Sequence Elements Research Articles

Tying the knot: Unraveling the intricacies of the coronavirus frameshift pseudoknot.

Understanding and targeting functional RNA structures towards treatment of coronavirus infection can help us to prepare for novel variants of SARS-CoV-2 (the virus causing COVID-19), and any other coronaviruses that could emerge via human-to-human transmission or potential zoonotic (inter-species) events. Leveraging the fact that all coronaviruses use a mechanism known as -1 programmed ribosomal frameshifting (-1 PRF) to replicate, we apply algorithms to predict the most energetically favourable secondary structures (each nucleotide involved in at most one pairing) that may be involved in regulating the -1 PRF event in coronaviruses, especially SARS-CoV-2. We compute previously unknown most stable structure predictions for the frameshift site of coronaviruses via hierarchical folding, a biologically motivated framework where initial non-crossing structure folds first, followed by subsequent, possibly crossing (pseudoknotted), structures. Using mutual information from 181 coronavirus sequences, in conjunction with the algorithm KnotAli, we compute secondary structure predictions for the frameshift site of different coronaviruses. We then utilize the Shapify algorithm to obtain most stable SARS-CoV-2 secondary structure predictions guided by frameshift sequence-specific and genome-wide experimental data. We build on our previous secondary structure investigation of the singular SARS-CoV-2 68 nt frameshift element sequence, by using Shapify to obtain predictions for 132 extended sequences and including covariation information. Previous investigations have not applied hierarchical folding to extended length SARS-CoV-2 frameshift sequences. By doing so, we simulate the effects of ribosome interaction with the frameshift site, providing insight to biological function. We contribute in-depth discussion to contextualize secondary structure dual-graph motifs for SARS-CoV-2, highlighting the energetic stability of the previously identified 3_8 motif alongside the known dominant 3_3 and 3_6 (native-type) -1 PRF structures. Using a combination of thermodynamic methods and sequence covariation, our novel predictions suggest function of the attenuator hairpin via previously unknown pseudoknotted base pairing. While certain initial RNA folding is consistent, other pseudoknotted base pairs form which indicate potential conformational switching between the two structures.

Teaching transposon classification as a means to crowd source the curation of repeat annotation – a tardigrade perspective

BackgroundThe advancement of sequencing technologies results in the rapid release of hundreds of new genome assemblies a year providing unprecedented resources for the study of genome evolution. Within this context, the significance of in-depth analyses of repetitive elements, transposable elements (TEs) in particular, is increasingly recognized in understanding genome evolution. Despite the plethora of available bioinformatic tools for identifying and annotating TEs, the phylogenetic distance of the target species from a curated and classified database of repetitive element sequences constrains any automated annotation effort. Moreover, manual curation of raw repeat libraries is deemed essential due to the frequent incompleteness of automatically generated consensus sequences.ResultsHere, we present an example of a crowd-sourcing effort aimed at curating and annotating TE libraries of two non-model species built around a collaborative, peer-reviewed teaching process. Manual curation and classification are time-consuming processes that offer limited short-term academic rewards and are typically confined to a few research groups where methods are taught through hands-on experience. Crowd-sourcing efforts could therefore offer a significant opportunity to bridge the gap between learning the methods of curation effectively and empowering the scientific community with high-quality, reusable repeat libraries.ConclusionsThe collaborative manual curation of TEs from two tardigrade species, for which there were no TE libraries available, resulted in the successful characterization of hundreds of new and diverse TEs in a reasonable time frame. Our crowd-sourcing setting can be used as a teaching reference guide for similar projects: A hidden treasure awaits discovery within non-model organisms.

