RNA

Regulation of RNA pools allows for adaptation to changing environments and stress, which is especially important in pathogenic bacteria such as Mycobacterium tuberculosis. RNA degradation is a significant contributor to RNA abundance, and Ribonuclease (RNase) E has a rate-limiting role in degradation of a majority of mycobacterial transcripts. However, many open questions remain about the RNA substrate requirements and specificities for efficient cleavage by mycobacterial RNase E. Here, using both Mycolicibacterium smegmatis and M. tuberculosis RNase E, we demonstrate that this enzyme is only active on substrates with a minimum length of approximately 27 nt. Furthermore, we show that mycobacterial RNase E prefers substrates with 5 monophosphates rather than 5 triphosphates, and that the positions of cleavage events within substrates are dictated by both sequence and distance from the RNA ends. Our results also suggest that RNase E may be affected by product inhibition. Finally, we show that M. smegmatis RNase E behaves similarly to M. tuberculosis RNase E, validating the use of this model organism for RNA degradation studies.

CASP16 provided a community-wide benchmark for assessing RNA structure prediction, including the first large-scale blind assessment of RNA-RNA multimer prediction. The results showed that achieving high atomic precision remains a major challenge across the field. In this work, we use the performance of our group (LCBio) as a diagnostic case study to examine the current limits of RNA structure prediction. Our workflow ranked first in the RNA multimer category and remained competitive for monomers. We combine hierarchical analysis with representative case studies to identify a pattern of predictive breakdown, in which modeling fidelity degrades from reliable local features to increasingly speculative global architectures. Multi-helix junctions appear to mark a major transition boundary where 2D topological success often fails to translate into 3D geometric realism, leading to cascading errors in global architecture. This hierarchical breakdown is especially pronounced in RNA multimers, where limitations in the recovery of junction geometry and tertiary interactions propagate directly into errors in higher-order assembly, making multimer prediction increasingly speculative. By placing benchmark performance in a direct structural context, this case study helps define the current limits of RNA structure prediction and highlights priorities for improving predictive accuracy. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/720187v2_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@1c3fe1aorg.highwire.dtl.DTLVardef@5f80beorg.highwire.dtl.DTLVardef@1fd5e0aorg.highwire.dtl.DTLVardef@128f708_HPS_FORMAT_FIGEXP M_FIG C_FIG Key PointsO_LIRNA structure prediction in CASP16 shows a hierarchical decline in accuracy, from relatively reliable local secondary structure to increasingly uncertain global architecture and multimer assembly. C_LIO_LIPrediction accuracy declines markedly at the level of multi-helix junctions, where correct 2D topology often does not translate into realistic 3D geometry. C_LIO_LINon-canonical interactions, stacking geometry, and specialized tertiary motifs remain major sources of error in current RNA modeling pipelines. C_LIO_LIHigh relative performance in RNA-RNA multimer prediction can be achieved despite limited atomic accuracy, highlighting the importance of expert-guided assembly and model curation. C_LIO_LIMany current multimer models are better interpreted as coarse-grained organizational hypotheses than as precise atomic structures. C_LI

Escherichia coli YicC enzyme is the founding member of a family of endoribonucleases that is encoded in virtually all bacterial species. Previous structural studies revealed that this ribonuclease binds RNA by a novel mechanism in which the hexameric apoprotein presents an open channel that undergoes a large rotation upon RNA binding and clamps down on the RNA. The current study follows up on these findings by examining the cleavage of various oligonucleotide substrates designed to probe recognition elements required for YicC binding and cleavage. A 26-nucleotide RNA oligomer (oligo), with a KD in the low micromolar range, was the standard to which numerous oligos with altered sequence were compared. In vitro RNase assays and fluorescence anisotropy binding measurements indicated that the preferred substrates for YicC were relatively small RNAs that contain some secondary structure. Larger RNAs or highly structured RNAs were less-than-optimal substrates. Similarly, RyhB RNA, a [~]90-nucleotide, iron-responsive RNA of E. coli, which has been described as a target of YicC binding and/or cleavage, was a poor YicC substrate in our assays. These results suggest that the native substrates for YicC-family members are very small RNAs or RNA fragments derived from larger RNAs.

