Roar: detecting alternative polyadenylation with standard mRNA sequencing libraries

Dynamic regulation of alternative polyadenylation by PQBP1 during neurogenesis

Alternative polyadenylation (APA) is a critical post-transcriptional process that generates mRNA isoforms with distinct 3' untranslated regions (3' UTRs), thereby regulating mRNA localization, stability, and translational efficiency. Cell-type-specific APA extensively shapes the diversity of the cellular transcriptome, particularly during cell fate transition. Despite its recognized significance, the precise regulatory mechanisms governing cell-type-specific APA remain unclear. In this study, we uncover PQBP1 as an emerging APA regulator that actively maintains cell-specific APA profiles in neural progenitor cells (NPCs) and delicately manages the equilibrium between NPC proliferation and differentiation. Multi-omics analysis shows that PQBP1 directly interacts with the upstream UGUA elements, impeding the recruitment of the CFIm complex and influencing polyadenylation site selection within genes associated with the cell cycle. Our findings elucidate the molecular mechanism by which PQBP1 orchestrates dynamic APA changes during neurogenesis, providing valuable insights into the precise regulation of cell-type-specific APA and the underlying pathogenic mechanisms in neurodevelopmental disorders.

Foxg1 regulates translation of neocortical neuronal genes, including the main NMDA receptor subunit gene, Grin1

BACKGROUND

Mainly known as a transcription factor patterning the rostral brain and governing its histogenesis, FOXG1 has been also detected outside the nucleus; however, biological meaning of that has been only partially clarified.

RESULTS

Prompted by FOXG1 expression in cytoplasm of pallial neurons, we investigated its implication in translational control. We documented the impact of FOXG1 on ribosomal recruitment of Grin1-mRNA, encoding for the main subunit of NMDA receptor. Next, we showed that FOXG1 increases GRIN1 protein level by enhancing the translation of its mRNA, while not increasing its stability. Molecular mechanisms underlying this activity included FOXG1 interaction with EIF4E and, possibly, Grin1-mRNA. Besides, we found that, within murine neocortical cultures, de novo synthesis of GRIN1 undergoes a prominent and reversible, homeostatic regulation and FOXG1 is instrumental to that. Finally, by integrated analysis of multiple omic data, we inferred that FOXG1 is implicated in translational control of hundreds of neuronal genes, modulating ribosome engagement and progression. In a few selected cases, we experimentally verified such inference.

CONCLUSIONS

These findings point to FOXG1 as a key effector, potentially crucial to multi-scale temporal tuning of neocortical pyramid activity, an issue with profound physiological and neuropathological implications.

Disruption of PABPN1 phase separation by SNRPD2 drives colorectal cancer cell proliferation and migration through promoting alternative polyadenylation of CTNNBIP1

Generally shortened 3' UTR due to alternative polyadenylation (APA) is widely observed in cancer, but its regulation mechanisms for cancer are not well characterized. Here, with profiling of APA in colorectal cancer tissues and poly(A) signal editing, we firstly identified that the shortened 3' UTR of CTNNIBP1 in colorectal cancer promotes cell proliferation and migration. We found that liquid-liquid phase separation (LLPS) of PABPN1 is reduced albeit with higher expression in cancer, and the reduction of LLPS leads to the shortened 3' UTR of CTNNBIP1 and promotes cell proliferation and migration. Notably, the splicing factor SNRPD2 upregulated in colorectal cancer, can interact with glutamic-proline (EP) domain of PABPN1, and then disrupt LLPS of PABPN1, which attenuates the repression effect of PABPN1 on the proximal poly(A) sites. Our results firstly reveal a new regulation mechanism of APA by disruption of LLPS of PABPN1, suggesting that regulation of APA by interfering LLPS of 3' end processing factor may have the potential as a new way for the treatment of cancer.

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.

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.

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.

REPAC: analysis of alternative polyadenylation from RNA-sequencing data

Alternative polyadenylation (APA) is an important post-transcriptional mechanism that has major implications in biological processes and diseases. Although specialized sequencing methods for polyadenylation exist, availability of these data are limited compared to RNA-sequencing data. We developed REPAC, a framework for the analysis of APA from RNA-sequencing data. Using REPAC, we investigate the landscape of APA caused by activation of B cells. We also show that REPAC is faster than alternative methods by at least 7-fold and that it scales well to hundreds of samples. Overall, the REPAC method offers an accurate, easy, and convenient solution for the exploration of APA.

