Widespread Expansion of Protein Interaction Capabilities by Alternative Splicing

The alternative proteome in neurobiology

Translation involves the biosynthesis of a protein sequence following the decoding of the genetic information embedded in a messenger RNA (mRNA). Typically, the eukaryotic mRNA was considered to be inherently monocistronic, but this paradigm is not in agreement with the translational landscape of cells, tissues, and organs. Recent ribosome sequencing (Ribo-seq) and proteomics studies show that, in addition to currently annotated reference proteins (RefProt), other proteins termed alternative proteins (AltProts), and microproteins are encoded in regions of mRNAs thought to be untranslated or in transcripts annotated as non-coding. This experimental evidence expands the repertoire of functional proteins within a cell and potentially provides important information on biological processes. This review explores the hitherto overlooked alternative proteome in neurobiology and considers the role of AltProts in pathological and healthy neuromolecular processes.

Construction and analysis of sample-specific driver modules for breast cancer

BACKGROUND

It is important to understand the functional impact of somatic mutation and methylation aberration at an individual level to implement precision medicine. Recent studies have demonstrated that the perturbation of gene interaction networks can provide a fundamental link between genotype (or epigenotype) and phenotype. However, it is unclear how individual mutations affect the function of biological networks, especially for individual methylation aberration. To solve this, we provided a sample-specific driver module construction method using the 2-order network theory and hub-gene theory to identify individual perturbation networks driven by mutations or methylation aberrations.

RESULTS

Our method integrated multi-omics of breast cancer, including genomics, transcriptomics, epigenomics and interactomics, and provided new insight into the synergistic collaboration between methylation and mutation at an individual level. A common driver pattern of breast cancer was identified from a novel perspective of a driver module, which is correlated to the occurrence and development of breast cancer. The constructed driver module reflects the survival prognosis and degree of malignancy among different subtypes of breast cancer. Additionally, subtype-specific driver modules were identified.

CONCLUSIONS

This study explores the driver module of individual cancer, and contributes to a better understanding of the mechanism of breast cancer driven by the mutations and methylation variations from the point of view of the driver network. This work will help identify new therapeutic combinations of gene mutations and drugs in humans.

Bridging the splicing gap in human genetics with long-read RNA sequencing: finding the protein isoform drivers of disease

Aberrant splicing underlies many human diseases, including cancer, cardiovascular diseases and neurological disorders. Genome-wide mapping of splicing quantitative trait loci (sQTLs) has shown that genetic regulation of alternative splicing is widespread. However, identification of the corresponding isoform or protein products associated with disease-associated sQTLs is challenging with short-read RNA-seq, which cannot precisely characterize full-length transcript isoforms. Furthermore, contemporary sQTL interpretation often relies on reference transcript annotations, which are incomplete. Solutions to these issues may be found through integration of newly emerging long-read sequencing technologies. Long-read sequencing offers the capability to sequence full-length mRNA transcripts and, in some cases, to link sQTLs to transcript isoforms containing disease-relevant protein alterations. Here, we provide an overview of sQTL mapping approaches, the use of long-read sequencing to characterize sQTL effects on isoforms, the linkage of RNA isoforms to protein-level functions and comment on future directions in the field. Based on recent progress, long-read RNA sequencing promises to be part of the human disease genetics toolkit to discover and treat protein isoforms causing rare and complex diseases.

Stimulus-specific remodeling of the neuronal transcriptome through nuclear intron-retaining transcripts

The nuclear envelope has long been considered primarily a physical barrier separating nuclear and cytosolic contents. More recently, nuclear compartmentalization has been shown to have additional regulatory functions in controlling gene expression. A sizeable proportion of protein-coding mRNAs is more prevalent in the nucleus than in the cytosol, suggesting regulated mRNA trafficking to the cytosol, but the mechanisms underlying controlled nuclear mRNA retention remain unclear. Here, we provide a comprehensive map of the subcellular localization of mRNAs in mature mouse cortical neurons, and reveal that transcripts retained in the nucleus comprise the majority of stable intron-retaining mRNAs. Systematically probing the fate of nuclear transcripts upon neuronal stimulation, we found opposite effects on sub-populations of transcripts: while some are targeted for degradation, others complete splicing to generate fully mature mRNAs that are exported to the cytosol and mediate rapid increases in protein levels. Finally, different forms of stimulation mobilize distinct groups of intron-retaining transcripts, with this selectivity arising from the activation of specific signaling pathways. Overall, our findings uncover a cue-specific control of intron retention as a major regulator of acute remodeling of the neuronal transcriptome.

Tissue Specificity Based Isoform Function Prediction

Alternative splicing enables a gene spliced into different isoforms and hence protein variants. Identifying individual functions of these isoforms help deciphering the functional diversity of proteins. Although much efforts have been made for automatic gene function prediction, few efforts have been moved toward computational isoform function prediction, mainly due to the unavailable (or scanty) functional annotations of isoforms. Existing efforts directly combine multiple RNA-seq datasets without account of the important tissue specificity of alternative splicing. To bridge this gap, we introduce a novel approach called TS-Isofun to predict the functions of isoforms by integrating multiple functional association networks with respect to tissue specificity. TS-Isofun first constructs tissue-specific isoform functional association networks using multiple RNA-seq datasets from tissue-wise. Next, TS-Isofun assigns weights to these networks and models the tissue specificity by selectively integrating them with adaptive weights. It then introduces a joint matrix factorization-based data fusion model to leverage the integrated network, gene-level data and functional annotations of genes to infer the functions of isoforms. To achieve coherent weight assignment and isoform function prediction, TS-Isofun jointly optimizes the weights of individual networks and the isoform function prediction in a unified objective function. Experimental results show that TS-Isofun significantly outperforms state-of-the-art methods and the account of tissue specificity contributes to more accurate isoform function prediction.

Systematic exploration of dynamic splicing networks reveals conserved multistage regulators of neurogenesis

Alternative splicing (AS) is a critical regulatory layer; yet, factors controlling functionally coordinated splicing programs during developmental transitions are poorly understood. Here, we employ a screening strategy to identify factors controlling dynamic splicing events important for mammalian neurogenesis. Among previously unknown regulators, Rbm38 acts widely to negatively control neural AS, in part through interactions mediated by the established repressor of splicing, Ptbp1. Puf60, a ubiquitous factor, is surprisingly found to promote neural splicing patterns. This activity requires a conserved, neural-differential exon that remodels Puf60 co-factor interactions. Ablation of this exon rewires distinct AS networks in embryonic stem cells and at different stages of mouse neurogenesis. Single-cell transcriptome analyses further reveal distinct roles for Rbm38 and Puf60 isoforms in establishing neuronal identity. Our results describe important roles for previously unknown regulators of neurogenesis and establish how an alternative exon in a widely expressed splicing factor orchestrates temporal control over cell differentiation.

