APADB: a database for alternative polyadenylation and microRNA regulation events

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.

Pan-cancer analysis of NUDT21 and its effect on the proliferation of human head and neck squamous cell carcinoma

BACKGROUND

Based on bioinformatics research of NUDT21 in pan-cancer, we aimed to clarify the mechanism of NUDT21 in HHNC by experiment.

METHODS

The correlation between differential expression of NUDT21 in pan-cancer and survival prognosis, genomic instability, tumor stemness, DNA repair, RNA methylation and with immune microenvironment were analyzed by the application of different pan-cancer analysis web databases. In addition, immunohistochemistry staining and genetic detection of NUDT21 in HHNCC tumor tissues by immunohistochemistry and qRT-PCR. Then, through in vitro cell experiments, NUDT21 was knocked down by lentivirus to detect the proliferation, cycle, apoptosis of FaDu and CNE-2Z cells, and finally by PathScan intracellular signaling array reagent to detect the apoptotic protein content.

RESULTS

Based on the pan-cancer analysis, we found that elevated expression of NUDT21 in most cancers was significantly correlated with TMB, MSI, neoantigens and chromosomal ploidy, and in epigenetics, elevated NUDT21 expression was strongly associated with genomic stability, mismatch repair genes, tumor stemness, and RNA methylation. Based on immunosuppressive score, we found that NUDT21 plays an essential role in the immunosuppressive environment by suppressing immune checkpointing effect in most cancers. In addition, using HHNSCC as a study target, PCR and pathological detection of NUDT21 in tumor tissues was significantly increased than that in paracancerous normal tissues. In vitro cellular assays, silencing NUDT21 inhibited proliferation and promoted apoptosis in FaDu and CNE-2Z cells, and blocked the cell cycle in the G2/M phase. Therefore, the experiments confirmed that NUDT21 promotes the proliferation of FaDu by suppressing the expression of apoptotic.

LUBAC-mediated M1 Ub regulates necroptosis by segregating the cellular distribution of active MLKL

Plasma membrane accumulation of phosphorylated mixed lineage kinase domain-like (MLKL) is a hallmark of necroptosis, leading to membrane rupture and inflammatory cell death. Pro-death functions of MLKL are tightly controlled by several checkpoints, including phosphorylation. Endo- and exocytosis limit MLKL membrane accumulation and counteract necroptosis, but the exact mechanisms remain poorly understood. Here, we identify linear ubiquitin chain assembly complex (LUBAC)-mediated M1 poly-ubiquitination (poly-Ub) as novel checkpoint for necroptosis regulation downstream of activated MLKL in cells of human origin. Loss of LUBAC activity inhibits tumor necrosis factor α (TNFα)-mediated necroptosis, not by affecting necroptotic signaling, but by preventing membrane accumulation of activated MLKL. Finally, we confirm LUBAC-dependent activation of necroptosis in primary human pancreatic organoids. Our findings identify LUBAC as novel regulator of necroptosis which promotes MLKL membrane accumulation in human cells and pioneer primary human organoids to model necroptosis in near-physiological settings.

Genome-wide identification of dominant polyadenylation hexamers for use in variant classification

Polyadenylation is an essential process for the stabilization and export of mRNAs to the cytoplasm and the polyadenylation signal hexamer (herein referred to as hexamer) plays a key role in this process. Yet, only 14 Mendelian disorders have been associated with hexamer variants. This is likely an under-ascertainment as hexamers are not well defined and not routinely examined in molecular analysis. To facilitate the interrogation of putatively pathogenic hexamer variants, we set out to define functionally important hexamers genome-wide as a resource for research and clinical testing interrogation. We identified predominant polyA sites (herein referred to as pPAS) and putative predominant hexamers across protein coding genes (PAS usage >50% per gene). As a measure of the validity of these sites, the population constraint of 4532 predominant hexamers were measured. The predominant hexamers had fewer observed variants compared to non-predominant hexamers and trimer controls, and CADD scores for variants in these hexamers were significantly higher than controls. Exome data for 1477 individuals were interrogated for hexamer variants and transcriptome data were generated for 76 individuals with 65 variants in predominant hexamers. 3' RNA-seq data showed these variants resulted in alternate polyadenylation events (38%) and in elongated mRNA transcripts (12%). Our list of pPAS and predominant hexamers are available in the UCSC genome browser and on GitHub. We suggest this list of predominant hexamers can be used to interrogate exome and genome data. Variants in these predominant hexamers should be considered candidates for pathogenic variation in human disease, and to that end we suggest pathogenicity criteria for classifying hexamer variants.

Deep learning of human polyadenylation sites at nucleotide resolution reveals molecular determinants of site usage and relevance in disease

The genomic distribution of cleavage and polyadenylation (polyA) sites should be co-evolutionally optimized with the local gene structure. Otherwise, spurious polyadenylation can cause premature transcription termination and generate aberrant proteins. To obtain mechanistic insights into polyA site optimization across the human genome, we develop deep/machine learning models to identify genome-wide putative polyA sites at unprecedented nucleotide-level resolution and calculate their strength and usage in the genomic context. Our models quantitatively measure position-specific motif importance and their crosstalk in polyA site formation and cleavage heterogeneity. The intronic site expression is governed by the surrounding splicing landscape. The usage of alternative polyA sites in terminal exons is modulated by their relative locations and distance to downstream genes. Finally, we apply our models to reveal thousands of disease- and trait-associated genetic variants altering polyadenylation activity. Altogether, our models represent a valuable resource to dissect molecular mechanisms mediating genome-wide polyA site expression and characterize their functional roles in human diseases.

Extension of mRNA poly(A) tails and 3'UTRs during neuronal differentiation exhibits variable association with post-transcriptional dynamics

Differentiation of neural progenitor cells into mature neuronal phenotypes relies on extensive temporospatial coordination of mRNA expression to support the development of functional brain circuitry. Cleavage and polyadenylation of mRNA has tremendous regulatory capacity through the alteration of mRNA stability and modulation of microRNA (miRNA) function, however the extent of utilization in neuronal development is currently unclear. Here, we employed poly(A) tail sequencing, mRNA sequencing, ribosome profiling and small RNA sequencing to explore the functional relationship between mRNA abundance, translation, poly(A) tail length, alternative polyadenylation (APA) and miRNA expression in an in vitro model of neuronal differentiation. Differential analysis revealed a strong bias towards poly(A) tail and 3'UTR lengthening during differentiation, both of which were positively correlated with changes in mRNA abundance, but not translation. Globally, changes in miRNA expression were predominantly associated with mRNA abundance and translation, however several miRNA-mRNA pairings with potential to regulate poly(A) tail length were identified. Furthermore, 3'UTR lengthening was observed to significantly increase the inclusion of non-conserved miRNA binding sites, potentially enhancing the regulatory capacity of these molecules in mature neuronal cells. Together, our findings suggest poly(A) tail length and APA function as part of a rich post-transcriptional regulatory matrix during neuronal differentiation.

Applications of deep learning in understanding gene regulation

Gene regulation is a central topic in cell biology. Advances in omics technologies and the accumulation of omics data have provided better opportunities for gene regulation studies than ever before. For this reason deep learning, as a data-driven predictive modeling approach, has been successfully applied to this field during the past decade. In this article, we aim to give a brief yet comprehensive overview of representative deep-learning methods for gene regulation. Specifically, we discuss and compare the design principles and datasets used by each method, creating a reference for researchers who wish to replicate or improve existing methods. We also discuss the common problems of existing approaches and prospectively introduce the emerging deep-learning paradigms that will potentially alleviate them. We hope that this article will provide a rich and up-to-date resource and shed light on future research directions in this area.

