Quantitative Activity Profile and Context Dependence of All Human 5' Splice Sites

Neuron-specific repression of alternative splicing by the conserved CELF protein UNC-75 in Caenorhabditis elegans

Tissue-regulated alternative exons are dictated by the interplay between cis-elements and trans-regulatory factors such as RNA-binding proteins (RBPs). Despite extensive research on splicing regulation, the full repertoire of these cis and trans features and their evolutionary dynamics across species are yet to be fully characterized. Members of the CUG-binding protein and ETR-like family (CELF) of RBPs are known to play a key role in the regulation of tissue-biased splicing patterns, and when mutated, these proteins have been implicated in a number of neurological and muscular disorders. In this study, we sought to characterize specific mechanisms that drive tissue-specific splicing in vivo of a model switch-like exon regulated by the neuronal-enriched CELF ortholog in Caenorhabditis elegans, UNC-75. Using sequence alignments, we identified deeply conserved intronic UNC-75 binding motifs overlapping the 5' splice site and upstream of the 3' splice site, flanking a strongly neural-repressed alternative exon in the Zonula Occludens gene zoo-1. We confirmed that loss of UNC-75 or mutations in either of these cis-elements lead to substantial de-repression of the alternative exon in neurons. Moreover, mis-expression of UNC-75 in muscle cells is sufficient to induce the neuron-like robust skipping of this alternative exon. Lastly, we demonstrate that overlapping an UNC-75 motif within a heterologous 5' splice site leads to increased skipping of the adjacent alternative exon in an unrelated splicing event. Together, we have demonstrated that a specific configuration and combination of cis elements bound by this important family of RBPs can achieve robust splicing outcomes in vivo.

Identifying six single nucleotide variants in the COL17A1 gene that alter RNA splicing: database analysis and minigene assays

Collagen type XVII alpha 1 chain (COL17A1) is a protein in the collagen family crucial for maintaining the integrity of skin and epithelial tissues. It is also vital for enamel formation and plays a significant role in the differentiation of ameloblasts. Many studies have indicated that single nucleotide variants (SNVs) can disrupt normal splicing process of the pre-mRNA by altering various splicing regulatory signals. This study aimed to explore the potential impact of SNVs in COL17A1 geneon splicing events, with the ultimate aim of improving the prediction of disease prognosis. Here, we analyzed 703 SNVs including 446 exonic variants and 257 intronic variants in the COL17A1 gene using bioinformatics tools and identified candidate variants that may induce splicing alterations via minigene assays. Our study identified that, among eight candidate variants, six variants (c.1139 C > T, c.1834G > A, c.3198 C > T, c.202 + 6T > G, c.1222 + 4 A > G, c.3071-5G > A) induced splicing alterations by interfering with the recognition of classical splice sites or disrupting the ratio of exonic splicing enhancers/exonic splicing silencers, or both. This study emphasizes the necessity of assessing the effects of SNVs on at the mRNA level, aiding accurate characterization of COL17A1 variants and enabling the development of personalized treatment options.

Gauge fixing for sequence-function relationships

Quantitative models of sequence-function relationships are ubiquitous in computational biology, e.g., for modeling the DNA binding of transcription factors or the fitness landscapes of proteins. Interpreting these models, however, is complicated by the fact that the values of model parameters can often be changed without affecting model predictions. Before the values of model parameters can be meaningfully interpreted, one must remove these degrees of freedom (called "gauge freedoms" in physics) by imposing additional constraints (a process called "fixing the gauge"). However, strategies for fixing the gauge of sequence-function relationships have received little attention. Here we derive an analytically tractable family of gauges for a large class of sequence-function relationships. These gauges are derived in the context of models with all-order interactions, but an important subset of these gauges can be applied to diverse types of models, including additive models, pairwise-interaction models, and models with higher-order interactions. Many commonly used gauges are special cases of gauges within this family. We demonstrate the utility of this family of gauges by showing how different choices of gauge can be used both to explore complex activity landscapes and to reveal simplified models that are approximately correct within localized regions of sequence space. The results provide practical gauge-fixing strategies and demonstrate the utility of gauge-fixing for model exploration and interpretation.

Inference and visualization of complex genotype-phenotype maps with gpmap-tools

Multiplex assays of variant effect (MAVEs) allow the functional characterization of an unprecedented number of sequence variants in both gene regulatory regions and protein coding sequences. This has enabled the study of nearly complete combinatorial libraries of mutational variants and revealed the widespread influence of higher-order genetic interactions that arise when multiple mutations are combined. However, the lack of appropriate tools for exploratory analysis of this high-dimensional data limits our overall understanding of the main qualitative properties of complex genotype-phenotype maps. To fill this gap, we have developed gpmap-tools (https://github.com/cmarti/gpmap-tools), a python library that integrates Gaussian process models for inference, phenotypic imputation, and error estimation from incomplete and noisy MAVE data and collections of natural sequences, together with methods for summarizing patterns of higher-order epistasis and non-linear dimensionality reduction techniques that allow visualization of genotype-phenotype maps containing up to millions of genotypes. Here, we used gpmap-tools to study the genotype-phenotype map of the Shine-Dalgarno sequence, a motif that modulates binding of the 16S rRNA to the 5' untranslated region (UTR) of mRNAs through base pair complementarity during translation initiation in prokaryotes. We inferred full combinatorial landscapes containing 262,144 different sequences from the sequences of 5,311 5'UTRs in the E. coli genome and from experimental MAVE data. Visualizations of the inferred landscapes were largely consistent with each other, and unveiled a simple molecular mechanism underlying the highly epistatic genotype-phenotype map of the Shine-Dalgarno sequence.

LUC7 proteins define two major classes of 5' splice sites in animals and plants

Mutation or deletion of the U1 snRNP-associated factor LUC7L2 is associated with myeloid neoplasms, and knockout of LUC7L2 alters cellular metabolism. Here, we show that members of the LUC7 protein family differentially regulate two major classes of 5' splice sites (5'SS) and broadly regulate mRNA splicing in both human cell lines and leukemias with LUC7L2 copy number variation. We describe distinctive 5'SS features of exons impacted by the three human LUC7 paralogs: LUC7L2 and LUC7L enhance splicing of "right-handed" 5'SS with stronger consensus matching on the intron side of the near invariant /GU, while LUC7L3 enhances splicing of "left-handed" 5'SS with stronger consensus matching upstream of the /GU. We validated our model of sequence-specific 5'SS regulation both by mutating splice sites and swapping domains between human LUC7 proteins. Evolutionary analysis indicates that the LUC7L2/LUC7L3 subfamilies evolved before the split between animals and plants. Analysis of Arabidopsis thaliana mutants confirmed that plant LUC7 orthologs possess similar specificity to their human counterparts, indicating that 5'SS regulation by LUC7 proteins is highly conserved.

RNA splicing: a split consensus reveals two major 5' splice site classes

The established consensus sequence for human 5' splice sites masks the presence of two major splice site classes defined by preferential base-pairing potentials with either U5 snRNA loop 1 or the U6 snRNA ACAGA box. The two 5' splice site classes are separable in genome sequences, sensitized by specific genotypes and associated with splicing complexity. The two classes reflect the commitment to 5' splice site usage occurring primarily during 5' splice site transfer to U6 snRNA. Separating the human 5' splice site consensus into its two major constituents can help us understand fundamental features of eukaryote genome architecture and splicing mechanisms and inform treatment design for diseases caused by genetic variation affecting splicing.