A roadmap for the functional annotation of protein families: a community perspective

Over the last 25 years, biology has entered the genomic era and is becoming a science of 'big data'. Most interpretations of genomic analyses rely on accurate functional annotations of the proteins encoded by more than 500 000 genomes sequenced to date. By different estimates, only half the predicted sequenced proteins carry an accurate functional annotation, and this percentage varies drastically between different organismal lineages. Such a large gap in knowledge hampers all aspects of biological enterprise and, thereby, is standing in the way of genomic biology reaching its full potential. A brainstorming meeting to address this issue funded by the National Science Foundation was held during 3-4 February 2022. Bringing together data scientists, biocurators, computational biologists and experimentalists within the same venue allowed for a comprehensive assessment of the current state of functional annotations of protein families. Further, major issues that were obstructing the field were identified and discussed, which ultimately allowed for the proposal of solutions on how to move forward.

Transcriptome variation in human tissues revealed by long-read sequencing

Regulation of transcript structure generates transcript diversity and plays an important role in human disease1-7. The advent of long-read sequencing technologies offers the opportunity to study the role of genetic variation in transcript structure8-16. In this Article, we present a large human long-read RNA-seq dataset using the Oxford Nanopore Technologies platform from 88 samples from Genotype-Tissue Expression (GTEx) tissues and cell lines, complementing the GTEx resource. We identified just over 70,000 novel transcripts for annotated genes, and validated the protein expression of 10% of novel transcripts. We developed a new computational package, LORALS, to analyse the genetic effects of rare and common variants on the transcriptome by allele-specific analysis of long reads. We characterized allele-specific expression and transcript structure events, providing new insights into the specific transcript alterations caused by common and rare genetic variants and highlighting the resolution gained from long-read data. We were able to perturb the transcript structure upon knockdown of PTBP1, an RNA binding protein that mediates splicing, thereby finding genetic regulatory effects that are modified by the cellular environment. Finally, we used this dataset to enhance variant interpretation and study rare variants leading to aberrant splicing patterns.

Alternative splicing as a source of phenotypic diversity

A major goal of evolutionary genetics is to understand the genetic processes that give rise to phenotypic diversity in multicellular organisms. Alternative splicing generates multiple transcripts from a single gene, enriching the diversity of proteins and phenotypic traits. It is well established that alternative splicing contributes to key innovations over long evolutionary timescales, such as brain development in bilaterians. However, recent developments in long-read sequencing and the generation of high-quality genome assemblies for diverse organisms has facilitated comparisons of splicing profiles between closely related species, providing insights into how alternative splicing evolves over shorter timescales. Although most splicing variants are probably non-functional, alternative splicing is nonetheless emerging as a dynamic, evolutionarily labile process that can facilitate adaptation and contribute to species divergence.

The miR-199a-5p/PD-L1 axis regulates cell proliferation, migration and invasion in follicular thyroid carcinoma

Background

Follicular thyroid carcinoma (FTC) is the second most common cancer of the thyroid and easily develops into distant metastasis. PD-L1 is known to be associated with the carcinogenesis and progression of thyroid carcinoma. Our study aimed to investigate the biological functions of PD-L1 and to identify miRNAs that were responsible for modulating the activity of PD-L1.

Methods

A total of 72 patients with FTC at The Second Affiliated Hospital of Fujian Medical University were enrolled in this retrospective study. Immunohistochemical (IHC) assay was used to measure PD-L1 expression in FTC. The association between PD-L1 expression and clinicopathologic characteristics was evaluated. Bioinformatics analysis, RT–qPCR and western blotting were used to examine the relationships between miR-199a-5p, PD-L1 and Claudin-1. Cell proliferation, migration and invasion were evaluated by using CCK8 and Transwell migration and invasion assays. Target prediction and luciferase reporter assays were performed to verify the binding between miR-199a-5p and PD-L1. Rescue assay was performed to confirm whether PD-L1 downregulation abolished the inhibitory effect of miR-199a-5p.

Results

Among 72 pairs of tumor and normal specimens, the proportion of PD-L1 positive samples was higher in FTC tissues than in normal tissues. The results of ESTIMATE and CIBERSORT illustrated that there was a positive correlation between PD-L1 expression and immune infiltration, especially regulatory T cells and M1 macrophages. Prediction of immunotherapy revealed that patients with high PD-L1 expression might benefit from immune checkpoint inhibitors. Transwell migration and invasion assays showed that PD-L1 downregulation in FTC cells could significantly inhibit cell migration and invasion. The bioinformatics analysis and luciferase activity results indicated that PD-L1 was a potential target of miR-199a-5p. Knockdown of PD-L1 reversed the miR-199a-5p inhibitor mediated promotion effect. In addition, we found that PD-L1 expression was positively correlated with Claudin-1 expression and that miR-199a-5p affected the progression of FTC cells through the negative regulation of PD-L1 and Claudin-1.

Conclusions

Our study revealed that PD-L1 expression was elevated in FTC and was closely associated with tumor aggressiveness and progression. MiR-199a-5p has a functional role in the progression and metastasis of FTC by regulating PD-L1 and Claudin-1 expression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09838-0.

New Views of Old Proteins: Clarifying the Enigmatic Proteome

All human diseases involve proteins, yet our current tools to characterize and quantify them are limited. To better elucidate proteins across space, time, and molecular composition, we provide a >10 years of projection for technologies to meet the challenges that protein biology presents. With a broad perspective, we discuss grand opportunities to transition the science of proteomics into a more propulsive enterprise. Extrapolating recent trends, we describe a next generation of approaches to define, quantify, and visualize the multiple dimensions of the proteome, thereby transforming our understanding and interactions with human disease in the coming decade.

Uncovering the impacts of alternative splicing on the proteome with current omics techniques

The high-throughput sequencing of cellular RNAs has underscored a broad effect of isoform diversification through alternative splicing on the transcriptome. Moreover, the differential production of transcript isoforms from gene loci has been recognized as a critical mechanism in cell differentiation, organismal development, and disease. Yet, the extent of the impact of alternative splicing on protein production and cellular function remains a matter of debate. Multiple experimental and computational approaches have been developed in recent years to address this question. These studies have unveiled how molecular changes at different steps in the RNA processing pathway can lead to differences in protein production and have functional effects. New and emerging experimental technologies open exciting new opportunities to develop new methods to fully establish the connection between messenger RNA expression and protein production and to further investigate how RNA variation impacts the proteome and cell function. This article is categorized under: RNA Processing > Splicing Regulation/Alternative Splicing Translation > Regulation RNA Evolution and Genomics > Computational Analyses of RNA.

