APAlyzer: a bioinformatics package for analysis of alternative polyadenylation isoforms

A pan-cancer interrogation of intronic polyadenylation and its association with cancer characteristics

3'UTR-APAs have been extensively studied, but intronic polyadenylations (IPAs) remain largely unexplored. We characterized the profiles of 22 260 IPAs in 9679 patient samples across 32 cancer types from the Cancer Genome Atlas cohort. By comparing tumor and paired normal tissues, we identified 180 ~ 4645 dysregulated IPAs in 132 ~ 2249 genes in each of 690 patient tumors from 22 cancer types that showed consistent patterns within individual cancer types. We selected 2741 genes that showed consistently patterns across cancer types, including 1834 pan-cancer tumor-enriched and 907 tumor-depleted IPA genes; the former were amply represented in the functional pathways such as deoxyribonucleic acid damage repair. Expression of IPA isoforms was associated with tumor mutation burden and patient characteristics (e.g. sex, race, cancer stages, and subtypes) in cancer-specific and feature-specific manners, and could be a more accurate prognostic marker than gene expression (summary of all isoforms). In summary, our study reveals the roles and the clinical relevance of tumor-associated IPAs.

Molecular consequences of acute versus chronic CDK12 loss in prostate carcinoma nominates distinct therapeutic strategies

Genomic loss of the transcriptional kinase CDK12 occurs in ~6% of metastatic castration-resistant prostate cancers (mCRPC) and correlates with poor patient outcomes. Prior studies demonstrate that acute CDK12 loss confers a homologous recombination (HR) deficiency (HRd) phenotype via premature intronic polyadenylation (IPA) of key HR pathway genes, including ATM. However, mCRPC patients have not demonstrated benefit from therapies that exploit HRd such as inhibitors of polyADP ribose polymerase (PARP). Based on this discordance, we sought to test the hypothesis that an HRd phenotype is primarily a consequence of acute CDK12 loss and the effect is greatly diminished in prostate cancers adapted to CDK12 loss. Analyses of whole genome sequences (WGS) and RNA sequences (RNAseq) of human mCRPCs determined that tumors with biallelic CDK12 alterations (CDK12 BAL ) lack genomic scar signatures indicative of HRd, despite carrying bi-allelic loss and the appearance of the hallmark tandem-duplicator phenotype (TDP). Experiments confirmed that acute CDK12 inhibition resulted in aberrant polyadenylation and downregulation of long genes (including BRCA1 and BRCA2) but such effects were modest or absent in tumors adapted to chronic CDK12 BAL . One key exception was ATM, which did retain transcript shortening and reduced protein expression in the adapted CDK12 BAL models. However, CDK12 BAL cells demonstrated intact HR as measured by RAD51 foci formation following irradiation. CDK12 BAL cells showed a vulnerability to targeting of CDK13 by sgRNA or CDK12/13 inhibitors and in vivo treatment of prostate cancer xenograft lines showed that tumors with CDK12 BAL responded to the CDK12/13 inhibitor SR4835, while CDK12-intact lines did not. Collectively, these studies show that aberrant polyadenylation and long HR gene downregulation is primarily a consequence of acute CDK12 deficiency, which is largely compensated for in cells that have adapted to CDK12 loss. These results provide an explanation for why PARPi monotherapy has thus far failed to consistently benefit patients with CDK12 alterations, though alternate therapies that target CDK13 or transcription are candidates for future research and testing.

T helper cells exhibit a dynamic and reversible 3'-UTR landscape

3' untranslated regions (3' UTRs) are critical elements of messenger RNAs, as they contain binding sites for RNA-binding proteins (RBPs) and microRNAs that affect various aspects of the RNA life cycle including transcript stability and cellular localization. In response to T cell receptor activation, T cells undergo massive expansion during the effector phase of the immune response and dynamically modify their 3' UTRs. Whether this serves to directly regulate the abundance of specific mRNAs or is a secondary effect of proliferation remains unclear. To study 3'-UTR dynamics in T helper cells, we investigated division-dependent alternative polyadenylation (APA). In addition, we generated 3' end UTR sequencing data from naive, activated, memory, and regulatory CD4+ T cells. 3'-UTR length changes were estimated using a nonnegative matrix factorization approach and were compared with those inferred from long-read PacBio sequencing. We found that APA events were transient and reverted after effector phase expansion. Using an orthogonal bulk RNA-seq data set, we did not find evidence of APA association with differential gene expression or transcript usage, indicating that APA has only a marginal effect on transcript abundance. 3'-UTR sequence analysis revealed conserved binding sites for T cell-relevant microRNAs and RBPs in the alternative 3' UTRs. These results indicate that poly(A) site usage could play an important role in the control of cell fate decisions and homeostasis.

