well as pathological process, being able to accurately define the folding of RNA molecules within living cells has become a crucial need. We introduce here 2-aminopyridine-3-carboxylic acid imidazolide (2A3), as a general probe for the interrogation of RNA structures in vivo. 2A3 shows moderate improvements with respect to the state-of-the-art selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) reagent NAI on naked RNA under in vitro conditions, but it significantly outperforms NAI when probing RNA structure in vivo, particularly in bacteria, underlining its increased ability to permeate biological membranes. When used as a restraint to drive RNA structure prediction, data derived by SHAPE-MaP with 2A3 yields more accurate predictions than NAI-derived data. Due to its extreme efficiency and accuracy, we can anticipate that 2A3 will rapidly take over conventional SHAPE reagents for probing RNA structures both in vitro and in vivo
Analysing shifts in protein structure in relation to drug resistance in Mycobacterium tuberculosis
While the sequencing era has greatly increased the amount of protein sequences, in the eld of protein structure this increase has not occurred, mostly due to the high cost and workload of protein structure determination. This has resulted in a large gap between the amount of protein sequences and protein structures. In the case of TB drug resistance, this combined with the time consuming process of drug phenotype testing is posing a challenge for resolving the global health problem of drug resistant TB. Wehavebuilt SSP, a sequence to structure pipeline that aims to reduce the gap between sequence and structure availability using high throughput in silico protein structure prediction methods to produce protein structures. This is combined with a drug phenotype labeling based on phylogenetic properties of the genomic data. This combination attempts to tackle both the lack of protein structures and time consuming method for drug phenotype testing at the same time. We demonstrate the workings of SSP on two proteins of Mycobacterium tuberculosis. While we show that SSP creates protein structures that are consistent and reliable, the genotype-based labeling does not perform well for predicting drug resistant conveying mutations
RNA Framework for Assaying the Structure of RNAs by High-Throughput Sequencing
RNA structure is a key player in regulating a plethora of biological processes. A large part of the functions carried out by RNA is mediated by its structure. To this end, in the last decade big effort has been put in the development of new RNA probing methods based on Next-Generation Sequencing (NGS), aimed at the rapid transcriptome-scale interrogation of RNA structures. In this chapter we describe RNA Framework, the to date most comprehensive toolkit for the analysis of NGS-based RNA structure probing experiments. By using two published datasets, we here illustrate how to use the different components of the RNA Framework and how to choose the analysis parameters according to the experimental setup