Systematic analysis of the target recognition and repression by the Pumilio proteins

RNA binding proteins orchestrate the post-transcriptional fate of RNA molecules, but the principles of their action remain poorly understood. Pumilio (PUM) proteins bind 3' UTRs of mRNAs and lead to mRNA decay. To comprehensively map the determinants of recognition of sequences by PUM proteins in cells and to study the binding outcomes, we developed a massively parallel RNA assay that profiled thousands of PUM-binding sites in cells undergoing various perturbations or RNA immunoprecipitation. By studying fragments from the NORAD long non-coding RNA, we find two features that antagonize repression by PUM proteins - G/C rich sequences, particularly those upstream of the PUM recognition element, and binding of FAM120A, which limits the repression elicited by PUM-binding sites. We also find that arrays of PUM sites separated by 8-12 bases offer particularly strong repression and use them to develop a particularly sensitive reporter for PUM repression. In contrast, PUM sites separated by shorter linkers, such as some of those found in NORAD, exhibit strong activity interdependence, likely mediated by competition between PUM binding and formation of strong secondary structures. Overall, our findings expand our understanding of the determinants of PUM protein activity in human cells.

Integrated Biochemical and Computational Methods for Deciphering RNA-Processing Codes

RNA processing involves steps such as capping, splicing, polyadenylation, modification, and nuclear export. These steps are essential for transforming genetic information in DNA into proteins and contribute to RNA diversity and complexity. Many biochemical methods have been developed to profile and quantify RNAs, as well as to identify the interactions between RNAs and RNA-binding proteins (RBPs), especially when coupled with high-throughput sequencing technologies. With the rapid accumulation of diverse data, it is crucial to develop computational methods to convert the big data into biological knowledge. In particular, machine learning and deep learning models are commonly utilized to learn the rules or codes governing the transformation from DNA sequences to intriguing RNAs based on manually designed or automatically extracted features. When precise enough, the RNA codes can be incredibly useful for predicting RNA products, decoding the molecular mechanisms, forecasting the impact of disease variants on RNA processing events, and identifying driver mutations. In this review, we systematically summarize the biochemical and computational methods for deciphering five important RNA codes related to alternative splicing, alternative polyadenylation, RNA localization, RNA modifications, and RBP binding. For each code, we review the main types of experimental methods used to generate training data, as well as the key features, strategic model structures, and advantages of representative tools. We also discuss the challenges encountered in developing predictive models using large language models and extensive domain knowledge. Additionally, we highlight useful resources and propose ways to improve computational tools for studying RNA codes.

Decoding biology with massively parallel reporter assays and machine learning

Massively parallel reporter assays (MPRAs) are powerful tools for quantifying the impacts of sequence variation on gene expression. Reading out molecular phenotypes with sequencing enables interrogating the impact of sequence variation beyond genome scale. Machine learning models integrate and codify information learned from MPRAs and enable generalization by predicting sequences outside the training data set. Models can provide a quantitative understanding of cis-regulatory codes controlling gene expression, enable variant stratification, and guide the design of synthetic regulatory elements for applications from synthetic biology to mRNA and gene therapy. This review focuses on cis-regulatory MPRAs, particularly those that interrogate cotranscriptional and post-transcriptional processes: alternative splicing, cleavage and polyadenylation, translation, and mRNA decay.

OpenASO: RNA Rescue - designing splice-modulating antisense oligonucleotides through community science

Splice-modulating antisense oligonucleotides (ASOs) are precision RNA-based drugs that are becoming an established modality to treat human disease. Previously, we reported the discovery of ASOs that target a novel, putative intronic RNA structure to rescue splicing of multiple pathogenic variants of F8 exon 16 that cause hemophilia A. However, the conventional approach to discovering splice-modulating ASOs is both laborious and expensive. Here, we describe an alternative paradigm that integrates data-driven RNA structure prediction and community science to discover splice-modulating ASOs. Using a splicing-deficient pathogenic variant of F8 exon 16 as a model, we show that 25% of the top-scoring molecules designed in the Eterna OpenASO challenge have a statistically significant impact on enhancing exon 16 splicing. Additionally, we show that a distinct combination of ASOs designed by Eterna players can additively enhance the inclusion of the splicing-deficient exon 16 variant. Together, our data suggests that crowdsourcing designs from a community of citizen scientists may accelerate the discovery of splice-modulating ASOs with potential to treat human disease.

A sequential binding mechanism for 5' splice site recognition and modulation for the human U1 snRNP

Splice site recognition is essential for defining the transcriptome. Drugs like risdiplam and branaplam change how human U1 snRNP recognizes particular 5' splice sites (5'SS) and promote U1 snRNP binding and splicing at these locations. Despite the therapeutic potential of 5'SS modulators, the complexity of their interactions and snRNP substrates have precluded defining a mechanism for 5'SS modulation. We have determined a sequential binding mechanism for modulation of -1A bulged 5'SS by branaplam using a combination of ensemble kinetic measurements and colocalization single molecule spectroscopy (CoSMoS). Our mechanism establishes that U1-C protein binds reversibly to U1 snRNP, and branaplam binds to the U1 snRNP/U1-C complex only after it has engaged with a -1A bulged 5'SS. Obligate orders of binding and unbinding explain how reversible branaplam interactions cause formation of long-lived U1 snRNP/5'SS complexes. Branaplam targets a ribonucleoprotein, not only an RNA duplex, and its action depends on fundamental properties of 5'SS recognition.

U6 snRNA m6A modification is required for accurate and efficient splicing of C. elegans and human pre-mRNAs

pre-mRNA splicing is a critical feature of eukaryotic gene expression. Both cis- and trans-splicing rely on accurately recognising splice site sequences by spliceosomal U snRNAs and associated proteins. Spliceosomal snRNAs carry multiple RNA modifications with the potential to affect different stages of pre-mRNA splicing. Here, we show that the conserved U6 snRNA m6A methyltransferase METT-10 is required for accurate and efficient cis- and trans-splicing of C. elegans pre-mRNAs. The absence of METT-10 in C. elegans and METTL16 in humans primarily leads to alternative splicing at 5' splice sites with an adenosine at +4 position. In addition, METT-10 is required for splicing of weak 3' cis- and trans-splice sites. We identified a significant overlap between METT-10 and the conserved splicing factor SNRNP27K in regulating 5' splice sites with +4A. Finally, we show that editing endogenous 5' splice site +4A positions to +4U restores splicing to wild-type positions in a mett-10 mutant background, supporting a direct role for U6 snRNA m6A modification in 5' splice site recognition. We conclude that the U6 snRNA m6A modification is important for accurate and efficient pre-mRNA splicing.

RNA molecules display distinctive organization at nuclear speckles

RNA molecules often play critical roles in assisting the formation of membraneless organelles in eukaryotic cells. Yet, little is known about the organization of RNAs within membraneless organelles. Here, using super-resolution imaging and nuclear speckles as a model system, we demonstrate that different sequence domains of RNA transcripts exhibit differential spatial distributions within speckles. Specifically, we image transcripts containing a region enriched in binding motifs of serine/arginine-rich (SR) proteins and another region enriched in binding motifs of heterogeneous nuclear ribonucleoproteins (hnRNPs). We show that these transcripts localize to the outer shell of speckles, with the SR motif-rich region localizing closer to the speckle center relative to the hnRNP motif-rich region. Further, we identify that this intra-speckle RNA organization is driven by the strength of RNA-protein interactions inside and outside speckles. Our results hint at novel functional roles of nuclear speckles and likely other membraneless organelles in organizing RNA substrates for biochemical reactions.

