The Nep1 protein is essential for the formation of eukaryotic and archaeal small ribosomal subunits, and it catalyzes the site-directed SAM-dependent methylation of pseudouridine (Ψ) during pre-rRNA processing. It possesses a non-trivial topology, namely, a 31 knot in the active site. Here, we address the issue of seemingly unfeasible deprotonation of Ψ in Nep1 active site by a distant aspartate residue (D101 in S. cerevisiae), using a combination of bioinformatics, computational, and experimental methods. We identified a conserved hydroxyl-containing amino acid (S233 in S. cerevisiae, T198 in A. fulgidus) that may act as a proton-transfer mediator. Molecular dynamics simulations, based on the crystal structure of S. cerevisiae, and on a complex generated by molecular docking in A. fulgidus, confirmed that this amino acid can shuttle protons, however, a water molecule in the active site may also serve this role. Quantum-chemical calculations based on density functional theory and the cluster approach showed that the water-mediated pathway is the most favorable for catalysis. Experimental kinetic and mutational studies reinforce the requirement for the aspartate D101, but not S233. These findings provide insight into the catalytic mechanisms underlying proton transfer over extended distances and comprehensively elucidate the mode of action of Nep1.

Alternative cleavage and polyadenylation (APA), an RNA processing event, occurs in over 70% of human protein-coding genes. APA results in mRNA transcripts with distinct 3\' ends. Most APA occurs within 3\' UTRs, which harbor regulatory elements that can impact mRNA stability, translation, and localization.
APA can be profiled using a number of established computational tools that infer polyadenylation sites from standard, short-read RNA-seq datasets. Here, we benchmarked a number of such tools-TAPAS, QAPA, DaPars2, GETUTR, and APATrap- against 3\'-Seq, a specialized RNA-seq protocol that enriches for reads at the 3\' ends of genes, and Iso-Seq, a Pacific Biosciences (PacBio) single-molecule full-length RNA-seq method in their ability to identify polyadenylation sites and quantify polyadenylation site usage. We demonstrate that 3\'-Seq and Iso-Seq are able to identify and quantify the usage of polyadenylation sites more reliably than computational tools that take short-read RNA-seq as input. However, we find that running one such tool, QAPA, with a set of polyadenylation site annotations derived from small quantities of 3\'-Seq or Iso-Seq can reliably quantify variation in APA across conditions, such asacross genotypes, as demonstrated by the successful mapping of alternative polyadenylation quantitative trait loci (apaQTL).
We envisage that our analyses will shed light on the advantages of studying APA with more specialized sequencing protocols, such as 3\'-Seq or Iso-Seq, and the limitations of studying APA with short-read RNA-seq. We provide a computational pipeline to aid in the identification of polyadenylation sites and quantification of polyadenylation site usages using Iso-Seq data as input.

In all three kingdoms of life, RNA is not only involved in the expression of genetic information, but also carries out extremely diverse cellular functions. This versatility is essentially due to the fact that RNA molecules can exploit the power of base pairing to allow them to fold into a wide variety of structures through which they can perform diverse roles, but also to selectively target and bind to other nucleic acids. This is true in particular for bacterial small regulatory RNAs that act by imperfect base-pairing with target mRNAs, and thereby control their expression through different mechanisms. Here we outline an overview of in vivo and in vitro approaches that are currently used to gain mechanistic insights into how these sRNAs control gene expression in bacteria.

After an RNA is transcribed, it undergoes a variety of processing steps that can change the encoded protein sequence (through alternative splicing and RNA editing), regulate the stability of the RNA, and control subcellular localization, timing, and rate of translation. The recent explosion in genomics techniques has enabled transcriptome-wide profiling of RNA processing in an unbiased manner. However, it has also brought with it both experimental challenges in developing improved methods to probe distinct processing steps, as well as computational challenges in data storage, processing, and analysis tools to enable large-scale interpretation in the genomics era. In this chapter we review experimental techniques and challenges in profiling various aspects of RNA processing, as well as recent efforts to develop analyses integrating multiple data sources and techniques to infer RNA regulatory networks.

SIRT1 is a key protein deacetylase that regulates cellular metabolism through lysine deacetylation on both histones and non-histone proteins. Lysine acetylation is a wide-spread post-translational modification found on many regulatory proteins and it plays an essential role in cell signaling, transcription and metabolism. In mice, SIRT1 has known protective functions during high-fat diet but the acetylome regulated by SIRT1 in adipocytes is not completely understood. Here we conducted acetylome analyses in murine adipocytes treated with small-molecule modulators that inhibit or activate the deacetylase activity of SIRT1. We identified a total of 302 acetylated peptides from 78 proteins in this study. From the list of potential SIRT1 targets, we selected seven candidates and further verified that six of them can be deacetylated by SIRT1 in-vitro. Among them, half of the SIRT1 targets are involved in regulating chromatin structure and the other half is involved in RNA processing. Our results provide a resource for further SIRT1 target validation in fat cells and suggest a potential role of SIRT1 in the regulation of chromatin structure and RNA processing, which may possibly extend to other cell types as well.

Dysregulation of alternative splicing (AS) is one of the molecular hallmarks of cancer, with splicing alteration of numerous genes in cancer patients. However, studying splicing mis-regulation in cancer is complicated by the large noise generated from tissue-specific splicing. To obtain a global picture of cancer-specific splicing, we analyzed transcriptome sequencing data from 1149 patients in The Cancer Genome Atlas project, producing a core set of AS events significantly altered across multiple cancer types. These cancer-specific AS events are highly conserved, are more likely to maintain protein reading frame, and mainly function in cell cycle, cell adhesion/migration, and insulin signaling pathways. Furthermore, these events can serve as new molecular biomarkers to distinguish cancer from normal tissues, to separate cancer subtypes, and to predict patient survival. We also found that most genes whose expression is closely associated with cancer-specific splicing are key regulators of the cell cycle. This study uncovers a common set of cancer-specific AS events altered across multiple cancers, providing mechanistic insight into how splicing is mis-regulated in cancers.