Multilevel Monte Carlo Methods for Stochastic Convection–Diffusion Eigenvalue Problems

We develop new multilevel Monte Carlo (MLMC) methods to estimate the expectation of the smallest eigenvalue of a stochastic convection–diffusion operator with random coefficients. The MLMC method is based on a sequence of finite element (FE) discretizations of the eigenvalue problem on a hierarchy of increasingly finer meshes. For the discretized, algebraic eigenproblems we use both the Rayleigh quotient (RQ) iteration and implicitly restarted Arnoldi (IRA), providing an analysis of the cost in each case. By studying the variance on each level and adapting classical FE error bounds to the stochastic setting, we are able to bound the total error of our MLMC estimator and provide a complexity analysis. As expected, the complexity bound for our MLMC estimator is superior to plain Monte Carlo. To improve the efficiency of the MLMC further, we exploit the hierarchy of meshes and use coarser approximations as starting values for the eigensolvers on finer ones. To improve the stability of the MLMC method for convection-dominated problems, we employ two additional strategies. First, we consider the streamline upwind Petrov–Galerkin formulation of the discrete eigenvalue problem, which allows us to start the MLMC method on coarser meshes than is possible with standard FEs. Second, we apply a homotopy method to add stability to the eigensolver for each sample. Finally, we present a multilevel quasi-Monte Carlo method that replaces Monte Carlo with a quasi-Monte Carlo (QMC) rule on each level. Due to the faster convergence of QMC, this improves the overall complexity. We provide detailed numerical results comparing our different strategies to demonstrate the practical feasibility of the MLMC method in different use cases. The results support our complexity analysis and further demonstrate the superiority over plain Monte Carlo in all cases.

Discovery of Borosin Catalytic Strategies and Function through Bioinformatic Profiling.

Borosins are ribosomally synthesized and post-translationally modified peptides (RiPPs) containing backbone α-N-methylations. These modifications confer favorable pharmacokinetic properties including increased membrane permeability and resistance to proteolytic degradation. Previous studies have biochemically and bioinformatically explored several borosins, revealing (1) numerous domain architectures and (2) diverse core regions lacking conserved sequence elements. Due to these characteristics, large-scale computational identification of borosin biosynthetic genes remains challenging and often requires additional, time-intensive manual inspection. This work builds upon previous findings and updates the genome-mining tool RODEO to automatically evaluate borosin biosynthetic gene clusters (BGCs) and identify putative precursor peptides. Using the new RODEO module, we provide an updated analysis of borosin BGCs identified in the NCBI database. From our data set, we bioinformatically predict and experimentally characterize a new fused borosin domain architecture, in which the modified natural product core is encoded N-terminal to the methyltransferase domain. Additionally, we demonstrate that a borosin precursor peptide is a native substrate of shewasin A, a reported aspartyl peptidase with no previously identified substrates. Shewasin A requires post-translational modification of the leader peptide for proteolytic maturation, a feature not previously observed in RiPPs. Overall, this work provides a user-friendly and open-access tool for the analysis of borosin BGCs and we demonstrate its utility to uncover additional biosynthetic strategies within the borosin class of RiPPs.

Deep learning the cis-regulatory code for gene expression in selected model plants

Elucidating the relationship between non-coding regulatory element sequences and gene expression is crucial for understanding gene regulation and genetic variation. We explored this link with the training of interpretable deep learning models predicting gene expression profiles from gene flanking regions of the plant species Arabidopsis thaliana, Solanum lycopersicum, Sorghum bicolor, and Zea mays. With over 80% accuracy, our models enabled predictive feature selection, highlighting e.g. the significant role of UTR regions in determining gene expression levels. The models demonstrated remarkable cross-species performance, effectively identifying both conserved and species-specific regulatory sequence features and their predictive power for gene expression. We illustrated the application of our approach by revealing causal links between genetic variation and gene expression changes across fourteen tomato genomes. Lastly, our models efficiently predicted genotype-specific expression of key functional gene groups, exemplified by underscoring known phenotypic and metabolic differences between Solanum lycopersicum and its wild, drought-resistant relative, Solanum pennellii.