An interpretable model of pre-mRNA splicing for animal and plant genes

Pre-mRNA splicing is a fundamental step in gene expression, conserved across eukaryotes, in which the spliceosome recognizes motifs at the 3' and 5' splice sites (SSs), excises introns, and ligates exons. SS recognition and pairing is often influenced by protein splicing factors (SFs) that bind to splicing regulatory elements (SREs). Here, we describe SMsplice, a fully interpretable model of pre-mRNA splicing that combines models of core SS motifs, SREs, and exonic and intronic length preferences. We learn models that predict SS locations with 83 to 86% accuracy in fish, insects, and plants and about 70% in mammals. Learned SRE motifs include both known SF binding motifs and unfamiliar motifs, and both motif classes are supported by genetic analyses. Our comparisons across species highlight similarities between non-mammals, increased reliance on intronic SREs in plant splicing, and a greater reliance on SREs in mammalian splicing.

The diversity of splicing modifiers acting on A-1 bulged 5'-splice sites reveals rules for rational drug design

Pharmacological modulation of RNA splicing by small molecules is an emerging facet of drug discovery. In this context, the SMN2 splicing modifier SMN-C5 was used as a prototype to understand the mode of action of small molecule splicing modifiers and propose the concept of 5'-splice site bulge repair. In this study, we combined in vitro binding assays and structure determination by NMR spectroscopy to identify the binding modes of four other small molecule splicing modifiers that switch the splicing of either the SMN2 or the HTT gene. Here, we determined the solution structures of risdiplam, branaplam, SMN-CX and SMN-CY bound to the intermolecular RNA helix epitope containing an unpaired adenine within the G-2A-1G+1U+2 motif of the 5'-splice site. Despite notable differences in their scaffolds, risdiplam, SMN-CX, SMN-CY and branaplam contact the RNA epitope similarly to SMN-C5, suggesting that the 5'-splice site bulge repair mechanism can be generalised. These findings not only deepen our understanding of the chemical diversity of splicing modifiers that target A-1 bulged 5'-splice sites, but also identify common pharmacophores required for modulating 5'-splice site selection with small molecules.

A Sequential Binding Mechanism for 5' Splice Site Recognition and Modulation for the Human U1 snRNP

Splice site recognition is essential for defining the transcriptome. Drugs like risdiplam and branaplam change how U1 snRNP recognizes particular 5' splice sites (5'SS) and promote U1 snRNP binding and splicing at these locations. Despite the therapeutic potential of 5'SS modulators, the complexity of their interactions and snRNP substrates have precluded defining a mechanism for 5'SS modulation. We have determined a sequential binding mechanism for modulation of -1A bulged 5'SS by branaplam using a combination of ensemble kinetic measurements and colocalization single molecule spectroscopy (CoSMoS). Our mechanism establishes that U1-C protein binds reversibly to U1 snRNP, and branaplam binds to the U1 snRNP/U1-C complex only after it has engaged a -1A bulged 5'SS. Obligate orders of binding and unbinding explain how reversible branaplam interactions cause formation of long-lived U1 snRNP/5'SS complexes. Branaplam is a ribonucleoprotein, not RNA duplex alone, targeting drug whose action depends on fundamental properties of 5'SS recognition.

Specificity, synergy, and mechanisms of splice-modifying drugs

Drugs that target pre-mRNA splicing hold great therapeutic potential, but the quantitative understanding of how these drugs work is limited. Here we introduce mechanistically interpretable quantitative models for the sequence-specific and concentration-dependent behavior of splice-modifying drugs. Using massively parallel splicing assays, RNA-seq experiments, and precision dose-response curves, we obtain quantitative models for two small-molecule drugs, risdiplam and branaplam, developed for treating spinal muscular atrophy. The results quantitatively characterize the specificities of risdiplam and branaplam for 5' splice site sequences, suggest that branaplam recognizes 5' splice sites via two distinct interaction modes, and contradict the prevailing two-site hypothesis for risdiplam activity at SMN2 exon 7. The results also show that anomalous single-drug cooperativity, as well as multi-drug synergy, are widespread among small-molecule drugs and antisense-oligonucleotide drugs that promote exon inclusion. Our quantitative models thus clarify the mechanisms of existing treatments and provide a basis for the rational development of new therapies.

The unusual gene architecture of polyubiquitin is created by dual-specific splice sites

BACKGROUND

The removal of introns occurs through the splicing of a 5' splice site (5'ss) with a 3' splice site (3'ss). These two elements are recognized by distinct components of the spliceosome. However, introns in higher eukaryotes contain many matches to the 5' and 3' splice-site motifs that are presumed not to be used.

RESULTS

Here, we find that many of these sites can be used. We also find occurrences of the AGGT motif that can function as either a 5'ss or a 3'ss-previously referred to as dual-specific splice sites (DSSs)-within introns. Analysis of the Sequence Read Archive reveals a 3.1-fold enrichment of DSSs relative to expectation, implying synergy between the ability to function as a 5'ss and 3'ss. Despite this suggested mechanistic advantage, DSSs are 2.7- and 4.7-fold underrepresented in annotated 5' and 3' splice sites. A curious exception is the polyubiquitin gene UBC, which contains a tandem array of DSSs that precisely delimit the boundary of each ubiquitin monomer. The resulting isoforms splice stochastically to include a variable number of ubiquitin monomers. We found no evidence of tissue-specific or feedback regulation but note the 8.4-fold enrichment of DSS-spliced introns in tandem repeat genes suggests a driving role in the evolution of genes like UBC.

CONCLUSIONS

We find an excess of unannotated splice sites and the utilization of DSSs in tandem repeats supports the role of splicing in gene evolution. These findings enhance our understanding of the diverse and complex nature of the splicing process.

Quantitative analysis of transcription start site selection reveals control by DNA sequence, RNA polymerase II activity and NTP levels

Transcription start site (TSS) selection is a key step in gene expression and occurs at many promoter positions over a wide range of efficiencies. Here we develop a massively parallel reporter assay to quantitatively dissect contributions of promoter sequence, nucleoside triphosphate substrate levels and RNA polymerase II (Pol II) activity to TSS selection by 'promoter scanning' in Saccharomyces cerevisiae (Pol II MAssively Systematic Transcript End Readout, 'Pol II MASTER'). Using Pol II MASTER, we measure the efficiency of Pol II initiation at 1,000,000 individual TSS sequences in a defined promoter context. Pol II MASTER confirms proposed critical qualities of S. cerevisiae TSS -8, -1 and +1 positions, quantitatively, in a controlled promoter context. Pol II MASTER extends quantitative analysis to surrounding sequences and determines that they tune initiation over a wide range of efficiencies. These results enabled the development of a predictive model for initiation efficiency based on sequence. We show that genetic perturbation of Pol II catalytic activity alters initiation efficiency mostly independently of TSS sequence, but selectively modulates preference for the initiating nucleotide. Intriguingly, we find that Pol II initiation efficiency is directly sensitive to guanosine-5'-triphosphate levels at the first five transcript positions and to cytosine-5'-triphosphate and uridine-5'-triphosphate levels at the second position genome wide. These results suggest individual nucleoside triphosphate levels can have transcript-specific effects on initiation, representing a cryptic layer of potential regulation at the level of Pol II biochemical properties. The results establish Pol II MASTER as a method for quantitative dissection of transcription initiation in eukaryotes.