Nearest neighbor parameters are widely used in software for estimating the conformational stability of an RNA sequence folding into a specific structure. Folding stability for RNA with canonical nucleotides A, C, G, and U has been widely studied, but the same is not true for most modified nucleotides. In this work, we present a comprehensive set of nearest neighbor parameters for estimating the folding stability of RNA including pseudouridine in helical or loop contexts. These parameters are derived from 210 optical melting experiments involving helices with pseudouridine-A and pseudouridine-G pairs and with pseudouridine in loop motifs. The experiments include sequences with pseudouridine and U in the same strand, including U-A and U-G pairs, allowing us to consider the folding stability of sequences with both U and pseudouridine. On average, pseudouridine stabilizes RNA folding compared to U in an analogous motif, although this effect is sequence-context dependent. These parameters improve the modeling of folding stability for RNA secondary structures containing pseudouridine. We demonstrate that these parameters successfully model the secondary structure change for Saccharomyces cerevisiae U2 snRNA when two additional inducible pseudouridines are present. These parameters are freely available and incorporated into the RNAstructure software package. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/725682v1_ufig1.gif" ALT="Figure 1"> View larger version (14K): org.highwire.dtl.DTLVardef@e1167aorg.highwire.dtl.DTLVardef@18ac7f0org.highwire.dtl.DTLVardef@4c909eorg.highwire.dtl.DTLVardef@aa8bca_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundSmall non-coding RNAs (sncRNAs) play central roles in post-transcriptional gene regulation. In addition to canonical microRNAs (miRNAs), fragments derived from vault RNAs (vtRNAs), called small vault RNAs (svtRNAs), have been reported in human cells. However, the absence of a standardized annotation framework has hindered their systematic detection, quantification, and comparison across small RNA sequencing (small RNA-seq) studies. MethodsWe developed an expression-based annotation strategy to identify svtRNAs from human small RNA-seq datasets. Using FlaiMapper followed by structure and expression-based filtering, we generated two annotation sets: a stringent "miRNA-like" set enriched in Argonaute-associated datasets, and (ii) a broader "Total" set derived from total small RNA-seq libraries under relaxed structural constraints. We explored the expression of the annotated svtRNAs across the different datasets analyzed: multiple normal and tumor-derived human cell lines, including Argonaute immunoprecipitation datasets. ResultsWe identified a repertoire of svtRNAs that are detected across independent datasets and, in several cases, reach abundance levels comparable to canonical miRNAs. Several highly abundant svtRNAs correspond to molecules with experimental validation from prior studies, supporting the robustness of our annotation strategy. Importantly, the same "dominant" (in terms of gene expression) svtRNAs emerged independently from Argonaute-associated and total small RNA datasets, supporting the idea of enzymatically consistent, reproducible svtRNA processing. We further identified svtRNAs derived from distinct vtRNA precursors that could share identical seed sequences, suggesting the possibility of svtRNA families with potential miRNA-like regulatory properties. We provide a standardized annotation that enables reproducible svtRNA quantification. ConclusionsOur study establishes a comprehensive expression-based annotation resource for human svtRNAs. By enabling their systematic detection and reproducible quantification, we show that svtRNAs appear to represent an abundant component of the human small RNA landscape.