Alternative polyadenylation quantitative trait methylation mapping in human cancers provides clues into the molecular mechanisms of APA

Genetic variants are involved in the orchestration of alternative polyadenylation (APA) events, while the role of DNA methylation in regulating APA remains unclear. We generated a comprehensive atlas of APA quantitative trait methylation sites (apaQTMs) across 21 different types of cancer (1,612 to 60,219 acting in cis and 4,448 to 142,349 in trans). Potential causal apaQTMs in non-cancer samples were also identified. Mechanistically, we observed a strong enrichment of cis-apaQTMs near polyadenylation sites (PASs) and both cis- and trans-apaQTMs in proximity to transcription factor (TF) binding regions. Through the integration of ChIP-signals and RNA-seq data from cell lines, we have identified several regulators of APA events, acting either directly or indirectly, implicating novel functions of some important genes, such as TCF7L2, which is known for its involvement in type 2 diabetes and cancers. Furthermore, we have identified a vast number of QTMs that share the same putative causal CpG sites with five different cancer types, underscoring the roles of QTMs, including apaQTMs, in the process of tumorigenesis. DNA methylation is extensively involved in the regulation of APA events in human cancers. In an attempt to elucidate the potential underlying molecular mechanisms of APA by DNA methylation, our study paves the way for subsequent experimental validations into the intricate biological functions of DNA methylation in APA regulation and the pathogenesis of human cancers. To present a comprehensive catalog of apaQTM patterns, we introduce the Pancan-apaQTM database, available at https://pancan-apaqtm-zju.shinyapps.io/pancanaQTM/.

PolyAMiner-Bulk is a deep learning-based algorithm that decodes alternative polyadenylation dynamics from bulk RNA-seq data

Alternative polyadenylation (APA) is a key post-transcriptional regulatory mechanism; yet, its regulation and impact on human diseases remain understudied. Existing bulk RNA sequencing (RNA-seq)-based APA methods predominantly rely on predefined annotations, severely impacting their ability to decode novel tissue- and disease-specific APA changes. Furthermore, they only account for the most proximal and distal cleavage and polyadenylation sites (C/PASs). Deconvoluting overlapping C/PASs and the inherent noisy 3' UTR coverage in bulk RNA-seq data pose additional challenges. To overcome these limitations, we introduce PolyAMiner-Bulk, an attention-based deep learning algorithm that accurately recapitulates C/PAS sequence grammar, resolves overlapping C/PASs, captures non-proximal-to-distal APA changes, and generates visualizations to illustrate APA dynamics. Evaluation on multiple datasets strongly evinces the performance merit of PolyAMiner-Bulk, accurately identifying more APA changes compared with other methods. With the growing importance of APA and the abundance of bulk RNA-seq data, PolyAMiner-Bulk establishes a robust paradigm of APA analysis.

Multiplexed screening reveals how cancer-specific alternative polyadenylation shapes tumor growth in vivo

Alternative polyadenylation (APA) is strikingly dysregulated in many cancers. Although global APA dysregulation is frequently associated with poor prognosis, the importance of most individual APA events is controversial simply because few have been functionally studied. Here, we address this gap by developing a CRISPR-Cas9-based screen to manipulate endogenous polyadenylation and systematically quantify how APA events contribute to tumor growth in vivo. Our screen reveals individual APA events that control mouse melanoma growth in an immunocompetent host, with concordant associations in clinical human cancer. For example, forced Atg7 3' UTR lengthening in mouse melanoma suppresses ATG7 protein levels, slows tumor growth, and improves host survival; similarly, in clinical human melanoma, a long ATG7 3' UTR is associated with significantly prolonged patient survival. Overall, our study provides an easily adaptable means to functionally dissect APA in physiological systems and directly quantifies the contributions of recurrent APA events to tumorigenic phenotypes.

TDP-43 nuclear loss in FTD/ALS causes widespread alternative polyadenylation changes

In frontotemporal dementia and amyotrophic lateral sclerosis, the RNA-binding protein TDP-43 is depleted from the nucleus. TDP-43 loss leads to cryptic exon inclusion but a role in other RNA processing events remains unresolved. Here, we show that loss of TDP-43 causes widespread changes in alternative polyadenylation, impacting expression of disease-relevant genes (e.g., ELP1, NEFL, and TMEM106B) and providing evidence that alternative polyadenylation is a new facet of TDP-43 pathology.

Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data

The tremendous rate with which data is generated and analysis methods emerge makes it increasingly difficult to keep track of their domain of applicability, assumptions, limitations, and consequently, of the efficacy and precision with which they solve specific tasks. Therefore, there is an increasing need for benchmarks, and for the provision of infrastructure for continuous method evaluation. APAeval is an international community effort, organized by the RNA Society in 2021, to benchmark tools for the identification and quantification of the usage of alternative polyadenylation (APA) sites from short-read, bulk RNA-sequencing (RNA-seq) data. Here, we reviewed 17 tools and benchmarked eight on their ability to perform APA identification and quantification, using a comprehensive set of RNA-seq experiments comprising real, synthetic, and matched 3'-end sequencing data. To support continuous benchmarking, we have incorporated the results into the OpenEBench online platform, which allows for continuous extension of the set of methods, metrics, and challenges. We envisage that our analyses will assist researchers in selecting the appropriate tools for their studies, while the containers and reproducible workflows could easily be deployed and extended to evaluate new methods or data sets.