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.

Landscape and regulation of alternative splicing and alternative polyadenylation in a plant pathogenic fungus

Alternative splicing (AS) and alternative polyadenylation (APA) contribute significantly to the regulation of gene expression in higher eukaryotes. Their biological impact in filamentous fungi, however, is largely unknown. Here we combine PacBio Isoform-Sequencing and strand-specific RNA-sequencing of multiple tissues and mutant characterization to reveal the landscape and regulation of AS and APA in Fusarium graminearum. We generated a transcript annotation comprising 51 617 isoforms from 17 189 genes. In total, 4997 and 11 133 genes are alternatively spliced and polyadenylated, respectively. Majority of the AS events alter coding sequences. Unexpectedly, the AS transcripts containing premature-termination codons are not sensitive to nonsense-mediated messenger RNA decay. Unlike in yeasts and animals, distal APA sites have strong signals, but proximal APA isoforms are highly expressed in F. graminearum. The 3'-end processing factors FgRNA15, FgHRP1, and FgFIP1 play roles in promoting proximal APA site usage and intron splicing. A genome-wide increase in intron inclusion and distal APA site usage and downregulation of the spliceosomal and 3'-end processing factors were observed in older and quiescent tissues, indicating intron inclusion and 3'-untranslated region lengthening as novel mechanisms in regulating aging and dormancy in fungi. This study provides new insights into the complexity and regulation of AS and APA in filamentous fungi.

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.

Pseudouridine synthases modify human pre-mRNA co-transcriptionally and affect pre-mRNA processing

Pseudouridine is a modified nucleotide that is prevalent in human mRNAs and is dynamically regulated. Here, we investigate when in their life cycle mRNAs become pseudouridylated to illuminate the potential regulatory functions of endogenous mRNA pseudouridylation. Using single-nucleotide resolution pseudouridine profiling on chromatin-associated RNA from human cells, we identified pseudouridines in nascent pre-mRNA at locations associated with alternatively spliced regions, enriched near splice sites, and overlapping hundreds of binding sites for RNA-binding proteins. In vitro splicing assays establish a direct effect of individual endogenous pre-mRNA pseudouridines on splicing efficiency. We validate hundreds of pre-mRNA sites as direct targets of distinct pseudouridine synthases and show that PUS1, PUS7, and RPUSD4-three pre-mRNA-modifying pseudouridine synthases with tissue-specific expression-control widespread changes in alternative pre-mRNA splicing and 3' end processing. Our results establish a vast potential for cotranscriptional pre-mRNA pseudouridylation to regulate human gene expression via alternative pre-mRNA processing.

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.

flexiMAP: a regression-based method for discovering differential alternative polyadenylation events in standard RNA-seq data

Motivation

We present flexible Modeling of Alternative PolyAdenylation (flexiMAP), a new beta-regression-based method implemented in R, for discovering differential alternative polyadenylation events in standard RNA-seq data.

Results

We show, using both simulated and real data, that flexiMAP exhibits a good balance between specificity and sensitivity and compares favourably to existing methods, especially at low fold changes. In addition, the tests on simulated data reveal some hitherto unrecognized caveats of existing methods. Importantly, flexiMAP allows modeling of multiple known covariates that often confound the results of RNA-seq data analysis.

Availability and implementation

The flexiMAP R package is available at: https://github.com/kszkop/flexiMAP. Scripts and data to reproduce the analysis in this paper are available at: https://doi.org/10.5281/zenodo.3689788.

Supplementary information

Supplementary data are available at Bioinformatics online.

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.

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.