Pre-mRNA splicing is an essential step in eukaryotic gene expression during which spliceosomes remove introns from nascent RNAs while ligating the adjacent exons. Spliceosomes are cellular nanomachines composed of five small nuclear (snRNA) components and dozens of proteins, most of which are highly conserved. Despite the high conservation of many splicing factors between S. cerevisiae and H. sapiens, several protein components of the S. cerevisiae spliceosome are not essential for growth under normal laboratory conditions. This is particularly surprising for nonessential factors whose conserved domains contact the spliceosomes catalytic core. Uncovering a function for these splicing factors can be challenging since they are not required for viability, may engage in functionally redundant interactions, and may display only weak phenotypes in the absence of secondary mutations in other spliceosome components. One such nonessential factor is the Cwc15 protein. Cwc15s highly conserved N-terminus directly contacts the U2/U6 di-snRNA within the spliceosome catalytic core; yet its precise role in splicing has not been defined in any organism. In this work, we use molecular genetics in S. cerevisiae combined with splicing reporter assays to study Cwc15p function. We propose that Cwc15p not only promotes active site stability during 5 splice site cleavage but also impacts structural transitions into and out of this spliceosome conformation. This function may be critical for splicing in S. cerevisiae under nonoptimal conditions, facilitating use of weak or alternate splice sites, and could have implications for proofreading of spliceosome active site formation. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=146 SRC="FIGDIR/small/713263v1_ufig1.gif" ALT="Figure 1"> View larger version (74K): org.highwire.dtl.DTLVardef@b296c5org.highwire.dtl.DTLVardef@c87b91org.highwire.dtl.DTLVardef@287011org.highwire.dtl.DTLVardef@d59741_HPS_FORMAT_FIGEXP M_FIG C_FIG Article SummaryPre-mRNA splicing is carried out by large macromolecular machines called spliceosomes which are composed of several snRNAs and dozens of proteins. Despite decades of study, the functions of many splicing factors such as S. cerevisiae Cwc15p remain unknown. Cwc15p is highly conserved among eukaryotes and directly contacts the spliceosome catalytic core. Here, we have used genetic and splicing reporter assays to study the function of Cwc15p during splicing in vivo. We propose that Cwc15p both stabilizes the spliceosome active site during 5 splice site cleavage and impacts remodeling of that site.

RNA thermometers (RNATs) are temperature-responsive structures in 5' untranslated regions (UTRs) of bacterial messenger RNA (mRNA) that control translation by modulating ribosome access. The Listeria monocytogenes prfA RNAT represses translation of PrfA (positive regulatory factor A), the master virulence regulator, at ambient temperature and activates it near the human host temperature ([~]37 {degrees}C) by modulating ribosome binding site (RBS) accessibility. However, the prfA RNAT shares no homology with known RNAT classes, and its unfolding mechanism remains unclear. Here, we used analytical ultracentrifugation and single-molecule kinetic analysis of RNA transient structure (SiM-KARTS) to map prfA RNAT unfolding. SiM-KARTS analysis demonstrates that thermal opening occurs predominantly at the RBS, while the upper helix of the RNAT hairpin remains largely folded at 37 {degrees}C. The RBS binding kinetics increases with temperature in parallel with translation output, establishing a quantitative link between structural unfolding and function. Mutations in the upper helix impair thermal regulation, indicating that this region tunes switching even as it stays structured at host temperature. Together, these data reveal a hierarchical unfolding pathway in which initial RBS opening triggers activation, whereas the upper helix remotely tunes temperature sensitivity. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/717274v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@a95daborg.highwire.dtl.DTLVardef@144bc42org.highwire.dtl.DTLVardef@1a39bf6org.highwire.dtl.DTLVardef@545e60_HPS_FORMAT_FIGEXP M_FIG C_FIG

RNA modifications are important for RNA structure, stability, and ribosome function, but their identification and localisation remains challenging. Oxford Nanopore direct RNA sequencing (DRS) enables modification-agnostic detection in native RNA, but existing tool benchmarks have focused almost exclusively on m6A in eukaryotic mRNA, leaving multi-modification tool performance in bacterial systems largely untested. Here, we benchmark ten RNA modification detection tools spanning signal-comparison, error-rate, and hybrid approaches on Escherichia coli K-12 MG1655 16S and 23S rRNA, which harbour 11 and 25 known modified sites, respectively, across 17 modification types. Using native RNA and in vitro transcribed (IVT) unmodified RNA, we evaluate performance across 25 coverage levels (5x to 1000x). DiffErr and JACUSA2 showed the strongest discrimination performance (AUROC >0.9 on both 16S and 23S rRNA), with DiffErr achieving the highest F1 score on 16S and JACUSA2 showing the most consistent precision-recall balance across both rRNAs. Both tools achieved full transcript-wide scoring and, along with DRUMMER, exact positional localisation. Several other tools produced no output at many rRNA positions, and restricting evaluation to reported positions inflated apparent performance. Signal-based tools showed a systematic 1-4 nucleotide 5' offset from known modified positions, consistent with the [~]5-mer nucleotide stretch present in the read head of the nanopore; applying tool-specific offset corrections substantially improved per-site recovery and reduced false positives, substantially improving the performance of tools such as EpiNano and nanoDoc. At single-site resolution, no known modified site was recovered by all tools, and several m5C, m5U, and m6A sites were missed by the majority of tools. Tool combination analysis showed that pairing error-rate-based tools with offset-corrected signal-based tools improved site recovery beyond any individual tool, with the best three-tool combination recovering 30 of the 36 known sites while maintaining low false positive rates. These results establish that discrimination metrics (e.g. AUROC) alone are insufficient to evaluate modification detection tools: output completeness, positional precision, and per-modification-type sensitivity should be reported alongside standard benchmarking metrics.