Deciphering the impact of genetic variation on human polyadenylation using APARENT2

BACKGROUND

3'-end processing by cleavage and polyadenylation is an important and finely tuned regulatory process during mRNA maturation. Numerous genetic variants are known to cause or contribute to human disorders by disrupting the cis-regulatory code of polyadenylation signals. Yet, due to the complexity of this code, variant interpretation remains challenging.

RESULTS

We introduce a residual neural network model, APARENT2, that can infer 3'-cleavage and polyadenylation from DNA sequence more accurately than any previous model. This model generalizes to the case of alternative polyadenylation (APA) for a variable number of polyadenylation signals. We demonstrate APARENT2's performance on several variant datasets, including functional reporter data and human 3' aQTLs from GTEx. We apply neural network interpretation methods to gain insights into disrupted or protective higher-order features of polyadenylation. We fine-tune APARENT2 on human tissue-resolved transcriptomic data to elucidate tissue-specific variant effects. By combining APARENT2 with models of mRNA stability, we extend aQTL effect size predictions to the entire 3' untranslated region. Finally, we perform in silico saturation mutagenesis of all human polyadenylation signals and compare the predicted effects of [Formula: see text] million variants against gnomAD. While loss-of-function variants were generally selected against, we also find specific clinical conditions linked to gain-of-function mutations. For example, we detect an association between gain-of-function mutations in the 3'-end and autism spectrum disorder. To experimentally validate APARENT2's predictions, we assayed clinically relevant variants in multiple cell lines, including microglia-derived cells.

CONCLUSIONS

A sequence-to-function model based on deep residual learning enables accurate functional interpretation of genetic variants in polyadenylation signals and, when coupled with large human variation databases, elucidates the link between functional 3'-end mutations and human health.

Shortening of the KHDRBS1 3'UTR by alternative cleavage and polyadenylation alters miRNA-mediated regulation and promotes gastric cancer progression

The shortening of the 3' untranslated regions (3'UTRs) due to alternative polyadenylation (APA) has become an important characteristic of cancer. However, the function of APA-induced 3'UTR shortening in gastric cancer (GC) remains unclear. KHDRBS1 (sam68), as an RNA-binding protein (RBP), is significantly upregulated in GC. In this study, we found that the 3'UTR of KHDRBS1 is generally shortened in GC tissues compared to paracancer tissues. Moreover, KHDRBS1 mRNA with a shortened 3'UTR can escape the inhibitory effect of miRNAs, resulting in its increased expression in GC. Overexpression of KHDRBS1, especially KHDRBS1 with a shortened 3'UTR, promotes the growth and metastasis of GC in vivo and in vitro. In conclusion, the experimental results show that shortening of the KHDRBS1 mRNA 3'UTR can mediate the overexpression of KHDRBS1 in GC cells and promote the progression of GC.

Inferring microRNA regulation: A proteome perspective

Post-transcriptional regulation in multicellular organisms is mediated by microRNAs. However, the principles that determine if a gene is regulated by miRNAs are poorly understood. Previous works focused mostly on miRNA seed matches and other features of the 3′-UTR of transcripts. These common approaches rely on knowledge of the miRNA families, and computational approaches still yield poor, inconsistent results, with many false positives. In this work, we present a different paradigm for predicting miRNA-regulated genes based on the encoded proteins. In a novel, automated machine learning framework, we use sequence as well as diverse functional annotations to train models on multiple organisms using experimentally validated data. We present insights from tens of millions of features extracted and ranked from different modalities. We show high predictive performance per organism and in generalization across species. We provide a list of novel predictions including Danio rerio (zebrafish) and Arabidopsis thaliana (mouse-ear cress). We compare genomic models and observe that our protein model outperforms, whereas a unified model improves on both. While most membranous and disease related proteins are regulated by miRNAs, the G-protein coupled receptor (GPCR) family is an exception, being mostly unregulated by miRNAs. We further show that the evolutionary conservation among paralogs does not imply any coherence in miRNA regulation. We conclude that duplicated paralogous genes that often changed their function, also diverse in their tendency to be miRNA regulated. We conclude that protein function is informative across species in predicting post-transcriptional miRNA regulation in living cells.

Comprehensive characterization of posttranscriptional impairment-related 3'-UTR mutations in 2413 whole genomes of cancer patients

The 3' untranslated region (3'-UTR) is the vital element regulating gene expression, but most studies have focused on variations in RNA-binding proteins (RBPs), miRNAs, alternative polyadenylation (APA) and RNA modifications. To explore the posttranscriptional function of 3'-UTR somatic mutations in tumorigenesis, we collected whole-genome data from 2413 patients across 18 cancer types. Our updated algorithm, PIVar, revealed 25,216 3'-UTR posttranscriptional impairment-related SNVs (3'-UTR piSNVs) spanning 2930 genes; 24 related RBPs were significantly enriched. The somatic 3'-UTR piSNV ratio was markedly increased across all 18 cancer types, which was associated with worse survival for four cancer types. Several cancer-related genes appeared to facilitate tumorigenesis at the protein and posttranscriptional regulation levels, whereas some 3'-UTR piSNV-affected genes functioned mainly via posttranscriptional mechanisms. Moreover, we assessed immune cell and checkpoint characteristics between the high/low 3'-UTR piSNV ratio groups and predicted 80 compounds associated with the 3'-UTR piSNV-affected gene expression signature. In summary, our study revealed the prevalence and clinical relevance of 3'-UTR piSNVs in cancers, and also demonstrates that in addition to affecting miRNAs, 3'-UTR piSNVs perturb RBPs binding, APA and m6A RNA modification, which emphasized the importance of considering 3'-UTR piSNVs in cancer biology.

Implications of Poly(A) Tail Processing in Repeat Expansion Diseases

Repeat expansion diseases are a group of more than 40 disorders that affect mainly the nervous and/or muscular system and include myotonic dystrophies, Huntington’s disease, and fragile X syndrome. The mutation-driven expanded repeat tract occurs in specific genes and is composed of tri- to dodeca-nucleotide-long units. Mutant mRNA is a pathogenic factor or important contributor to the disease and has great potential as a therapeutic target. Although repeat expansion diseases are quite well known, there are limited studies concerning polyadenylation events for implicated transcripts that could have profound effects on transcript stability, localization, and translation efficiency. In this review, we briefly present polyadenylation and alternative polyadenylation (APA) mechanisms and discuss their role in the pathogenesis of selected diseases. We also discuss several methods for poly(A) tail measurement (both transcript-specific and transcriptome-wide analyses) and APA site identification—the further development and use of which may contribute to a better understanding of the correlation between APA events and repeat expansion diseases. Finally, we point out some future perspectives on the research into repeat expansion diseases, as well as APA studies.

Cardiac SARS-CoV-2 infection is associated with pro-inflammatory transcriptomic alterations within the heart

Aims

Cardiac involvement in COVID-19 is associated with adverse outcome. However, it is unclear whether cell-specific consequences are associated with cardiac SARS-CoV-2 infection. Therefore, we investigated heart tissue utilizing in situ hybridization, immunohistochemistry, and RNA-sequencing in consecutive autopsy cases to quantify virus load and characterize cardiac involvement in COVID-19.

