RNA splicing analysis using heterogeneous and large RNA-seq datasets.

The ubiquity of RNA-seq has led to many methods that use RNA-seq data to analyze variations in RNA splicing. However, available methods are not well suited for handling heterogeneous and large datasets. Such datasets scale to thousands of samples across dozens of experimental conditions, exhibit increased variability compared to biological replicates, and involve thousands of unannotated splice variants resulting in increased transcriptome complexity. We describe here a suite of algorithms and tools implemented in the MAJIQ v2 package to address challenges in detection, quantification, and visualization of splicing variations from such datasets. Using both large scale synthetic data and GTEx v8 as benchmark datasets, we assess the advantages of MAJIQ v2 compared to existing methods. We then apply MAJIQ v2 package to analyze differential splicing across 2,335 samples from 13 brain subregions, demonstrating its ability to offer insights into brain subregion-specific splicing regulation.

Evidence for the role of transcription factors in the co-transcriptional regulation of intron retention.

BACKGROUND: Alternative splicing is a widespread regulatory phenomenon that enables a single gene to produce multiple transcripts. Among the different types of alternative splicing, intron retention is one of the least explored despite its high prevalence in both plants and animals. The recent discovery that the majority of splicing is co-transcriptional has led to the finding that chromatin state affects alternative splicing. Therefore, it is plausible that transcription factors can regulate splicing outcomes. RESULTS: We provide evidence for the hypothesis that transcription factors are involved in the regulation of intron retention by studying regions of open chromatin in retained and excised introns. Using deep learning models designed to distinguish between regions of open chromatin in retained introns and non-retained introns, we identified motifs enriched in IR events with significant hits to known human transcription factors. Our model predicts that the majority of transcription factors that affect intron retention come from the zinc finger family. We demonstrate the validity of these predictions using ChIP-seq data for multiple zinc finger transcription factors and find strong over-representation for their peaks in intron retention events. CONCLUSIONS: This work opens up opportunities for further studies that elucidate the mechanisms by which transcription factors affect intron retention and other forms of splicing. AVAILABILITY: Source code available at https://github.com/fahadahaf/chromir.

Detection and targeting of splicing deregulation in pediatric acute myeloid leukemia stem cells.

Pediatric acute myeloid leukemia (pAML) is typified by high relapse rates and a relative paucity of somatic DNA mutations. Although seminal studies show that splicing factor mutations and mis-splicing fuel therapy-resistant leukemia stem cell (LSC) generation in adults, splicing deregulation has not been extensively studied in pAML. Herein, we describe single-cell proteogenomics analyses, transcriptome-wide analyses of FACS-purified hematopoietic stem and progenitor cells followed by differential splicing analyses, dual-fluorescence lentiviral splicing reporter assays, and the potential of a selective splicing modulator, Rebecsinib, in pAML. Using these methods, we discover transcriptomic splicing deregulation typified by differential exon usage. In addition, we discover downregulation of splicing regulator RBFOX2 and CD47 splice isoform upregulation. Importantly, splicing deregulation in pAML induces a therapeutic vulnerability to Rebecsinib in survival, self-renewal, and lentiviral splicing reporter assays. Taken together, the detection and targeting of splicing deregulation represent a potentially clinically tractable strategy for pAML therapy.

A cryptic clue to neurodegeneration?

Antisense oligonucleotides rescue cryptic RNA splicing and neuron regeneration.

Therapeutic potential of CDK11 in cancer.

Human cyclin-dependent kinases (CDKs) direct the progression of the cell cycle and transcription. They are deregulated in tumours, and despite their involvement in the regulation of basic cellular processes, many CDKs are promising targets for cancer therapy. CDK11 is an essential gene for the growth of many malignancies; however, its primary cellular function has been obscure, and the mode-of-action of OTS964, the first CDK11 inhibitor and antiproliferative compound, has been unknown. A recent study has shown that OTS964 prevents spliceosome activation, revealing a key role of CDK11 in the regulation of pre-mRNA splicing. In light of these findings, we discuss the therapeutic potential of CDK11 in cancer.