Pathogenicity evaluation of variants of uncertain significance at exon-intron junction by splicing assay in patients with Mowat-Wilson syndrome

High-throughput sequencing has identified vast numbers of variants in genetic disorders. However, the significance of variants at the exon-intron junction remains controversial. Even though most cases of Mowat-Wilson syndrome (MOWS) are caused by heterozygous loss-of-function variants in ZEB2, the pathogenicity of variants at exon-intron junction is often indeterminable. We identified four intronic variants in 5/173 patients with clinical suspicion for MOWS, and evaluated their pathogenicity by in vitro analyses. The minigene analysis showed that c.73+2T>G caused most of the transcripts skipping exon 2, while c.916+6T>G led to partial skipping of exon 7. No splicing abnormalities were detected in both c.917-21T>C and c.3067+6A>T. The minigene analysis reproduced the splicing observed in the blood cells of the patient with c.73+2T>G. The degree of the exon skipping was concordant with the severity of MOWS; while the patient with c.73+2T>G was typical MOWS, the patient with c.916+6T>G showed milder phenotype which has been seldom reported. Our results demonstrate that mRNA splicing assays using the minigenes are valuable for determining the clinical significance of intronic variants in patients with not only MOWS but also other genetic diseases with splicing aberrations and may explain atypical or milder cases, such as the current patient.

Conserved and divergent signals in 5' splice site sequences across fungi, metazoa and plants

In eukaryotic organisms the ensemble of 5' splice site sequences reflects the balance between natural nucleotide variability and minimal molecular constraints necessary to ensure splicing fidelity. This compromise shapes the underlying statistical patterns in the composition of donor splice site sequences. The scope of this study was to mine conserved and divergent signals in the composition of 5' splice site sequences. Because 5' donor sequences are a major cue for proper recognition of splice sites, we reasoned that statistical regularities in their composition could reflect the biological functionality and evolutionary history associated with splicing mechanisms. Results: We considered a regularized maximum entropy modeling framework to mine for non-trivial two-site correlations in donor sequence datasets corresponding to 30 different eukaryotes. For each analyzed species, we identified minimal sets of two-site coupling patterns that were able to replicate, at a given regularization level, the observed one-site and two-site frequencies in donor sequences. By performing a systematic and comparative analysis of 5'splice sites we showed that lineage information could be traced from joint di-nucleotide probabilities. We were able to identify characteristic two-site coupling patterns for plants and animals, and propose that they may echo differences in splicing regulation previously reported between these groups.

Sequence variations affect the 5' splice site selection of plant introns

Introns are noncoding sequences spliced out of pre-mRNAs by the spliceosome to produce mature mRNAs. The 5' ends of introns mostly begin with GU and have a conserved sequence motif of AG/GUAAGU that could base-pair with the core sequence of U1 snRNA of the spliceosome. Intriguingly, ∼ 1% of introns in various eukaryotic species begin with GC. This occurrence could cause misannotation of genes; however, the underlying splicing mechanism is unclear. We analyzed the sequences around the intron 5' splice site (ss) in Arabidopsis (Arabidopsis thaliana) and found sequences at the GC intron ss are much more stringent than those of GT introns. Mutational analysis at various positions of the intron 5' ss revealed that although mutations impair base pairing, different mutations at the same site can have different effects, suggesting that steric hindrance also affects splicing. Moreover, mutations of 5' ss often activate a hidden ss nearby. Our data suggest that the 5' ss is selected via a competition between the major ss and the nearby minor ss. This work not only provides insights into the splicing mechanism of intron 5' ss but also improves the accuracy of gene annotation and the study of the evolution of intron 5' ss.

Deciphering hERG Mutation in Long QT Syndrome Type 2 Using Antisense Oligonucleotide-Mediated Techniques: Lessons from Cystic Fibrosis

Long QT syndrome type 2 (LQT2) is a genetic disorder caused by mutations in the KCNH2 gene, also known as the human ether-a-go-go-related gene (hERG). Over 30% of hERG mutations result in a premature termination codon (PTC) that triggers a process called nonsense-mediated mRNA decay (NMD), where the mRNA transcript is degraded. NMD is a quality control mechanism that removes faulty mRNA to prevent the translation of truncated proteins. Recent advances in antisense oligonucleotide (ASO) technology in the field of cystic fibrosis (CF) have yielded significant progress, including the ASO-mediated comprehensive characterization of key NMD factors and exon-skipping therapy. These advances have contributed to our understanding of the role of PTC-containing mutations in disease phenotypes and have also led to the development of potentially useful therapeutic strategies. Historically, studies of CF have provided valuable insights for the research on LQT2, particularly concerning increasing the expression of hERG. In this article, we outline the current state of knowledge regarding ASO, NMD, and hERG and discuss the introduction of ASO technology in the CF to elucidate the pathogenic mechanisms through targeting NMD. We also discuss the potential clinical therapeutic benefits and limitations of ASO for the management of LQT2. By drawing on lessons learned from CF research, we explore the potential translational values of these advances into LQT2 studies.

Regulation of pre-mRNA splicing: roles in physiology and disease, and therapeutic prospects

The removal of introns from mRNA precursors and its regulation by alternative splicing are key for eukaryotic gene expression and cellular function, as evidenced by the numerous pathologies induced or modified by splicing alterations. Major recent advances have been made in understanding the structures and functions of the splicing machinery, in the description and classification of physiological and pathological isoforms and in the development of the first therapies for genetic diseases based on modulation of splicing. Here, we review this progress and discuss important remaining challenges, including predicting splice sites from genomic sequences, understanding the variety of molecular mechanisms and logic of splicing regulation, and harnessing this knowledge for probing gene function and disease aetiology and for the design of novel therapeutic approaches.

Alternative mRNA Splicing and Promising Therapies in Cancer

Cancer is among the leading causes of mortality worldwide. While considerable attention has been given to genetic and epigenetic sources of cancer-specific cellular activities, the role of alternative mRNA splicing has only recently received attention as a major contributor to cancer initiation and progression. The distribution of alternate mRNA splicing variants in cancer cells is different from their non-cancer counterparts, and cancer cells are more sensitive than non-cancer cells to drugs that target components of the splicing regulatory network. While many of the alternatively spliced mRNAs in cancer cells may represent "noise" from splicing dysregulation, certain recurring splicing variants have been shown to contribute to tumor progression. Some pathogenic splicing disruption events result from mutations in cis-acting splicing regulatory sequences in disease-associated genes, while others may result from shifts in balance among naturally occurring alternate splicing variants among mRNAs that participate in cell cycle progression and the regulation of apoptosis. This review provides examples of cancer-related alternate splicing events resulting from each step of mRNA processing and the promising therapies that may be used to address them.

Scalable Functional Assays for the Interpretation of Human Genetic Variation

Scalable sequence-function studies have enabled the systematic analysis and cataloging of hundreds of thousands of coding and noncoding genetic variants in the human genome. This has improved clinical variant interpretation and provided insights into the molecular, biophysical, and cellular effects of genetic variants at an astonishing scale and resolution across the spectrum of allele frequencies. In this review, we explore current applications and prospects for the field and outline the principles underlying scalable functional assay design, with a focus on the study of single-nucleotide coding and noncoding variants.

m6A modification of U6 snRNA modulates usage of two major classes of pre-mRNA 5' splice site

Alternative splicing of messenger RNAs is associated with the evolution of developmentally complex eukaryotes. Splicing is mediated by the spliceosome, and docking of the pre-mRNA 5' splice site into the spliceosome active site depends upon pairing with the conserved ACAGA sequence of U6 snRNA. In some species, including humans, the central adenosine of the ACAGA box is modified by N6 methylation, but the role of this m6A modification is poorly understood. Here, we show that m6A modified U6 snRNA determines the accuracy and efficiency of splicing. We reveal that the conserved methyltransferase, FIONA1, is required for Arabidopsis U6 snRNA m6A modification. Arabidopsis fio1 mutants show disrupted patterns of splicing that can be explained by the sequence composition of 5' splice sites and cooperative roles for U5 and U6 snRNA in splice site selection. U6 snRNA m6A influences 3' splice site usage. We generalise these findings to reveal two major classes of 5' splice site in diverse eukaryotes, which display anti-correlated interaction potential with U5 snRNA loop 1 and the U6 snRNA ACAGA box. We conclude that U6 snRNA m6A modification contributes to the selection of degenerate 5' splice sites crucial to alternative splicing.

