RNA Biology

The Illumina TruSeq Stranded and Illumina Stranded mRNA protocols are commonly used for strand-specific bulk RNA-seq and they typically yield >99% antisense reads. We show that these protocols can generate sense-oriented reads for transcripts with extremely low U content (<3%). Indeed, such regions can bypass the dUTP-based blockade of cDNA second strand amplification. A small number of genes are affected by this issue (three in Drosophila melanogaster, including the glue gene Sgs3, and 46 in Mus musculus). To prevent overestimation of expression levels, we recommend excluding sense reads for all genes.

Transcriptional termination efficiency is considered an important parameter for fine tuning bacterial gene expression. Still, the design principles that determine transcription termination efficiency remain poorly understood. In this study, we aimed to investigate the impact of the 3' untranslated region (3'UTR) on gene expression in Escherichia coli and other bacteria. First, 3'UTR variant sequences were generated, with randomized 30 bp sequences inserted between the STOP-codon and an intrinsic terminator, consisting of a GC-rich hairpin and a downstream poly(U)-tail. Using three reporter genes, it was found that different 3'UTR sequences resulted in an up to five-fold difference in protein production, independent of the upstream coding sequence. The highest protein production was achieved when an adenosine was present directly upstream of the terminator hairpin. This was consolidated by systematic substitution of key nucleotides of the terminator and assessing their effect on mRNA and protein levels. Subsequently, we developed a predictive random forest machine learning model trained on the termination efficiency of different natural and synthetic terminator sequences, revealing an important role for the nucleotides directly upstream of the terminator hairpin. Altogether, this study showed that an additional adenosine nucleotide upstream of the terminator hairpin leads to improved protein production while reducing terminator read-through.

Bacterial small non-coding RNAs (sRNAs) are central post-transcriptional regulators, yet their computational identification suffers from high false-positive rates due to transcriptional noise and the absence of canonical coding features. We developed a three-stage pipeline integrating sRNA prediction (sRNA-Detect), transcription start site mapping (TSSAR, dRNA-seq), and Rho-independent terminator detection (RNIE), applied across nine phylogenetically diverse bacterial species spanning six phyla. Sequential filtering achieved 1.4 to 33 fold precision improvements across nine species, reducing candidate sets by up to 99.6% while recovering known sRNAs at rates reflecting reference database depth (6% recall in S. aureus, 33-34% in E. coli and S. enterica) TSS and RIT constraints constitute universal, genome-size-independent biological filters that substantially enrich sRNA predictions across bacterial diversity. Precision variation across species reflects database incompleteness rather than pipeline failure, with unmatched predictions in poorly annotated organisms representing candidate novel sRNAs rather than false positives. RNA-seq coverage depth provides a reliable secondary indicator of biological relevance, though its interpretation requires accounting for sequencing depth variation across datasets.

Small regulatory RNAs (sRNAs) are key players in bacterial adaptation to stress. They often occupy central positions in regulatory networks and control the expression of multiple targets. In a striking example of this, the enterobacterial OmrA and OmrB paralogous sRNAs are known to regulate about ten different targets, with extensive data suggesting the regulon is in fact much larger. Here we performed transcriptome and proteome analyses and identified more than fifteen new targets of Escherichia coli OmrA and OmrB. We validated several, including genes involved in central carbon metabolism and fatty acid synthesis, among which ppc, actP and fabA. Consistent with a role in carbon metabolism, overproducing OmrA or OmrB inhibited growth on glucose minimal medium. The analysis of suppressor mutants shows that this is due to a decreased carbon flux through the TCA cycle. Incorporating other datasets such as RIL-seq, we generated a multi-omics-based prediction of target candidates. Together, our results show that OmrA/B base-pair to various regions of their mRNA targets, and therefore likely act through diverse regulatory mechanisms. Hence, this work extends the OmrA and OmrB regulons, establishes an unsuspected connection with carbon usage, and shows the benefits of combining global analyses to investigate sRNA regulons.