Application and design considerations for 3'-end sequencing using click-chemistry

Over the past 15 years, investigations into alternative polyadenylation (APA) and its function in cellular physiology and pathology have greatly expanded due to the emergent appreciation of its key role in driving transcriptomic diversity. This growth has necessitated the development of new technologies capable of monitoring cleavage and polyadenylation events genome-wide. Advancements in approaches include both the creation of computational tools to re-analyze RNA-seq to identify APA events as well as targeted sequencing approaches customized to focus on the 3'-end of mRNA. Here we describe a streamlined protocol for polyA-Click-seq (PAC-seq), which utilizes click-chemistry to create mRNA 3'-ends sequencing libraries. Importantly, we offer additional considerations not present in our previous protocols including the use of spike-ins, unique molecular identifier primers, and guidance for appropriate depth of PAC-seq. In conjunction with the companion chapter on PolyA-miner (Yalamanchili et al., 2021) to computationally analyze PAC-seq data, we provide a complete experimental pipeline to analyze mRNA 3'-end usage in eukaryotic cells.

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.

Quantifying alternative polyadenylation in RNAseq data with LABRAT

Alternative polyadenylation (APA) generates transcript isoforms that differ in their 3' UTR content and may therefore be subject to different regulatory fates. Although the existence of APA has been known for decades, quantification of APA isoforms from high-throughput RNA sequencing data has been difficult. To facilitate the study of APA in large datasets, we developed an APA quantification technique called LABRAT (Lightweight Alignment-Based Reckoning of Alternative Three-prime ends). LABRAT leverages modern transcriptome quantification approaches to determine the relative abundances of APA isoforms. In this manuscript we describe how LABRAT produces its calculations, provide a step-by-step protocol for its use, and demonstrate its ability to quantify APA in single-cell RNAseq data.

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.

Animal-APAdb: a comprehensive animal alternative polyadenylation database

Alternative polyadenylation (APA) is an important post-transcriptional regulatory mechanism that recognizes different polyadenylation signals on transcripts, resulting in transcripts with different lengths of 3′ untranslated regions and thereby influencing a series of biological processes. Recent studies have highlighted the important roles of APA in human. However, APA profiles in other animals have not been fully recognized, and there is no database that provides comprehensive APA information for other animals except human. Here, by using the RNA sequencing data collected from public databases, we systematically characterized the APA profiles in 9244 samples of 18 species. In total, we identified 342 952 APA events with a median of 17 020 per species using the DaPars2 algorithm, and 315 691 APA events with a median of 17 953 per species using the QAPA algorithm in these 18 species, respectively. In addition, we predicted the polyadenylation sites (PAS) and motifs near PAS of these species. We further developed Animal-APAdb, a user-friendly database (http://gong_lab.hzau.edu.cn/Animal-APAdb/) for data searching, browsing and downloading. With comprehensive information of APA events in different tissues of different species, Animal-APAdb may greatly facilitate the exploration of animal APA patterns and novel mechanisms, gene expression regulation and APA evolution across tissues and species.

Alternative polyadenylation drives oncogenic gene expression in pancreatic ductal adenocarcinoma

Alternative polyadenylation (APA) is a gene regulatory process that dictates mRNA 3'-UTR length, resulting in changes in mRNA stability and localization. APA is frequently disrupted in cancer and promotes tumorigenesis through altered expression of oncogenes and tumor suppressors. Pan-cancer analyses have revealed common APA events across the tumor landscape; however, little is known about tumor type-specific alterations that may uncover novel events and vulnerabilities. Here, we integrate RNA-sequencing data from the Genotype-Tissue Expression (GTEx) project and The Cancer Genome Atlas (TCGA) to comprehensively analyze APA events in 148 pancreatic ductal adenocarcinomas (PDACs). We report widespread, recurrent, and functionally relevant 3'-UTR alterations associated with gene expression changes of known and newly identified PDAC growth-promoting genes and experimentally validate the effects of these APA events on protein expression. We find enrichment for APA events in genes associated with known PDAC pathways, loss of tumor-suppressive miRNA binding sites, and increased heterogeneity in 3'-UTR forms of metabolic genes. Survival analyses reveal a subset of 3'-UTR alterations that independently characterize a poor prognostic cohort among PDAC patients. Finally, we identify and validate the casein kinase CSNK1A1 (also known as CK1alpha or CK1a) as an APA-regulated therapeutic target in PDAC. Knockdown or pharmacological inhibition of CSNK1A1 attenuates PDAC cell proliferation and clonogenic growth. Our single-cancer analysis reveals APA as an underappreciated driver of protumorigenic gene expression in PDAC via the loss of miRNA regulation.