Peptides that Mimic RS repeats modulate phase separation of SRSF1, revealing a reliance on combined stacking and electrostatic interactions.

Phase separation plays crucial roles in both sustaining cellular function and perpetuating disease states. Despite extensive studies, our understanding of this process is hindered by low solubility of phase-separating proteins. One example of this is found in SR and SR-related proteins. These proteins are characterized by domains rich in arginine and serine (RS domains), which are essential to alternative splicing and in vivo phase separation. However, they are also responsible for a low solubility that has made these proteins difficult to study for decades. Here, we solubilize the founding member of the SR family, SRSF1, by introducing a peptide mimicking RS repeats as a co-solute. We find that this RS-mimic peptide forms interactions similar to those of the protein's RS domain. Both interact with a combination of surface-exposed aromatic residues and acidic residues on SRSF1's RNA Recognition Motifs (RRMs) through electrostatic and cation-pi interactions. Analysis of RRM domains from human SR proteins indicates that these sites are conserved across the protein family. In addition to opening an avenue to previously unavailable proteins, our work provides insight into how SR proteins phase separate and participate in nuclear speckles.

Plant pathogens and symbionts target the plant nucleus.

In plant-microbe interactions, symbionts and pathogens live within plants and attempt to avoid triggering plant defense responses. In order to do so, these microbes have evolved multiple mechanisms that target components of the plant cell nucleus. Rhizobia-induced symbiotic signaling requires the function of specific legume nucleoporins within the nuclear pore complex. Symbiont and pathogen effectors harbor nuclear localization sequences that facilitate movement across nuclear pores, allowing these proteins to target transcription factors that function in defense. Oomycete pathogens introduce proteins that interact with plant pre-mRNA splicing components in order to alter host splicing of defense-related transcripts. Together, these functions indicate that the nucleus is an active site of symbiotic and pathogenic functioning in plant-microbe interactions.

Snapshots of the second-step self-splicing of Tetrahymena ribozyme revealed by cryo-EM.

Group I introns are catalytic RNAs that coordinate two consecutive transesterification reactions for self-splicing. To understand how the group I intron promotes catalysis and coordinates self-splicing reactions, we determine the structures of L-16 Tetrahymena ribozyme in complex with a 5'-splice site analog product and a 3'-splice site analog substrate using cryo-EM. We solve six conformations from a single specimen, corresponding to different splicing intermediates after the first ester-transfer reaction. The structures reveal dynamics during self-splicing, including large conformational changes of the internal guide sequence and the J5/4 junction as well as subtle rearrangements of active-site metals and the hydrogen bond formed between the 2'-OH group of A261 and the N2 group of guanosine substrate. These results help complete a detailed structural and mechanistic view of this paradigmatic group I intron undergoing the second step of self-splicing.

Well-TEMP-seq as a microwell-based strategy for massively parallel profiling of single-cell temporal RNA dynamics.

Single-cell RNA sequencing (scRNA-seq) reveals the transcriptional heterogeneity of cells, but the static snapshots fail to reveal the time-resolved dynamics of transcription. Herein, we develop Well-TEMP-seq, a high-throughput, cost-effective, accurate, and efficient method for massively parallel profiling the temporal dynamics of single-cell gene expression. Well-TEMP-seq combines metabolic RNA labeling with scRNA-seq method Well-paired-seq to distinguish newly transcribed RNAs marked by T-to-C substitutions from pre-existing RNAs in each of thousands of single cells. The Well-paired-seq chip ensures a high single cell/barcoded bead pairing rate (~80%) and the improved alkylation chemistry on beads greatly alleviates chemical conversion-induced cell loss (~67.5% recovery). We further apply Well-TEMP-seq to profile the transcriptional dynamics of colorectal cancer cells exposed to 5-AZA-CdR, a DNA-demethylating drug. Well-TEMP-seq unbiasedly captures the RNA dynamics and outperforms the splicing-based RNA velocity method. We anticipate that Well-TEMP-seq will be broadly applicable to unveil the dynamics of single-cell gene expression in diverse biological processes.