A forward genetic screen in C. elegans identifies conserved residues of spliceosomal proteins PRP8 and SNRNP200/BRR2 with a role in maintaining 5' splice site identity

The spliceosome undergoes extensive rearrangements as it assembles onto precursor messenger RNAs. In the earliest assembly step, U1snRNA identifies the 5' splice site. However, U1snRNA leaves the spliceosome relatively early in assembly, and 5' splice site identity is subsequently maintained through interactions with U6snRNA, protein factor PRP8, and other components during the rearrangements that build the catalytic site. Using a forward genetic screen in Caenorhabditis elegans, we have identified suppressors of a locomotion defect caused by a 5'ss mutation. Here we report three new suppressor alleles from this screen, two in PRP8 and one in SNRNP200/BRR2. mRNASeq studies of these suppressor strains indicate that they also affect specific native alternative 5'ss, especially for suppressor PRP8 D1549N. A strong suppressor at the unstructured N-terminus of SNRNP200, N18K, indicates a novel role for this region. By examining distinct changes in the splicing of native genes, examining double mutants between suppressors, comparing these new suppressors to previously identified splicing suppressors from yeast, and mapping conserved suppressor residues onto cryoEM structural models of assembling human spliceosomes, we conclude that there are multiple interactions at multiple stages in spliceosome assembly responsible for maintaining the initial 5'ss identified by U1snRNA for entry into the catalytic core.

A massively parallel reporter assay reveals focused and broadly encoded RNA localization signals in neurons

Asymmetric subcellular mRNA localization allows spatial regulation of gene expression and functional compartmentalization. In neurons, localization of specific mRNAs to neurites is essential for cellular functioning. However, it is largely unknown how transcript sorting works in a sequence-specific manner. Here, we combined subcellular transcriptomics and massively parallel reporter assays and tested ∼50 000 sequences for their ability to localize to neurites. Mapping the localization potential of >300 genes revealed two ways neurite targeting can be achieved: focused localization motifs and broadly encoded localization potential. We characterized the interplay between RNA stability and localization and identified motifs able to bias localization towards neurite or soma as well as the trans-acting factors required for their action. Based on our data, we devised machine learning models that were able to predict the localization behavior of novel reporter sequences. Testing this predictor on native mRNA sequencing data showed good agreement between predicted and observed localization potential, suggesting that the rules uncovered by our MPRA also apply to the localization of native full-length transcripts.

Higher-order epistasis and phenotypic prediction

One core goal of genetics is to systematically understand the mapping between the DNA sequence of an organism (genotype) and its measurable characteristics (phenotype). Understanding this mapping is often challenging because of interactions between mutations, where the result of combining several different mutations can be very different than the sum of their individual effects. Here we provide a statistical framework for modeling complex genetic interactions of this type. The key idea is to ask how fast the effects of mutations change when introducing the same mutation in increasingly distant genetic backgrounds. We then propose a model for phenotypic prediction that takes into account this tendency for the effects of mutations to be more similar in nearby genetic backgrounds.

Contemporary high-throughput mutagenesis experiments are providing an increasingly detailed view of the complex patterns of genetic interaction that occur between multiple mutations within a single protein or regulatory element. By simultaneously measuring the effects of thousands of combinations of mutations, these experiments have revealed that the genotype–phenotype relationship typically reflects not only genetic interactions between pairs of sites but also higher-order interactions among larger numbers of sites. However, modeling and understanding these higher-order interactions remains challenging. Here we present a method for reconstructing sequence-to-function mappings from partially observed data that can accommodate all orders of genetic interaction. The main idea is to make predictions for unobserved genotypes that match the type and extent of epistasis found in the observed data. This information on the type and extent of epistasis can be extracted by considering how phenotypic correlations change as a function of mutational distance, which is equivalent to estimating the fraction of phenotypic variance due to each order of genetic interaction (additive, pairwise, three-way, etc.). Using these estimated variance components, we then define an empirical Bayes prior that in expectation matches the observed pattern of epistasis and reconstruct the genotype–phenotype mapping by conducting Gaussian process regression under this prior. To demonstrate the power of this approach, we present an application to the antibody-binding domain GB1 and also provide a detailed exploration of a dataset consisting of high-throughput measurements for the splicing efficiency of human pre-mRNA 5′ splice sites, for which we also validate our model predictions via additional low-throughput experiments.

Modeling splicing outcome by combining 5'ss strength and splicing regulatory elements

Correct pre-mRNA processing in higher eukaryotes vastly depends on splice site recognition. Beyond conserved 5'ss and 3'ss motifs, splicing regulatory elements (SREs) play a pivotal role in this recognition process. Here, we present in silico designed sequences with arbitrary a priori prescribed splicing regulatory HEXplorer properties that can be concatenated to arbitrary length without changing their regulatory properties. We experimentally validated in silico predictions in a massively parallel splicing reporter assay on more than 3000 sequences and exemplarily identified some SRE binding proteins. Aiming at a unified 'functional splice site strength' encompassing both U1 snRNA complementarity and impact from neighboring SREs, we developed a novel RNA-seq based 5'ss usage landscape, mapping the competition of pairs of high confidence 5'ss and neighboring exonic GT sites along HBond and HEXplorer score coordinate axes on human fibroblast and endothelium transcriptome datasets. These RNA-seq data served as basis for a logistic 5'ss usage prediction model, which greatly improved discrimination between strong but unused exonic GT sites and annotated highly used 5'ss. Our 5'ss usage landscape offers a unified view on 5'ss and SRE neighborhood impact on splice site recognition, and may contribute to improved mutation assessment in human genetics.

Synthetic introns enable splicing factor mutation-dependent targeting of cancer cells

Many cancers carry recurrent, change-of-function mutations affecting RNA splicing factors. Here, we describe a method to harness this abnormal splicing activity to drive splicing factor mutation-dependent gene expression to selectively eliminate tumor cells. We engineered synthetic introns that were efficiently spliced in cancer cells bearing SF3B1 mutations, but unspliced in otherwise isogenic wild-type cells, to yield mutation-dependent protein production. A massively parallel screen of 8,878 introns delineated ideal intronic size and mapped elements underlying mutation-dependent splicing. Synthetic introns enabled mutation-dependent expression of herpes simplex virus-thymidine kinase (HSV-TK) and subsequent ganciclovir (GCV)-mediated killing of SF3B1-mutant leukemia, breast cancer, uveal melanoma and pancreatic cancer cells in vitro, while leaving wild-type cells unaffected. Delivery of synthetic intron-containing HSV-TK constructs to leukemia, breast cancer and uveal melanoma cells and GCV treatment in vivo significantly suppressed the growth of these otherwise lethal xenografts and improved mouse host survival. Synthetic introns provide a means to exploit tumor-specific changes in RNA splicing for cancer gene therapy.

MAVE-NN: learning genotype-phenotype maps from multiplex assays of variant effect

Multiplex assays of variant effect (MAVEs) are a family of methods that includes deep mutational scanning experiments on proteins and massively parallel reporter assays on gene regulatory sequences. Despite their increasing popularity, a general strategy for inferring quantitative models of genotype-phenotype maps from MAVE data is lacking. Here we introduce MAVE-NN, a neural-network-based Python package that implements a broadly applicable information-theoretic framework for learning genotype-phenotype maps-including biophysically interpretable models-from MAVE datasets. We demonstrate MAVE-NN in multiple biological contexts, and highlight the ability of our approach to deconvolve mutational effects from otherwise confounding experimental nonlinearities and noise.