Methods and results

In this study, 95 SARS-CoV-2-positive autopsy cases were included. A relevant SARS-CoV-2 virus load in the cardiac tissue was detected in 41/95 deceased (43%). Massive analysis of cDNA ends (MACE)-RNA-sequencing was performed to identify molecular pathomechanisms caused by the infection of the heart. A signature matrix was generated based on the single-cell dataset ‘Heart Cell Atlas’ and used for digital cytometry on the MACE-RNA-sequencing data. Thus, immune cell fractions were estimated and revealed no difference in immune cell numbers in cases with and without cardiac infection. This result was confirmed by quantitative immunohistological diagnosis. MACE-RNA-sequencing revealed 19 differentially expressed genes (DEGs) with a q-value <0.05 (e.g. up: IFI44L, IFT3, TRIM25; down: NPPB, MB, MYPN). The upregulated DEGs were linked to interferon pathways and originate predominantly from endothelial cells. In contrast, the downregulated DEGs originate predominately from cardiomyocytes. Immunofluorescent staining showed viral protein in cells positive for the endothelial marker ICAM1 but rarely in cardiomyocytes. The Gene Ontology (GO) term analysis revealed that downregulated GO terms were linked to cardiomyocyte structure, whereas upregulated GO terms were linked to anti-virus immune response.

Conclusion

This study reveals that cardiac infection induced transcriptomic alterations mainly linked to immune response and destruction of cardiomyocytes. While endothelial cells are primarily targeted by the virus, we suggest cardiomyocyte destruction by paracrine effects. Increased pro-inflammatory gene expression was detected in SARS-CoV-2-infected cardiac tissue but no increased SARS-CoV-2 associated immune cell infiltration was observed.

scAPAatlas: an atlas of alternative polyadenylation across cell types in human and mouse

Alternative polyadenylation (APA) has been widely recognized as a crucial step during the post-transcriptional regulation of eukaryotic genes. Recent studies have demonstrated that APA exerts key regulatory roles in many biological processes and often occurs in a tissue- and cell-type-specific manner. However, to our knowledge, there is no database incorporating information about APA at the cell-type level. Single-cell RNA-seq is a rapidly evolving and powerful tool that enable APA analysis at the cell-type level. Here, we present a comprehensive resource, scAPAatlas (http://www.bioailab.com:3838/scAPAatlas), for exploring APA across different cell types, and interpreting potential biological functions. Based on the curated scRNA-seq data from 24 human and 25 mouse normal tissues, we systematically identified cell-type-specific APA events for different cell types and examined the correlations between APA and gene expression level. We also estimated the crosstalk between cell-type-specific APA events and microRNAs or RNA-binding proteins. A user-friendly web interface has been constructed to support browsing, searching and visualizing multi-layer information of cell-type-specific APA events. Overall, scAPAatlas, incorporating a rich resource for exploration of APA at the cell-type level, will greatly help researchers chart cell type with APA and elucidate the biological functions of APA.

scAPAdb: a comprehensive database of alternative polyadenylation at single-cell resolution

Alternative polyadenylation (APA) is a widespread regulatory mechanism of transcript diversification in eukaryotes, which is increasingly recognized as an important layer for eukaryotic gene expression. Recent studies based on single-cell RNA-seq (scRNA-seq) have revealed cell-to-cell heterogeneity in APA usage and APA dynamics across different cell types in various tissues, biological processes and diseases. However, currently available APA databases were all collected from bulk 3′-seq and/or RNA-seq data, and no existing database has provided APA information at single-cell resolution. Here, we present a user-friendly database called scAPAdb (http://www.bmibig.cn/scAPAdb), which provides a comprehensive and manually curated atlas of poly(A) sites, APA events and poly(A) signals at the single-cell level. Currently, scAPAdb collects APA information from > 360 scRNA-seq experiments, covering six species including human, mouse and several other plant species. scAPAdb also provides batch download of data, and users can query the database through a variety of keywords such as gene identifier, gene function and accession number. scAPAdb would be a valuable and extendable resource for the study of cell-to-cell heterogeneity in APA isoform usages and APA-mediated gene regulation at the single-cell level under diverse cell types, tissues and species.

CD20 as a gatekeeper of the resting state of human B cells

Worldwide about one million patients are given anti-CD20 antibodies such as rituximab (RTX) for the treatment of B cell-associated diseases. Despite the success of this first therapeutic antibody, little is known about the function of its target. The role of CD20 only becomes clear in the context of the nanoscale compartmentalization of the B lymphocyte membrane. We found that CD20 is an organizer of the IgD-class nanocluster on the B cell membrane. The loss of CD20 on human B cells results in a dissolution of the IgD-class nanocluster and a transient B cell activation inducing a B cell-to-PC differentiation. Thus, CD20 is an essential gatekeeper of a membrane nanodomain and the resting state of naive B cells.

CD20 is a B cell-specific membrane protein and represents an attractive target for therapeutic antibodies. Despite widespread usage of anti-CD20 antibodies for B cell depletion therapies, the biological function of their target remains unclear. Here, we demonstrate that CD20 controls the nanoscale organization of receptors on the surface of resting B lymphocytes. CRISPR/Cas9-mediated ablation of CD20 in resting B cells resulted in relocalization and interaction of the IgM-class B cell antigen receptor with the coreceptor CD19. This receptor rearrangement led to a transient activation of B cells, accompanied by the internalization of many B cell surface marker proteins. Reexpression of CD20 restored the expression of the B cell surface proteins and the resting state of Ramos B cells. Similarly, treatment of Ramos or naive human B cells with the anti-CD20 antibody rituximab induced nanoscale receptor rearrangements and transient B cell activation in vitro and in vivo. A departure from the resting B cell state followed by the loss of B cell identity of CD20-deficient Ramos B cells was accompanied by a PAX5 to BLIMP-1 transcriptional switch, metabolic reprogramming toward oxidative phosphorylation, and a shift toward plasma cell development. Thus, anti-CD20 engagement or the loss of CD20 disrupts membrane organization, profoundly altering the fate of human B cells.

Volatile Compounds From Bacillus, Serratia, and Pseudomonas Promote Growth and Alter the Transcriptional Landscape of Solanum tuberosum in a Passively Ventilated Growth System

The interaction of an array of volatile organic compounds (VOCs) termed bacterial volatile compounds (BVCs) with plants is now a major area of study under the umbrella of plant-microbe interactions. Many growth systems have been developed to determine the nature of these interactions in vitro. However, each of these systems have their benefits and drawbacks with respect to one another and can greatly influence the end-point interpretation of the BVC effect on plant physiology. To address the need for novel growth systems in BVC-plant interactions, our study investigated the use of a passively ventilated growth system, made possible via Microbox^® growth chambers, to determine the effect of BVCs emitted by six bacterial isolates from the genera Bacillus, Serratia, and Pseudomonas. Solid-phase microextraction GC/MS was utilized to determine the BVC profile of each bacterial isolate when cultured in three different growth media each with varying carbon content. 66 BVCs were identified in total, with alcohols and alkanes being the most abundant. When cultured in tryptic soy broth, all six isolates were capable of producing 2,5-dimethylpyrazine, however BVC emission associated with this media were deemed to have negative effects on plant growth. The two remaining media types, namely Methyl Red-Voges Proskeur (MR-VP) and Murashige and Skoog (M + S), were selected for bacterial growth in co-cultivation experiments with Solanum tuberosum L. cv. ‘Golden Wonder.’ The BVC emissions of Bacillus and Serratia isolates cultured on MR-VP induced alterations in the transcriptional landscape of potato across all treatments with 956 significantly differentially expressed genes. This study has yielded interesting results which indicate that BVCs may not always broadly upregulate expression of defense genes and this may be due to choice of plant-bacteria co-cultivation apparatus, bacterial growth media and/or strain, or likely, a complex interaction between these factors. The multifactorial complexities of observed effects of BVCs on target organisms, while intensely studied in recent years, need to be further elucidated before the translation of lab to open-field applications can be fully realized.