The emerging theme of 3'UTR mRNA isoform regulation in reprogramming of cell metabolism

The 3' untranslated region (3'UTR) of mRNA plays a key role in the post-transcriptional regulation of gene expression. Most eukaryotic protein-coding genes express 3'UTR isoforms owing to alternative cleavage and polyadenylation (APA). The 3'UTR isoform expression profile of a cell changes in cell proliferation, differentiation, and stress conditions. Here, we review the emerging theme of regulation of 3'UTR isoforms in cell metabolic reprogramming, focusing on cell growth and autophagy responses through the mTOR pathway. We discuss regulatory events that converge on the Cleavage Factor I complex, a master regulator of APA in 3'UTRs, and recent understandings of isoform-specific m6A modification and endomembrane association in determining differential metabolic fates of 3'UTR isoforms.

Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data

The tremendous rate with which data is generated and analysis methods emerge makes it increasingly difficult to keep track of their domain of applicability, assumptions, and limitations and consequently, of the efficacy and precision with which they solve specific tasks. Therefore, there is an increasing need for benchmarks, and for the provision of infrastructure for continuous method evaluation. APAeval is an international community effort, organized by the RNA Society in 2021, to benchmark tools for the identification and quantification of the usage of alternative polyadenylation (APA) sites from short-read, bulk RNA-sequencing (RNA-seq) data. Here, we reviewed 17 tools and benchmarked eight on their ability to perform APA identification and quantification, using a comprehensive set of RNA-seq experiments comprising real, synthetic, and matched 3'-end sequencing data. To support continuous benchmarking, we have incorporated the results into the OpenEBench online platform, which allows for seamless extension of the set of methods, metrics, and challenges. We envisage that our analyses will assist researchers in selecting the appropriate tools for their studies. Furthermore, the containers and reproducible workflows generated in the course of this project can be seamlessly deployed and extended in the future to evaluate new methods or datasets.

Pro-inflammatory polarization and colorectal cancer modulate alternative and intronic polyadenylation in primary human macrophages

Introduction

Macrophages are essential cells of the immune system that alter their inflammatory profile depending on their microenvironment. Alternative polyadenylation in the 3'UTR (3'UTR-APA) and intronic polyadenylation (IPA) are mechanisms that modulate gene expression, particularly in cancer and activated immune cells. Yet, how polarization and colorectal cancer (CRC) cells affect 3'UTR-APA and IPA in primary human macrophages was unclear.

Methods

In this study, we isolated primary human monocytes from healthy donors, differentiated and polarized them into a pro-inflammatory state and performed indirect co-cultures with CRC cells. ChrRNA-Seq and 3'RNA-Seq was performed to quantify gene expression and characterize new 3'UTR-APA and IPA mRNA isoforms.

Results

Our results show that polarization of human macrophages from naïve to a pro-inflammatory state causes a marked increase of proximal polyA site selection in the 3'UTR and IPA events in genes relevant to macrophage functions. Additionally, we found a negative correlation between differential gene expression and IPA during pro-inflammatory polarization of primary human macrophages. As macrophages are abundant immune cells in the CRC microenvironment that either promote or abrogate cancer progression, we investigated how indirect exposure to CRC cells affects macrophage gene expression and 3'UTR-APA and IPA events. Co-culture with CRC cells alters the inflammatory phenotype of macrophages, increases the expression of pro-tumoral genes and induces 3'UTR-APA alterations. Notably, some of these gene expression differences were also found in tumor-associated macrophages of CRC patients, indicating that they are physiologically relevant. Upon macrophage pro-inflammatory polarization, SRSF12 is the pre-mRNA processing gene that is most upregulated. After SRSF12 knockdown in M1 macrophages there is a global downregulation of gene expression, in particular in genes involved in gene expression regulation and in immune responses.

Discussion

Our results reveal new 3'UTR-APA and IPA mRNA isoforms produced during pro-inflammatory polarization of primary human macrophages and CRC co-culture that may be used in the future as diagnostic or therapeutic tools. Furthermore, our results highlight a function for SRSF12 in pro-inflammatory macrophages, key cells in the tumor response.