DeepIII: Predicting Isoform-Isoform Interactions by Deep Neural Networks and Data Fusion

Alternative splicing enables a gene translating into different isoforms and into the corresponding proteoforms, which actually accomplish various biological functions of a living body. Isoform-isoform interactions (IIIs) provide a higher resolution interactome to explore the cellular processes and disease mechanisms than the canonically studied protein-protein interactions (PPIs), which are often recorded at the coarse gene level. The knowledge of IIIs is critical to map pathways, understand protein complexity and functional diversity, but the known IIIs are very scanty. In this paper, we propose a deep learning based method called DeepIII to systematically predict genome-wide IIIs by integrating diverse data sources, including RNA-seq datasets of different human tissues, exon array data, domain-domain interactions (DDIs) of proteins, nucleotide sequences and amino acid sequences. Particularly, DeepIII fuses these data to learn the representation of isoform pairs with a four-layer deep neural networks, and then performs binary classification on the learnt representation to achieve the prediction of IIIs. Experimental results show that DeepIII achieves a superior prediction performance to the state-of-the-art solutions and the III network constructed by DeepIII gives more accurate isoform function prediction. Case studies further confirm that DeepIII can differentiate the individual interaction partners of different isoforms spliced from the same gene. The code and datasets of DeepIII are available at http://mlda.swu.edu.cn/codes.php?name=DeepIII.

Identification of Novel Circular RNAs of the Human Protein Arginine Methyltransferase 1 (PRMT1) Gene, Expressed in Breast Cancer Cells

Circular RNAs (circRNAs) constitute a type of RNA formed through back-splicing. In breast cancer, circRNAs are implicated in tumor onset and progression. Although histone methylation by PRMT1 is largely involved in breast cancer development and metastasis, the effect of circular transcripts deriving from this gene has not been examined. In this study, total RNA was extracted from four breast cancer cell lines and reversely transcribed using random hexamer primers. Next, first- and second-round PCRs were performed using gene-specific divergent primers. Sanger sequencing followed for the determination of the sequence of each novel PRMT1 circRNA. Lastly, bioinformatics analysis was conducted to predict the functions of the novel circRNAs. In total, nine novel circRNAs were identified, comprising both complete and truncated exons of the PRMT1 gene. Interestingly, we demonstrated that the back-splice junctions consist of novel splice sites of the PRMT1 exons. Moreover, the circRNA expression pattern differed among these four breast cancer cell lines. All the novel circRNAs are predicted to act as miRNA and/or protein sponges, while five circRNAs also possess an open reading frame. In summary, we described the complete sequence of nine novel circRNAs of the PRMT1 gene, comprising distinct back-splice junctions and probably having different molecular properties.

HNRNPH1 destabilizes the G-quadruplex structures formed by G-rich RNA sequences that regulate the alternative splicing of an oncogenic fusion transcript

In the presence of physiological monovalent cations, thousands of RNA G-rich sequences can form parallel G-quadruplexes (G4s) unless RNA-binding proteins inhibit, destabilize, or resolve the formation of such secondary RNA structures. Here, we have used a disease-relevant model system to investigate the biophysical properties of the RNA-binding protein HNRNPH1's interaction with G-rich sequences. We demonstrate the importance of two EWSR1-exon 8 G-rich regions in mediating the exclusion of this exon from the oncogenic EWS-FLI1 transcripts expressed in a subset of Ewing sarcomas, using complementary analysis of tumor data, long-read sequencing, and minigene studies. We determined that HNRNPH1 binds the EWSR1-exon 8 G-rich sequences with low nM affinities irrespective of whether in a non-G4 or G4 state but exhibits different kinetics depending on RNA structure. Specifically, HNRNPH1 associates and dissociates from G4-folded RNA faster than the identical sequences in a non-G4 state. Importantly, we demonstrate using gel shift and spectroscopic assays that HNRNPH1, particularly the qRRM1-qRRM2 domains, destabilizes the G4s formed by the EWSR1-exon 8 G-rich sequences in a non-catalytic fashion. Our results indicate that HNRNPH1's binding of G-rich sequences favors the accumulation of RNA in a non-G4 state and that this contributes to its regulation of RNA processing.

ASpediaFI: Functional Interaction Analysis of Alternative Splicing Events

Alternative splicing (AS) regulates biological processes governing phenotypes and diseases. Differential AS (DAS) gene test methods have been developed to investigate important exonic expression from high-throughput datasets. However, the DAS events extracted using statistical tests are insufficient to delineate relevant biological processes. In this study, we developed a novel application, Alternative Splicing Encyclopedia: Functional Interaction (ASpediaFI), to systemically identify DAS events and co-regulated genes and pathways. ASpediaFI establishes a heterogeneous interaction network of genes and their feature nodes (i.e., AS events and pathways) connected by co-expression or pathway gene set knowledge. Next, ASpediaFI explores the interaction network using the random walk with restart algorithm and interrogates the proximity from a query gene set. Finally, ASpediaFI extracts significant AS events, genes, and pathways. To evaluate the performance of our method, we simulated RNA sequencing (RNA-seq) datasets to consider various conditions of sequencing depth and sample size. The performance was compared with that of other methods. Additionally, we analyzed three public datasets of cancer patients or cell lines to evaluate how well ASpediaFI detects biologically relevant candidates. ASpediaFI exhibits strong performance in both simulated and public datasets. Our integrative approach reveals that DAS events that recognize a global co-expression network and relevant pathways determine the functional importance of spliced genes in the subnetwork. ASpediaFI is publicly available at https://bioconductor.org/packages/ASpediaFI.

Alternative splicing of the human rhomboid family-1 gene RHBDF1 inhibits epidermal growth factor receptor activation

The human rhomboid-5 homolog-1 (RHBDF1) is a multi-transmembrane protein present mainly on the endoplasmic reticulum. RHBDF1 has been implicated in the activation of epidermal growth factor receptor (EGFR)-derived cell growth signals and other activities critical to cellular responses to stressful conditions, but details of this activation mechanism are unclear. Here, we report a RHBDF1 mRNA transcript alternative splicing variant X6 (RHBDF1 X6 or RHX6) that antagonizes RHBDF1 activities. We found that while the RHBDF1 gene is marginally expressed in breast tumor-adjacent normal tissues, it is markedly elevated in the tumor tissues. In sharp contrast, the RHX6 mRNA represents the primary RHBDF1 variant in normal breast epithelial cells and tumor-adjacent normal tissues but is diminished in breast cancer cells and tumors. We demonstrate that, functionally, RHX6 acts as an inhibitor of RHBDF1 activities. We show that artificially overexpressing RHX6 in breast cancer cells leads to retarded proliferation, migration, and decreased production of epithelial-mesenchymal transition-related adhesion molecules. Mechanically, RHX6 is able to inhibit the maturation of TACE, a protease that processes pro-TGFα, a pro-ligand of EGFR, and to prevent intracellular transportation of pro-TGFα to the cell surface. Additionally, we show that the production of RHX6 is under the control of the alternative splicing regulator RNA binding motif protein-4 (RBM4). Our findings suggest that differential splicing of the RHBDF1 gene transcript may have a regulatory role in the development of epithelial cell cancers.