Small RNAs (sRNAs) rarely cause strong growth phenotypes upon overexpression, complicating efforts to link regulatory interactions to physiological outcomes. Here, we report that high levels of the Escherichia coli sRNA OmrA, but not its sibling OmrB, severely inhibit growth in glucose minimal medium. Genetic, biochemical, and physiological analyses indicate that OmrA-dependent toxicity results from reduced flux through the tricarboxylic acid (TCA) cycle. A UV-based suppressor screen identified mutations in the gene encoding Hfq, the RNA-chaperone that aids sRNA-mRNA interactions. Secondly, three independent mutations clustered in the ribosome-binding site of ppc, encoding phosphoenolpyruvate carboxylase, a key anaplerotic enzyme. OmrA directly inhibits Ppc translation via Hfq-dependent base-pairing in the ppc 5' UTR, including the mutated nucleotides obtained in the genetic screen. OmrA is significantly more effective than OmrB in ppc repression in vivo and in vitro, consistent with sequence divergence in their central regions. Supplementation with glutamate, glutamine, or downstream TCA cycle metabolites fully restores growth, linking reduced Ppc levels to metabolic limitation. These results identify ppc as a physiologically relevant OmrA target and suggest how RNA toxicity can uncover central metabolic nodes used by sRNAs to modulate bacterial physiology.

The most prevalent RNA alteration in the mammalian genome is N-6-methylenediosine (m6A). There is mounting evidence linking dysregulation of m6A regulatory factors and alterations in m6A levels to the development, course, or prognosis of ovarian cancer. Genes having prognostic value were screened using the univariate, multifactorial, and Least Absolute Shrinkage Selection Operator (LASSO) Cox regression analyses. Important genes' m6A expression in clinical material was verified by real-time fluorescent quantitative polymerase chain reaction (RT-qPCR). In present study, all 23 regulators were significantly differentially expressed in ovarian cancer tissues. LASSO regression analysis screened for 10 key genes associ-ated with both autophagy and m6A. A risk score was constructed and nomogram was developed to forecast the prognosis of ovarian cancer patients. Additionally, individuals with ovarian cancer were classified as high-risk or low-risk; and the low-risk group might be more likely to benefit from im-munotherapy. RT-qPCR was used for the bioinformatics study of human ovarian cancer and normal tissues. Lastly, PLK2 and LEPR were confirmed to be associated with tumorigenesis in scRNA-seq. The risk score established by m6A and autophagy can be used to predict prognosis and susceptibility to anticancer drugs in patients with ovarian cancer.

The bacterial three-hybrid (B3H) assay is a powerful genetic tool for detecting interactions between RNA and RNA-binding proteins (RBPs) and assessing the consequences of RBP mutations. This transcription-based system connects the strength of an RNA-protein interaction to the expression of a lacZ reporter gene in Escherichia coli cells. This in vivo approach allows researchers to dissect RNA-protein interactions within a cellular environment, bypassing the need for biochemical purification of RNAs or proteins. This chapter details a three-day protocol for generating quantitative B3H data. Since a significant challenge in B3H assays is RNA misfolding, we describe a recently optimized set of B3H constructs that mitigates this issue by isolating bait RNAs as discrete folding units.

Analysis of RNA-binding proteome data from different bacterial species revealed many cell wall metabolic enzymes cross-linking to RNA in vivo, hinting that these proteins directly bind RNA. Surprisingly, penicillin-binding proteins (PBPs) were also abundantly identified as putative RNA-binding proteins. The cell surface localisation properties of many of these proteins therefore beg the question at what stage of their cellular life cycle these proteins interact with RNA and what the functional significance is. Here, we characterised the RNA-binding activity of PBP2a, the alternative transpeptidase that confers {beta}-lactam resistance in MRSA. Using in vivo RNA-binding assays, we show that PBP2a interacts with hundreds of transcripts without apparent sequence specificity. Computational analyses identified a possible RNA-binding cleft in PBP2a proximal to its active site. Mutation of only two predicted positively charged residues located in this cleft substantially reduced cross-linking in vivo, implying that RNA recognition is largely dictated by RNA backbone interactions. While PBP2a does not regulate RNA steady-state levels, RNA-binding appears important for proper protein function: an RNA-binding deficient mutant exhibits reduced oxacillin resistance. These findings establish PBP2a as an RNA-binding protein in vivo and provide a framework to investigate how this non-canonical interaction may relate to cell wall biogenesis and {beta}-lactam resistance.