The Role of m6A Modifications in B-Cell Development and B-Cell-Related Diseases.

B cells are a class of professional antigen-presenting cells that produce antibodies to mediate humoral immune response and participate in immune regulation. m6A modification is the most common RNA modification in mRNA; it involves almost all aspects of RNA metabolism and can affect RNA splicing, translation, stability, etc. This review focuses on the B-cell maturation process as well as the role of three m6A modification-related regulators-writer, eraser, and reader-in B-cell development and B-cell-related diseases. The identification of genes and modifiers that contribute to immune deficiency may shed light on regulatory requirements for normal B-cell development and the underlying mechanism of some common diseases.

Integrated analysis of genomic and transcriptomic data for the discovery of splice-associated variants in cancer.

Somatic mutations within non-coding regions and even exons may have unidentified regulatory consequences that are often overlooked in analysis workflows. Here we present RegTools ( www.regtools.org ), a computationally efficient, free, and open-source software package designed to integrate somatic variants from genomic data with splice junctions from bulk or single cell transcriptomic data to identify variants that may cause aberrant splicing. We apply RegTools to over 9000 tumor samples with both tumor DNA and RNA sequence data. RegTools discovers 235,778 events where a splice-associated variant significantly increases the splicing of a particular junction, across 158,200 unique variants and 131,212 unique junctions. To characterize these somatic variants and their associated splice isoforms, we annotate them with the Variant Effect Predictor, SpliceAI, and Genotype-Tissue Expression junction counts and compare our results to other tools that integrate genomic and transcriptomic data. While many events are corroborated by the aforementioned tools, the flexibility of RegTools also allows us to identify splice-associated variants in known cancer drivers, such as TP53, CDKN2A, and B2M, and other genes.

SpliceVault predicts the precise nature of variant-associated mis-splicing.

Even for essential splice-site variants that are almost guaranteed to alter mRNA splicing, no current method can reliably predict whether exon-skipping, cryptic activation or multiple events will result, greatly complicating clinical interpretation of pathogenicity. Strikingly, ranking the four most common unannotated splicing events across 335,663 reference RNA-sequencing (RNA-seq) samples (300K-RNA Top-4) predicts the nature of variant-associated mis-splicing with 92% sensitivity. The 300K-RNA Top-4 events correctly identify 96% of exon-skipping events and 86% of cryptic splice sites for 140 clinical cases subject to RNA testing, showing higher sensitivity and positive predictive value than SpliceAI. Notably, RNA re-analyses showed we had missed 300K-RNA Top-4 events for several clinical cases tested before the development of this empirical predictive method. Simply, mis-splicing events that happen around a splice site in RNA-seq data are those most likely to be activated by a splice-site variant. The SpliceVault web portal allows users easy access to 300K-RNA for informed splice-site variant interpretation and classification.

Temporal-iCLIP captures co-transcriptional RNA-protein interactions.

Dynamic RNA-protein interactions govern the co-transcriptional packaging of RNA polymerase II (RNAPII)-derived transcripts. Yet, our current understanding of this process in vivo primarily stems from steady state analysis. To remedy this, we here conduct temporal-iCLIP (tiCLIP), combining RNAPII transcriptional synchronisation with UV cross-linking of RNA-protein complexes at serial timepoints. We apply tiCLIP to the RNA export adaptor, ALYREF; a component of the Nuclear Exosome Targeting (NEXT) complex, RBM7; and the nuclear cap binding complex (CBC). Regardless of function, all tested factors interact with nascent RNA as it exits RNAPII. Moreover, we demonstrate that the two transesterification steps of pre-mRNA splicing temporally separate ALYREF and RBM7 binding to splicing intermediates, and that exon-exon junction density drives RNA 5'end binding of ALYREF. Finally, we identify underappreciated steps in snoRNA 3'end processing performed by RBM7. Altogether, our data provide a temporal view of RNA-protein interactions during the early phases of transcription.