Tandem-trapped ion mobility spectrometry/mass spectrometry (tTIMS/MS): a promising analytical method for investigating heterogenous samples

Ion mobility spectrometry/mass spectrometry (IMS/MS) is widely used to study various levels of protein structure. Here, we review the current state of affairs in tandem-trapped ion mobility spectrometry/mass spectrometry (tTIMS/MS). Two different tTIMS/MS instruments are discussed in detail: the first tTIMS/MS instrument, constructed from coaxially aligning two TIMS devices; and an orthogonal tTIMS/MS configuration that comprises an ion trap for irradiation of ions with UV photons. We discuss the various workflows the two tTIMS/MS setups offer and how these can be used to study primary, tertiary, and quaternary structures of protein systems. We also discuss, from a more fundamental perspective, the processes that lead to denaturation of protein systems in tTIMS/MS and how to soften the measurement so that biologically meaningful structures can be characterised with tTIMS/MS. We emphasize the concepts underlying tTIMS/MS to underscore the opportunities tandem-ion mobility spectrometry methods offer for investigating heterogeneous samples.

Identification of Protein Isoforms Using Reference Databases Built from Long and Short Read RNA-Sequencing

Alternative splicing can lead to distinct protein isoforms. These can have different functions in specific cells and tissues or in different developmental stages. In this study, we explored whether transcripts assembled from long read, nanopore-based, direct RNA-sequencing (RNA-seq) could improve the identification of protein isoforms in human K562 cells. By comparing with Illumina-based short read RNA-seq, we showed that a large proportion of Ensembl transcripts (5949/14,326) and genes expressing alternatively spliced transcripts (486/2981) identified with long direct reads were missed by short paired-end reads. By co-analyzing proteomic and transcriptomic data, we also showed that some peptides (826/35,976), proteins (262/3215), and protein isoforms arising from distinct transcript variants (574/1212) identified with isoform-specific peptides via custom long-read-based databases were missed in Illumina-derived databases. Finally, we generated unequivocal peptide evidence for a set of protein isoforms and showed that long read, direct RNA-seq allows the discovery of novel protein isoforms not already in reference databases or custom databases built from short read RNA-seq data. Our analysis highlights the benefits of long read RNA-seq data in the generation of reference databases to increase tandem mass spectrometry (MS/MS) identification of protein isoforms.

ScisorWiz: Visualizing Differential Isoform Expression in Single-Cell Long-Read Data

Summary

RNA isoforms contribute to the diverse functionality of the proteins they encode within the cell. Visualizing how isoform expression differs across cell types and brain regions can inform our understanding of disease and gain or loss of functionality caused by alternative splicing with potential negative impacts. However, the extent to which this occurs in specific cell types and brain regions is largely unknown. This is the kind of information that ScisorWiz plots can provide in an informative and easily communicable manner. ScisorWiz affords its user the opportunity to visualize specific genes across any number of cell types, and provides various sorting options for the user to gain different ways to understand their data. ScisorWiz provides a clear picture of differential isoform expression through various clustering methods and highlights features such as alternative exons and single-nucleotide variants. Tools like ScisorWiz are key for interpreting single-cell isoform sequencing data. This tool applies to any single-cell long-read RNA sequencing data in any cell type, tissue or species.

Availability and implementation

Source code is available at http://github.com/ans4013/ScisorWiz. No new data were generated for this publication. Data used to generate figures was sourced from GEO accession token GSE158450 and available on GitHub as example data.

Neurodevelopmental disorders, immunity, and cancer are connected

Immunity could be viewed as the common factor in neurodevelopmental disorders and cancer. The immune and nervous systems coevolve as the embryo develops. Immunity can release cytokines that activate MAPK signaling in neural cells. In specific embryonic brain cell types, dysregulated signaling that results from germline or embryonic mutations can promote changes in chromatin organization and gene accessibility, and thus expression levels of essential genes in neurodevelopment. In cancer, dysregulated signaling can emerge from sporadic somatic mutations during human life. Neurodevelopmental disorders and cancer share similarities. In neurodevelopmental disorders, immunity, and cancer, there appears an almost invariable involvement of small GTPases (e.g., Ras, RhoA, and Rac) and their pathways. TLRs, IL-1, GIT1, and FGFR signaling pathways, all can be dysregulated in neurodevelopmental disorders and cancer. Although there are signaling similarities, decisive differentiating factors are timing windows, and cell type specific perturbation levels, pointing to chromatin reorganization. Finally, we discuss drug discovery.

The Importance of a Genome-Wide Association Analysis in the Study of Alternative Splicing Mutations in Plants with a Special Focus on Maize

Alternative splicing is an important mechanism for regulating gene expressions at the post-transcriptional level. In eukaryotes, the genes are transcribed in the nucleus to produce pre-mRNAs and alternative splicing can splice a pre-mRNA to eventually form multiple different mature mRNAs, greatly increasing the number of genes and protein diversity. Alternative splicing is involved in the regulation of various plant life activities, especially the response of plants to abiotic stresses and is also an important process of plant growth and development. This review aims to clarify the usefulness of a genome-wide association analysis in the study of alternatively spliced variants by summarizing the application of alternative splicing, genome-wide association analyses and genome-wide association analyses in alternative splicing, as well as summarizing the related research progress.

Are transient protein-protein interactions more dispensable?

Protein-protein interactions (PPIs) are key drivers of cell function and evolution. While it is widely assumed that most permanent PPIs are important for cellular function, it remains unclear whether transient PPIs are equally important. Here, we estimate and compare dispensable content among transient PPIs and permanent PPIs in human. Starting with a human reference interactome mapped by experiments, we construct a human structural interactome by building three-dimensional structural models for PPIs, and then distinguish transient PPIs from permanent PPIs using several structural and biophysical properties. We map common mutations from healthy individuals and disease-causing mutations onto the structural interactome, and perform structure-based calculations of the probabilities for common mutations (assumed to be neutral) and disease mutations (assumed to be mildly deleterious) to disrupt transient PPIs and permanent PPIs. Using Bayes' theorem we estimate that a similarly small fraction (<~20%) of both transient and permanent PPIs are completely dispensable, i.e., effectively neutral upon disruption. Hence, transient and permanent interactions are subject to similarly strong selective constraints in the human interactome.

Diverse and Complementary Effects of Ghrelin and Obestatin

Ghrelin and obestatin are two "sibling proteins" encoded by the same preproghrelin gene but possess an array of diverse and complex functions. While there are ample literature documenting ghrelin's functions, the roles of obestatin are less clear and controversial. Ghrelin and obestatin have been perceived to be antagonistic initially; however, recent studies challenge this dogma. While they have opposing effects in some systems, they function synergistically in other systems, with many functions remaining debatable. In this review, we discuss their functional relationship under three "C" categories, namely complex, complementary, and contradictory. Their functions in food intake, weight regulation, hydration, gastrointestinal motility, inflammation, and insulin secretion are complex. Their functions in pancreatic beta cells, cardiovascular, muscle, neuroprotection, cancer, and digestive system are complementary. Their functions in white adipose tissue, thermogenesis, and sleep regulation are contradictory. Overall, this review accumulates the multifaceted functions of ghrelin and obestatin under both physiological and pathological conditions, with the intent of contributing to a better understanding of these two important gut hormones.