QRNAstruct: a method for extracting secondary structural features of RNA via regression with biological activity

Recent technological advances have enabled the generation of large amounts of data consisting of RNA sequences and their functional activity. Here, we propose a method for extracting secondary structure features that affect the functional activity of RNA from sequence–activity data. Given pairs of RNA sequences and their corresponding bioactivity values, our method calculates position-specific structural features of the input RNA sequences, considering every possible secondary structure of each RNA. A Ridge regression model is trained using the structural features as feature vectors and the bioactivity values as response variables. Optimized model parameters indicate how secondary structure features affect bioactivity. We used our method to extract intramolecular structural features of bacterial translation initiation sites and self-cleaving ribozymes, and the intermolecular features between rRNAs and Shine–Dalgarno sequences and between U1 RNAs and splicing sites. We not only identified known structural features but also revealed more detailed insights into structure–activity relationships than previously reported. Importantly, the datasets we analyzed here were obtained from different experimental systems and differed in size, sequence length and similarity, and number of RNA molecules involved, demonstrating that our method is applicable to various types of data consisting of RNA sequences and bioactivity values.

A genetic screen in C. elegans reveals roles for KIN17 and PRCC in maintaining 5' splice site identity

Pre-mRNA splicing is an essential step of eukaryotic gene expression carried out by a series of dynamic macromolecular protein/RNA complexes, known collectively and individually as the spliceosome. This series of spliceosomal complexes define, assemble on, and catalyze the removal of introns. Molecular model snapshots of intermediates in the process have been created from cryo-EM data, however, many aspects of the dynamic changes that occur in the spliceosome are not fully understood. Caenorhabditis elegans follow the GU-AG rule of splicing, with almost all introns beginning with 5’ GU and ending with 3’ AG. These splice sites are identified early in the splicing cycle, but as the cycle progresses and “custody” of the pre-mRNA splice sites is passed from factor to factor as the catalytic site is built, the mechanism by which splice site identity is maintained or re-established through these dynamic changes is unclear. We performed a genetic screen in C. elegans for factors that are capable of changing 5’ splice site choice. We report that KIN17 and PRCC are involved in splice site choice, the first functional splicing role proposed for either of these proteins. Previously identified suppressors of cryptic 5’ splicing promote distal cryptic GU splice sites, however, mutations in KIN17 and PRCC instead promote usage of an unusual proximal 5’ splice site which defines an intron beginning with UU, separated by 1nt from a GU donor. We performed high-throughput mRNA sequencing analysis and found that mutations in PRCC, and to a lesser extent KIN17, changed alternative 5’ splice site usage at native sites genome-wide, often promoting usage of nearby non-consensus sites. Our work has uncovered both fine and coarse mechanisms by which the spliceosome maintains splice site identity during the complex assembly process.

Pre-messenger RNA splicing is an important regulator of eukaryotic gene expression, changing the content, frame, and functionality of both coding and non-coding transcripts. Our understanding of how the spliceosome chooses where to cut has focused on the initial identification of splice sites. However, our results suggest that the spliceosome also relies on other components in later steps to maintain the identity of the splice donor sites. We are currently in the midst of a “resolution revolution”, with ever-clearer cryo-EM snapshots of stalled complexes, allowing researchers to visualize moments in time in the splicing cycle. These models are illuminating, but do not always elucidate mechanistic functioning of a highly dynamic ribonucleoprotein complex. Therefore, our lab takes a complementary approach, using the power of genetics in a multicellular animal to gain functional insights into the spliceosome. Using a C.elegans genetic screen, we have found novel functional splicing roles for two proteins, KIN17 and PRCC. Mutations in PRCC in particular promote nearby alternative 5’ splice sites at native loci. This work improves our understanding of how the spliceosome maintains the identity of where to cut the pre-mRNA, and thus how genes are expressed and used in multicellular animals.

Systematic characterization of short intronic splicing-regulatory elements in SMN2 pre-mRNA

Intronic splicing enhancers and silencers (ISEs and ISSs) are two groups of splicing-regulatory elements (SREs) that play critical roles in determining splice-site selection, particularly for alternatively spliced introns or exons. SREs are often short motifs; their mutation or dysregulation of their cognate proteins frequently causes aberrant splicing and results in disease. To date, however, knowledge about SRE sequences and how they regulate splicing remains limited. Here, using an SMN2 minigene, we generated a complete pentamer-sequence library that comprises all possible combinations of 5 nucleotides in intron 7, at a fixed site downstream of the 5′ splice site. We systematically analyzed the effects of all 1023 mutant pentamers on exon 7 splicing, in comparison to the wild-type minigene, in HEK293 cells. Our data show that the majority of pentamers significantly affect exon 7 splicing: 584 of them are stimulatory and 230 are inhibitory. To identify actual SREs, we utilized a motif set enrichment analysis (MSEA), from which we identified groups of stimulatory and inhibitory SRE motifs. We experimentally validated several strong SREs in SMN1/2 and other minigene settings. Our results provide a valuable resource for understanding how short RNA sequences regulate splicing. Many novel SREs can be explored further to elucidate their mechanism of action.

Splice site proximity influences alternative exon definition

Alternative splicing enables higher eukaryotes to expand mRNA diversity from a finite number of genes through highly combinatorial splice site selection mechanisms that are influenced by the sequence of competing splice sites, cis-regulatory elements binding trans-acting factors, the length of exons and introns harbouring alternative splice sites and RNA secondary structures at putative splice junctions. To test the hypothesis that the intron definition or exon definition modes of splice site recognition direct the selection of alternative splice patterns, we created a database of alternative splice site usage (ALTssDB). When alternative splice sites are embedded within short introns (intron definition), the 5' and 3' splice sites closest to each other across the intron preferentially pair, consistent with previous observations. However, when alternative splice sites are embedded within large flanking introns (exon definition), the 5' and 3' splice sites closest to each other across the exon are preferentially selected. Thus, alternative splicing decisions are influenced by the intron and exon definition modes of splice site recognition. The results demonstrate that the spliceosome pairs splice sites that are closest in proximity within the unit of initial splice site selection.

Principles and correction of 5'-splice site selection

In Eukarya, immature mRNA transcripts (pre-mRNA) often contain coding sequences, or exons, interleaved by non-coding sequences, or introns. Introns are removed upon splicing, and further regulation of the retained exons leads to alternatively spliced mRNA. The splicing reaction requires the stepwise assembly of the spliceosome, a macromolecular machine composed of small nuclear ribonucleoproteins (snRNPs). This review focuses on the early stage of spliceosome assembly, when U1 snRNP defines each intron 5'-splice site (5'ss) in the pre-mRNA. We first introduce the splicing reaction and the impact of alternative splicing on gene expression regulation. Thereafter, we extensively discuss splicing descriptors that influence the 5'ss selection by U1 snRNP, such as sequence determinants, and interactions mediated by U1-specific proteins or U1 small nuclear RNA (U1 snRNA). We also include examples of diseases that affect the 5'ss selection by U1 snRNP, and discuss recent therapeutic advances that manipulate U1 snRNP 5'ss selectivity with antisense oligonucleotides and small-molecule splicing switches.