Transcriptome sequencing suggests that pre-mRNA splicing counteracts widespread intronic cleavage and polyadenylation

Alternative splicing (AS) and alternative polyadenylation (APA) are two crucial steps in the post-transcriptional regulation of eukaryotic gene expression. Protocols capturing and sequencing RNA 3'-ends have uncovered widespread intronic polyadenylation (IPA) in normal and disease conditions, where it is currently attributed to stochastic variations in the pre-mRNA processing. Here, we took advantage of the massive amount of RNA-seq data generated by the Genotype Tissue Expression project (GTEx) to simultaneously identify and match tissue-specific expression of intronic polyadenylation sites with tissue-specific splicing. A combination of computational methods including the analysis of short reads with non-templated adenines revealed that APA events are more abundant in introns than in exons. While the rate of IPA in composite terminal exons and skipped terminal exons expectedly correlates with splicing, we observed a considerable fraction of IPA events that lack AS support and attributed them to spliced polyadenylated introns (SPI). We hypothesize that SPIs represent transient byproducts of a dynamic coupling between APA and AS, in which the spliceosome removes the intron while it is being cleaved and polyadenylated. These findings indicate that cotranscriptional pre-mRNA splicing could serve as a rescue mechanism to suppress premature transcription termination at intronic polyadenylation sites.

PolyAMiner-Bulk: A Machine Learning Based Bioinformatics Algorithm to Infer and Decode Alternative Polyadenylation Dynamics from bulk RNA-seq data

More than half of human genes exercise alternative polyadenylation (APA) and generate mRNA transcripts with varying 3' untranslated regions (UTR). However, current computational approaches for identifying cleavage and polyadenylation sites (C/PASs) and quantifying 3'UTR length changes from bulk RNA-seq data fail to unravel tissue- and disease-specific APA dynamics. Here, we developed a next-generation bioinformatics algorithm and application, PolyAMiner-Bulk, that utilizes an attention-based machine learning architecture and an improved vector projection-based engine to infer differential APA dynamics accurately. When applied to earlier studies, PolyAMiner-Bulk accurately identified more than twice the number of APA changes in an RBM17 knockdown bulk RNA-seq dataset compared to current generation tools. Moreover, on a separate dataset, PolyAMiner-Bulk revealed novel APA dynamics and pathways in scleroderma pathology and identified differential APA in a gene that was identified as being involved in scleroderma pathogenesis in an independent study. Lastly, we used PolyAMiner-Bulk to analyze the RNA-seq data of post-mortem prefrontal cortexes from the ROSMAP data consortium and unraveled novel APA dynamics in Alzheimer's Disease. Our method, PolyAMiner-Bulk, creates a paradigm for future alternative polyadenylation analysis from bulk RNA-seq data.

Transcript shortening via alternative polyadenylation promotes gene expression during fracture healing

Maturation of the 3' end of almost all eukaryotic messenger RNAs (mRNAs) requires cleavage and polyadenylation. Most mammalian mRNAs are polyadenylated at different sites within the last exon, generating alternative polyadenylation (APA) isoforms that have the same coding region but distinct 3' untranslated regions (UTRs). The 3'UTR contains motifs that regulate mRNA metabolism; thus, changing the 3'UTR length via APA can significantly affect gene expression. Endochondral ossification is a central process in bone healing, but the impact of APA on gene expression during this process is unknown. Here, we report the widespread occurrence of APA, which impacts multiple pathways that are known to participate in bone healing. Importantly, the progression of endochondral ossification involves global 3'UTR shortening, which is coupled with an increased abundance of shortened transcripts relative to other transcripts; these results highlight the role of APA in promoting gene expression during endochondral bone formation. Our mechanistic studies of transcripts that undergo APA in the fracture callus revealed an intricate regulatory network in which APA enhances the expression of the collagen, type I, alpha 1 (Col1a1) and Col1a2 genes, which encode the 2 subunits of the abundantly expressed protein collagen 1. APA exerts this effect by shortening the 3'UTRs of the Col1a1 and Col1a2 mRNAs, thus removing the binding sites of miR-29a-3p, which would otherwise strongly promote the degradation of both transcripts. Taken together, our study is the first to characterize the crucial roles of APA in regulating the 3'UTR landscape and modulating gene expression during fracture healing.

UBE3D Regulates mRNA 3'-End Processing and Maintains Adipogenic Potential in 3T3-L1 Cells

We have previously described the role of an essential Saccharomyces cerevisiae gene, important for cleavage and polyadenylation 1 (IPA1), in the regulation of gene expression through its interaction with Ysh1, the endonuclease subunit of the mRNA 3'-end processing complex. Through a similar mechanism, the mammalian homolog ubiquitin protein ligase E3D (UBE3D) promotes the migratory and invasive potential of breast cancer cells, but its role in the regulation of gene expression during normal cellular differentiation has not previously been described. In this study, we show that CRISPR/Cas9-mediated knockout of Ube3d in 3T3-L1 cells blocks their ability to differentiate into mature adipocytes. Consistent with previous studies in other cell types, Ube3d knockout leads to decreased levels of CPSF73 and global changes in cellular mRNAs indicative of a loss of 3'-end processing capacity. Ube3d knockout cells also display decreased expression of known preadipogenic markers. Overexpression of either UBE3D or CPSF73 rescues the differentiation defect and partially restores protein levels of these markers. These results support a model in which UBE3D is necessary for the maintenance of the adipocyte-committed state via its regulation of the mRNA 3'-end processing machinery.