Biomarkers of intrahepatic cholangiocarcinoma: diagnosis and response to therapy

Intrahepatic cholangiocarcinoma (ICC) is the second most common primary liver cancer behind hepatocellular carcinoma (HCC) and carries a dismal prognosis. Improved genetic analysis has paved the way for a better understanding of the distinct somatic genomic landscapes of ICC. The use of next generation sequencing has paved the way for more personalized medicine through identifying unique mutations which may prove to be therapeutic targets. The ability to identify biomarkers specific to ICC will assist in establishing a diagnosis, monitoring response to therapy, as well as assist in identifying novel therapies and personalized medicine. Herein, we discuss potential biomarkers for ICC and how these markers can assist in diagnosis, monitor response to therapy, and potentially identify novel interventions for the treatment of ICC.

Enhanced protein isoform characterization through long-read proteogenomics

BACKGROUND

The detection of physiologically relevant protein isoforms encoded by the human genome is critical to biomedicine. Mass spectrometry (MS)-based proteomics is the preeminent method for protein detection, but isoform-resolved proteomic analysis relies on accurate reference databases that match the sample; neither a subset nor a superset database is ideal. Long-read RNA sequencing (e.g., PacBio or Oxford Nanopore) provides full-length transcripts which can be used to predict full-length protein isoforms.

RESULTS

We describe here a long-read proteogenomics approach for integrating sample-matched long-read RNA-seq and MS-based proteomics data to enhance isoform characterization. We introduce a classification scheme for protein isoforms, discover novel protein isoforms, and present the first protein inference algorithm for the direct incorporation of long-read transcriptome data to enable detection of protein isoforms previously intractable to MS-based detection. We have released an open-source Nextflow pipeline that integrates long-read sequencing in a proteomic workflow for isoform-resolved analysis.

CONCLUSIONS

Our work suggests that the incorporation of long-read sequencing and proteomic data can facilitate improved characterization of human protein isoform diversity. Our first-generation pipeline provides a strong foundation for future development of long-read proteogenomics and its adoption for both basic and translational research.

Applications and advancements of FT-ICR-MS for interactome studies

The set of all intra- and intermolecular interactions, collectively known as the interactome, is currently an unmet challenge for any analytical method, but if measured, could provide unparalleled insight on molecular function in living systems. Developments and applications of chemical cross-linking and high-performance mass spectrometry technologies are beginning to reveal details on how proteins interact in cells and how protein conformations and interactions inside cells change with phenotype or during drug treatment or other perturbations. A major contributor to these advances is Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) technology and its implementation with accurate mass measurements on cross-linked peptide-pair precursor and fragment ions to enable improved identification methods. However, these applications place increased demands on mass spectrometer performance in terms of high-resolution spectral acquisition rates for on-line MSn experiments. Moreover, FT-ICR-MS also offers unique opportunities to develop and implement parallel ICR cells for multiplexed signal acquisition and the potential to greatly advance accurate mass acquisition rates for interactome studies. This review highlights our efforts to exploit accurate mass FT-ICR-MS technologies with chemical cross-linking and developments being pursued to realize parallel MS array capabilities that will further advance visualization of the interactome.

The effects of H22 tumor on the quality of oocytes and the development of early embryos from host mice: A single-cell RNA sequencing approach

The association between cancer and female reproduction remains largely unknown. Here we investigated the quality of oocytes and the developmental potential of zygotes using H22 tumor-bearing mice model. The results showed that the number of oocytes was decreased in tumor-bearing mice compared with the control mice, and accompanied scattered chromosomes was observed. Further study revealed an abnormal epigenetic reprogramming occurred in the zygotes from the H22 tumor-bearing mice, as exemplified by the aberrant 5hmC/5mC modifications in the pronuclei. Finally, single-cell RNA sequencing was performed on the oocytes collected from the H22 tumor-bearing mice. Our data showed that 45 of the 202 differentially expressed genes in tumor-bearing group were closely associated with oocyte quality. Protein interaction analysis indicated that the potential interaction among these 45 genes. Collectively, our study uncovered that the quality of oocytes and early embryonic development were affected by H22 tumor bearing via the altered expression patterns of genes related with reproduction, providing new insights into the reproductive capability of female cancer patients.

Genetic Control of Splicing at SIRPG Modulates Risk of Type 1 Diabetes

Signal regulatory protein SIRPγ (CD172G) is expressed on the surface of lymphocytes, where it acts by engaging its ligand, CD47. SIRPG, which encodes SIRPγ, contains a nonsynonymous coding variant, rs6043409, which is significantly associated with risk for type 1 diabetes. SIRPG produces multiple transcript isoforms via alternative splicing, all encoding potentially functional proteins. We show that rs6043409 alters a predicted exonic splicing enhancer, resulting in significant shifts in the distribution of SIRPG transcript isoforms. All of these transcript isoforms produced protein upon transient expression in vitro. However, CRISPR/Cas9 targeting of one of the alternatively spliced exons in SIRPG eliminated all SIRPγ expression in Jurkat T cells. These targeted cells formed fewer cell-cell conjugates with each other than with wild-type Jurkat cells, expressed reduced levels of genes associated with CD47 signaling, and had significantly increased levels of cell-surface CD47. In primary CD4+ and CD8+ T cells, cell-surface SIRPγ levels in response to anti-CD3 stimulation varied quantitatively by rs6043409 genotype. Our results suggest that SIRPG is the most likely causative gene for type 1 diabetes risk in the 20p13 region and highlight the role of alternative splicing in lymphocytes in mediating the genetic risk for autoimmunity.

The Blood Proteoform Atlas: A reference map of proteoforms in human hematopoietic cells

Human biology is tightly linked to proteins, yet most measurements do not precisely determine alternatively spliced sequences or posttranslational modifications. Here, we present the primary structures of ~30,000 unique proteoforms, nearly 10 times more than in previous studies, expressed from 1690 human genes across 21 cell types and plasma from human blood and bone marrow. The results, compiled in the Blood Proteoform Atlas (BPA), indicate that proteoforms better describe protein-level biology and are more specific indicators of differentiation than their corresponding proteins, which are more broadly expressed across cell types. We demonstrate the potential for clinical application, by interrogating the BPA in the context of liver transplantation and identifying cell and proteoform signatures that distinguish normal graft function from acute rejection and other causes of graft dysfunction.

Identification and Characterization of Immunogene-Related Alternative Splicing Patterns and Tumor Microenvironment Infiltration Patterns in Breast Cancer

Alternative splicing (AS) plays a crucial role in tumor development and tumor microenvironment (TME) formation. However, our current knowledge about AS, especially immunogene-related alternative splicing (IGAS) patterns in cancers, remains limited. Herein, we identified and characterized post-transcriptional mechanisms of breast cancer based on IGAS, TME, prognosis, and immuno/chemotherapy. We screened the differentially spliced IGAS events and constructed the IGAS prognostic model (p-values < 0.001, AUC = 0.939), which could be used as an independent prognostic factor. Besides, the AS regulatory network suggested a complex cooperative or competitive relationship between splicing factors and IGAS events, which explained the diversity of splice isoforms. In addition, more than half of the immune cells displayed varying degrees of infiltration in the IGAS risk groups, and the prognostic characteristics of IGAS demonstrated a remarkable and consistent trend correlation with the infiltration levels of immune cell types. The IGAS risk groups showed substantial differences in the sensitivity of immunotherapy and chemotherapy. Finally, IGAS clusters defined by unsupervised cluster analysis had distinct prognostic patterns, suggesting an essential heterogeneity of IGAS events. Significant differences in immune infiltration and unique prognostic capacity of immune cells were also detected in each IGAS cluster. In conclusion, our comprehensive analysis remarkably enhanced the understanding of IGAS patterns and TME in breast cancer, which may help clarify the underlying mechanisms of IGAS in neoplasia and provide clues to molecular mechanisms of oncogenesis and progression.