The Detection and Bioinformatic Analysis of Alternative 3' UTR Isoforms as Potential Cancer Biomarkers

Alternative transcript cleavage and polyadenylation is linked to cancer cell transformation, proliferation and outcome. This has led researchers to develop methods to detect and bioinformatically analyse alternative polyadenylation as potential cancer biomarkers. If incorporated into standard prognostic measures such as gene expression and clinical parameters, these could advance cancer prognostic testing and possibly guide therapy. In this review, we focus on the existing methodologies, both experimental and computational, that have been applied to support the use of alternative polyadenylation as cancer biomarkers.

Computational analysis of alternative polyadenylation from standard RNA-seq and single-cell RNA-seq data

Alternative polyadenylation (APA) is a major mechanism of post-transcriptional regulation in various cellular processes including cell proliferation and differentiation. Since conventional APA profiling methods have not been widely adopted, global APA studies are very limited. In this chapter, we summarize current computational methods for analyzing APA in standard RNA-seq and scRNA-seq data and describe two state-of-the-art bioinformatic algorithms DaPars and scDaPars in detail. The bioinformatic pipelines for both DaPars and scDaPars are presented and the application of both algorithms are highlighted.

PAS-seq 2: A fast and sensitive method for global profiling of polyadenylated RNAs

Alternative polyadenylation (APA) is a widespread phenomenon in eukaryotes that contributes to regulating gene expression and generating proteomic diversity. APA plays critical roles in development and its mis-regulation has been implicated in a wide variety of human diseases, including cancer. To study APA on the transcriptome-wide level, numerous deep sequencing methods that capture 3' end of mRNAs have been developed in the past decade, but they generally require a large amount of hands-on time and/or high RNA input. Here, we introduce PAS-seq 2, a fast and sensitive method for global and quantitative profiling of polyadenylated RNAs. Compared to our original PAS-seq, this method takes less time and requires much lower total RNA input due to improvement in the reverse transcription process. PAS-seq 2 can be applied to both APA and differential gene expression analyses.

On the function and relevance of alternative 3'-UTRs in gene expression regulation

Messanger RNA (mRNA) isoforms with alternative 3'-untranslated regions (3'-UTRs) are produced by alternative polyadenylation (APA), which occurs during transcription in most eukaryotic genes. APA fine-tunes gene expression in a cell-type- and cellular state-dependent manner. Selection of an APA site entails the binding of core cleavage and polyadenylation factors to a particular polyadenylation site localized in the pre-mRNA and is controlled by multiple regulatory determinants, including transcription, pre-mRNA cis-regulatory sequences, and protein factors. Alternative 3'-UTRs serve as platforms for specific RNA binding proteins and microRNAs, which regulate gene expression in a coordinated manner by controlling mRNA fate and function in the cell. Genome-wide studies illustrated the full extent of APA prevalence and revealed that specific 3'-UTR profiles are associated with particular cellular states and diseases. Generally, short 3'-UTRs are associated with proliferative and cancer cells, and long 3'-UTRs are mostly found in polarized and differentiated cells. Fundamental new insights on the physiological consequences of this widespread event and the molecular mechanisms involved have been revealed through single-cell studies. Publicly available comprehensive databases that cover all APA mRNA isoforms identified in many cellular states and diseases reveal specific APA signatures. Therapies tackling APA mRNA isoforms or APA regulators may be regarded as innovative and attractive tools for diagnostics or treatment of several pathologies. We highlight the function of APA and alternative 3'-UTRs in gene expression regulation, the control of these mechanisms, their physiological consequences, and their potential use as new biomarkers and therapeutic tools. This article is categorized under: RNA Processing > 3' End Processing RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications RNA in Disease and Development > RNA in Disease.

SRSF3 and SRSF7 modulate 3'UTR length through suppression or activation of proximal polyadenylation sites and regulation of CFIm levels

Background

Alternative polyadenylation (APA) refers to the regulated selection of polyadenylation sites (PASs) in transcripts, which determines the length of their 3′ untranslated regions (3′UTRs). We have recently shown that SRSF3 and SRSF7, two closely related SR proteins, connect APA with mRNA export. The mechanism underlying APA regulation by SRSF3 and SRSF7 remained unknown.

Results

Here we combine iCLIP and 3′-end sequencing and find that SRSF3 and SRSF7 bind upstream of proximal PASs (pPASs), but they exert opposite effects on 3′UTR length. SRSF7 enhances pPAS usage in a concentration-dependent but splicing-independent manner by recruiting the cleavage factor FIP1, generating short 3′UTRs. Protein domains unique to SRSF7, which are absent from SRSF3, contribute to FIP1 recruitment. In contrast, SRSF3 promotes distal PAS (dPAS) usage and hence long 3′UTRs directly by counteracting SRSF7, but also indirectly by maintaining high levels of cleavage factor Im (CFIm) via alternative splicing. Upon SRSF3 depletion, CFIm levels decrease and 3′UTRs are shortened. The indirect SRSF3 targets are particularly sensitive to low CFIm levels, because here CFIm serves a dual function; it enhances dPAS and inhibits pPAS usage by binding immediately downstream and assembling unproductive cleavage complexes, which together promotes long 3′UTRs.

Conclusions

We demonstrate that SRSF3 and SRSF7 are direct modulators of pPAS usage and show how small differences in the domain architecture of SR proteins can confer opposite effects on pPAS regulation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-021-02298-y.

Cytoplasmic cleavage of IMPA1 3' UTR is necessary for maintaining axon integrity

The 3' untranslated regions (3' UTRs) of messenger RNAs (mRNAs) are non-coding sequences involved in many aspects of mRNA metabolism, including intracellular localization and translation. Incorrect processing and delivery of mRNA cause severe developmental defects and have been implicated in many neurological disorders. Here, we use deep sequencing to show that in sympathetic neuron axons, the 3' UTRs of many transcripts undergo cleavage, generating isoforms that express the coding sequence with a short 3' UTR and stable 3' UTR-derived fragments of unknown function. Cleavage of the long 3' UTR of Inositol Monophosphatase 1 (IMPA1) mediated by a protein complex containing the endonuclease argonaute 2 (Ago2) generates a translatable isoform that is necessary for maintaining the integrity of sympathetic neuron axons. Thus, our study provides a mechanism of mRNA metabolism that simultaneously regulates local protein synthesis and generates an additional class of 3' UTR-derived RNAs.

Alternative polyadenylation: methods, mechanism, function, and role in cancer

Occurring in over 60% of human genes, alternative polyadenylation (APA) results in numerous transcripts with differing 3'ends, thus greatly expanding the diversity of mRNAs and of proteins derived from a single gene. As a key molecular mechanism, APA is involved in various gene regulation steps including mRNA maturation, mRNA stability, cellular RNA decay, and protein diversification. APA is frequently dysregulated in cancers leading to changes in oncogenes and tumor suppressor gene expressions. Recent studies have revealed various APA regulatory mechanisms that promote the development and progression of a number of human diseases, including cancer. Here, we provide an overview of four types of APA and their impacts on gene regulation. We focus particularly on the interaction of APA with microRNAs, RNA binding proteins and other related factors, the core pre-mRNA 3'end processing complex, and 3'UTR length change. We also describe next-generation sequencing methods and computational tools for use in poly(A) signal detection and APA repositories and databases. Finally, we summarize the current understanding of APA in cancer and provide our vision for future APA related research.