Oocyte competence is maintained by m6A methyltransferase KIAA1429-mediated RNA metabolism during mouse follicular development

KIAA1429 (also known as vir-like m⁶A methyltransferase-associated protein (VIRMA)), a newly identified component of the RNA m⁶A methyltransferase complex, plays critical roles in guiding region-selective m⁶A deposition. However, in mammals, whether KIAA1429 mediates RNA m⁶A regulatory pathway functions in vivo remains unknown. Here, we show that the Kiaa1429-specific deficiency in oocytes resulted in female infertility with defective follicular development and fully grown germinal vesicle (GV) oocytes failing to undergo germinal vesicle breakdown (GVBD) and consequently losing the ability to resume meiosis. The oocyte growth is accompanied by the accumulation of abundant RNAs and posttranscriptional regulation. We found that the loss of Kiaa1429 could also lead to abnormal RNA metabolism in GV oocytes. RNA-seq profiling revealed that Kiaa1429 deletion altered the expression pattern of the oocyte-derived factors essential for follicular development. In addition, our data show that the conditional depletion of Kiaa1429 decreased the m⁶A levels in oocytes and mainly affected the alternative splicing of genes associated with oogenesis. In summary, the m⁶A methyltransferase KIAA1429-mediated RNA metabolism plays critical roles in folliculogenesis and the maintenance of oocyte competence.

What Are 3' UTRs Doing?

3' untranslated regions (3' UTRs) of messenger RNAs (mRNAs) are best known to regulate mRNA-based processes, such as mRNA localization, mRNA stability, and translation. In addition, 3' UTRs can establish 3' UTR-mediated protein-protein interactions (PPIs), and thus can transmit genetic information encoded in 3' UTRs to proteins. This function has been shown to regulate diverse protein features, including protein complex formation or posttranslational modifications, but is also expected to alter protein conformations. Therefore, 3' UTR-mediated information transfer can regulate protein features that are not encoded in the amino acid sequence. This review summarizes both 3' UTR functions-the regulation of mRNA and protein-based processes-and highlights how each 3' UTR function was discovered with a focus on experimental approaches used and the concepts that were learned. This review also discusses novel approaches to study 3' UTR functions in the future by taking advantage of recent advances in technology.

TAPAS: tool for alternative polyadenylation site analysis

Motivation

The length of the 3' untranslated region (3' UTR) of an mRNA is essential for many biological activities such as mRNA stability, sub-cellular localization, protein translation, protein binding and translation efficiency. Moreover, correlation between diseases and the shortening (or lengthening) of 3' UTRs has been reported in the literature. This length is largely determined by the polyadenylation cleavage site in the mRNA. As alternative polyadenylation (APA) sites are common in mammalian genes, several tools have been published recently for detecting APA sites from RNA-Seq data or performing shortening/lengthening analysis. These tools consider either up to only two APA sites in a gene or only APA sites that occur in the last exon of a gene, although a gene may generally have more than two APA sites and an APA site may sometimes occur before the last exon. Furthermore, the tools are unable to integrate the analysis of shortening/lengthening events with APA site detection.

Results

We propose a new tool, called TAPAS, for detecting novel APA sites from RNA-Seq data. It can deal with more than two APA sites in a gene as well as APA sites that occur before the last exon. The tool is based on an existing method for finding change points in time series data, but some filtration techniques are also adopted to remove change points that are likely false APA sites. It is then extended to identify APA sites that are expressed differently between two biological samples and genes that contain 3' UTRs with shortening/lengthening events. Our extensive experiments on simulated and real RNA-Seq data demonstrate that TAPAS outperforms the existing tools for APA site detection or shortening/lengthening analysis significantly.

Availability and implementation

https://github.com/arefeen/TAPAS.

Supplementary information

Supplementary data are available at Bioinformatics online.