Splicing is governed by interactions between the spliceosome and precursor RNA sequence and structural elements. However, the relative contributions of RNA sequence and structural elements remain unclear. Here, we systematically dissect these determinants using a high-throughput mutagenesis approach with the MAP3K7 intron reporter. The MAP3K7 gene encodes a serine/threonine kinase involved in response to environmental stress. MAP3K7 precursor RNA contains a cryptic 3 splice site that increases in use when the core spliceosomal protein SF3B1 is mutated. SF3B1 mutations are known to promote aberrant splicing and are associated with cancer, particularly the lysine 700 to glutamate mutation (K700E). We designed a pooled library of 249 MAP3K7 mutants targeting branch points, RNA-binding protein motifs, nucleotide composition and predicted structural elements. The impact of these mutants on splicing was measured in the context of normal and SF3B1 K700E expression. RNA structure was assessed in parallel using in vitro high-throughput SHAPE-MAP chemical probing. We found that branchpoint mutations drive the strongest increases in cryptic splice-site use. There is no overall correlation between cryptic splice-site use and structural similarity to the wild-type MAP3K7 RNA. However, mutants within an RNA binding protein hotspot (containing U2AF2, U2AF1, KHSRP and SRSF2 sites) are associated with cryptic splice-site use and structural similarity to wild-type MAP3K7 RNA. These structural changes are associated with increased ensemble diversity. Our results demonstrate that although there are key structured regions within an RNA, there is also extensive variability where divergent RNA structures allow for accurate splicing.

A morphospace is an abstract space of theoretically possible biological traits, shapes, or property values. It is interesting to explore which parts of a morphospace life occupies, as compared to those parts which could be occupied, but are not. Comparing random and natural non-coding (nc) RNA secondary structures is an established approach to studying morphospace occupation for RNA structures. Most earlier studies have focused on the minimum free energy (MFE) structure, while relatively few have looked at the Boltzmann distribution, describing the ensemble of energetically suboptimal RNA folds. These suboptimal structures may have important roles and functions, and hence should be examined carefully. Here we compare random and natural ncRNA in terms of their Boltzmann distributions, finding that natural RNA tend to have very similar profiles to random RNA, with the main difference being that natural RNA are slightly more energetically stable, except for very short sequences (20 to 30 nucleotides) which tend to be slightly less stable. We infer that natural ncRNA occupy similar parts of the morphospace that random RNA do, indicating that the biophysics of the genotype-phenotype map largely determines the ensemble properties of ncRNA.

Codon optimality promotes efficient translation and, as recent research has shown, also extends mRNA lifetimes. However, how control is distributed between translation and mRNA degradation remains unclear. We show that this relative impact depends strongly on the measurement approach. Using fluorescent protein reporters can underestimate codon-optimality-dependent increases in translation efficiency. Conversely, analyses based on poly(A)-selected RNA overestimate the impact on translation, because stable transcripts undergoing poly(A) shortening are often inefficiently captured, leading to skewed protein-to-mRNA ratios. This technical bias is not offset by the marginal decline in ribosomal association observed as mRNAs age. Estimates based on total RNA measurements redistribute some of the control attributed to translation to mRNA stability, making the contributions comparable for mRNAs with shorter coding sequences. For longer mRNAs, codon optimality increasingly controls elongation speed, with a greater effect on translation efficiency than on degradation. These insights highlight the importance of measurement strategy for accurately quantifying the determinants of mRNA stability and protein synthesis.