RNA-methyltransferase Nsun5 controls the maternal-to-zygotic transition by regulating maternal mRNA stability

BACKGROUND

RNA modification-induced ovarian dysgenesis appears to be necessary for ovary development. However, how m⁵ C (5-methylcytosine)-coordinating modificatory transcripts are dynamically regulated during oogenesis, and ovarian development is unknown. The purpose of this study was to determine whether NOP2/Sun RNA methyltransferase 5 (Nsun5) deletion leads to suppression of ovarian function and arrest of embryonic development. The regulation of mRNA decay and stability by m⁵ C modification is essential at multiple stages during the maternal-to-zygotic (MZT) transition.

METHODS

Mouse ovaries and oocytes with Nsun5^KO and the KGN cell line were subjected to m⁵ C identification, alternative splicing analysis and protein expression. BS-m⁵ C-seq, real-time polymerase chain reaction, Western blot, immunofluorescence and actinomycin D treatment assays were used. In particular, BS-m⁵ C-seq revealed a dynamic pattern of m⁵ C sites and genes in the ovaries between Nsun5^KO and WT mice at the 2-month and 6-month stages. Diverse bioinformatic tools were employed to identify target genes for Nsun5.

RESULTS

Here, a maternal mRNA stability study showed that deletion of the m⁵ C methyltransferase Nsun5 obstructs follicular development and ovarian function, which leads directly to inhibition of embryogenesis and embryo development. Dynamic analysis of m⁵ C revealed that the level of m⁵ C decreased in a time-dependent manner after Nsun5 knockout. Regarding the molecular mechanism, we found that Nsun5 deficiency caused a m⁵ C decline in the exon and 3'UTR regions that influenced the translation efficiency of Mitotic arrest deficient 2 like 2 (MAD2L2) and Growth differentiation factor 9 (GDF9) in the ovary. Mechanistic investigation of alternative splicing indicated that Nsun5^KO triggers aberrant events in the exon region of Brd8.

CONCLUSIONS

Nsun5 loss arrests follicular genesis and development in ovarian aging, indicating that Nsun5/m⁵ C-regulated maternal mRNA stabilization is essential for MZT transition.

CYCLIN K down-regulation induces androgen receptor gene intronic polyadenylation, variant expression and PARP inhibitor vulnerability in castration-resistant prostate cancer

Expression of androgen receptor variants (AR-Vs) is implicated in the development of castration-resistant prostate cancer (PCa). Others have shown that androgen depletion or antiandrogen treatment induces AR-V expression in PCa cell lines, xenografts, and patient samples, although the underlying mechanism remains unclear. Our findings reveal that hormonal therapy–induced CYCLIN K down-regulation represents a key mechanism that drives intronic polyadenylation (IPA) usage in the AR gene and AR-V expression and castration resistance in PCa, and that this mechanism of action can be therapeutically targeted by the PARP inhibitor.

Androgen receptor (AR) messenger RNA (mRNA) alternative splicing variants (AR-Vs) are implicated in castration-resistant progression of prostate cancer (PCa), although the molecular mechanism underlying the genesis of AR-Vs remains poorly understood. The CDK12 gene is often deleted or mutated in PCa and CDK12 deficiency is known to cause homologous recombination repair gene alteration or BRCAness via alternative polyadenylation (APA). Here, we demonstrate that pharmacological inhibition or genetic inactivation of CDK12 induces AR gene intronic (intron 3) polyadenylation (IPA) usage, AR-V expression, and PCa cell resistance to the antiandrogen enzalutamide (ENZ). We further show that AR binds to the CCNK gene promoter and up-regulates CYCLIN K expression. In contrast, ENZ decreases AR occupancy at the CCNK gene promoter and suppresses CYCLIN K expression. Similar to the effect of the CDK12 inhibitor, CYCLIN K degrader or ENZ treatment promotes AR gene IPA usage, AR-V expression, and ENZ-resistant growth of PCa cells. Importantly, we show that targeting BRCAness induced by CYCLIN K down-regulation with the PARP inhibitor overcomes ENZ resistance. Our findings identify CYCLIN K down-regulation as a key driver of IPA usage, hormonal therapy–induced AR-V expression, and castration resistance in PCa. These results suggest that hormonal therapy–induced AR-V expression and therapy resistance are vulnerable to PARP inhibitor treatment.