The Length of the Expressed 3' UTR Is an Intermediate Molecular Phenotype Linking Genetic Variants to Complex Diseases

In the last decades, genome-wide association studies (GWAS) have uncovered tens of thousands of associations between common genetic variants and complex diseases. However, these statistical associations can rarely be interpreted functionally and mechanistically. As the majority of the disease-associated variants are located far from coding sequences, even the relevant gene is often unclear. A way to gain insight into the relevant mechanisms is to study the genetic determinants of intermediate molecular phenotypes, such as gene expression and transcript structure. We propose a computational strategy to discover genetic variants affecting the relative expression of alternative 3′ untranslated region (UTR) isoforms, generated through alternative polyadenylation, a widespread posttranscriptional regulatory mechanism known to have relevant functional consequences. When applied to a large dataset in which whole genome and RNA sequencing data are available for 373 European individuals, 2,530 genes with alternative polyadenylation quantitative trait loci (apaQTL) were identified. We analyze and discuss possible mechanisms of action of these variants, and we show that they are significantly enriched in GWAS hits, in particular those concerning immune-related and neurological disorders. Our results point to an important role for genetically determined alternative polyadenylation in affecting predisposition to complex diseases, and suggest new ways to extract functional information from GWAS data.

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 cleavage and polyadenylation in health and disease

Most human genes have multiple sites at which RNA 3' end cleavage and polyadenylation can occur, enabling the expression of distinct transcript isoforms under different conditions. Novel methods to sequence RNA 3' ends have generated comprehensive catalogues of polyadenylation (poly(A)) sites; their analysis using innovative computational methods has revealed how poly(A) site choice is regulated by core RNA 3' end processing factors, such as cleavage factor I and cleavage and polyadenylation specificity factor, as well as by other RNA-binding proteins, particularly splicing factors. Here, we review the experimental and computational methods that have enabled the global mapping of mRNA and of long non-coding RNA 3' ends, quantification of the resulting isoforms and the discovery of regulators of alternative cleavage and polyadenylation (APA). We highlight the different types of APA-derived isoforms and their functional differences, and illustrate how APA contributes to human diseases, including cancer and haematological, immunological and neurological diseases.

Alternative polyadenylation of single cells delineates cell types and serves as a prognostic marker in early stage breast cancer

Alternative polyadenylation (APA) in 3’ untranslated regions (3’ UTR) plays an important role in regulating transcript abundance, localization, and interaction with microRNAs. Length-variation of 3’UTRs by APA contributes to efficient proliferation of cancer cells. In this study, we investigated APA in single cancer cells and tumor microenvironment cells to understand the physiological implication of APA in different cell types. We analyzed APA patterns and the expression level of genes from the 515 single-cell RNA sequencing (scRNA-seq) dataset from 11 breast cancer patients. Although the overall 3’UTR length of individual genes was distributed equally in tumor and non-tumor cells, we found a differential pattern of polyadenylation in gene sets between tumor and non-tumor cells. In addition, we found a differential pattern of APA across tumor types using scRNA-seq data from 3 glioblastoma patients and 1 renal cell carcinoma patients. In detail, 1,176 gene sets and 53 genes showed the distinct pattern of 3’UTR shortening and over-expression as signatures for five cell types including B lymphocytes, T lymphocytes, myeloid cells, stromal cells, and breast cancer cells. Functional categories of gene sets for cellular proliferation demonstrated concordant regulation of APA and gene expression specific to cell types. The expression of APA genes in breast cancer was significantly correlated with the clinical outcome of earlier stage breast cancer patients. We identified cell type-specific APA in single cells, which allows the identification of cell types based on 3’UTR length variation in combination with gene expression. Specifically, an immune-specific APA signature in breast cancer could be utilized as a prognostic marker of early stage breast cancer.

Alternative cleavage and polyadenylation of genes associated with protein turnover and mitochondrial function are deregulated in Parkinson's, Alzheimer's and ALS disease

BACKGROUND

Transcriptome wide changes have been assessed extensively during the progression of neurodegenerative diseases. Alternative polyadenylation (APA) occurs in over 70% of human protein coding genes and it has recently been recognised as a critical regulator of gene expression during disease. However, the effect of APA in the context of neurodegenerative diseases, to date, has not been widely investigated. Dynamic Analysis of Alternative Polyadenylation from RNA-seq (DaPars) is a method by Xia and colleagues [Nat Commun. 5:5274, 2014] to investigate APA using standard RNA-seq data. Here, we employed this method to interrogate APA using publicly available RNA-seq data from Alzheimer's disease (AD), Parkinson's disease (PD) and Amyotrophic Lateral Sclerosis (ALS) patients and matched healthy individuals.