Triple-negative breast cancer (TNBC) remains one of the most aggressive breast cancer subtypes and lacks durable targeted therapies. Dysregulation of cell-cycle control, particularly through CDK4/6 signaling, is a defining feature of TNBC biology (Garrido-Castro et al., 2019). Extracts of Moringa oleifera have repeatedly been shown to induce G1-phase arrest in breast cancer models, yet the molecular basis of this phenotype remains unclear (Al-Asmari et al., 2015) (Gaffar et al., 2019). Emerging work on cross-kingdom regulation has raised the possibility that plant-derived microRNAs may, under specific conditions, interact with mammalian transcripts (Zhang et al., 2012) (Chin et al., 2016). Sequence shuffling for the negative control was performed with set.seed(42) to ensure reproducibility. Additional visualisations (nucleotide alignment and thermodynamic analyses) were generated using Python 3 (matplotlib v3.7). Here, we performed a high-stringency computational screen of conserved Moringa microRNAs against 30 genes implicated in TNBC pathogenesis using local sequence alignment. We identify a predicted high-affinity interaction between mol-miR156 and the human CDK4 3' untranslated region (3'UTR), characterized by an uninterrupted 12-nucleotide complementary motif that exceeds canonical mammalian microRNA seed requirements. These findings support the hypothesis that conserved plant microRNAs may exhibit latent structural compatibility with oncogenic human transcripts. While physiological delivery and functional repression are not demonstrated here, this work establishes a molecular framework for future experimental investigation into cross-kingdom RNA interactions relevant to cancer cell-cycle regulation. Impact StatementA high-stringency computational screen identifies latent molecular compatibility between a conserved plant microRNA and the human CDK4 oncogene, establishing a testable framework for cross-kingdom RNA interference in triple-negative breast cancer.

The ability to access, search, and analyse large collections of RNA molecules together with their secondary structure and evolutionary context is essential for comparative and phylogeny-driven studies. Although RNA secondary structure is known to be more conserved than primary sequence, no existing resource systematically associates individual RNA molecules with curated phylogenetic classifications. Here, we introduce PhyloRNA, a curated meta-database that provides large-scale access to RNA secondary structures collected from public resources or derived from experimentally resolved 3D structures. PhyloRNA allows users to search, select, and download extensive sets of RNA molecules in multiple textual formats, each entry being explicitly linked to phylogenetic annotations derived from five curated taxonomy systems. In addition to taxonomic information, each RNA molecule is accompanied by a rich set of descriptors, including pseudoknot order, genus, and three levels of structural abstraction--Core, Core Plus, and Shape--which facilitate comparative analyses across sets of molecules. PhyloRNA is publicly available at https://bdslab.unicam.it/phylorna/ and is regularly updated to incorporate newly available data and revised taxonomic annotations.

Mutations in the low complexity domains of RNA-binding proteins are associated with neurodegenerative disease pathology. The TIA1 RNA-binding protein harbors seven such mutations linked to a clinical cohort of ALS patients. The altered low complexity domain sequence increases the number of TIA1-rich stress granules in cultured cells, delays their disassembly, and is associated with increased fibril formation. Altered molecular motions and contacts in condensed states like stress granules that result in the formation of amyloid-like fibril states is commonly observed for RNA-binding biomolecular condensates. Here we focus on the influence of the ALS mutations on fibril formation of the TIA1 low complexity domain. Repetitive seeding preparations of the seven TIA1 protein mutants all yield amyloid-like fibrils based on transmission electron microscopy images and increased thioflavin T fluorescence. Analysis of solid state nuclear magnetic resonance spectra recorded on all seven mutant fibrils reveals distinct structural differences in the relative to wild-type fibrils. Our results shed light on how the mutations affect structural conformations accessible to the TIA1 low complexity domain.

