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Nucleotide recoding RNA sequencing methods (NR-seq; TimeLapse-seq, SLAM-seq, TUC-seq, etc.) are powerful approaches for assaying transcript population dynamics. In addition, these methods have been extended to probe a host of regulated steps in the RNA life cycle. Current bioinformatic tools significantly constrain analyses of NR-seq data. To address this limitation, we developed EZbakR, an R package to facilitate a more comprehensive set of NR-seq analyses, and fastq2EZbakR, a Snakemake pipeline for flexible preprocessing of NR-seq datasets, collectively referred to as the EZbakR suite. Together, these tools generalize many aspects of the NR-seq analysis workflow. The fastq2EZbakR pipeline can assign reads to a diverse set of genomic features (e.g., genes, exons, splice junctions, etc.), and EZbakR can perform analyses on any combination of these features. EZbakR extends standard NR-seq mutational modeling to support multi-label analyses (e.g., s 4 U and s 6 G dual labeling), and implements an improved hierarchical model to better account for transcript-to-transcript variance in metabolic label incorporation. EZbakR also generalizes dynamical systems modeling of NR-seq data to support analyses of premature mRNA processing and flow between subcellular compartments. Finally, EZbakR implements flexible and well-powered comparative analyses of all estimated parameters via design matrix-specified generalized linear modeling. The EZbakR suite will thus allow researchers to make full, effective use of NR-seq data.

Human pre-mRNA splicing is primarily catalyzed by the major spliceosome, comprising five small nuclear ribonucleoprotein complexes, U1, U2, U4, U5, and U6 snRNPs, each of which contains the corresponding U-rich snRNA. These snRNAs are encoded by large gene families exhibiting significant sequence variation, but it remains unknown if most human snRNA genes are untranscribed pseudogenes or produce variant snRNAs with the potential to differentially influence splicing. Since gene duplication and variation are powerful mechanisms of evolutionary adaptation, we sought to address this knowledge gap by systematically profiling human U1, U2, U4, and U5 snRNA variant gene transcripts. We identified 55 transcripts that are detectably expressed in human cells, 38 of which incorporate into snRNPs and spliceosomes in 293T cells. All U1 snRNA variants are more than 1000-fold less abundant in spliceosomes than the canonical U1, whereas at least 1% of spliceosomes contain a variant of U2 or U4. In contrast, eight U5 snRNA sequence variants occupy spliceosomes at levels of 1% to 46%. Furthermore, snRNA variants display distinct expression patterns across five human cell lines and adult and fetal tissues. Different RNA degradation rates contribute to the diverse steady state levels of snRNA variants. Our findings suggest that variant spliceosomes containing noncanonical snRNAs may contribute to different tissue- and cell-type-specific alternative splicing patterns., (© 2021 Mabin et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.)

In eukaryotic cells, proteins that associate with RNA regulate its activity to control cellular function. To fully illuminate the basis of RNA function, it is essential to identify such RNA-associated proteins, their mode of action on RNA, and their preferred RNA targets and binding sites. By analyzing catalogs of human RNA-associated proteins defined by ultraviolet light (UV)-dependent and -independent approaches, we classify these proteins into two major groups: (i) the widely recognized RNA binding proteins (RBPs), which bind RNA directly and UV-crosslink efficiently to RNA, and (ii) a new group of RBP-associated factors (RAFs), which bind RNA indirectly via RBPs and UV-crosslink poorly to RNA. As the UV crosslinking and immunoprecipitation followed by sequencing (CLIP-seq) approach will be unsuitable to identify binding sites of RAFs, we show that formaldehyde crosslinking stabilizes RAFs within ribonucleoproteins to allow for their immunoprecipitation under stringent conditions. Using an RBP (CASC3) and an RAF (RNPS1) within the exon junction complex (EJC) as examples, we show that formaldehyde crosslinking combined with RNA immunoprecipitation in tandem followed by sequencing (xRIPiT-seq) far exceeds CLIP-seq to identify binding sites of RNPS1. xRIPiT-seq reveals that RNPS1 occupancy is increased on exons immediately upstream of strong recursively spliced exons, which depend on the EJC for their inclusion., (© 2020 Patton et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.)