A Survey on Methods for Predicting Polyadenylation Sites from DNA Sequences, Bulk RNA-seq, and Single-cell RNA-seq

Alternative polyadenylation (APA) plays important roles in modulating mRNA stability, translation, and subcellular localization, and contributes extensively to shaping eukaryotic transcriptome complexity and proteome diversity. Identification of poly(A) sites (pAs) on a genome-wide scale is a critical step toward understanding the underlying mechanism of APA-mediated gene regulation. A number of established computational tools have been proposed to predict pAs from diverse genomic data. Here we provided an exhaustive overview of computational approaches for predicting pAs from DNA sequences, bulk RNA sequencing (RNA-seq) data, and single-cell RNA sequencing (scRNA-seq) data. Particularly, we examined several representative tools using bulk RNA-seq and scRNA-seq data from peripheral blood mononuclear cells and put forward operable suggestions on how to assess the reliability of pAs predicted by different tools. We also proposed practical guidelines on choosing appropriate methods applicable to diverse scenarios. Moreover, we discussed in depth the challenges in improving the performance of pA prediction and benchmarking different methods. Additionally, we highlighted outstanding challenges and opportunities using new machine learning and integrative multi-omics techniques, and provided our perspective on how computational methodologies might evolve in the future for non-3' untranslated region, tissue-specific, cross-species, and single-cell pA prediction.

Lung cancer cells expressing a shortened CDK16 3'UTR escape senescence through impaired miR-485-5p targeting

Inducing senescence in cancer cells is an emerging strategy for cancer therapy. The dysregulation and mutation of genes encoding cyclin‐dependent kinases (CDKs) have been implicated in various human cancers. However, whether CDK can induce cancer cell senescence remains poorly understood. We observed that CDK16 expression was high in multiple cancer types, including lung cancer, whereas various replicative senescence models displayed low CDK16 expression. CDK16 knockdown caused senescence‐associated phenotypes in lung cancer cell lines. Interestingly, the CDK16 3′ UTR was shortened in cancer and lengthened in senescence models, which was regulated by alternative polyadenylation (APA). The longer 3′UTR [using the distal polyA (pA) site] generated less protein than the shorter one (using the proximal pA site). Since microRNAs (miRNAs) usually bind to the 3′UTR of target genes to suppress their expression, we investigated whether miRNAs targeting the region between the shortened and longer 3′UTR are responsible for the reduced expression. We found that miR‐485‐5p targeted the 3′UTR between the distal and proximal pA site and caused senescence‐associated phenotypes by reducing protein production from the longer CDK16 transcript. Of note, CDK16 knockdown led to a reduced expression of MYC proto‐oncogene, bHLH transcription factor (MYC) and CD274 molecule (PD‐L1), which in turn enhanced the tumor‐suppressive effects of senescent cancer cells. The present study discovered that CDK16, whose expression is under the regulation of APA and miR‐485‐5p, is a potential target for prosenescence therapy for lung cancer.

Cancer-associated dynamics and potential regulators of intronic polyadenylation revealed by IPAFinder using standard RNA-seq data

Intronic polyadenylation (IpA) usually leads to changes in the coding region of an mRNA, and its implication in diseases has been recognized, although at its very beginning status. Conveniently and accurately identifying IpA is of great importance for further evaluating its biological significance. Here, we developed IPAFinder, a bioinformatic method for the de novo identification of intronic poly(A) sites and their dynamic changes from standard RNA-seq data. Applying IPAFinder to 256 pan-cancer tumor/normal pairs across six tumor types, we discovered 490 recurrent dynamically changed IpA events, some of which are novel and derived from cancer-associated genes such as TSC1, SPERD2, and CCND2. Furthermore, IPAFinder revealed that IpA could be regulated by factors related to splicing and m⁶A modification. In summary, IPAFinder enables the global discovery and characterization of biologically regulated IpA with standard RNA-seq data and should reveal the biological significance of IpA in various processes.

Emerging roles of alternative cleavage and polyadenylation (APA) in human disease

In the messenger RNA (mRNA) maturation process, the 3'-end of pre-mRNA is cleaved and a poly(A) sequence is added, this is an important determinant of mRNA stability and its cellular functions. More than 60%-70% of human genes have three or more polyadenylation (APA) sites and can be cleaved at different sites, generating mRNA transcripts of varying lengths. This phenomenon is termed as alternative cleavage and polyadenylation (APA) and it plays role in key biological processes like gene regulation, cell proliferation, senescence, and also in various human diseases. Loss of regulatory microRNA binding sites and interactions with RNA-binding proteins leading to APA are largely investigated in human diseases. However, the functions of the core APA machinery and related factors during disease conditions remain largely unknown. In this review, we discuss the roles of polyadenylation machinery in relation to brain disease, cardiac failure, pulmonary fibrosis, cancer, infectious conditions, and other human diseases. Collectively, we believe this review will be a useful avenue for understanding the emerging role of APA in the pathobiology of various human diseases.

