High-Resolution Mapping of 3' Extremities of RNA Exosome Substrates by 3' RACE-Seq

Current Analytical Strategies for mRNA-Based Therapeutics

Recent advancements in mRNA technology, utilized in vaccines, immunotherapies, protein replacement therapies, and genome editing, have emerged as promising and increasingly viable treatments. The rapid, potent, and transient properties of mRNA-encoded proteins make them attractive tools for the effective treatment of a variety of conditions, ranging from infectious diseases to cancer and single-gene disorders. The capability for rapid and large-scale production of mRNA therapeutics fueled the global response to the COVID-19 pandemic. For effective clinical implementation, it is crucial to deeply characterize and control important mRNA attributes such as purity/integrity, identity, structural quality features, and functionality. This implies the use of powerful and advanced analytical techniques for quality control and characterization of mRNA. Improvements in analytical techniques such as electrophoresis, chromatography, mass spectrometry, sequencing, and functionality assessments have significantly enhanced the quality and detail of information available for product and process characterization, as well as for routine stability and release testing. Here, we review the latest advancements in analytical techniques for the characterization of mRNA-based therapeutics, typically employed by the biopharmaceutical industry for eventual market release.

Multiplexed single-cell characterization of alternative polyadenylation regulators

Most mammalian genes have multiple polyA sites, representing a substantial source of transcript diversity regulated by the cleavage and polyadenylation (CPA) machinery. To better understand how these proteins govern polyA site choice, we introduce CPA-Perturb-seq, a multiplexed perturbation screen dataset of 42 CPA regulators with a 3' scRNA-seq readout that enables transcriptome-wide inference of polyA site usage. We develop a framework to detect perturbation-dependent changes in polyadenylation and characterize modules of co-regulated polyA sites. We find groups of intronic polyA sites regulated by distinct components of the nuclear RNA life cycle, including elongation, splicing, termination, and surveillance. We train and validate a deep neural network (APARENT-Perturb) for tandem polyA site usage, delineating a cis-regulatory code that predicts perturbation response and reveals interactions between regulatory complexes. Our work highlights the potential for multiplexed single-cell perturbation screens to further our understanding of post-transcriptional regulation.

An extensive survey of phytoviral RNA 3' uridylation identifies extreme variations and virus-specific patterns

Viral RNAs can be uridylated in eukaryotic hosts. However, our knowledge of uridylation patterns and roles remains rudimentary for phytoviruses. Here, we report global 3' terminal RNA uridylation profiles for representatives of the main families of positive single-stranded RNA phytoviruses. We detected uridylation in all 47 viral RNAs investigated here, revealing its prevalence. Yet, uridylation levels of viral RNAs varied from 0.2% to 90%. Unexpectedly, most poly(A) tails of grapevine fanleaf virus (GFLV) RNAs, including encapsidated tails, were strictly monouridylated, which corresponds to an unidentified type of viral genomic RNA extremity. This monouridylation appears beneficial for GFLV because it became dominant when plants were infected with nonuridylated GFLV transcripts. We found that GFLV RNA monouridylation is independent of the known terminal uridylyltransferases (TUTases) HEN1 SUPPRESSOR 1 (HESO1) and UTP:RNA URIDYLYLTRANSFERASE 1 (URT1) in Arabidopsis (Arabidopsis thaliana). By contrast, both TUTases can uridylate other viral RNAs like turnip crinkle virus (TCV) and turnip mosaic virus (TuMV) RNAs. Interestingly, TCV and TuMV degradation intermediates were differentially uridylated by HESO1 and URT1. Although the lack of both TUTases did not prevent viral infection, we detected degradation intermediates of TCV RNA at higher levels in an Arabidopsis heso1 urt1 mutant, suggesting that uridylation participates in clearing viral RNA. Collectively, our work unveils an extreme diversity of uridylation patterns across phytoviruses and constitutes a valuable resource to further decipher pro- and antiviral roles of uridylation.

Sequence and thermodynamic characteristics of terminators revealed by FlowSeq and the discrimination of terminators strength

The intrinsic terminator in prokaryotic forms secondary RNA structure and terminates the transcription. However, leaking transcription is common due to varied terminator strength. Besides of the representative hairpin and U-tract structure, detailed sequence and thermodynamic features of terminators were not completely clear, and the effect of terminator on the upstream gene expression was unclearly. Thus, it is still challenging to use terminator to control expression with higher precision. Here, in E. Coli, we firstly determined the effect of the 3′-end sequences including spacer sequences and terminator sequences on the expression of upstream and downstream genes. Secondly, terminator mutation library was constructed, and the thermodynamic and sequence features differing in the termination efficiency were analyzed using the FlowSeq technique. The result showed that under the regulation of terminators, a negative correlation was presented between the expression of upstream and downstream genes (r=−0.60), and the terminators with lower free energy corelated with higher upstream gene expression. Meanwhile, the terminator with longer stem length, more compact loop and perfect U-tract structure was benefit to the transcription termination. Finally, a terminator strength classification model was established, and the verification experiment based on 20 synthetic terminators indicated that the model can distinguish strong and weak terminators to certain extent. The results help to elucidate the role of terminators in gene expression, and the key factors identified are crucial for rational design of terminators, and the model provided a method for terminator strength prediction.