TREND-DB-a transcriptome-wide atlas of the dynamic landscape of alternative polyadenylation

Alternative polyadenylation (APA) profoundly expands the transcriptome complexity. Perturbations of APA can disrupt biological processes, ultimately resulting in devastating disorders. A major challenge in identifying mechanisms and consequences of APA (and its perturbations) lies in the complexity of RNA 3′ end processing, involving poorly conserved RNA motifs and multi-component complexes consisting of far more than 50 proteins. This is further complicated in that RNA 3′ end maturation is closely linked to transcription, RNA processing and even epigenetic (histone/DNA/RNA) modifications. Here, we present TREND-DB (http://shiny.imbei.uni-mainz.de:3838/trend-db), a resource cataloging the dynamic landscape of APA after depletion of >170 proteins involved in various facets of transcriptional, co- and post-transcriptional gene regulation, epigenetic modifications and further processes. TREND-DB visualizes the dynamics of transcriptome 3′ end diversification (TREND) in a highly interactive manner; it provides a global APA network map and allows interrogating genes affected by specific APA-regulators and vice versa. It also permits condition-specific functional enrichment analyses of APA-affected genes, which suggest wide biological and clinical relevance across all RNAi conditions. The implementation of the UCSC Genome Browser provides additional customizable layers of gene regulation accounting for individual transcript isoforms (e.g. epigenetics, miRNA-binding sites and RNA-binding proteins). TREND-DB thereby fosters disentangling the role of APA for various biological programs, including potential disease mechanisms, and helps identify their diagnostic and therapeutic potential.

Pervasive Selection against MicroRNA Target Sites in Human Populations

MicroRNA target sites are often conserved during evolution and purifying selection to maintain such sites is expected. On the other hand, comparative analyses identified a paucity of microRNA target sites in coexpressed transcripts, and novel target sites can potentially be deleterious. We proposed that selection against novel target sites pervasive. The analysis of derived allele frequencies revealed that, when the derived allele is a target site, the proportion of nontarget sites is higher than expected, particularly for highly expressed microRNAs. Thus, new alleles generating novel microRNA target sites can be deleterious and selected against. When we analyzed ancestral target sites, the derived (nontarget) allele frequency does not show statistical support for microRNA target allele conservation. We investigated the joint effects of microRNA conservation and expression and found that selection against microRNA target sites depends mostly on the expression level of the microRNA. We identified microRNA target sites with relatively high levels of population differentiation. However, when we analyze separately target sites in which the target allele is ancestral to the population, the proportion of single-nucleotide polymorphisms with high F_st significantly increases. These findings support that population differentiation is more likely in target sites that are lost than in the gain of new target sites. Our results indicate that selection against novel microRNA target sites is prevalent and, although individual sites may have a weak selective pressure, the overall effect across untranslated regions is not negligible and should be accounted when studying the evolution of genomic sequences.

Advances in the Bioinformatics Knowledge of mRNA Polyadenylation in Baculovirus Genes

Baculoviruses are a group of insect viruses with large circular dsDNA genomes exploited in numerous biotechnological applications, such as the biological control of agricultural pests, the expression of recombinant proteins or the gene delivery of therapeutic sequences in mammals, among others. Their genomes encode between 80 and 200 proteins, of which 38 are shared by all reported species. Thanks to multi-omic studies, there is remarkable information about the baculoviral proteome and the temporality in the virus gene expression. This allows some functional elements of the genome to be very well described, such as promoters and open reading frames. However, less information is available about the transcription termination signals and, consequently, there are still imprecisions about what are the limits of the transcriptional units present in the baculovirus genomes and how is the processing of the 3′ end of viral mRNA. Regarding to this, in this review we provide an update about the characteristics of DNA signals involved in this process and we contribute to their correct prediction through an exhaustive analysis that involves bibliography information, data mining, RNA structure and a comprehensive study of the core gene 3′ ends from 180 baculovirus genomes.

The role of 3'UTR-protein complexes in the regulation of protein multifunctionality and subcellular localization

Multifunctional proteins often perform their different functions when localized in different subcellular compartments. However, the mechanisms leading to their localization are largely unknown. Recently, 3'UTRs were found to regulate the cellular localization of newly synthesized proteins through the formation of 3'UTR-protein complexes. Here, we investigate the formation of 3'UTR-protein complexes involving multifunctional proteins by exploiting large-scale protein-protein and protein-RNA interaction networks. Focusing on 238 human 'extreme multifunctional' (EMF) proteins, we predicted 1411 3'UTR-protein complexes involving 54% of those proteins and evaluated their role in regulating protein cellular localization and multifunctionality. We find that EMF proteins lacking localization addressing signals, yet present at both the nucleus and cell surface, often form 3'UTR-protein complexes, and that the formation of these complexes could provide EMF proteins with the diversity of interaction partners necessary to their multifunctionality. Our findings are reinforced by archetypal moonlighting proteins predicted to form 3'UTR-protein complexes. Finally, the formation of 3'UTR-protein complexes that involves up to 17% of the proteins in the human protein-protein interaction network, may be a common and yet underestimated protein trafficking mechanism, particularly suited to regulate the localization of multifunctional proteins.

Emerging Roles of RNA 3'-end Cleavage and Polyadenylation in Pathogenesis, Diagnosis and Therapy of Human Disorders

A crucial feature of gene expression involves RNA processing to produce 3′ ends through a process termed 3′ end cleavage and polyadenylation (CPA). This ensures the nascent RNA molecule can exit the nucleus and be translated to ultimately give rise to a protein which can execute a function. Further, alternative polyadenylation (APA) can produce distinct transcript isoforms, profoundly expanding the complexity of the transcriptome. CPA is carried out by multi-component protein complexes interacting with multiple RNA motifs and is tightly coupled to transcription, other steps of RNA processing, and even epigenetic modifications. CPA and APA contribute to the maintenance of a multitude of diverse physiological processes. It is therefore not surprising that disruptions of CPA and APA can lead to devastating disorders. Here, we review potential CPA and APA mechanisms involving both loss and gain of function that can have tremendous impacts on health and disease. Ultimately we highlight the emerging diagnostic and therapeutic potential CPA and APA offer.

Comparative genomic analysis of the 3' UTR of human MDM2 identifies multiple transposable elements, an RLP24 pseudogene and a cluster of novel repeat sequences that arose during primate evolution

The MDM2 oncogene is a negative regulator of the p53 tumour suppressor. This relationship appears to have originated over a billion years ago. The human MDM2 gene encodes a variety of mRNAs with exceptionally long 3'UTRs (up to 5.7 kb); however, it was unclear whether MDM2 3'UTRs from other species are similarly long or conserved at the sequence level. Here, we report that all but one of the primate species most closely related to humans (greater and lesser apes) have similarly long 3'UTRs with high sequence similarity across their entire length. More distantly related species (Old world monkeys and new world monkeys) tend to have shorter MDM2 3'UTRs homologous to the corresponding position of the human MDM2 3'UTR while non-primate species exhibit little similarity at all. Remarkably, DNA sequences downstream of the shorter primate 3'UTRs are syntenic with distal regions in the human and other ape MDM2 3'UTRs. These homologous non-transcribed intergenic and transcribed 3'UTR-encoding regions are comprised of a variety of transposable elements, an RLP24 pseudogene and a cluster of novel repeat sequences suggestive of another unknown transposable element. Our analysis suggests that the primary difference between long and short MDM2 3'UTRs is a switch in polyA site usage to include conserved transposable elements that remain intergenic in more distantly related primates. It will be important to determine the relative contribution of these elements to post-transcriptional and translational regulation of MDM2 and hence p53-mediated tumour suppression.