RESULTS

For all three diseases, we found that APA profile changes were limited to a relative small number of genes suggesting that APA is not globally deregulated in neurodegenerative disease. However, for each disease phenotype we identified a subgroup of genes that showed disease-specific deregulation of APA. Whilst the affected genes differ between the RNA-seq datasets, in each cohort we identified an overrepresentation of genes that are associated with protein turnover pathways and mitochondrial function.

CONCLUSIONS

Our findings, while drawn from a relatively small sample size, suggest that deregulation of APA may play a significant role in neurodegeneration by altering the expression of genes including UBR1 and OGDHL in AD, LONP1 in PD and UCHL1 in ALS. This report thus provides important novel insights into how APA can shape neurodegenerative disease characteristic transcriptomes.

The Untranslated Regions of mRNAs in Cancer

The 5' and 3' untranslated regions (UTRs) regulate crucial aspects of post-transcriptional gene regulation that are necessary for the maintenance of cellular homeostasis. When these processes go awry through mutation or misexpression of certain regulatory elements, the subsequent deregulation of oncogenic gene expression can drive or enhance cancer pathogenesis. Although the number of known cancer-related mutations in UTR regulatory elements has recently increased markedly as a result of advances in whole-genome sequencing, little is known about how the majority of these genetic aberrations contribute functionally to disease. In this review we explore the regulatory functions of UTRs, how they are co-opted in cancer, new technologies to interrogate cancerous UTRs, and potential therapeutic opportunities stemming from these regions.

Detection of Differentially Expressed Cleavage Site Intervals Within 3' Untranslated Regions Using CSI-UTR Reveals Regulated Interaction Motifs

The length of untranslated regions at the 3' end of transcripts (3'UTRs) is regulated by alternate polyadenylation (APA). 3'UTRs contain regions that harbor binding motifs for regulatory molecules. However, the mechanisms that coordinate the 3'UTR length of specific groups of transcripts are not well-understood. We therefore developed a method, CSI-UTR, that models 3'UTR structure as tandem segments between functional alternative-polyadenylation sites (termed cleavage site intervals-CSIs). This approach facilitated (1) profiling of 3'UTR isoform expression changes and (2) statistical enrichment of putative regulatory motifs. CSI-UTR analysis is UTR-annotation independent and can interrogate legacy data generated from standard RNA-Seq libraries. CSI-UTR identified a set of CSIs in human and rodent transcriptomes. Analysis of RNA-Seq datasets from neural tissue identified differential expression events within 3'UTRs not detected by standard gene-based differential expression analyses. Further, in many instances 3'UTR and CDS from the same gene were regulated differently. This modulation of motifs for RNA-interacting molecules with potential condition-dependent and tissue-specific RNA binding partners near the polyA signal and CSI junction may play a mechanistic role in the specificity of alternative polyadenylation. Source code, CSI BED files and example datasets are available at: https://github.com/UofLBioinformatics/CSI-UTR.

Choice of Alternative Polyadenylation Sites, Mediated by the RNA-Binding Protein Elavl3, Plays a Role in Differentiation of Inhibitory Neuronal Progenitors

Alternative polyadenylation (APA) is a widespread mechanism involving about half of the expressed genes, resulting in varying lengths of the 3′ untranslated region (3′UTR). Variations in length and sequence of the 3′UTR may underlie changes of post-transcriptional processing, localization, miRNA targeting and stability of mRNAs. During embryonic development a large array of mRNAs exhibit APA, with a prevalence of the longer 3′UTR versions in differentiating cells. Little is known about polyA+ site usage during differentiation of mammalian neural progenitors. Here we exploit a model of adherent neural stem (ANS) cells, which homogeneously and efficiently differentiate into GABAergic neurons. RNAseq data shows a global trend towards lengthening of the 3′UTRs during differentiation. Enriched expression of the longer 3′UTR variants of Pes1 and Gng2 was detected in the mouse brain in areas of cortical and subcortical neuronal differentiation, respectively, by two-probes fluorescent in situ hybridization (FISH). Among the coding genes upregulated during differentiation of ANS cells we found Elavl3, a neural-specific RNA-binding protein homologous to Drosophila Elav. In the insect, Elav regulates polyA+ site choice while interacting with paused Pol-II promoters. We tested the role of Elavl3 in ANS cells, by silencing Elavl3 and observed consistent changes in 3′UTR length and delayed neuronal differentiation. These results indicate that choice of the polyA+ site and lengthening of 3′UTRs is a possible additional mechanism of posttranscriptional RNA modification involved in neuronal differentiation.