Alternative splicing is commonly quantified using the Percent-Spliced-In (PSI) metric, which measures the relative abundances of alternatively spliced isoforms. However, some transcript isoforms are targeted by the nonsense-mediated decay (NMD) pathway, introducing a strong bias that leads to underestimation of their true splicing rates. To correct for this bias, we developed an analytical framework and a set of statistical models employing a linear fractional transformation depending on a single parameter capturing the degradation rate of NMD-sensitive transcripts relative to normal mRNA decay. Using Gaussian mixture models, we demonstrated a clear separation of splicing events into two classes, responders and non-responders, with the former exhibiting strong upregulation upon NMD inhibition and the latter showing little or no response. Moreover, non-responders displayed higher coding potential and stronger translation signals both upstream and downstream of the stop codon, which are characteristic of NMD escape through translational readthrough. We further showed that incorporation of event-specific relative decay rates improves the interpretation of differential splicing patterns for NMD-sensitive transcripts. In sum, our results provide a solid framework for unbiased estimation of splicing metrics in NMD-sensitive transcripts from short-read RNA-seq data, without requiring NMD inhibition experiments.

The zebra mussel (Dreissena polymorpha) is an invasive species that causes extensive economic and ecological damage. Here, we identify and characterize the key components of the small RNA (sRNA) and RNA interference (RNAi) pathways in zebra mussels. Like other mollusks, zebra mussels have extensive microRNA (miRNA) and Piwi-interacting RNA (piRNA) machinery but lack or have modified canonical factors needed to produce small interfering RNA (siRNA). Specifically, the zebra mussel Dicer sequence displays substitutions in the conserved DEAD box motif that is required for substrate processivity, and this organism also lacks some attendant accessory factors such as R2D2. We sequenced the small RNA found in both isolated somatic tissue (adductor muscle) and whole animals (including germline), and identified both conserved and novel miRNA and diverse piRNA sequences, but few endogenous siRNAs. To determine whether their remaining sRNA machinery could still be co-opted to initiate gene silencing, we injected dsRNA targeting several genes into zebra mussel adductor muscle. The injected rpn8-targeting dsRNA reduced rpn8 mRNA levels and was processed into sRNA that resemble endogenous miRNAs and piRNAs. The levels of both sRNA types correlated with mRNA knockdown, suggesting that they may act together to initiate RNAi as seen elsewhere. dsRNA targeting other genes produced variable results suggesting that particular criteria may be needed to trigger an RNAi response in this assay. Our results characterize endogenous sRNA pathways in zebra mussels, establish that dsRNA can induce RNAi, and lay the groundwork for further optimizations to establish RNAi-based genetic manipulation tools for this damaging invasive species.

Interleukin 27 (IL-27) is an anti-HIV cytokine that induces 14 novel microRNAs (miRNAs) in T cells. We previously reported that transfection of two of these miRNA mimics, miRTC10 and miRTC14, differentially induced interferons (IFN)A2, A8, A13, and L1 expression in human primary macrophages. However, the mechanism underlying this activation remains unclear. Here, we show that miRTC14 does not directly target IFN-regulatory genes but instead engages cytosolic RNA-sensing proteins. Using miRNA pull-down coupled with mass spectrometry and immunoblotting, we identified a metabolic enzyme, pyruvate carboxylase (PC) and laboratory of genetics and physiology 2 (LGP2/DHX58) as direct binding partners of miRTC14. Functional analyses revealed that miRTC14 induces IFN expression by more than100-fold (p < 0.001), whereas PC and LGP2 depletion markedly attenuated this response (50-100 fold reduction, p < 0.01). Reconstitution of PC and LGP2 in deficient HEK293 cells restored miRTC14-driven IFN induction. We found that miRTC14-induced IFN activation depends on sequence features at the duplex termini and is unlikely to arise from canonical miRNA-mediated gene silencing. These findings establish PC as a novel miRNA-binding protein and define a previously unrecognized RNA-sensing mechanism by which miRTC14 drives IFN production, linking metabolic enzymes to RNA sequence-dependent innate immunity.