A modular library for fast prototyping of solution-state nuclear magnetic resonance experiments

Abstract. We present a framework library (Modular Elements, ME) for the development of pulse sequences for Bruker spectrometers. It implements a two-level abstraction approach – the lower level comprises basic functional elements of pulse sequences and the higher one often-reused blocks comprising several evolution periods. The low-level abstractions reduce code duplication between variants of experiments such as hard-pulse and selective variants of individual NMR experiments. The high-level modules enable further reuse of pulse program code and aid in the construction of complex experiments. We show the library's functionality by presenting pulse programs that can be switched between standard and TROSY variants as well as hard and shaped pulses and that can seamlessly incorporate real-time homodecoupling. Adaptability is further demonstrated in a configurable 4D NOESY program.

Motility-activating mutations upstream of flhDC reduce acid shock survival of Escherichia coli.

Many neutralophilic bacterial species try to evade acid stress with an escape strategy, which is reflected in the increased expression of genes coding for flagellar components. Extremely acid-tolerant bacteria, such as Escherichia coli, survive the strong acid stress, e.g., in the stomach of vertebrates. Recently, we were able to show that the induction of motility genes in E. coli is strictly dependent on the degree of acid stress, i.e., they are induced under mild acid stress but not under severe acid stress. However, it was not known to what extent fine-tuned expression of motility genes is related to fitness and the ability to survive periods of acid shock. In this study, we demonstrate that the expression of FlhDC, the master regulator of flagellation, is inversely correlated with the acid shock survival of E. coli. We encountered this phenomenon when analyzing mutants from the Keio collection, in which the expression of flhDC was altered by an insertion sequence element. These results suggest a fitness trade-off between acid tolerance and motility.IMPORTANCEEscherichia coli is extremely acid-resistant, which is crucial for survival in the gastrointestinal tract of vertebrates. Recently, we systematically studied the response of E. coli to mild and severe acidic conditions using Ribo-Seq and RNA-Seq. We found that motility genes are induced at pH 5.8 but not at pH 4.4, indicating stress-dependent synthesis of flagellar components. In this study, we demonstrate that motility-activating mutations upstream of flhDC, encoding the master regulator of flagella genes, reduce the ability of E. coli to survive periods of acid shock. Furthermore, we show an inverse correlation between motility and acid survival using a chromosomal isopropyl β-D-thio-galactopyranoside (IPTG)-inducible flhDC promoter and by sampling differentially motile subpopulations from swim agar plates. These results reveal a previously undiscovered trade-off between motility and acid tolerance and suggest a differentiation of E. coli into motile and acid-tolerant subpopulations, driven by the integration of insertion sequence elements.

Forecasting carbon price with attention mechanism and bidirectional long short-term memory network

To improve the precision of carbon price forecasting, our study aims to propose a novel hybrid forecasting model which integrates recurrent neural networks and attention mechanisms. First, the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) algorithm is employed to decompose carbon prices into several regular intrinsic mode functions (IMFs) and a residual. Second, multiscale entropy is utilized to differentiate and reconstruct these components to reduce cumulative errors in subsequent forecasting. Subsequently, a bidirectional long short-term memory network (Bi-LSTM) equipped with attention mechanisms is used to forecast each reconstructed component. Attention mechanisms identifies crucial sequence elements, assigns different weights to hidden information, and extracts richer information from the series. Finally, the results of all components are integrated to obtain the final forecasting result. Empirical analysis conducted on real datasets from the Guangdong and Hubei carbon markets demonstrates that the proposed hybrid model outperform prevailing mainstream forecasting models in terms of both horizontal and directional forecasting metrics.

U-CAN-seq: A Universal Competition Assay by Nanopore Sequencing.