[The role of jigsaw karyotype analysis in the teaching of chromosomal recognition].

Karyotype analysis is the basic method in cytogenetics, and is also recognized as the "gold standard" for diagnosing chromosomal disorders. The teaching and training for traditional karyotyping analysis is time-consuming and even boring. The individual's ability for mastering the chromosome morphology can vary greatly. Therefore, it is necessary to improve the teaching method. On the basis of the traditional method, we have added auxiliary analysis software during the teaching. This type of splicing karyotype teaching has increased the students' interest and improved their ability for karyotyping, allowing them to quickly remember the characteristic bands of chromosomes. Through enhanced memory of a large number of karyotypic images, the students' ability to recognize individual chromosomes has improved.

Studying the connection between SF3B1 and four types of cancer by analyzing networks constructed based on published research.

Splicing factor 3B subunit 1 (SF3B1) is the largest component of SF3b protein complex which is involved in the pre-mRNA splicing mechanism. Somatic mutations of SF3B1 were shown to be associated with aberrant splicing, producing abnormal transcripts that drive cancer development and/or prognosis. In this study, we focus on the relationship between SF3B1 and four types of cancer, namely myelodysplastic syndrome (MDS), acute myeloid leukemia (AML), and chronic lymphocytic leukemia (CLL) and breast cancer (BC). For this purpose, we identified from the Pubmed library only articles which mentioned SF3B1 in connection with the investigated types of cancer for the period 2007 to 2018 to reveal how the connection has developed over time. We left out all published articles which mentioned SF3B1 in other contexts. We retrieved the target articles and investigated the association between SF3B1 and the mentioned four types of cancer. For this we utilized some of the publicly available databases to retrieve gene/variant/disease information related to SF3B1. We used the outcome to derive and analyze a variety of complex networks that reflect the correlation between the considered diseases and variants associated with SF3B1. The results achieved based on the analyzed articles and reported in this article illustrated that SF3B1 is associated with hematologic malignancies, such as MDS, AML, and CLL more than BC. We found that different gene networks may be required for investigating the impact of mutant splicing factors on cancer development based on the target cancer type. Additionally, based on the literature analyzed in this study, we highlighted and summarized what other researchers have reported as the set of genes and cellular pathways that are affected by aberrant splicing in cancerous cells.

SpliceAI-visual: a free online tool to improve SpliceAI splicing variant interpretation.

SpliceAI is an open-source deep learning splicing prediction algorithm that has demonstrated in the past few years its high ability to predict splicing defects caused by DNA variations. However, its outputs present several drawbacks: (1) although the numerical values are very convenient for batch filtering, their precise interpretation can be difficult, (2) the outputs are delta scores which can sometimes mask a severe consequence, and (3) complex delins are most often not handled. We present here SpliceAI-visual, a free online tool based on the SpliceAI algorithm, and show how it complements the traditional SpliceAI analysis. First, SpliceAI-visual manipulates raw scores and not delta scores, as the latter can be misleading in certain circumstances. Second, the outcome of SpliceAI-visual is user-friendly thanks to the graphical presentation. Third, SpliceAI-visual is currently one of the only SpliceAI-derived implementations able to annotate complex variants (e.g., complex delins). We report here the benefits of using SpliceAI-visual and demonstrate its relevance in the assessment/modulation of the PVS1 classification criteria. We also show how SpliceAI-visual can elucidate several complex splicing defects taken from the literature but also from unpublished cases. SpliceAI-visual is available as a Google Colab notebook and has also been fully integrated in a free online variant interpretation tool, MobiDetails ( https://mobidetails.iurc.montp.inserm.fr/MD ).

From tuberculosis bedside to bench: UBE2B splicing as a potential biomarker and its regulatory mechanism.