Since the discovery of viral Internal Ribosome Entry Sites (IRESes), researchers have sought to find similar elements in mammalian host genes, termed "cellular IRESes". However, the plasmid systems used to measure cellular IRES activity are vulnerable to false positives due to promoter activity in candidate IRESes. Orthogonal methods are needed to validate putative IRESes while carefully avoiding artifacts known to cause false positives. Recently, Koch et al. proposed approaches for studying IRESes, primarily circular RNA-generating plasmids, and for validating mRNA transcripts using smFISH and qRT-PCR. Here, we demonstrate confounding variables and artifacts in each of these approaches that can lead to inappropriate conclusions about potential cellular IRES activity. We show the back-splicing circRNA plasmid creates linear mRNA artifacts associated with false-positive IRES signals. Using orthogonal, gold-standard assays validated with viral IRESes, we find putative cellular IRESes reported using the back-splicing plasmid have no IRES activity. Furthermore, we demonstrate that smFISH and qRT-PCR can misidentify nuclear non-coding RNAs as mRNAs and we validate a single molecule sequencing assay for identifying genuine mRNA 5 ends. Our work establishes reliable methods for robust transcript annotation and IRES studies that avoid documented artifacts arising from bicistronic and back-splicing circRNA plasmid reporters.

Polycomb Repressive Complex 2 (PRC2) maintains repression of genes specific for other cell differentiation states. PRC2 binds RNA in vitro with a preference for G-rich sequences. UV-based crosslinking coupled with immunoprecipitation (CLIP) experiments have shown that PRC2 also binds RNA in cells. Recently, Guo et al reported that a stringent denaturing variant of CLIP called CLAP did not detect PRC2 RNA binding in cells. We present a reanalysis of CLAP data that supports direct interaction of PRC2 with RNA in cells. CLAP for Halo-tagged PRC2 subunits from mixed populations of human and mouse cells specifically enriched for RNA from the species in which the proteins were tagged. The lack of apparent PRC2 RNA binding in Guo and colleagues analysis stems from a scaling step that deflates enrichment scores for low-complexity CLAP samples. Our findings pave the way for studies seeking to determine the physiological roles of PRC2 RNA binding activity.

The correct assembly of ribosomes is essential for viability and faithful gene expression. In eukaryotic cells, the pre-40S and pre-60S ribosomal subunits are largely pre-assembled in the nucleolus before they are exported to the cytoplasm for final maturation. Although most ribosomal proteins of the large subunit are loaded onto pre-60S particles in the early nucleolar steps, a few, including eL24, are loaded in the cytoplasm. eL24 is thought to recruit the zinc-finger protein Rei1 (ZNF622 in humans). In yeast, Rei1 has a paralog, Reh1. While we and others have previously shown that Rei1 facilitates the removal of Arx1, Rei1 and Reh1 appear to have an additional unknown function. To identify this function, we first examined the protein composition of pre-60S subunits isolated from rei1{Delta} reh1{Delta} mutant cells and found that these subunits were specifically defective for eL24. However, the absence of eL24 did not impair Rei1 binding to pre-60S. Moreover, overexpression of eL24 suppressed the growth defect of the double mutant. As an alternative approach to understanding the function of Rei1 and Reh1, we screened for bypass suppressors of the growth defect of rei1{Delta} reh1{Delta} cells. We identified mutations in the genes coding for ribosomal protein uL3, the GTPase Lsg1 and the protein phosphatase Ppq1. Importantly, these suppressors all partially reversed the eL24 loading defect of rei1{Delta} reh1{Delta} cells. Based on these results, we propose a revised order of cytoplasmic assembly events where Rei1 and Reh1 facilitate the recruitment of eL24 to the pre-60S particle.