CD46 isoforms influence the mode of entry by human herpesvirus 6A/B in T cells

CD46 is a receptor for human herpesvirus 6A (HHV-6A) and is in some cells also important for infection with HHV-6B. CD46 has several isoforms of which the most commonly expressed can be distinguished by expression of a BC domain or a C domain in a serine-threonine-proline rich (STP) extracellular region. Using a SupT1 CD46 CRISPR-Cas9 knockout model system reconstituted with specific CD46 isoforms, we demonstrated that HHV-6A infection was more efficient when BC-isoforms were expressed as opposed to C-isoforms, measured by higher levels of intracellular viral transcripts and recovery of more progeny virus. Although the B domain contains several O-glycosylations, mutations of Ser and Thr residues did not prevent infection with HHV-6A. The HHV-6A infection was blocked by inhibitors of clathrin-mediated endocytosis. In contrast, infection with HHV-6B was preferentially promoted by C-isoforms mediating fusion-from-without, and this infection was less affected by inhibitors of clathrin-mediated endocytosis. Taken together, HHV-6A preferred BC isoforms, mediating endocytosis, whereas HHV-6B preferred C isoforms, mediating fusion-from-without. This demonstrates that the STP region of CD46 is important for regulating the mode of infection in SupT1 cells and suggests an epigenetic regulation of the host susceptibility to HHV-6A and HHV-6B infection. Importance CD46 is the receptor used by human herpesvirus 6A (HHV-6A) during infection of T cells, but it is also involved in infection of certain T cells by HHV-6B. The gene for CD46 allows expression of several variants of CD46, known as isoforms, but whether the isoforms matter for infection of T cells is unknown. We used a genetic approach to delete CD46 from T cells and reconstituted them with separate isoforms to study these individually. We expressed the isoforms known as BC and C, which are distinguished by the potential inclusion of a B domain in the CD46 molecule. We demonstrate that HHV-6A prefers the BC isoform to infect T cells, and this occurs predominantly by clathrin-mediated endocytosis. In contrast, HHV-6B prefers the C isoform and infects predominantly by fusion-from-without. Thus, CD46 isoforms may affect susceptibility of T cells to infection with HHV-6A and HHV-6B.

Genomic variants reducing expression of two endocytic receptors in 46,XY differences of sex development

Transporter-dependent steroid hormone uptake into target cells was demonstrated in genetically engineered mice and fruit flies. We hypothesized that mutations in such transporters may cause differences in sex development (DSD) in humans. Exome sequencing was performed in 16 genetically unsolved cases of 46,XY DSD selected from an anonymized collection of 708 lines of genital fibroblasts (GF) that were taken from individuals with incomplete virilization. Selection criteria were based on available biochemical characterization of GF compatible with reduced androgen uptake. Two unrelated individuals were identified with mutations in LDL receptor-related protein 2 (LRP2), a gene previously associated with partial sex steroid insensitivity in mice. Like Lrp2^-/- mice, affected individuals had non-descended testes. Western blots on GF confirmed reduced LRP2 expression, and endocytosis of sex hormone-binding globulin was reduced. In three unrelated individuals, two with undescended testes, mutations in another endocytic receptor gene, limb development membrane protein 1 like (LMBR1L), were detected. Two of these individuals had mutations affecting the same codon. In a transfected cell model, mutated LMBR1L showed reduced cell surface expression. Our findings suggest that endocytic androgen uptake in complex with sex hormone-binding globulin is relevant in human. LMBR1L may play a similar role in androgen uptake.

Identification of a metastable uranium metal–organic framework isomer through non-equilibrium synthesis

Since the structure of supramolecular isomers determines their performance, rational synthesis of a specific isomer hinges on understanding the energetic relationships between isomeric possibilities. To this end, we have systematically interrogated a pair of uranium-based metal–organic framework topological isomers both synthetically and through density functional theory (DFT) energetic calculations. Although synthetic and energetic data initially appeared to mismatch, we assigned this phenomenon to the appearance of a metastable isomer, driven by levers defined by Le Châtelier's principle. Identifying the relationship between structure and energetics in this study reveals how non-equilibrium synthetic conditions can be used as a strategy to target metastable MOFs. Additionally, this study demonstrates how defined MOF design rules may enable access to products within the energetic phase space which are more complex than conventional binary (e.g., kinetic vs. thermodynamic) products.

Identifying the relationship between structure and energetics in a uranium MOF isomer system reveals how non-equilibrium synthetic conditions can be used as a strategy to target metastable MOFs.

An alternative splicing hypothesis for neuropathology of schizophrenia: evidence from studies on historical candidate genes and multi-omics data

Alternative splicing of schizophrenia risk genes, such as DRD2, GRM3, and DISC1, has been extensively described. Nevertheless, the alternative splicing characteristics of the growing number of schizophrenia risk genes identified through genetic analyses remain relatively opaque. Recently, transcriptomic analyses in human brains based on short-read RNA-sequencing have discovered many "local splicing" events (e.g., exon skipping junctions) associated with genetic risk of schizophrenia, and further molecular characterizations have identified novel spliced isoforms, such as AS3MT^d2d3 and ZNF804A^E3E4. In addition, long-read sequencing analyses of schizophrenia risk genes (e.g., CACNA1C and NRXN1) have revealed multiple previously unannotated brain-abundant isoforms with therapeutic potentials, and functional analyses of KCNH2-3.1 and Ube3a1 have provided examples for investigating such spliced isoforms in vitro and in vivo. These findings suggest that alternative splicing may be an essential molecular mechanism underlying genetic risk of schizophrenia, however, the incomplete annotations of human brain transcriptomes might have limited our understanding of schizophrenia pathogenesis, and further efforts to elucidate these transcriptional characteristics are urgently needed to gain insights into the illness-correlated brain physiology and pathology as well as to translate genetic discoveries into novel therapeutic targets.