RNA viruses quickly evolve subtle genotypic changes that can have major impacts on viral fitness and host range, with potential consequences for human health. It is therefore important to understand the evolutionary fitness of novel viral variants relative to well-studied genotypes of epidemic viruses. Competition assays are an effective and rigorous system with which to assess the relative fitness of viral genotypes. However, it is challenging to quickly and cheaply distinguish and quantify fitness differences between very similar viral genotypes. Here, we describe a protocol for using reverse transcription PCR in combination with commercial nanopore sequencing services to perform competition assays on untagged RNA viruses. Our assay, called the Universal Competition Assay by Nanopore Sequencing (U-CAN-seq), is relatively cheap and highly sensitive. We used a well-studied N24A mutation in the chikungunya virus (CHIKV) nsp3 gene to confirm that we could detect a competitive disadvantage using U-CAN-seq. We also used this approach to show that mutations to the CHIKV 5' conserved sequence element that disrupt sequence but not structure did not affect the fitness of CHIKV. However, similar mutations to an adjacent CHIKV stem loop (SL3) did cause a fitness disadvantage compared to wild-type CHIKV, suggesting that structure-independent, primary sequence determinants in this loop play an important role in CHIKV biology. Our novel findings illustrate the utility of the U-CAN-seq competition assay.

Lesions in a songbird vocal circuit increase variability in song syntax.

Complex skills like speech and dance are composed of ordered sequences of simpler elements, but the neuronal basis for the syntactic ordering of actions is poorly understood. Birdsong is a learned vocal behavior composed of syntactically ordered syllables, controlled in part by the songbird premotor nucleus HVC (proper name). Here, we test whether one of HVC's recurrent inputs, mMAN (medial magnocellular nucleus of the anterior nidopallium), contributes to sequencing in adult male Bengalese finches (Lonchura striata domestica). Bengalese finch song includes several patterns: (1) chunks, comprising stereotyped syllable sequences; (2) branch points, where a given syllable can be followed probabilistically by multiple syllables; and (3) repeat phrases, where individual syllables are repeated variable numbers of times. We found that following bilateral lesions of mMAN, acoustic structure of syllables remained largely intact, but sequencing became more variable, as evidenced by 'breaks' in previously stereotyped chunks, increased uncertainty at branch points, and increased variability in repeat numbers. Our results show that mMAN contributes to the variable sequencing of vocal elements in Bengalese finch song and demonstrate the influence of recurrent projections to HVC. Furthermore, they highlight the utility of species with complex syntax in investigating neuronal control of ordered sequences.

Lesions in a songbird vocal circuit increase variability in song syntax

Complex skills like speech and dance are composed of ordered sequences of simpler elements, but the neuronal basis for the syntactic ordering of actions is poorly understood. Birdsong is a learned vocal behavior composed of syntactically ordered syllables, controlled in part by the songbird premotor nucleus HVC (proper name). Here, we test whether one of HVC’s recurrent inputs, mMAN (medial magnocellular nucleus of the anterior nidopallium), contributes to sequencing in adult male Bengalese finches (Lonchura striata domestica). Bengalese finch song includes several patterns: (1) chunks, comprising stereotyped syllable sequences; (2) branch points, where a given syllable can be followed probabilistically by multiple syllables; and (3) repeat phrases, where individual syllables are repeated variable numbers of times. We found that following bilateral lesions of mMAN, acoustic structure of syllables remained largely intact, but sequencing became more variable, as evidenced by ‘breaks’ in previously stereotyped chunks, increased uncertainty at branch points, and increased variability in repeat numbers. Our results show that mMAN contributes to the variable sequencing of vocal elements in Bengalese finch song and demonstrate the influence of recurrent projections to HVC. Furthermore, they highlight the utility of species with complex syntax in investigating neuronal control of ordered sequences.

The effect of DNA-binding proteins on insertion sequence element transposition upstream of the bgl operon in Escherichia coli.