Quantitative PCR (qPCR) depends on reliable quantification cycle (Cq) estimation from amplification curves, which are not always well-behaved. We developed qPCR Guru to provide a complete analysis pipeline including data quality assessment, relative quantification, standard-curve diagnostics, and dual-method Cq evaluation. The latter compares the conventional instrument-derived threshold ("Reported") Cq versus the full-curve five-parameter logistic (5PL) second-derivative-maximum ("Fit") Cq and automatically flags curve-shape abnormalities and disagreement between the two estimates. On high-expressing targets (mRNA and microRNA), the two methods showed strong convergence, confirming general-purpose performance. On low-expressing targets, such as serum microRNA, baseline artifacts and biphasic amplification result in threshold miscalls that standard instrument analysis does not flag. Fit Cq restored replicate-concordant values where Reported Cq split the technical replicates by 17-20 cycles, recovered MIQE-compliant amplification efficiencies lost to biphasic miscalls (from 74% to 102% and 387% to 98%), and lowered within-group variability by 48% and 68% in feline and bovine samples, respectively. Together, these results demonstrate that full-curve estimation, with integrated curve-level diagnostics, strengthens qPCR analyses against threshold miscalls. ARTICLE HIGHLIGHTSO_LIqPCR Guru is a free, browser-based platform that provides a complete analysis pipeline and facilitates side-by-side comparisons of an instruments threshold (Reported) Cq and a full-curve (Fit) Cq, from the five-parameter logistic fitting with second-derivative-maximum (SDM/cpD2). C_LIO_LIFor every well the application automatically flags curve-shape abnormalities and disagreement between the two Cq estimates. C_LIO_LIOn clean, high-expressing mRNA and microRNA targets, the two estimators (Reported Cq and Fit Cq) were strongly concordant and produced equivalent relative quantification with comparable precision. C_LIO_LIIn low-expressing serum microRNA, baseline artifacts and biphasic amplification produced threshold Cq miscalls of up to [~]20 cycles and were detected by curve-shape flags and/or method disagreement. C_LIO_LIThe full-curve Cq estimate recovered replicate-concordant values, restored MIQE-compliant amplification efficiencies, and reduced within-group variability in serum microRNA. C_LI

SARS-CoV-2 nonstructural protein 1 (Nsp1) binds to 40S ribosomal subunits and induces host protein synthesis shut off by inhibiting translation initiation and triggering endonucleolytic cleavage of cellular mRNAs. Irrespective of the mode of initiation, Nsp1-mediated cleavage is induced by the cooperative action of the N-terminal domain of Nsp1, the RRM domain of eIF3g and 40S subunits. Using in vitro reconstitution, we determined that cleavage occurs by transesterification following intramolecular nucleophilic attack of the 2’OH of the ribose on the adjacent phosphodiester bond yielding 5’OH and 2’,3‘-cyclic phosphate termini. Cleavage requires a guanosine ∼10-22 nucleotides from the 5’ end of mRNA, occurs within a narrow window upstream of this G, is most efficient between nucleotides at positions -6/-7 and -7/-8 relative to G, and shows a preference for Pu at positions -7 or -8 which provides the 2’OH for the nucleophilic attack. Zero-length UV cross-linking of Nsp1 to nucleotides at positions -1 and -2 suggests that the critical guanosine may be recognized by Nsp1. Resistance to Nsp1-mediated cleavage of SARS-CoV-2 mRNA was ensured both by the relatively long distance between its G 23 G 24 and the 5’end and by the preceding oligoPy stretch lacking purines at positions -7 or -8 upstream of G 23 G 24 .

During translation initiation, the 40S small ribosomal subunit is recruited to the mRNA 5' cap and scans the 5' untranslated region (UTR) to locate the start codon. While the mechanism of 40S translocation remains elusive, the RNA helicase eIF4A has long been suspected as the primary molecular motor driving 40S scanning. In this study, we utilized GFP reporter mRNAs to investigate the impact of 5' UTR length on translational efficiency. We found that an 8-fold variation in the length of unstructured 5' UTRs did not lead to substantial changes in translation efficiency in wheat germ extract (WGE) and human HEK293T cell lysate. By contrast, the presence of a stable stem-loop in the middle of the 5' UTR significantly reduced cap-dependent translation. These results suggest that mRNA scanning is not rate-limiting when the UTR is devoid of secondary structure. Inhibition of eIF4A by hippuristanol in cell-free protein synthesis systems yielded an equivalent decrease in translation for mRNAs with short and long unstructured 5' UTRs, indicating that eIF4A may be dispensable for 40S scanning. Our data suggest that helicase-independent one-dimensional diffusion may be the primary mechanism enabling 40S movement along the 5' UTR during initiation.