Alternative splicing (AS) is an important approach for pathogens and hosts to remodel transcriptome. However, tuberculosis (TB)-related AS has not been sufficiently explored. Here we presented the first landscape of TB-related AS by long-read sequencing, and screened four AS events (S100A8-intron1-retention intron, RPS20-exon1-alternaitve promoter, KIF13B-exon4-skipping exon (SE) and UBE2B-exon7-SE) as potential biomarkers in an in-house cohort-1. The validations in an in-house cohort-2 (2274 samples) and public datasets (1557 samples) indicated that the latter three AS events are potential promising biomarkers for TB diagnosis, but not for TB progression and prognosis. The excellent performance of classifiers further underscored the diagnostic value of these three biomarkers. Subgroup analyses indicated that UBE2B-exon7-SE splicing was not affected by confounding factors and thus had relatively stable performance. The splicing of UBE2B-exon7-SE can be changed by heat-killed mycobacterium tuberculosis through inhibiting SRSF1 expression. After heat-killed mycobacterium tuberculosis stimulation, 231 ubiquitination proteins in macrophages were differentially expressed, and most of them are apoptosis-related proteins. Taken together, we depicted a global TB-associated splicing profile, developed TB-related AS biomarkers, demonstrated an optimal application scope of target biomarkers and preliminarily elucidated mycobacterium tuberculosis-host interaction from the perspective of splicing, offering a novel insight into the pathophysiology of TB.

Alternative Splicing in the Regulatory Circuit of Plant Temperature Response.

As sessile organisms, plants have evolved complex mechanisms to rapidly respond to ever-changing ambient temperatures. Temperature response in plants is modulated by a multilayer regulatory network, including transcriptional and post-transcriptional regulations. Alternative splicing (AS) is an essential post-transcriptional regulatory mechanism. Extensive studies have confirmed its key role in plant temperature response, from adjustment to diurnal and seasonal temperature changes to response to extreme temperatures, which has been well documented by previous reviews. As a key node in the temperature response regulatory network, AS can be modulated by various upstream regulations, such as chromatin modification, transcription rate, RNA binding proteins, RNA structure and RNA modifications. Meanwhile, a number of downstream mechanisms are affected by AS, such as nonsense-mediated mRNA decay (NMD) pathway, translation efficiency and production of different protein variants. In this review, we focus on the links between splicing regulation and other mechanisms in plant temperature response. Recent advances regarding how AS is regulated and the following consequences in gene functional modulation in plant temperature response will be discussed. Substantial evidence suggests that a multilayer regulatory network integrating AS in plant temperature response has been unveiled.

Alzheimer's Disease-Associated Alternative Splicing of CD33 Is Regulated by the HNRNPA Family Proteins.

Genetic variations of CD33 have been implicated as a susceptibility factor of Alzheimer's disease (AD). A polymorphism on exon 2 of CD33, rs12459419, affects the alternative splicing of this exon. The minor allele is associated with a reduced risk of AD and promotes the skipping of exon 2 to produce a shorter CD33 isoform lacking the extracellular ligand-binding domain, leading to decreased suppressive signaling on microglial activity. Therefore, factors that regulate the splicing of exon 2 may alter the disease-associated properties of CD33. Herein, we sought to identify the regulatory proteins of CD33 splicing. Using a panel of RNA-binding proteins and a human CD33 minigene, we found that exon 2 skipping of CD33 was promoted by HNRNPA1. Although the knockdown of HNRNPA1 alone did not reduce exon 2 skipping, simultaneous knockdown of HNRNPA1 together with that of HNRNPA2B1 and HNRNPA3 promoted exon 2 inclusion, suggesting functional redundancy among HNRNPA proteins. Similar redundant regulation by HNRNPA proteins was observed in endogenous CD33 of THP-1 and human microglia-like cells. Although mouse Cd33 showed a unique splicing pattern of exon 2, we confirmed that HNRNPA1 promoted the skipping of this exon. Collectively, our results revealed novel regulatory relationships between CD33 and HNRNPA proteins.