MAAPER: model-based analysis of alternative polyadenylation using 3' end-linked reads

Most eukaryotic genes express alternative polyadenylation (APA) isoforms. A growing number of RNA sequencing methods, especially those used for single-cell transcriptome analysis, generate reads close to the polyadenylation site (PAS), termed nearSite reads, hence inherently containing information about APA isoform abundance. Here, we present a probabilistic model-based method named MAAPER to utilize nearSite reads for APA analysis. MAAPER predicts PASs with high accuracy and sensitivity and examines different types of APA events with robust statistics. We show MAAPER's performance with both bulk and single-cell data and its applicability in unpaired or paired experimental designs.

CRISPRpas: programmable regulation of alternative polyadenylation by dCas9

Most human protein-coding genes produce alternative polyadenylation (APA) isoforms that differ in 3' UTR size or, when coupled with splicing, have variable coding sequences. APA is an important layer of gene expression program critical for defining cell identity. Here, by using a catalytically dead Cas9 and coupling its target site with polyadenylation site (PAS), we develop a method, named CRISPRpas, to alter APA isoform abundance. CRISPRpas functions by enhancing proximal PAS usage, whose efficiency is influenced by several factors, including targeting strand of DNA, distance between PAS and target sequence and strength of the PAS. For intronic polyadenylation (IPA), splicing features, such as strengths of 5' splice site and 3' splice site, also affect CRISPRpas efficiency. We show modulation of APA of multiple endogenous genes, including IPA of PCF11, a master regulator of APA and gene expression. In sum, CRISPRpas offers a programmable tool for APA regulation that impacts gene expression.

Alternative 3' UTRs play a widespread role in translation-independent mRNA association with the endoplasmic reticulum

Transcripts encoding membrane and secreted proteins are known to associate with the endoplasmic reticulum (ER) through translation. Here, using cell fractionation, polysome profiling, and 3' end sequencing, we show that transcripts differ substantially in translation-independent ER association (TiERA). Genes in certain functional groups, such as cell signaling, tend to have significantly higher TiERA potentials than others, suggesting the importance of ER association for their mRNA metabolism, such as localized translation. The TiERA potential of a transcript is determined largely by size, sequence content, and RNA structures. Alternative polyadenylation (APA) isoforms can have distinct TiERA potentials because of changes in transcript features. The widespread 3' UTR lengthening in cell differentiation leads to greater transcript association with the ER, especially for genes that are capable of expressing very long 3' UTRs. Our data also indicate that TiERA is in dynamic competition with translation-dependent ER association, suggesting limited space on the ER for mRNA association.

LABRAT reveals association of alternative polyadenylation with transcript localization, RNA binding protein expression, transcription speed, and cancer survival

BACKGROUND

The sequence content of the 3' UTRs of many mRNA transcripts is regulated through alternative polyadenylation (APA). The study of this process using RNAseq data, though, has been historically challenging.

RESULTS

To combat this problem, we developed LABRAT, an APA isoform quantification method. LABRAT takes advantage of newly developed transcriptome quantification techniques to accurately determine relative APA site usage and how it varies across conditions. Using LABRAT, we found consistent relationships between gene-distal APA and subcellular RNA localization in multiple cell types. We also observed connections between transcription speed and APA site choice as well as tumor-specific transcriptome-wide shifts in APA isoform abundance in hundreds of patient-derived tumor samples that were associated with patient prognosis. We investigated the effects of APA on transcript expression and found a weak overall relationship, although many individual genes showed strong correlations between relative APA isoform abundance and overall gene expression. We interrogated the roles of 191 RNA-binding proteins in the regulation of APA isoforms, finding that dozens promote broad, directional shifts in relative APA isoform abundance both in vitro and in patient-derived samples. Finally, we find that APA site shifts in the two classes of APA, tandem UTRs and alternative last exons, are strongly correlated across many contexts, suggesting that they are coregulated.

CONCLUSIONS

We conclude that LABRAT has the ability to accurately quantify APA isoform ratios from RNAseq data across a variety of sample types. Further, LABRAT is able to derive biologically meaningful insights that connect APA isoform regulation to cellular and molecular phenotypes.

A computational pipeline to infer alternative poly-adenylation from 3' sequencing data

An increasing number of investigations have established alternative polyadenylation (APA) as a key mechanism of gene regulation through altering the length of 3' untranslated region (UTR) and generating distinct mRNA termini. Further, appreciation for the significance of APA in disease contexts propelled the development of several 3' sequencing techniques. While these RNA sequencing technologies have advanced APA analysis, the intrinsic limitation of 3' read coverage and lack of appropriate computational tools constrain precise mapping and quantification of polyadenylation sites. Notably, Poly(A)-ClickSeq (PAC-seq) overcomes limiting factors such as poly(A) enrichment and 3' linker ligation steps using click-chemistry. Here we provide an updated PolyA-miner protocol, a computational approach to analyze PAC-seq or other 3'-Seq datasets. As a key practical constraint, we also provide a detailed account on the impact of sequencing depth on the number of detected polyadenylation sites and APA changes. This protocol is also updated to handle unique molecular identifiers used to address PCR duplication potentially observed in PAC-seq.