Chimeric RNA molecules, which contain nucleotide sequences originating from multiple genes, are generated by chromosomal rearrangements, transcriptional read-throughs, or trans-splicing between separate parental transcripts. Chimeric RNAs have been functionally validated in both pathological and normal healthy physiological contexts indicating the biological significance of chimeric RNA expression. There is, however, currently no standard for computationally quantifying chimeric RNA expression and only limited benchmarking data available for the few chimeric RNA detection software that attempt to measure the abundance of the predicted chimeras. Here, we develop the relative index of chimeric expression, RICE, that is calculated based on the relative expression of chimeric transcripts compared to the respective parental WT transcripts. We evaluate three different methods for generating this measurement from simulated RNA sequencing data with known transcript abundances. Our BLAST-based approach outperforms STAR and Kallisto based approaches when considering both accuracy and consistency between simulated data of different read lengths and sequencing depths. We further demonstrate that RICE values can be validated using qPCR and are sensitive to dynamic conditions using siRNA targeting chimeric RNA expression. Finally, we apply our RICE analysis pipeline to clinical prostate cancer data. We quantify over 1200 chimeric RNAs in primary prostate cancer, metastatic prostate cancer, and non-cancer tissue samples from GTEx. Our differential RICE analysis revealed a clustering of prostate cancer tissue samples from three different sequencing cohorts distinct from their associated tissue type noncancer GTEx clusters. Our pipeline is publicly available on github and can be run on a personal laptop with computational resources and processing time dependent on the number of quantified chimeras.

Efficient protein synthesis in eukaryotic cells typically requires a 5' cap structure on messenger RNAs (mRNAs). However, under stress conditions or in viral infection, translation can also occur independently of the cap via internal ribosomal entry sites (IRES). IRES elements are therefore key regulators of protein expression in both viral and cellular contexts. Here we describe a cell-free protocol to quantitatively assess IRES-mediated translation using wheat germ extract (WGE) and a firefly luciferase (FLuc) reporter. The protocol includes template preparation, RNA synthesis and luminescence measurement following in vitro translation in WGE. This method enables rapid and robust comparison of IRES activity under controlled conditions and can additionally be applied to evaluate mRNA modifications designed to enhance translation efficiency. Key featuresO_LIStringent in vitro workflow from DNA template preparation through RNA synthesis and protein synthesis to reporter readout, including quality controls. C_LIO_LIEvaluation of IRES-driven translation suitable for testing combinations of IRES and CDS. C_LIO_LItranslation analysis without radioactive labeling. C_LI Graphical overview O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/716985v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@1457b00org.highwire.dtl.DTLVardef@8e7405org.highwire.dtl.DTLVardef@6303eforg.highwire.dtl.DTLVardef@974d71_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical AbstractPipeline for the production and evaluation of IRES-firefly luciferase constructs using wheat germ extract. (1-4) Preparation: IRES-firefly luciferase constructs are amplified in E. coli and isolated from bacterial cells. Plasmids are linearized to prepare for in vitro transcription. (5-6) Transcript synthesis and verification: In vitro transcription is followed by electrophoretic validation to confirm integrity and correct molecular weight. (7-8) Translation and detection: Translation is executed in wheat germ extract and quantified by measuring reporter activity in a luminometer.

Accurate detection of RNA splice variants is often hindered when transcripts lack large distinguishable exonic regions, making conventional PCR strategies challenging. We developed a simple melting temperature (Tm)-guided exon-exon junction (EEJ) RT-PCR method to enable variant-specific detection under these conditions. Uni-directional primers spanning exon-exon junctions were designed so that approximately each half anneals to adjacent exons. The Tm of each half-site was set >7{degrees}C below the annealing temperature, preventing stable binding to individual exons and enforcing junction-dependent amplification. The method was evaluated using HTRA1-AS1 long noncoding RNA variants that share overlapping exon sequences but differ in splice connectivity. HTRA1-AS1 comprises five variants, only one with a large distinguishable exon. Tm-guided EEJ primers robustly discriminated the remaining four variants. After optimization, amplification yielded sharp, single bands with minimal cross-reactivity. Compared with conventional designs, this approach reduced heteroduplex and heteroquadruplex formation, improving band clarity. Sanger sequencing confirmed junction specificity, and the method performed well in multiplex settings. Overall, Tm-guided EEJ RT-PCR is a cost-effective, high-resolution approach for detecting RNA variants lacking easily distinguishable exonic regions, readily compatible with standard RT-PCR and qPCR workflows.