The exon junction complex (EJC) deposited upstream of mRNA exon junctions shapes structure, composition, and fate of spliced mRNA ribonucleoprotein particles (mRNPs). To achieve this, the EJC core nucleates assembly of a dynamic shell of peripheral proteins that function in diverse post-transcriptional processes. To illuminate consequences of EJC composition change, we purified EJCs from human cells via peripheral proteins RNPS1 and CASC3. We show that the EJC originates as an SR-rich mega-dalton-sized RNP that contains RNPS1 but lacks CASC3. Sometime before or during translation, the EJC undergoes compositional and structural remodeling into an SR-devoid monomeric complex that contains CASC3. Surprisingly, RNPS1 is important for nonsense-mediated mRNA decay (NMD) in general, whereas CASC3 is needed for NMD of only select mRNAs. The switch to CASC3-EJC slows down NMD. Overall, the EJC compositional switch dramatically alters mRNP structure and specifies two distinct phases of EJC-dependent NMD., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

Argonaute proteins (AGOs) are loaded with small RNAs as guides to recognize target mRNAs. Since the target specificity heavily depends on the base complementarity between two strands, it is important to identify small guide and long target RNAs bound to AGOs. For this purpose, next-generation sequencing (NGS) technologies have extended our appreciation truly to the nucleotide level. However, the identification of RNAs via NGS from scarce RNA samples remains a challenge. Further, most commercial and published methods are compatible with either small RNAs or long RNAs, but are not equally applicable to both. Therefore, a single method that yields quantitative, bias-free NGS libraries to identify small and long RNAs from low levels of input will be of wide interest. Here, we introduce such a procedure that is based on several modifications of two published protocols and allows robust, sensitive, and reproducible cloning and sequencing of small amounts of RNAs of variable lengths. The method was applied to the identification of small RNAs bound to a purified eukaryotic AGO. Following ligation of a DNA adapter to RNA 3'-end, the key feature of this method is to use the adapter for priming reverse transcription (RT) wherein biotinylated deoxyribonucleotides specifically incorporated into the extended complementary DNA. Such RT products are enriched on streptavidin beads, circularized while immobilized on beads and directly used for PCR amplification. We provide a stepwise guide to generate RNA-Seq libraries, their purification, quantification, validation, and preparation for next-generation sequencing. We also provide basic steps in post-NGS data analyses using Galaxy, an open-source, web-based platform.

During messenger RNA (mRNA) biogenesis and processing in the nucleus, many proteins are imprinted on mRNAs assembling them into messenger ribonucleoproteins (mRNPs). Some of these proteins remain stably bound within mRNPs and have a long-lasting impact on their fate. One of the best-studied examples is the exon junction complex (EJC), a multiprotein complex deposited primarily 24 nucleotides upstream of exon-exon junctions as a consequence of pre-mRNA splicing. The EJC maintains a stable, sequence-independent, hold on the mRNA until its removal during translation in the cytoplasm. Acting as a molecular shepherd, the EJC travels with mRNA across the cellular landscape coupling pre-mRNA splicing to downstream, posttranscriptional processes such as mRNA export, mRNA localization, translation, and nonsense-mediated mRNA decay (NMD). In this review, we discuss our current understanding of the EJC's functions during these processes, and expound its newly discovered functions (e.g., pre-mRNA splicing). Another focal point is the recently unveiled in vivo EJC interactome, which has shed new light on the EJC's location on the spliced RNAs and its intimate relationship with other mRNP components. We summarize new strides being made in connecting the EJC's molecular function with phenotypes, informed by studies of human disorders and model organisms. The progress toward understanding EJC functions has revealed, in its wake, even more questions, which are discussed throughout. WIREs RNA 2017, 8:e1411. doi: 10.1002/wrna.1411 For further resources related to this article, please visit the WIREs website., (© 2016 Wiley Periodicals, Inc.)

Cytochrome P450 enzymes are hemeproteins that catalyze the monooxygenation of a wide-range of structurally diverse substrates of endogenous and exogenous origin. These heme monooxygenases receive electrons from NADH/NADPH via electron transfer proteins. The cytochrome P450 enzymes, which constitute a diverse superfamily of more than 8,700 proteins, share a common tertiary fold but < 25% sequence identity. Based on their electron transfer protein partner, cytochrome P450 proteins are classified into six broad classes. Traditional methods of pro are based on the canonical paradigm that attributes proteins' function to their three-dimensional structure, which is determined by their primary structure that is the amino acid sequence. It is increasingly recognized that protein dynamics play an important role in molecular recognition and catalytic activity. As the mobility of a protein is an intrinsic property that is encrypted in its primary structure, we examined if different classes of cytochrome P450 enzymes display any unique patterns of intrinsic mobility. Normal mode analysis was performed to characterize the intrinsic dynamics of five classes of cytochrome P450 proteins. The present study revealed that cytochrome P450 enzymes share a strong dynamic similarity (root mean squared inner product > 55% and Bhattacharyya coefficient > 80%), despite the low sequence identity (< 25%) and sequence similarity (< 50%) across the cytochrome P450 superfamily. Noticeable differences in Cα atom fluctuations of structural elements responsible for substrate binding were noticed. These differences in residue fluctuations might be crucial for substrate selectivity in these enzymes., (© 2015 The Protein Society.)