Primary tumors release ITGBL1-rich extracellular vesicles to promote distal metastatic tumor growth through fibroblast-niche formation

Tumor metastasis is a hallmark of cancer. Metastatic cancer cells often reside in distal tissues and organs in their dormant state. Mechanisms underlying the pre-metastatic niche formation are poorly understood. Here we show that in a colorectal cancer (CRC) model, primary tumors release integrin beta-like 1 (ITGBL1)-rich extracellular vesicles (EVs) to the circulation to activate resident fibroblasts in remote organs. The activated fibroblasts induce the pre-metastatic niche formation and promote metastatic cancer growth by secreting pro-inflammatory cytokine, such as IL-6 and IL-8. Mechanistically, the primary CRC-derived ITGBL1-enriched EVs stimulate the TNFAIP3-mediated NF-κB signaling pathway to activate fibroblasts. Consequently, the activated fibroblasts produce high levels of pro-inflammatory cytokines to promote metastatic cancer growth. These findings uncover a tumor-stromal interaction in the metastatic tumor microenvironment and an intimate signaling communication between primary tumors and metastases through the ITGBL1-loaded EVs. Targeting the EVs-ITGBL1-CAFs-TNFAIP3-NF-κB signaling axis provides an attractive approach for treating metastatic diseases.

APAatlas: decoding alternative polyadenylation across human tissues

Alternative polyadenylation (APA) is an RNA-processing mechanism on the 3' terminus that generates distinct isoforms of mRNAs and/or other RNA polymerase II transcripts with different 3'UTR lengths. Widespread APA affects post-transcriptional gene regulation in mRNA translation, stability, and localization, and exhibits strong tissue specificity. However, no existing database provides comprehensive information about APA events in a large number of human normal tissues. Using the RNA-seq data from the Genotype-Tissue Expression project, we systematically identified APA events from 9475 samples across 53 human tissues and examined their associations with multiple traits and gene expression across tissues. We further developed APAatlas, a user-friendly database (https://hanlab.uth.edu/apa/) for searching, browsing and downloading related information. APAatlas will help the biomedical research community elucidate the functions and mechanisms of APA events in human tissues.

PlantAPAdb: A Comprehensive Database for Alternative Polyadenylation Sites in Plants

Alternative cleavage and polyadenylation (APA) is increasingly recognized as an important regulatory mechanism in eukaryotic gene expression and is dynamically modulated in a developmental, tissue-specific, or environmentally responsive manner. Given the functional importance of APA and the rapid accumulation of APA sites in plants, a comprehensive and easily accessible APA site database is necessary for improved understanding of APA-mediated gene expression regulation. We present a database called PlantAPAdb that catalogs the most comprehensive APA site data derived from sequences from diverse 3' sequencing protocols and biological samples in plants. Currently, PlantAPAdb contains APA sites in six species, Oryza sativa (japonica and indica), Arabidopsis (Arabidopsis thaliana), Medicago truncatula, Trifolium pratense, Phyllostachys edulis, and Chlamydomonas reinhardtii APA sites in PlantAPAdb are available for bulk download and can be queried in a Google-like manner. PlantAPAdb provides rich information of the whole-genome APA sites, including genomic locations, heterogeneous cleavage sites, expression levels, and sample information. It also provides comprehensive poly(A) signals for APA sites in different genomic regions according to distinct profiles of cis-elements in plants. In addition, PlantAPAdb contains events of 3' untranslated region shortening/lengthening resulting from APA, which helps to understand the mechanisms underlying systematic changes in 3' untranslated region lengths. Additional information about conservation of APA sites in plants is also available, providing insights into the evolutionary polyadenylation configuration across species. As a user-friendly database, PlantAPAdb is a large and extendable resource for elucidating APA mechanisms, APA conservation, and gene expression regulation.

Inference of the human polyadenylation code

Motivation

Processing of transcripts at the 3′-end involves cleavage at a polyadenylation site followed by the addition of a poly(A)-tail. By selecting which site is cleaved, the process of alternative polyadenylation enables genes to produce transcript isoforms with different 3′-ends. To facilitate the identification and treatment of disease-causing mutations that affect polyadenylation and to understand the sequence determinants underlying this regulatory process, a computational model that can accurately predict polyadenylation patterns from genomic features is desirable.

Results

Previous works have focused on identifying candidate polyadenylation sites and classifying tissue-specific sites. By training on how multiple sites in genes are competitively selected for polyadenylation from 3′-end sequencing data, we developed a deep learning model that can predict the tissue-specific strength of a polyadenylation site in the 3′ untranslated region of the human genome given only its genomic sequence. We demonstrate the model’s broad utility on multiple tasks, without any application-specific training. The model can be used to predict which polyadenylation site is more likely to be selected in genes with multiple sites. It can be used to scan the 3′ untranslated region to find candidate polyadenylation sites. It can be used to classify the pathogenicity of variants near annotated polyadenylation sites in ClinVar. It can also be used to anticipate the effect of antisense oligonucleotide experiments to redirect polyadenylation. We provide analysis on how different features affect the model’s predictive performance and a method to identify sensitive regions of the genome at the single-based resolution that can affect polyadenylation regulation.

Supplementary information

Supplementary data are available at Bioinformatics online.

PolyA_DB 3 catalogs cleavage and polyadenylation sites identified by deep sequencing in multiple genomes

PolyA_DB is a database cataloging cleavage and polyadenylation sites (PASs) in several genomes. Previous versions were based mainly on expressed sequence tags (ESTs), which had a limited amount and could lead to inaccurate PAS identification due to the presence of internal A-rich sequences in transcripts. Here, we present an updated version of the database based solely on deep sequencing data. First, PASs are mapped by the 3′ region extraction and deep sequencing (3′READS) method, ensuring unequivocal PAS identification. Second, a large volume of data based on diverse biological samples increases PAS coverage by 3.5-fold over the EST-based version and provides PAS usage information. Third, strand-specific RNA-seq data are used to extend annotated 3′ ends of genes to obtain more thorough annotations of alternative polyadenylation (APA) sites. Fourth, conservation information of PAS across mammals sheds light on significance of APA sites. The database (URL: http://www.polya-db.org/v3) currently holds PASs in human, mouse, rat and chicken, and has links to the UCSC genome browser for further visualization and for integration with other genomic data.

TC3A: The Cancer 3' UTR Atlas

Widespread alternative polyadenylation (APA) occurs during enhanced cellular proliferation and transformation. Recently, we demonstrated that CFIm25-mediated 3′ UTR shortening through APA promotes glioblastoma tumor growth in vitro and in vivo, further underscoring its significance to tumorigenesis. Here, we report The Cancer 3′ UTR Atlas (TC3A), a comprehensive resource of APA usage for 10,537 tumors across 32 cancer types. These APA events represent potentially novel prognostic biomarkers and may uncover novel mechanisms for the regulation of cancer driver genes. TC3A is built on top of the now de facto standard cBioPortal. Therefore, the large community of existing cBioPortal users and clinical researchers will find TC3A familiar and immediately usable. TC3A is currently fully functional and freely available at http://tc3a.org.

Alternative polyadenylation produces multiple 3' untranslated regions of odorant receptor mRNAs in mouse olfactory sensory neurons

BACKGROUND

Odorant receptor genes constitute the largest gene family in mammalian genomes and this family has been extensively studied in several species, but to date far less attention has been paid to the characterization of their mRNA 3' untranslated regions (3'UTRs). Given the increasing importance of UTRs in the understanding of RNA metabolism, and the growing interest in alternative polyadenylation especially in the nervous system, we aimed at identifying the alternative isoforms of odorant receptor mRNAs generated through 3'UTR variation.