Processing of the precursor ribosomal RNAs (pre-rRNAs) is a key aspect of ribosomal subunit assembly that is closely coordinated with other maturation events. The ribonucleases that mediate pre-rRNA cleavages require regulation to ensure that their activities are exerted in a timely manner. Post-translational modifications can influence protein functions, and although many human ribosome assembly factors are reported to be post-translationally modified, most of these sites remain unconfirmed and functional insights are lacking. Here, we show that NOB1, the PIN domain endoribonuclease responsible for cleavage of the 3' end of the 18S rRNA, is phosphorylated within an evolutionarily conserved acidic tract that can be modified by casein kinase II in vitro. Association of NOB1 with pre-ribosomes is independent of these phosphorylations, and lack of NOB1 phosphorylation only mildly perturbs the efficiency of SSU maturation events upstream of 3' end cleavage of the 18S rRNA. Interestingly, our analyses of pre-rRNA levels in cells depleted of NOB1 or lacking its catalytic activity revealed not only accumulation of the 18SE precursor of the 18S rRNA, but also altered levels of pre-rRNAs containing 5' external transcribed spacer (ETS) sequences (43S, 26S and 30S). This suggests that lack of NOB1-mediated pre-rRNA cleavage impairs recycling of assembly factors required during early biogenesis steps, leading to altered kinetics of 5' ETS processing. Taken together these data provide new insights into the role of NOB1 during SSU biogenesis and the post-translational regulation of this ribonuclease.

RNA molecules form specific 3D structures that facilitate a variety of functions through interactions with other macromolecules. Many RNA viral genomes maintain these structures to interact with and evade host immunity machinery. One such element, the competitive inhibitor RNA (ciRNA), discovered in the protein coding region of the poliovirus serotype 1 (PV1) genome, inhibits a host antiviral protein, ribonuclease L (RNase L). Although some functionally essential structural motifs of the PV1 ciRNA have been studied, the extent of its evolutionary conservation and other structural requirements remained unexplored. Here we combined bioinformatic and biochemical techniques to further define the requirements of a functional ciRNA and assess its phylogenetic distribution. We systematically mutated ciRNA structural features, verifying that ciRNA inhibitory activity requires a conserved loop E motif and a long-range base-pairing interaction, but its peripheral stems are dispensable and in fact a circularly permuted version maintains function. A structure-based homology search identified potential ciRNAs across the Picornaviridae family, but only a subset of those tested were functional - all are in Enterovirus coxsackiepol. When structural features needed for function were transposed from PV1 ciRNA to an RNA unable to inhibit RNase L, the chimeric RNAs did not gain wild-type function, and chemical probing data revealed that these nonfunctional RNAs are unable to form the correct secondary structure. Overall, the dual constraints of encoding a protein and forming a specific functional structure appear to not only limit the sequence diversity, but also the phylogenetic distribution, of ciRNAs.

Non-coding RNAs play diverse roles in a wide range of cellular processes, with their spatial structure being pivotal to their function. RNA secondary structure is a key determinant of its overall fold. Given the scarcity of experimentally determined RNA 3D structures, understanding secondary structure is vital for discerning RNA function. Currently, there is no universally effective solution for de novo RNA secondary structure prediction. Existing methods are becoming increasingly complex without marked improvements in accuracy and often overlook critical features such as pseudoknots and alternative folds. Here, we introduce SQUARNA, a new approach to de novo RNA secondary structure prediction that is suitable for both individual RNA analysis and large-scale structural searches. SQUARNA revisits the concept of base pair maximization and develops it into a stem maximization idea coupled with the widely used free energy minimization (MFE) framework. SQUARNA can predict alternative structures and handle pseudoknots of arbitrary complexity. Benchmarking shows that SQUARNA outperforms existing methods, including deep learning models, in both single-sequence and alignment-based RNA secondary structure prediction. SQUARNA seamlessly integrates sequence and alignment information with experimental data, such as residue reactivities obtained by chemical probing, as well as other structural restraints, including automated searches for Rfam database templates, G-quadruplex patterns, and protein-binding motifs. SQUARNA is available as a standalone tool at https://github.com/febos/SQUARNA and as a web server at https://larnal.imol.institute.