High-Throughput Quantitation of Yeast uORF Regulatory Impacts Using FACS-uORF

Eukaryotic upstream Open Reading Frames (uORFs) are short translated regions found in many transcript leaders (Barbosa et al. PLoS Genet 9:e1003529, 2013; Zhang et al. Trends Biochem Sci 44:782-794, 2019). Modern transcript annotations and ribosome profiling studies have found thousands of AUG-initiated uORFs, and many more uORFs initiated by near-cognate codons (CUG, GUG, UUG, etc.). Their translation generally decreases the expression of the main encoded protein by preventing ribosomes from reaching the main ORF of each gene, and by inducing nonsense mediated decay (NMD) through premature termination. Under many cellular stresses, uORF containing transcripts are de-repressed due to decreased translation initiation (Young et al. J Biol Chem 291:16927-16935, 2016). Traditional experimental evaluation of uORFs involves comparing expression from matched uORF-containing and start-codon mutated transcript leader reporter plasmids. This tedious process has precluded analysis of large numbers of uORFs. We recently used FACS-uORF to simultaneously assay thousands of yeast uORFs in order to evaluate the impact of codon usage on their functions (Lin et al. Nucleic Acids Res 2:1-10, 2019). Here, we provide a step-by-step protocol for this assay.

Cross talk between the upstream exon-intron junction and Prp2 facilitates splicing of non-consensus introns

Splicing of mRNA precursors is essential in the regulation of gene expression. U2AF65 recognizes the poly-pyrimidine tract and helps in the recognition of the branch point. Inactivation of fission yeast U2AF65 (Prp2) blocks splicing of most, but not all, pre-mRNAs, for reasons that are not understood. Here, we have determined genome-wide the splicing efficiency of fission yeast cells as they progress into synchronous meiosis in the presence or absence of functional Prp2. Our data indicate that in addition to the splicing elements at the 3' end of any intron, the nucleotides immediately upstream the intron will determine whether Prp2 is required or dispensable for splicing. By changing those nucleotides in any given intron, we regulate its Prp2 dependency. Our results suggest a model in which Prp2 is required for the coordinated recognition of both intronic ends, placing Prp2 as a key regulatory element in the determination of the exon-intron boundaries.

Discovery of a pre-mRNA structural scaffold as a contributor to the mammalian splicing code

The specific recognition of splice signals at or near exon-intron junctions is not explained by their weak conservation and instead is postulated to require a multitude of features embedded in the pre-mRNA strand. We explored the possibility of 3D structural scaffold of AdML-a model pre-mRNA substrate-guiding early spliceosomal components to the splice signal sequences. We find that mutations in the non-cognate splice signal sequences impede recruitment of early spliceosomal components due to disruption of the global structure of the pre-mRNA. We further find that the pre-mRNA segments potentially interacting with the early spliceosomal component U1 snRNP are distributed across the intron, that there is a spatial proximity of 5' and 3' splice sites within the pre-mRNA scaffold, and that an interplay exists between the structural scaffold and splicing regulatory elements in recruiting early spliceosomal components. These results suggest that early spliceosomal components can recognize a 3D structural scaffold beyond the short splice signal sequences, and that in our model pre-mRNA, this scaffold is formed across the intron involving the major splice signals. This provides a conceptual basis to analyze the contribution of recognizable 3D structural scaffolds to the splicing code across the mammalian transcriptome.

U5 snRNA Interactions With Exons Ensure Splicing Precision

Imperfect conservation of human pre-mRNA splice sites is necessary to produce alternative isoforms. This flexibility is combined with the precision of the message reading frame. Apart from intron-termini GU_AG and the branchpoint A, the most conserved are the exon-end guanine and +5G of the intron start. Association between these guanines cannot be explained solely by base-pairing with U1 snRNA in the early spliceosome complex. U6 succeeds U1 and pairs +5G in the pre-catalytic spliceosome, while U5 binds the exon end. Current U5 snRNA reconstructions by CryoEM cannot explain the conservation of the exon-end G. Conversely, human mutation analyses show that guanines of both exon termini can suppress splicing mutations. Our U5 hypothesis explains the mechanism of splicing precision and the role of these conserved guanines in the pre-catalytic spliceosome. We propose: (1) optimal binding register for human exons and U5-the exon junction positioned at U5Loop1 C₃₉|C₃₈; (2) common mechanism for base-pairing of human U5 snRNA with diverse exons and bacterial Ll.LtrB intron with new loci in retrotransposition-guided by base pair geometry; and (3) U5 plays a significant role in specific exon recognition in the pre-catalytic spliceosome. Statistical analyses showed increased U5 Watson-Crick pairs with the 5'exon in the absence of +5G at the intron start. In 5'exon positions -3 and -5, this effect is specific to U5 snRNA rather than U1 snRNA of the early spliceosome. Increased U5 Watson-Crick pairs with 3'exon position +1 coincide with substitutions of the conserved -3C at the intron 3'end. Based on mutation and X-ray evidence, we propose that -3C pairs with U2 G₃₁ juxtaposing the branchpoint and the 3'intron end. The intron-termini pair, formed in the pre-catalytic spliceosome to be ready for transition after branching, and the early involvement of the 3'intron end ensure that the 3'exon contacts U5 in the pre-catalytic complex. We suggest that splicing precision is safeguarded cooperatively by U5, U6, and U2 snRNAs that stabilize the pre-catalytic complex by Watson-Crick base pairing. In addition, our new U5 model explains the splicing effect of exon-start +1G mutations: U5 Watson-Crick pairs with exon +2C/+3G strongly promote exon inclusion. We discuss potential applications for snRNA therapeutics and gene repair by reverse splicing.

Chicken C/EBPζ gene: Expression profiles, association analysis, and identification of functional variants for abdominal fat

CCAAT enhancer binding protein ζ (C/EBPζ) plays an important role in adipose proliferation and differentiation in humans. However, very little is known about the effect of C/EBPζ on the growth and development of adipose tissues in domesticated animals. The present study attempted to investigate the mRNA expression profiles of chicken C/EBPζ in a variety of tissues; analyze the association of its variants with abdominal fat; and identify the functional variants for abdominal fat. The tissue expression profiles revealed that C/EBPζ was highly expressed in 19 tissues obtained from broilers. The expression level of C/EBPζ in fat broilers was significantly lower than that in lean broilers in the duodenum, ileum, cecum, kidney, pectoral muscle, and liver (P < 0.05). Among 170 polymorphic loci of C/EBPζ, 9 single nucleotide polymorphisms (SNPs) demonstrated a significant association with chicken abdominal fat traits (P < 0.05) as well as significant discrepancies in their allelic frequencies between fat and lean birds. Particularly, only C/EBPζ g.7085A>C exhibited significant correlation with abdominal fat traits (P < 0.00015) using the Bonferroni method. The results revealed that, in preadipocyte immortalized cells (ICPI), the luciferase activity of the A allele of g.7085A>C locus was remarkably stronger than that of the C allele (P < 0.05). In silico analysis showed that g.7085A>C locus was located in the binding region of the transcription factor SOX5, which possesses the ability to transform C/EBPζ transcription efficiency through binding with SOX5. In summary, the data obtained from this study suggested that C/EBPζ is a potential candidate gene responsible for abdominal fat deposition in chicken and that g.7085A>C is a functional SNP that can be promisingly leveraged for marker assisted selection (MAS) in future chicken breeding programs.

Hotspot exons are common targets of splicing perturbations

High-throughput splicing assays have demonstrated that many exonic variants can disrupt splicing; however, splice-disrupting variants distribute non-uniformly across genes. We propose the existence of exons that are particularly susceptible to splice-disrupting variants, which we refer to as hotspot exons. Hotspot exons are also more susceptible to splicing perturbation through drug treatment and knock-down of RNA-binding proteins. We develop a classifier for exonic splice-disrupting variants and use it to infer hotspot exons. We estimate that 1400 exons in the human genome are hotspots. Using panels of splicing reporters, we demonstrate how the ability of an exon to tolerate a mutation is inversely proportional to the strength of its neighboring splice sites.