RESULTS

We implemented a dedicated pipeline using IsoSCM instead of Cufflinks to analyze RNA-Seq data from whole olfactory mucosa of adult mice and obtained an extensive description of the 3'UTR isoforms of odorant receptor mRNAs. To validate our bioinformatics approach, we exhaustively analyzed the 3'UTR isoforms produced from 2 pilot genes, using molecular approaches including northern blot and RNA ligation mediated polyadenylation test. Comparison between datasets further validated the pipeline and confirmed the alternative polyadenylation patterns of odorant receptors. Qualitative and quantitative analyses of the annotated 3' regions demonstrate that 1) Odorant receptor 3'UTRs are longer than previously described in the literature; 2) More than 77% of odorant receptor mRNAs are subject to alternative polyadenylation, hence generating at least 2 detectable 3'UTR isoforms; 3) Splicing events in 3'UTRs are restricted to a limited subset of odorant receptor genes; and 4) Comparison between male and female data shows no sex-specific differences in odorant receptor 3'UTR isoforms.

CONCLUSIONS

We demonstrated for the first time that odorant receptor genes are extensively subject to alternative polyadenylation. This ground-breaking change to the landscape of 3'UTR isoforms of Olfr mRNAs opens new avenues for investigating their respective functions, especially during the differentiation of olfactory sensory neurons.

A survey on identification and quantification of alternative polyadenylation sites from RNA-seq data

Alternative polyadenylation (APA) has been implicated to play an important role in post-transcriptional regulation by regulating mRNA abundance, stability, localization and translation, which contributes considerably to transcriptome diversity and gene expression regulation. RNA-seq has become a routine approach for transcriptome profiling, generating unprecedented data that could be used to identify and quantify APA site usage. A number of computational approaches for identifying APA sites and/or dynamic APA events from RNA-seq data have emerged in the literature, which provide valuable yet preliminary results that should be refined to yield credible guidelines for the scientific community. In this review, we provided a comprehensive overview of the status of currently available computational approaches. We also conducted objective benchmarking analysis using RNA-seq data sets from different species (human, mouse and Arabidopsis) and simulated data sets to present a systematic evaluation of 11 representative methods. Our benchmarking study showed that the overall performance of all tools investigated is moderate, reflecting that there is still lot of scope to improve the prediction of APA site or dynamic APA events from RNA-seq data. Particularly, prediction results from individual tools differ considerably, and only a limited number of predicted APA sites or genes are common among different tools. Accordingly, we attempted to give some advice on how to assess the reliability of the obtained results. We also proposed practical recommendations on the appropriate method applicable to diverse scenarios and discussed implications and future directions relevant to profiling APA from RNA-seq data.

Alternative polyadenylation confers Pten mRNAs stability and resistance to microRNAs

Fine regulation of the phosphatase and tensin homologue (PTEN) phosphatase dosage is critical for homeostasis and tumour suppression. The 3'-untranslated region (3'-UTR) of Pten mRNA was extensively linked to post-transcriptional regulation by microRNAs (miRNAs). In spite of this critical regulatory role, alternative 3'-UTRs of Pten have not been systematically characterized. Here, we reveal an important diversity of Pten mRNA isoforms generated by alternative polyadenylation sites. Several 3'-UTRs are co-expressed and their relative expression is dynamically regulated. In spite of encoding multiple validated miRNA-binding sites, longer isoforms are largely refractory to miRNA-mediated silencing, are more stable and contribute to the bulk of PTEN protein and signalling functions. Taken together, our results warrant a mechanistic re-interpretation of the post-transcriptional mechanisms involving Pten mRNAs and raise concerns on how miRNA-binding sites are being validated.

A Deep Neural Network for Predicting and Engineering Alternative Polyadenylation

Alternative polyadenylation (APA) is a major driver of transcriptome diversity in human cells. Here, we use deep learning to predict APA from DNA sequence alone. We trained our model (APARENT, APA REgression NeT) on isoform expression data from over 3 million APA reporters. APARENT's predictions are highly accurate when tasked with inferring APA in synthetic and human 3'UTRs. Visualizing features learned across all network layers reveals that APARENT recognizes sequence motifs known to recruit APA regulators, discovers previously unknown sequence determinants of 3' end processing, and integrates these features into a comprehensive, interpretable, cis-regulatory code. We apply APARENT to forward engineer functional polyadenylation signals with precisely defined cleavage position and isoform usage and validate predictions experimentally. Finally, we use APARENT to quantify the impact of genetic variants on APA. Our approach detects pathogenic variants in a wide range of disease contexts, expanding our understanding of the genetic origins of disease.

CFIm25 and alternative polyadenylation: Conflicting roles in cancer

Alternative polyadenylation (APA) is now widely recognized to regulate gene expression. APA is an RNA-processing mechanism that generates distinct 3' termini on mRNAs, producing mRNA isoforms. Different factors influence the initiation and development of this process. CFIm25 (among others) is a cleavage and polyadenylation factor that plays a key role in the regulation of APA. Shortening of the 3'UTRs on mRNAs leads to enhanced cellular proliferation and tumorigenicity. One reason may be the up-regulation of growth promoting factors, such as Cyclin D1. Different studies have reported a dual role of CFIm25 in cancer (both oncogenic and tumor suppressor). microRNAs (miRNAs) may be involved in CFIm25 function as well as competing endogenous RNAs (ceRNAs). The present review focuses on the role of CFIm25 in cancer, cancer treatment, and possible involvement in other human diseases. We highlight the involvement of miRNAs and ceRNAs in the function of CFIm25 to affect gene expression. The lack of understanding of the mechanisms and regulation of CFIm25 and APA has underscored the need for further research regarding their role in cancer and other diseases.

MALAT1 regulates the transcriptional and translational levels of proto-oncogene RUNX2 in colorectal cancer metastasis

Ectopic expression of lncRNA-MALAT1 has been discovered in recurrent colorectal cancer (CRC) and metastatic sites in postsurgical patients, however, its biological mechanism remained unelucidated. Our study first revealed the novel roles of MALAT1 in promoting CRC metastasis through two mechanisms: first, MALAT1 binds miR-15 family members, to "de-inhibit" their effect on LRP6 expression, enhances β-catenin signaling, leading to elevated transcriptional levels of downstream target genes RUNX2. Second, MALAT1 binds SFPQ, and dissociates SFPQ/PTBP2 dimer to release free PTBP2, which elevates translational levels of RUNX2, through interacting with IRES domain in the 5'UTR of the corresponding RUNX2 mRNAs. Moreover, increased RUNX2 expression levels were detected in recurrent CRC tumors, which were closely associated with TMN stages, metastasis, as well as CRC patients' survival. Our study demonstrated that MALAT1 and RUNX2 may serve as two biomarkers for predicting the recurrence and metastasis of CRC patients.

Nudt21 regulates the alternative polyadenylation of Pak1 and is predictive in the prognosis of glioblastoma patients

Alternative polyadenylation (APA) has emerged as a prevalent feature associated with cancer development and progression. The advantage of APA to tumor progression is to induce oncogenes through 3'-UTR shortening, and to inactivate tumor suppressor genes via the re-routing of microRNA competition. We previously identified the Mammalian Cleavage Factor I-25 (CFIm25) (encoded by Nudt21 gene) as a master APA regulator whose expression levels directly impact the tumorigenicity of glioblastoma (GBM) in vitro and in vivo. Despite its importance, the role of Nudt21 in GBM development is not known and the genes subject to Nudt21 APA regulation that contribute to GBM progression have not been identified. Here, we find that Nudt21 is reduced in low grade glioma (LGG) and all four subtypes of high grade glioma (GBM). Reduced expression of Nudt21 associates with worse survival in TCGA LGG cohorts and two TCGA GBM cohorts. Moreover, although CFIm25 was initially identified as biochemically associated with both CFIm59 and CFIm68, we observed three CFIm distinct subcomplexes exist and CFIm59 protein level is dependent on Nudt21 expression in GBM cells, but CFIm68 is not, and that only CFIm59 predicts prognosis of GBM patients similar to Nudt21. Through the use of Poly(A)-Click-Seq to characterize APA, we define the mRNAs subject to 3'-UTR shortening upon Nudt21 depletion in GBM cells and observed enrichment in genes important in the Ras signaling pathway, including Pak1. Remarkably, we find that Pak1 expression is regulated by Nudt21 through its 3'-UTR APA, and the combination of Pak1 and Nudt21 expression generates an even stronger prognostic indicator of GBM survival versus either value used alone. Collectively, our data uncover Nudt21 and its downstream target Pak1 as a potential "combination biomarker" for predicting prognosis of GBM patients.