From complete cross-docking to partners identification and binding sites predictions

Proteins ensure their biological functions by interacting with each other. Hence, characterising protein interactions is fundamental for our understanding of the cellular machinery, and for improving medicine and bioengineering. Over the past years, a large body of experimental data has been accumulated on who interacts with whom and in what manner. However, these data are highly heterogeneous and sometimes contradictory, noisy, and biased. Ab initio methods provide a means to a "blind" protein-protein interaction network reconstruction. Here, we report on a molecular cross-docking-based approach for the identification of protein partners. The docking algorithm uses a coarse-grained representation of the protein structures and treats them as rigid bodies. We applied the approach to a few hundred of proteins, in the unbound conformations, and we systematically investigated the influence of several key ingredients, such as the size and quality of the interfaces, and the scoring function. We achieved some significant improvement compared to previous works, and a very high discriminative power on some specific functional classes. We provide a readout of the contributions of shape and physico-chemical complementarity, interface matching, and specificity, in the predictions. In addition, we assessed the ability of the approach to account for protein surface multiple usages, and we compared it with a sequence-based deep learning method. This work may contribute to guiding the exploitation of the large amounts of protein structural models now available toward the discovery of unexpected partners and their complex structure characterisation.

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.

How alternative splicing changes the properties of plant proteins

Most plant primary transcripts undergo alternative splicing (AS), and its impact on protein diversity is a subject of intensive investigation. Several studies have uncovered various mechanisms of how particular protein splice isoforms operate. However, the common principles behind the AS effects on protein function in plants have rarely been surveyed. Here, on the selected examples, we highlight diverse tissue expression patterns, subcellular localization, enzymatic activities, abilities to bind other molecules and other relevant features. We describe how the protein isoforms mutually interact to underline their intriguing roles in altering the functionality of protein complexes. Moreover, we also discuss the known cases when these interactions have been placed inside the autoregulatory loops. This review is particularly intended for plant cell and developmental biologists who would like to gain inspiration on how the splice variants encoded by their genes of interest may coordinately work.

基于精氨酸酶切的蛋白质C端肽段富集方法的优化及评估

基于聚合物的蛋白质C端反向富集策略是用于研究蛋白质C端最为广泛的策略之一。目前,基于胰蛋白酶(trypsin)切割精氨酸残基C端(ArgC型酶切)的蛋白C端组学方法对蛋白质C端的鉴定深度仍有待提高。为解决这一问题,该研究对此方法进行了优化和评估:建立了基于“V型”过滤装置的“一锅法”富集流程,避免了副反应的干扰,缩短了样本的制备时间;优化了蛋白水平乙酰化反应条件,最大限度地降低了丝氨酸、苏氨酸、酪氨酸残基上的副反应,提高了肽段鉴定的可信性;优化了基于固相萃取枪头膜片过滤柱(StageTip柱)的样品分离过程,使C端肽段的鉴定深度增加至原来的4倍。通过以上优化,按照肽段水平错误发现率(FDR)<0.01、离子分数(ion score)≥20,且C端带有乙醇胺修饰的数据筛选标准,从人HEK 293T细胞中共鉴定出696个蛋白质C端。若仅要求肽段水平FDR<0.01,鉴定数目进一步增加到933个,这是基于聚合物富集策略的蛋白质C端组学方法所得的最大数据集之一。探索了胰蛋白酶镜像酶(LysargiNase)切割精氨酸残基N端(ArgN型酶切)与不同肽段N端衍生化修饰组合对蛋白质C端鉴定数目和种类的影响,“LysargiNase酶切+肽段N端乙酰化”新策略在原有“胰蛋白酶酶切+肽段N端二甲基化”策略的基础上将鉴定蛋白质C端的种类提升了47%。综上,该研究通过对基于Arg型酶切的蛋白C端组学方法的优化,提升了C端肽段的鉴定深度,扩大了C端肽段鉴定的覆盖范围。该方法将有望成为系统性表征蛋白质C端的有力工具。

LINC00857 regulated by ZNF460 enhances the expression of CLDN12 by sponging miR-150-5p and recruiting SRSF1 for alternative splicing to promote epithelial-mesenchymal transformation of pancreatic adenocarcinoma cells

Recent research unveiled that LINC00857 plays a regulatory role in multiple human cancers, such as lung adenocarcinoma and gastric cancer. Nevertheless, the function of LINC00857 in pancreatic adenocarcinoma (PAAD) remains unclear. This study concentrates on LINC00857 to discuss the relevant molecular mechanism of this gene in PAAD. Quantitative reverse transcription polymerase chain reaction (RT-qPCR) and western blot were implemented for measuring the expressions of RNAs and proteins. Wound healing and Transwell assays were used to assess cell migration and invasion, and fluorescent in situ hybridization (FISH) to locate LINC00857 in PAAD cells. Additionally, mechanism assays were conducted to validate the interaction between genes. Results indicated that LINC00857 was upregulated in PAAD cells and the knockdown of LINC00857 impeded PAAD cell migration, invasion and epithelial-mesenchymal transition (EMT). Further, it was found that LNC00857 regulates CLDN12 expression by targeting miR-150-5p. Moreover, LINC00857 was confirmed to recruit serine/arginine-rich splicing factor 1 (SRSF1) to promote the alternative splicing (AS) targeting CLDN12, affecting the phenotypes of PAAD cells. In addition, the transcription factor ZNF460 was proven to positively regulate LINC00857 expression. To sum up, LINC00857 regulated by ZNF460 upregulates CLDN12 expression by sponging miR-150-5p and recruiting SRSF1 to facilitate the progression of PAAD cells.[Figure: see text].

Online μSEC2-nRPLC-MS for Improved Sensitivity of Intact Protein Detection of IEF-Separated Nonhuman Primate Cerebrospinal Fluid Proteins

Proteoform-resolved information, obtained by top-down (TD) "intact protein" proteomics, is expected to contribute substantially to the understanding of molecular pathogenic mechanisms and, in turn, identify novel therapeutic and diagnostic targets. However, the robustness of mass spectrometry (MS) analysis of intact proteins in complex biological samples is hindered by the high dynamic range in protein concentration and mass, protein instability, and buffer complexity. Here, we describe an evolutionary step for intact protein investigations through the online implementation of tandem microflow size-exclusion chromatography with nanoflow reversed-phase liquid chromatography and MS (μSEC2-nRPLC-MS). Online serial high-/low-pass SEC filtration overcomes the aforementioned hurdles to intact proteomic analysis through automated sample desalting/cleanup and enrichment of target mass ranges (5-155 kDa) prior to nRPLC-MS. The coupling of μSEC to nRPLC is achieved through a novel injection volume control (IVC) strategy of inserting protein trap columns, pre- and post-μSEC columns, to enable injection of dilute samples in high volumes without loss of sensitivity or resolution. Critical characteristics of the approach are tested via rigorous investigations on samples of varied complexity and chemical background. Application of the platform to cerebrospinal fluid (CSF) prefractionated by OFFGEL isoelectric focusing drastically increases the number of intact mass tags (IMTs) detected within the target mass range (5-30 kDa) in comparison to one-dimensional nRPLC-MS with approximately 100× less CSF than previous OFFGEL studies. Furthermore, the modular design of the μSEC2-nRPLC-MS platform is robust and promises significant flexibility for large-scale TDMS analysis of diverse samples either directly or in concert with other multidimensional fractionation steps.