UTRme: A Scoring-Based Tool to Annotate Untranslated Regions in Trypanosomatid Genomes

Most signals involved in post-transcriptional regulatory networks are located in the untranslated regions (UTRs) of the mRNAs. Therefore, to deepen our understanding of gene expression regulation, delimitation of these regions with high accuracy is needed. The trypanosomatid lineage includes a variety of parasitic protozoans causing a significant worldwide burden on human health. Given their peculiar mechanisms of gene expression, these organisms depend on post-transcriptional regulation as the main level of gene expression control. In this context, the definition of the UTR regions becomes of key importance. We have developed UTR-mini-exon (UTRme), a graphical user interface (GUI) stand-alone application to identify and annotate 5′ and 3′ UTR regions in a highly accurate way. UTRme implements a multiple scoring system tailored to address the issue of false positive UTR assignment that frequently arise because of the characteristics of the intergenic regions. Even though it was developed for trypanosomatids, the tool can be used to predict 3′ sites in any eukaryote and 5′ UTRs in any organism where trans-splicing occurs (such as the model organism C. elegans). UTRme offers a way for non-bioinformaticians to precisely determine UTRs from transcriptomic data. The tool is freely available via the conda and github repositories.

Analysis of alternative cleavage and polyadenylation in mature and differentiating neurons using RNA-seq data

Background

Most eukaryotic protein-coding genes exhibit alternative cleavage and polyadenylation (APA), resulting in mRNA isoforms with different 3' untranslated regions (3' UTRs). Studies have shown that brain cells tend to express long 3' UTR isoforms using distal cleavage and polyadenylation sites (PASs).

Methods

Using our recently developed, comprehensive PAS database PolyA_DB, we developed an efficient method to examine APA, named Significance Analysis of Alternative Polyadenylation using RNA-seq (SAAP-RS). We applied this method to study APA in brain cells and neurogenesis.

Results

We found that neurons globally express longer 3' UTRs than other cell types in brain, and microglia and endothelial cells express substantially shorter 3' UTRs. We show that the 3' UTR diversity across brain cells can be corroborated with single cell sequencing data. Further analysis of APA regulation of 3' UTRs during differentiation of embryonic stem cells into neurons indicates that a large fraction of the APA events regulated in neurogenesis are similarly modulated in myogenesis, but to a much greater extent.

Conclusion

Together, our data delineate APA profiles in different brain cells and indicate that APA regulation in neurogenesis is largely an augmented process taking place in other types of cell differentiation.

An integrative model for alternative polyadenylation, IntMAP, delineates mTOR-modulated endoplasmic reticulum stress response

3'-untranslated regions (UTRs) can vary through the use of alternative polyadenylation sites during pre-mRNA processing. Multiple publically available pipelines combining high profiling technologies and bioinformatics tools have been developed to catalog changes in 3'-UTR lengths. In our recent RNA-seq experiments using cells with hyper-activated mammalian target of rapamycin (mTOR), we found that cellular mTOR activation leads to transcriptome-wide alternative polyadenylation (APA), resulting in the activation of multiple cellular pathways. Here, we developed a novel bioinformatics algorithm, IntMAP, which integrates RNA-Seq and PolyA Site (PAS)-Seq data for a comprehensive characterization of APA events. By applying IntMAP to the datasets from cells with hyper-activated mTOR, we identified novel APA events that could otherwise not be identified by either profiling method alone. Several transcription factors including Cebpg (CCAAT/enhancer binding protein gamma) were among the newly discovered APA transcripts, indicating that diverse transcriptional networks may be regulated by mTOR-coordinated APA. The prevention of APA in Cebpg using the CRISPR/cas9-mediated genome editing tool showed that mTOR-driven 3'-UTR shortening in Cebpg is critical in protecting cells from endoplasmic reticulum (ER) stress. Taken together, we present IntMAP as a new bioinformatics algorithm for APA analysis by which we expand our understanding of the physiological role of mTOR-coordinated APA events to ER stress response. IntMAP toolbox is available at http://compbio.cs.umn.edu/IntMAP/.