The bglGFB operon in Escherichia coli K-12 strain BW25113, encoding the proteins necessary for the uptake and metabolism of β-glucosides, is normally not expressed. Insertion of either IS1 or IS5 upstream of the bgl promoter activates expression of the operon only when the cell is starving in the presence of a β-glucoside, drastically increasing transcription and allowing the cell to survive and grow using this carbon source. Details surrounding the exact mechanism and regulation of the IS insertional event remain unclear. In this work, the role of several DNA-binding proteins in how they affect the rate of insertion upstream of bgl are examined via mutation assays and protocols measuring transcription. Both Crp and IHF exert a positive effect on insertional Bgl+ mutations when present, active, and functional in the cell. Our results characterize IHF's effect in conjunction with other mutations, show that IHF's effect on IS insertion into bgl also affects other operons, and indicate that it may exert its effect by binding to and altering the DNA conformation of IS1 and IS5 in their native locations, rather than by directly influencing transposase gene expression. In contrast, the cAMP-CRP complex acts directly upon the bgl operon by binding upstream of the promoter, presumably altering local DNA into a conformation that enhances IS insertion.

Cell-type-specific mRNA transcription and degradation kinetics in zebrafish embryogenesis from metabolically labeled single-cell RNA-seq

During embryonic development, pluripotent cells assume specialized identities by adopting particular gene expression profiles. However, systematically dissecting the relative contributions of mRNA transcription and degradation to shaping those profiles remains challenging, especially within embryos with diverse cellular identities. Here, we combine single-cell RNA-Seq and metabolic labeling to capture temporal cellular transcriptomes of zebrafish embryos where newly-transcribed (zygotic) and pre-existing (maternal) mRNA can be distinguished. We introduce kinetic models to quantify mRNA transcription and degradation rates within individual cell types during their specification. These models reveal highly varied regulatory rates across thousands of genes, coordinated transcription and destruction rates for many transcripts, and link differences in degradation to specific sequence elements. They also identify cell-type-specific differences in degradation, namely selective retention of maternal transcripts within primordial germ cells and enveloping layer cells, two of the earliest specified cell types. Our study provides a quantitative approach to study mRNA regulation during a dynamic spatio-temporal response.

Abstract LB102: Triaging oral premalignant lesions: Plasma ultrashort cell-free DNA-based liquid biopsy approach

Abstract Background: Rapid advancements in cell-free DNA (cfDNA) based liquid biopsy (LB), has opened avenues of critical clinical importance. Recent discovery of a novel class of cell-free DNA 40-70 bps in length, ultrashort cfDNA (uscfDNA) is demonstrating immense potential as a cancer early detection biomarker. Globally, oral cavity squamous cell carcinomas (OCSCC) make up a significant proportion of head and neck squamous cell cancers. OCSCC commonly arises after the occurrence of oral premalignant lesions (OPLs), making it an ideal target for plasma-based LB screening initiatives. Methods: Current work focuses on preferential extraction of low molecular weight nucleic acids and single-stranded library preparation and sequencing, Broad Range cell-free DNA- Sequencing (BRcfDNA-Seq), to obtain uscf- & 167 bps mononucleosomal cfDNA (mncfDNA), for disease detection. Sequencing data was bioinformatically processed: paired-end reads merged (BBmerge), aligned with BWA-mem, deduplicated using SRSLY UMI, and blacklisted portions removed. This was followed by analysis for non-mutational features like fragmentomics, occurrence of G-Quad structures, 4-mer Motif sequences at the end of cfDNA sequences, functional genomic element peak formation by uscfDNA. These features have been recently described non-mutation metrics which have demonstrated evidence of clinical relevance. With non-mutational multi-modal analysis of uscfDNA, obtained using BRcfDNA-Seq, we were able to categorize oral premalignant disorders into two cohorts: one which progressed into OCSCC (PG-OPL) (n=19) & one which did not (nPG-OPL) (n=19). Results: Bioinformatic processing for fragmentomics, of the relative proportion of 40-53bps fragments to 54-70bps fragments in the uscfDNA population demonstrated a significant difference across 1700 chromosomal bins between PG & nPG-OPL (multiple t test, FDR 10%, p value = 0.044, AUROC = 0.7258). The occurrence of G-quadruplex structures in uscfDNA was also significantly different between the two groups (student t test, p= 0.02, AUROC= 0.6953). Examination of the end-motifs profiles of uscfDNA between PG-OPL & nPG-OPL samples showed the randomness of the motifs as revealed by the Shannon entropy score is significant between the two groups (p = 0.046, AUROC = 0.6482). We further evaluated individual motifs that could discriminate between the two groups and identified CCCC, CCCT, TGGG, etc. are highly discriminatory. uscfDNA contained a substantially higher proportion of functional genomic element sequences in the PG-OPL group than the nPG-OPL group like exon (p = 0.00067, AUROC = 0.7147) & 5’ UTR (p= 0.000006, AUROC= 0.7673) are different between the groups. Conclusion: Results demonstrated clinical relevance of BRcfDNA-Seq for plasma-derived cfDNA in assessment of malignancy progression of OPLs. These non-mutational multi-modal features of cfDNA maybe indicative of local and systemic factors associated with disease affecting cfDNA. Citation Format: Neeti Swarup, Jordan C. Cheng, Irene Choi, Mohammad Arshad Aziz, Kelly Y. Liu, Fang Wei, Feng Li, Yong Kim, Catherine Poh, David T. Wong. Triaging oral premalignant lesions: Plasma ultrashort cell-free DNA-based liquid biopsy approach [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB102.