Modulation of alternative cleavage and polyadenylation events by dCas9-mediated CRISPRpas

The CRISPR/Cas9 technology is revolutionizing genomic engineering. The high efficiency and selectivity of the system have inspired the development of various derived tools for gene regulation at different levels, such as transcriptional activation or inhibition, epigenetic modification, splicing, and base editing. Cleavage and polyadenylation (CPA) is an essential 3' end maturation step for almost all eukaryotic mRNAs. CPA is tightly coupled with transcriptional termination, and its activity impacts gene expression. Over half of all human genes display alternative polyadenylation (APA), where multiple cleavage and polyadenylation sites (PASs) lead to mRNA isoforms with variable termini. APA isoforms often have distinct metabolisms, and their relative abundance can change drastically in different cells. Here, we describe a method based on delivering a catalytically dead Cas9 (dCas9) to genomic regions nears the PAS, which alters APA site usage in 3'UTRs or introns. This method, named CRISPRpas, allows investigators to examine functional significance of APA isoforms of individual genes. We also describe using the bioinformatics program APAlyzer to examine APA events of interest with RNA-seq data.

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.

Streamlining differential exon and 3' UTR usage with diffUTR

Background

Despite the importance of alternative poly-adenylation and 3′ UTR length for a variety of biological phenomena, there are limited means of detecting UTR changes from standard transcriptomic data.

Results

We present the diffUTR Bioconductor package which streamlines and improves upon differential exon usage (DEU) analyses, and leverages existing DEU tools and alternative poly-adenylation site databases to enable differential 3′ UTR usage analysis. We demonstrate the diffUTR features and show that it is more flexible and more accurate than state-of-the-art alternatives, both in simulations and in real data.

Conclusions

diffUTR enables differential 3′ UTR analysis and more generally facilitates DEU and the exploration of their results.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04114-7.

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.

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.

N6-methyladenosine dynamics in neurodevelopment and aging, and its potential role in Alzheimer's disease

BACKGROUND

N6-methyladenosine (m6A) modification is known to impact many aspects of RNA metabolism, including mRNA stability and translation, and is highly prevalent in the brain.

RESULTS

We show that m6A modification displays temporal and spatial dynamics during neurodevelopment and aging. Genes that are temporally differentially methylated are more prone to have mRNA expression changes and affect many pathways associated with nervous system development. Furthermore, m6A shows a distinct tissue-specific methylation profile, which is most pronounced in the hypothalamus. Tissue-specific methylation is associated with an increase in mRNA expression and is associated with tissue-specific developmental processes. During the aging process, we observe significantly more m6A sites as age increases, in both mouse and human. We show a high level of overlap between mouse and human; however, humans at both young and old ages consistently show more m6A sites compared to mice. Differential m6A sites are found to be enriched in alternative untranslated regions of genes that affect aging-related pathways. These m6A sites are associated with a strong negative effect on mRNA expression. We also show that many Alzheimer-related transcripts exhibit decreased m6A methylation in a mouse model of Alzheimer's disease, which is correlated with reduced protein levels.

CONCLUSIONS

Our results suggest that m6A exerts a critical function in both early and late brain development in a spatio-temporal fashion. Furthermore, m6A controls protein levels of key genes involved in Alzheimer's disease-associated pathways, suggesting that m6A plays an important role in aging and neurodegenerative disease.

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.

movAPA: modeling and visualization of dynamics of alternative polyadenylation across biological samples

MOTIVATION

Alternative polyadenylation (APA) has been widely recognized as a widespread mechanism modulated dynamically. Studies based on 3' end sequencing and/or RNA-seq have profiled poly(A) sites in various species with diverse pipelines, yet no unified and easy-to-use toolkit is available for comprehensive APA analyses.

RESULTS

We developed an R package called movAPA for modeling and visualization of dynamics of alternative polyadenylation across biological samples. movAPA incorporates rich functions for preprocessing, annotation and statistical analyses of poly(A) sites, identification of poly(A) signals, profiling of APA dynamics and visualization. Particularly, seven metrics are provided for measuring the tissue-specificity or usages of APA sites across samples. Three methods are used for identifying 3' UTR shortening/lengthening events between conditions. APA site switching involving non-3' UTR polyadenylation can also be explored. Using poly(A) site data from rice and mouse sperm cells, we demonstrated the high scalability and flexibility of movAPA in profiling APA dynamics across tissues and single cells.

AVAILABILITY AND IMPLEMENTATION

https://github.com/BMILAB/movAPA.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.