Nuclear m6A reader YTHDC1 regulates alternative polyadenylation and splicing during mouse oocyte development

The N6-methyladenosine (m6A) modification is the most prevalent internal RNA modification in eukaryotes. The majority of m6A sites are found in the last exon and 3' UTRs. Here we show that the nuclear m6A reader YTHDC1 is essential for embryo viability and germline development in mouse. Specifically, YTHDC1 is required for spermatogonial development in males and for oocyte growth and maturation in females; Ythdc1-deficient oocytes are blocked at the primary follicle stage. Strikingly, loss of YTHDC1 leads to extensive alternative polyadenylation in oocytes, altering 3' UTR length. Furthermore, YTHDC1 deficiency causes massive alternative splicing defects in oocytes. The majority of splicing defects in mutant oocytes are rescued by introducing wild-type, but not m6A-binding-deficient, YTHDC1. YTHDC1 is associated with the pre-mRNA 3' end processing factors CPSF6, SRSF3, and SRSF7. Thus, YTHDC1 plays a critical role in processing of pre-mRNA transcripts in the oocyte nucleus and may have similar non-redundant roles throughout fetal development.

QAPA: a new method for the systematic analysis of alternative polyadenylation from RNA-seq data

Alternative polyadenylation (APA) affects most mammalian genes. The genome-wide investigation of APA has been hampered by an inability to reliably profile it using conventional RNA-seq. We describe 'Quantification of APA' (QAPA), a method that infers APA from conventional RNA-seq data. QAPA is faster and more sensitive than other methods. Application of QAPA reveals discrete, temporally coordinated APA programs during neurogenesis and that there is little overlap between genes regulated by alternative splicing and those by APA. Modeling of these data uncovers an APA sequence code. QAPA thus enables the discovery and characterization of programs of regulated APA using conventional RNA-seq.

Analyses of alternative polyadenylation: from old school biochemistry to high-throughput technologies

Alternations in usage of polyadenylation sites during transcription termination yield transcript isoforms from a gene. Recent findings of transcriptome-wide alternative polyadenylation (APA) as a molecular response to changes in biology position APA not only as a molecular event of early transcriptional termination but also as a cellular regulatory step affecting various biological pathways. With the development of high-throughput profiling technologies at a single nucleotide level and their applications targeted to the 3'-end of mRNAs, dynamics in the landscape of mRNA 3'-end is measureable at a global scale. In this review, methods and technologies that have been adopted to study APA events are discussed. In addition, various bioinformatics algorithms for APA isoform analysis using publicly available RNA-seq datasets are introduced. [BMB Reports 2017; 50(4): 201-207].

Untranslated Parts of Genes Interpreted: Making Heads or Tails of High-Throughput Transcriptomic Data via Computational Methods: Computational methods to discover and quantify isoforms with alternative untranslated regions

In this review we highlight the importance of defining the untranslated parts of transcripts, and present a number of computational approaches for the discovery and quantification of alternative transcription start and poly-adenylation events in high-throughput transcriptomic data. The fate of eukaryotic transcripts is closely linked to their untranslated regions, which are determined by the position at which transcription starts and ends at a genomic locus. Although the extent of alternative transcription starts and alternative poly-adenylation sites has been revealed by sequencing methods focused on the ends of transcripts, the application of these methods is not yet widely adopted by the community. We suggest that computational methods applied to standard high-throughput technologies are a useful, albeit less accurate, alternative to the expertise-demanding 5' and 3' sequencing and they are the only option for analysing legacy transcriptomic data. We review these methods here, focusing on technical challenges and arguing for the need to include better normalization of the data and more appropriate statistical models of the expected variation in the signal.