CANTOR’S THEOREM MAY FAIL FOR FINITARY PARTITIONS

Abstract A partition is finitary if all its members are finite. For a set A, $\mathscr {B}(A)$ denotes the set of all finitary partitions of A. It is shown consistent with $\mathsf {ZF}$ (without the axiom of choice) that there exist an infinite set A and a surjection from A onto $\mathscr {B}(A)$ . On the other hand, we prove in $\mathsf {ZF}$ some theorems concerning $\mathscr {B}(A)$ for infinite sets A, among which are the following: (1) If there is a finitary partition of A without singleton blocks, then there are no surjections from A onto $\mathscr {B}(A)$ and no finite-to-one functions from $\mathscr {B}(A)$ to A. (2) For all $n\in \omega $ , $|A^n|<|\mathscr {B}(A)|$ . (3) $|\mathscr {B}(A)|\neq |\mathrm {seq}(A)|$ , where $\mathrm {seq}(A)$ is the set of all finite sequences of elements of A.

A metagenomics pipeline reveals insertion sequence-driven evolution of the microbiota

Insertion sequence (IS) elements are mobile genetic elements in bacterial genomes that support adaptation. We developed a database of IS elements coupled to a computational pipeline that identifies IS element insertions in the microbiota. We discovered that diverse IS elements insert into the genomes of intestinal bacteria regardless of human host lifestyle. These insertions target bacterial accessory genes that aid in their adaptation to unique environmental conditions. Using IS expansion in Bacteroides, we show that IS activity leads to the insertion of "hot spots" in accessory genes. We show that IS insertions are stable and can be transferred between humans. Extreme environmental perturbations force IS elements to fall out of the microbiota, and many fail to rebound following homeostasis. Our work shows that IS elements drive bacterial genome diversification within the microbiota and establishes a framework for understanding how strain-level variation within the microbiota impacts human health.

150 Backbone Spiking Sequence as a Basis for Preplay, Replay, and Default States in Human Cortex

INTRODUCTION: Sequences of spiking activity are a fundamental feature of many neural systems, and recent evidence suggests that they play an important role in information coding in the human brain. A parallel set of studies also asserts that sequential activity may in part derive from a pre-existing network structure. Sequential spiking activity therefore may arise as a natural property of the neurophysiologic properties of the human cortex. METHODS: We measured single unit spiking activity in the human cortex by implanting Utah micro-electrode arrays into participants who performed an episodic memory task while undergoing invasive monitoring for potential resective epilepsy surgery. RESULTS: We confirm the presence of an average backbone spiking sequence identified during pre-task rest that is stable over time and different cognitive states. These resting backbone sequences served as a scaffold for cognitively relevant sequential spiking activity occurring later in the recording session. We further demonstrate that backbone sequences are composed of both rigid and flexible sequence elements, and that flexible elements serve to promote memory specificity when forming and retrieving new memories. CONCLUSIONS: Here we demonstrate that backbone sequences can be measured in the human cortex and that they persist over time and through different cognitive states. Our data show that backbone sequences are composed of both rigid and flexible elements, and flexibility around the backbone allows for the formation of memory specific spiking sequences. Taken together, our results provide the first evidence for backbone spiking sequences in the human cortex, and more generally suggest a cognitive role of predetermined spiking network dynamics in the human brain.