Transposable element-derived long intergenic noncoding RNAs are increasingly recognized as context-dependent regulators of gene expression, but the functional consequences of their ectopic activation in somatic cells remain poorly understood. We previously showed that U7 snRNA represses a subset of LTR12-associated lincRNAs, including lnc-ARRDC4-1 and lnc-ADCYAP1-2, two testis-enriched lincRNAs with minimal expression in somatic cells. Here, we examined the consequences of their increased expression in somatic cells. We showed that overexpression of either lincRNA led to overlapping transcriptomic and proteomic changes, impaired migration, altered adhesion and proliferation, and a [~]50% reduction in protein synthesis. Furthermore, we identified lnc-ARRDC4-1 as an upstream regulator of lnc-ADCYAP1-2 transcription. Downstream of this event, lnc-ADCYAP1-2 interacts with the RNA helicase DHX36, a regulator of G-quadruplex-containing mRNAs. lnc-ADCYAP1-2 activation reduces DHX36 protein levels which is accompanied by decreased protein output from a subset of DHX36 mRNA targets. At the cellular level, these effects correlate with altered cell proliferation, migration, adhesion, and global translation. Our results suggest a lnc-ARRDC4-1: lnc-ADCYAP1-2 : DHX36 regulatory cascade linking de-repression of LTR12-containing lincRNAs to reduced protein synthesis and altered cellular processes in somatic cells.

Various methods have detected miRNA-target interactions via immunoprecipitation of UV-crosslinked Argonaute ribonucleoprotein complexes, followed by intermolecular ligation of bound miRNAs to target strands, forming chimeric RNAs. To date, these methods have relied on conventional viral reverse transcriptases (RTs) to generate cDNAs for sequencing. However, crosslinked RNAs often retain adducts after purification, which can make them poor templates for viral RTs. Here, we adapted OTTR (Ordered Two-Template Relay) techniques to generate cDNAs from Ago2-bound RNAs. OTTR makes use of a modified retroelement-encoded RT, which is strongly processive even on templates with modifications or adducts. We show that this "OTTR-CLASH" method increases the frequency of generating chimeric RNAs compared to previous methods. We also developed an improved bioinformatic pipeline for analysis of these data, and we use this to catalog miRNA-target interactions not previously described in the literature. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=147 HEIGHT=200 SRC="FIGDIR/small/738487v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@13bc276org.highwire.dtl.DTLVardef@5beb41org.highwire.dtl.DTLVardef@b204e5org.highwire.dtl.DTLVardef@15f747d_HPS_FORMAT_FIGEXP M_FIG C_FIG

Premature termination of transcription (PTT), also known as attenuation, is a conserved gene regulatory mechanism that operates across all domains of life and in viruses. Attenuation enables rapid cellular responses to environmental and metabolic changes and fine-tunes expression of biosynthetic genes. In Saccharomyces cerevisiae, attenuation of RNA Polymerase II (Pol II) transcription was first linked to the Nrd1-Nab3-Sen1 (NNS) termination pathway for non-coding RNAs, and the mRNA 3-end processing factor Hrp1 has been implicated more recently. Substitutions in Hrp1 RNA Recognition Motifs (RRMs) cause attenuator readthrough and reduce RNA-binding affinity in vitro, but direct evidence for Hrp1 functioning at attenuators in vivo remains limited. Here, we characterized 5-end RNA terminator elements from several genes, including RAD3, SNG1, MNR2, and CPR8. Readthrough mutations clustered in AU-rich regions resembling polyadenylation site (pA) efficiency elements, consistent with Hrp1 binding targets. Amino acid substitutions of Hrp1 RRM residue F162 revealed a general requirement for aromaticity in RNA recognition that varied to some degree by gene context. To test Hrp1-RNA interactions independent of other yeast factors, we adapted a bacterial 3-hybrid (B3H) assay. Hrp1 interacted with RNA derived from the GAL7 3-end pA site and 5-end terminator regions of RAD3, MNR2, and CPR8. Mutations in AU-rich RNA regions that disrupted Pol II attenuation in yeast generally impaired B3H interactions. However, some Hrp1 mutants (M191T, I270T, D271G, M275V, T280I) retained binding to CPR8 terminator RNA, suggesting their defects require additional yeast components. These results demonstrate that Hrp1 is sufficient to bind multiple UA-rich attenuator RNAs in vivo, expanding Hrp1 function to include early transcription events.