The role of alternative splicing in adaptation and evolution

Regulation of gene expression plays a central role in adaptive divergence and evolution. Although the role of gene regulation in microevolutionary processes is gaining wide acceptance, most studies have only investigated the evolution of transcript levels, ignoring the potentially significant role of transcript structures. We argue that variation in alternative splicing plays an important and widely unexplored role in adaptation (e.g., by increasing transcriptome and/or proteome diversity, or buffering potentially deleterious genetic variation). New studies increasingly highlight the potential for independent evolution in alternative splicing and transcript level, providing alternative paths for selection to act upon. We propose that alternative splicing and transcript levels can provide contrasting, nonredundant mechanisms of equal importance for adaptive diversification of gene function and regulation.

Functional enrichment of alternative splicing events with NEASE reveals insights into tissue identity and diseases

Alternative splicing (AS) is an important aspect of gene regulation. Nevertheless, its role in molecular processes and pathobiology is far from understood. A roadblock is that tools for the functional analysis of AS-set events are lacking. To mitigate this, we developed NEASE, a tool integrating pathways with structural annotations of protein-protein interactions to functionally characterize AS events. We show in four application cases how NEASE can identify pathways contributing to tissue identity and cell type development, and how it highlights splicing-related biomarkers. With a unique view on AS, NEASE generates unique and meaningful biological insights complementary to classical pathways analysis.

Alternative splicing regulation of cell-cycle genes by SPF45/SR140/CHERP complex controls cell proliferation

The regulation of pre-mRNA processing has important consequences for cell division and the control of cancer cell proliferation, but the underlying molecular mechanisms remain poorly understood. We report that three splicing factors, SPF45, SR140, and CHERP, form a tight physical and functionally coherent complex that regulates a variety of alternative splicing events, frequently by repressing short exons flanked by suboptimal 3' splice sites. These comprise alternative exons embedded in genes with important functions in cell-cycle progression, including the G2/M key regulator FOXM1 and the spindle regulator SPDL1. Knockdown of either of the three factors leads to G2/M arrest and to enhanced apoptosis in HeLa cells. Promoting the changes in FOXM1 or SPDL1 splicing induced by SPF45/SR140/CHERP knockdown partially recapitulates the effects on cell growth, arguing that the complex orchestrates a program of alternative splicing necessary for efficient cell proliferation.

Predicting protein interaction network perturbation by alternative splicing with semi-supervised learning

Alternative splicing introduces an additional layer of protein diversity and complexity in regulating cellular functions that can be specific to the tissue and cell type, physiological state of a cell, or disease phenotype. Recent high-throughput experimental studies have illuminated the functional role of splicing events through rewiring protein-protein interactions; however, the extent to which the macromolecular interactions are affected by alternative splicing has yet to be fully understood. In silico methods provide a fast and cheap alternative to interrogating functional characteristics of thousands of alternatively spliced isoforms. Here, we develop an accurate feature-based machine learning approach that predicts whether a protein-protein interaction carried out by a reference isoform is perturbed by an alternatively spliced isoform. Our method, called the alternatively spliced interactions prediction (ALT-IN) tool, is compared with the state-of-the-art PPI prediction tools and shows superior performance, achieving 0.92 in precision and recall values.

Functional Peptides Encoded by Long Non-Coding RNAs in Gastrointestinal Cancer

Gastrointestinal cancer is by far the most common malignancy and the most common cause of cancer-related deaths worldwide. Recent studies have shown that long non-coding RNAs (lncRNAs) play an important role in the epigenetic regulation of cancer cells and regulate tumor progression by affecting chromatin modifications, gene transcription, translation, and sponge to miRNAs. In particular, lncRNA has recently been found to possess open reading frame (ORF), which can encode functional small peptides or proteins. These peptides interact with its targets to regulate transcription or the signal axis, thus promoting or inhibiting the occurrence and development of tumors. In this review, we summarize the involvement of lncRNAs and the function of lncRNAs encoded small peptides in gastrointestinal cancer.

Systematic discovery of signaling pathways linking immune activation to schizophrenia

Immune activation has been shown to play a critical role in the development of schizophrenia; however its underlying mechanism remains unknown. Our report demonstrates a high-quality protein interaction network for schizophrenia (SCZ Network), constructed using our “neighborhood walk” approach in combination with “random walk with restart”. The spatiotemporal expression pattern of the genes in this disease network revealed two developmental stages sensitive to perturbation by immune activation: mid-to late gestation, and adolescence. Furthermore, we induced immune activation at these stages in mice, carried out transcriptome sequencing on the mouse brains, and illustrated clear potential molecular pathways and key regulators correlating maternal immune activation during gestation and an increased risk for schizophrenia after a second immune activation at puberty. This work provides not only valuable resources for the study on molecular mechanisms underlying schizophrenia, but also a systematic strategy for the discovery of molecular pathways of complex mental disorders.

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A high-quality molecular network for schizophrenia (SCZ Network)

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A landscape of molecular pathways linking immune activation and schizophrenia

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The spatiotemporal network dynamics revealing stages susceptible to immune activation

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Identification of the molecular pathways and regulators in the immune-activated brain

Full-length transcript sequencing of human and mouse cerebral cortex identifies widespread isoform diversity and alternative splicing

Alternative splicing is a post-transcriptional regulatory mechanism producing distinct mRNA molecules from a single pre-mRNA with a prominent role in the development and function of the central nervous system. We used long-read isoform sequencing to generate full-length transcript sequences in the human and mouse cortex. We identify novel transcripts not present in existing genome annotations, including transcripts mapping to putative novel (unannotated) genes and fusion transcripts incorporating exons from multiple genes. Global patterns of transcript diversity are similar between human and mouse cortex, although certain genes are characterized by striking differences between species. We also identify developmental changes in alternative splicing, with differential transcript usage between human fetal and adult cortex. Our data confirm the importance of alternative splicing in the cortex, dramatically increasing transcriptional diversity and representing an important mechanism underpinning gene regulation in the brain. We provide transcript-level data for human and mouse cortex as a resource to the scientific community.

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There is widespread transcript diversity in the cortex and many novel transcripts

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Some genes display big differences in isoform number between human and mouse cortex

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There is evidence of differential transcript usage between human fetal and adult cortex

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There are many novel isoforms of genes associated with human brain disease

Applications of CRISPR-Cas Technologies to Proteomics

CRISPR-Cas-based genome editing is a revolutionary approach that has provided an unprecedented investigational power for the life sciences. Rapid and efficient, CRISPR-Cas technologies facilitate the generation of complex biological models and at the same time provide the necessary methods required to study these models in depth. The field of proteomics has already significantly benefited from leveraging the power of CRISPR-Cas technologies, however, many potential applications of these technologies in the context of proteomics remain unexplored. In this review, we intend to provide an introduction to the CRISPR-Cas technologies and demonstrate how they can be applied to solving proteome-centric questions. To achieve this goal, we begin with the description of the modern suite of CRISPR-Cas-based tools, focusing on the more mature CRISPR-Cas9 system. In the second part of this review, we highlight both established and potential applications of the CRISPR-Cas technologies to proteomics.