Loss of the Chr16p11.2 ASD candidate gene QPRT leads to aberrant neuronal differentiation in the SH-SY5Y neuronal cell model

Background

Altered neuronal development is discussed as the underlying pathogenic mechanism of autism spectrum disorders (ASD). Copy number variations of 16p11.2 have recurrently been identified in individuals with ASD. Of the 29 genes within this region, quinolinate phosphoribosyltransferase (QPRT) showed the strongest regulation during neuronal differentiation of SH-SY5Y neuroblastoma cells. We hypothesized a causal relation between this tryptophan metabolism-related enzyme and neuronal differentiation. We thus analyzed the effect of QPRT on the differentiation of SH-SY5Y and specifically focused on neuronal morphology, metabolites of the tryptophan pathway, and the neurodevelopmental transcriptome.

Methods

The gene dosage-dependent change of QPRT expression following Chr16p11.2 deletion was investigated in a lymphoblastoid cell line (LCL) of a deletion carrier and compared to his non-carrier parents. Expression of QPRT was tested for correlation with neuromorphology in SH-SY5Y cells. QPRT function was inhibited in SH-SY5Y neuroblastoma cells using (i) siRNA knockdown (KD), (ii) chemical mimicking of loss of QPRT, and (iii) complete CRISPR/Cas9-mediated knock out (KO). QPRT-KD cells underwent morphological analysis. Chemically inhibited and QPRT-KO cells were characterized using viability assays. Additionally, QPRT-KO cells underwent metabolite and whole transcriptome analyses. Genes differentially expressed upon KO of QPRT were tested for enrichment in biological processes and co-regulated gene-networks of the human brain.

Results

QPRT expression was reduced in the LCL of the deletion carrier and significantly correlated with the neuritic complexity of SH-SY5Y. The reduction of QPRT altered neuronal morphology of differentiated SH-SY5Y cells. Chemical inhibition as well as complete KO of the gene were lethal upon induction of neuronal differentiation, but not proliferation. The QPRT-associated tryptophan pathway was not affected by KO. At the transcriptome level, genes linked to neurodevelopmental processes and synaptic structures were affected. Differentially regulated genes were enriched for ASD candidates, and co-regulated gene networks were implicated in the development of the dorsolateral prefrontal cortex, the hippocampus, and the amygdala.

Conclusions

In this study, QPRT was causally related to in vitro neuronal differentiation of SH-SY5Y cells and affected the regulation of genes and gene networks previously implicated in ASD. Thus, our data suggest that QPRT may play an important role in the pathogenesis of ASD in Chr16p11.2 deletion carriers.

Maximizing the Utility of Cancer Transcriptomic Data

Transcriptomic profiling has been applied to large numbers of cancer samples, by large-scale consortia, including The Cancer Genome Atlas, International Cancer Genome Consortium, and Cancer Cell Line Encyclopedia. Advances in mining cancer transcriptomic data enable us to understand the endless complexity of the cancer transcriptome and thereby to discover new biomarkers and therapeutic targets. In this paper, we review computational resources for deep mining of transcriptomic data to identify, quantify, and determine the functional effects and clinical utility of transcriptomic events, including noncoding RNAs, post-transcriptional regulation, exogenous RNAs, and transcribed genetic variants. These approaches can be applied to other complex diseases, thereby greatly leveraging the impact of this work.

Alternative polyadenylation analysis in animals and plants: newly developed strategies for profiling, processing and validation

Alternative polyadenylation is an essential RNA processing event that contributes significantly to regulation of transcriptome diversity and functional dynamics in both animals and plants. Here we review newly developed next generation sequencing methods for genome-wide profiling of alternative polyadenylation (APA) sites, bioinformatics pipelines for data processing and both wet and dry laboratory approaches for APA validation. The library construction methods LITE-Seq (Low-Input 3'-Terminal sequencing) and PAC-seq (PolyA Click sequencing) tag polyA+ cDNA, while BAT-seq (BArcoded, three-prime specific sequencing) and PAPERCLIP (Poly(A) binding Protein-mediated mRNA 3'End Retrieval by CrossLinking ImmunoPrecipitation) enrich polyA+ RNA. Interestingly, only WTTS-seq (Whole Transcriptome Termini Site sequencing) targets both polyA+ RNA and polyA+ cDNA. Varieties of bioinformatics pipelines are well established to pursue read quality control, mapping, clustering, characterization and pathway analysis. The RHAPA (RNase H alternative polyadenylation assay) and 3'RACE-seq (3' rapid amplification of cDNA end sequencing) methods directly validate APA sites, while WTSS-seq (whole transcriptome start site sequencing), RNA-seq (RNA sequencing) and public APA databases can serve as indirect validation methods. We hope that these tools, pipelines and resources trigger huge waves of interest in the research community to investigate APA events underlying physiological, pathological and psychological changes and thus understand the information transfer events from genome to phenome relevant to economically important traits in both animals and plants.

Alternative 3' UTRs Modify the Localization, Regulatory Potential, Stability, and Plasticity of mRNAs in Neuronal Compartments

Neurons localize mRNAs near synapses where their translation can be regulated by synaptic demand and activity. Differences in the 3' UTRs of mRNAs can change their localization, stability, and translational regulation. Using 3' end RNA sequencing of microdissected rat brain slices, we discovered a huge diversity in mRNA 3' UTRs, with many transcripts showing enrichment for a particular 3' UTR isoform in either somata or the neuropil. The 3' UTR isoforms of localized transcripts are significantly longer than the 3' UTRs of non-localized transcripts and often code for proteins associated with axons, dendrites, and synapses. Surprisingly, long 3' UTRs add not only new, but also duplicate regulatory elements. The neuropil-enriched 3' UTR isoforms have significantly longer half-lives than somata-enriched isoforms. Finally, the 3' UTR isoforms can be significantly altered by enhanced activity. Most of the 3' UTR plasticity is transcription dependent, but intriguing examples of changes that are consistent with altered stability, trafficking between compartments, or local "remodeling" remain.

Alu exaptation enriches the human transcriptome by introducing new gene ends

In mammals, transposable elements are largely silenced, but under fortuitous circumstances may be co-opted to play a functional role. Here, we show that when Alu elements are inserted within or nearby genes in sense orientation, they may contribute to the transcriptome diversity by forming new cleavage and polyadenylation sites. We mapped these new gene ends in human onto the Alu sequence and identified three hotspots of cleavage and polyadenylation site formation. Interestingly, the native Alu sequence does not contain any canonical polyadenylation signal. We therefore studied what evolutionary processes might explain the formation of these specific hotspots of novel gene ends. We show that two of the three hotspots might have emerged from mutational processes that turned sequences that resemble polyadenylation signals into full-blown canonical signals, whereas one hotspot is tightly linked to the process of Alu insertion into the genome. Overall, Alu elements may lie behind the formation of 302 new gene end variants, affecting a total of 243 genes. Intergenic Alu elements may elongate genes by creating a downstream cleavage site, intronic Alu elements may lead to gene variants which code for truncated proteins, and 3'UTR Alu elements may result in gene variants with alternative 3'UTR.