Sequence prediction of missing data of spatio-temporal series of marine environmental elements based on ST-ResNet model

Spatial data of marine environmental elements are of great significance to the marine industry and marine safety, and they are also affected by external factors. This results in a new method for spatial and temporal sequence prediction of marine environmental elements based on the ST-ResNet model. Specifically, the temporal distance, period, and trend of marine regions are modelled by residual networks, and different residual sub-networks are used for each characteristic, in each sub-network, different weights are assigned to different branches and regions by simulating the changes of marine data, and the output is finally fitted to obtain the output. The ST-ResNet model was validated on the ERA5 dataset as an example, and compared with other prediction models, the ST-ResNet model achieved better results, which verified the effectiveness of the method in predicting the temporal and spatial sequences of marine environmental elements.

RNA polymerase SI3 domain modulates global transcriptional pausing and pause-site fluctuations.

Transcriptional pausing aids gene regulation by cellular RNA polymerases (RNAPs). A surface-exposed domain inserted into the catalytic trigger loop (TL) of Escherichia coli RNAP, called SI3, modulates pausing and is essential for growth. Here we describe a viable E. coli strain lacking SI3 enabled by a suppressor TL substitution (β'Ala941→Thr; ΔSI3*). ΔSI3* increased transcription rate in vitro relative to ΔSI3, possibly explaining its viability, but retained both positive and negative effects of ΔSI3 on pausing. ΔSI3* inhibited pauses stabilized by nascent RNA structures (pause hairpins; PHs) but enhanced other pauses. Using NET-seq, we found that ΔSI3*-enhanced pauses resemble the consensus elemental pause sequence whereas sequences at ΔSI3*-suppressed pauses, which exhibited greater association with PHs, were more divergent. ΔSI3*-suppressed pauses also were associated with apparent pausing one nucleotide upstream from the consensus sequence, often generating tandem pause sites. These '-2 pauses' were stimulated by pyrophosphate in vitro and by addition of apyrase to degrade residual NTPs during NET-seq sample processing. We propose that some pauses are readily reversible by pyrophosphorolysis or single-nucleotide cleavage. Our results document multiple ways that SI3 modulates pausing in vivo and may explain discrepancies in consensus pause sequences in some NET-seq studies.

Context base editing for splice correction of IVSI-110 β-thalassemia

Beta-thalassemia is brought about by defective β-globin (HBB) formation and in severe cases requires regular blood transfusion and iron chelation for survival. Genome editing of hematopoietic stem cells allows correction of underlying mutations as curative therapy. As potentially safer alternatives to double-strand-break–based editors, base editors (BEs) catalyze base transitions for precision editing of DNA target sites, prompting us to reclone and evaluate two recently published adenine BEs (ABE SpRY and SpG) with relaxed protospacer adjacent motif (PAM) requirements for their ability to correct the common HBBIVSI-110(G>A) splice mutation. Nucleofection of ABE components as RNA into patient-derived CD34+ cells achieved up to 90% editing of upstream sequence elements critical for aberrant splicing, allowing full characterization of the on-target base editing profile of each ABE and the detection of potentially context-dependent differences in on-target insertions and deletions. In addition, this study identifies opposing effects on splice correction for two neighboring context bases, establishes the frequency distribution of multiple BE editing events in the editing window, and shows high-efficiency functional correction of HBBIVSI-110(G>A) for our ABEs, including at the levels of RNA, protein and erythroid differentiation.