Splicing-disrupting mutations are linked to diseases. By employing a machine learning approach, the authors show that certain exons, termed hotspot exons, are enriched for splicing-disruption variants and susceptible to splicing perturbations.

Biology of the mRNA Splicing Machinery and Its Dysregulation in Cancer Providing Therapeutic Opportunities

Dysregulation of messenger RNA (mRNA) processing—in particular mRNA splicing—is a hallmark of cancer. Compared to normal cells, cancer cells frequently present aberrant mRNA splicing, which promotes cancer progression and treatment resistance. This hallmark provides opportunities for developing new targeted cancer treatments. Splicing of precursor mRNA into mature mRNA is executed by a dynamic complex of proteins and small RNAs called the spliceosome. Spliceosomes are part of the supraspliceosome, a macromolecular structure where all co-transcriptional mRNA processing activities in the cell nucleus are coordinated. Here we review the biology of the mRNA splicing machinery in the context of other mRNA processing activities in the supraspliceosome and present current knowledge of its dysregulation in lung cancer. In addition, we review investigations to discover therapeutic targets in the spliceosome and give an overview of inhibitors and modulators of the mRNA splicing process identified so far. Together, this provides insight into the value of targeting the spliceosome as a possible new treatment for lung cancer.

Comprehensive characterization of alternative splicing in renal cell carcinoma

Irregular splicing was associated with tumor formation and progression in renal cell carcinoma (RCC) and many other cancers. By using splicing data in the TCGA SpliceSeq database, RCC subtype classification was performed and splicing features and their correlations with clinical course, genetic variants, splicing factors, pathways activation and immune heterogeneity were systemically analyzed. In this research, alternative splicing was found useful for classifying RCC subtypes. Splicing inefficiency with upregulated intron retention and cassette exon was associated with advanced conditions and unfavorable overall survival of patients with RCC. Splicing characteristics like splice site strength, guanine and cytosine content and exon length may be important factors disrupting splicing balance in RCC. Other than cis-acting and trans-acting regulation, alternative splicing also differed in races and tissue types and is also affected by mutation conditions, pathway settings and the response to environmental changes. Severe irregular splicing in tumor not only indicated terrible intra-cellular homeostasis, but also changed the activity of cancer-associated pathways by different splicing effects including isoforms switching and expression regulation. Moreover, irregular splicing and splicing-associated antigens were involved in immune reprograming and formation of immunosuppressive tumor microenvironment. Overall, we have described several clinical and molecular features in RCC splicing subtypes, which may be important for patient management and targeting treatment.

Massively Parallel Reporter Assays: Defining Functional Psychiatric Genetic Variants Across Biological Contexts

Neuropsychiatric phenotypes have long been known to be influenced by heritable risk factors, directly confirmed by the past decade of genetic studies that have revealed specific genetic variants enriched in disease cohorts. However, the initial hope that a small set of genes would be responsible for a given disorder proved false. The more complex reality is that a given disorder may be influenced by myriad small-effect noncoding variants and/or by rare but severe coding variants, many de novo. Noncoding genomic sequences-for which molecular functions cannot usually be inferred-harbor a large portion of these variants, creating a substantial barrier to understanding higher-order molecular and biological systems of disease. Fortunately, novel genetic technologies-scalable oligonucleotide synthesis, RNA sequencing, and CRISPR (clustered regularly interspaced short palindromic repeats)-have opened novel avenues to experimentally identify biologically significant variants en masse. Massively parallel reporter assays (MPRAs) are an especially versatile technique resulting from such innovations. MPRAs are powerful molecular genetics tools that can be used to screen thousands of untranscribed or untranslated sequences and their variants for functional effects in a single experiment. This approach, though underutilized in psychiatric genetics, has several useful features for the field. We review methods for assaying putatively functional genetic variants and regions, emphasizing MPRAs and the opportunities they hold for dissection of psychiatric polygenicity. We discuss literature applying functional assays in neurogenetics, highlighting strengths, caveats, and design considerations-especially regarding disease-relevant variables (cell type, neurodevelopment, and sex), and we ultimately propose applications of MPRA to both computational and experimental neurogenetics of polygenic disease risk.

Intronic tRNAs of mitochondrial origin regulate constitutive and alternative splicing

BACKGROUND

The presence of nuclear mitochondrial DNA (numtDNA) has been reported within several nuclear genomes. Next to mitochondrial protein-coding genes, numtDNA sequences also encode for mitochondrial tRNA genes. However, the biological roles of numtDNA remain elusive.

RESULTS

Employing in silico analysis, we identify 281 mitochondrial tRNA homologs in the human genome, which we term nimtRNAs (nuclear intronic mitochondrial-derived tRNAs), being contained within introns of 76 nuclear host genes. Despite base changes in nimtRNAs when compared to their mtRNA homologs, a canonical tRNA cloverleaf structure is maintained. To address potential functions of intronic nimtRNAs, we insert them into introns of constitutive and alternative splicing reporters and demonstrate that nimtRNAs promote pre-mRNA splicing, dependent on the number and positioning of nimtRNA genes and splice site recognition efficiency. A mutational analysis reveals that the nimtRNA cloverleaf structure is required for the observed splicing increase. Utilizing a CRISPR/Cas9 approach, we show that a partial deletion of a single endogenous nimtRNALys within intron 28 of the PPFIBP1 gene decreases inclusion of the downstream-located exon 29 of the PPFIBP1 mRNA. By employing a pull-down approach followed by mass spectrometry, a 3'-splice site-associated protein network is identified, including KHDRBS1, which we show directly interacts with nimtRNATyr by an electrophoretic mobility shift assay.

CONCLUSIONS

We propose that nimtRNAs, along with associated protein factors, can act as a novel class of intronic splicing regulatory elements in the human genome by participating in the regulation of splicing.

Poison Exon Splicing Regulates a Coordinated Network of SR Protein Expression during Differentiation and Tumorigenesis

The RNA isoform repertoire is regulated by splicing factor (SF) expression, and alterations in SF levels are associated with disease. SFs contain ultraconserved poison exon (PE) sequences that exhibit greater identity across species than nearby coding exons, but their physiological role and molecular regulation is incompletely understood. We show that PEs in serine-arginine-rich (SR) proteins, a family of 14 essential SFs, are differentially spliced during induced pluripotent stem cell (iPSC) differentiation and in tumors versus normal tissues. We uncover an extensive cross-regulatory network of SR proteins controlling their expression via alternative splicing coupled to nonsense-mediated decay. We define sequences that regulate PE inclusion and protein expression of the oncogenic SF TRA2β using an RNA-targeting CRISPR screen. We demonstrate location dependency of RS domain activity on regulation of TRA2β-PE using CRISPR artificial SFs. Finally, we develop splice-switching antisense oligonucleotides to reverse the increased skipping of TRA2β-PE detected in breast tumors, altering breast cancer cell viability, proliferation, and migration.

Logomaker: beautiful sequence logos in Python

Summary

Sequence logos are visually compelling ways of illustrating the biological properties of DNA, RNA and protein sequences, yet it is currently difficult to generate and customize such logos within the Python programming environment. Here we introduce Logomaker, a Python API for creating publication-quality sequence logos. Logomaker can produce both standard and highly customized logos from either a matrix-like array of numbers or a multiple-sequence alignment. Logos are rendered as native matplotlib objects that are easy to stylize and incorporate into multi-panel figures.

Availability and implementation

Logomaker can be installed using the pip package manager and is compatible with both Python 2.7 and Python 3.6. Documentation is provided at http://logomaker.readthedocs.io; source code is available at http://github.com/jbkinney/logomaker.