Terminal exon characterization with TECtool reveals an abundance of cell-specific isoforms

InPACT: a computational method for accurate characterization of intronic polyadenylation from RNA sequencing data

Alternative polyadenylation can occur in introns, termed intronic polyadenylation (IPA), has been implicated in diverse biological processes and diseases, as it can produce noncoding transcripts or transcripts with truncated coding regions. However, a reliable method is required to accurately characterize IPA. Here, we propose a computational method called InPACT, which allows for the precise characterization of IPA from conventional RNA-seq data. InPACT successfully identifies numerous previously unannotated IPA transcripts in human cells, many of which are translated, as evidenced by ribosome profiling data. We have demonstrated that InPACT outperforms other methods in terms of IPA identification and quantification. Moreover, InPACT applied to monocyte activation reveals temporally coordinated IPA events. Further application on single-cell RNA-seq data of human fetal bone marrow reveals the expression of several IPA isoforms in a context-specific manner. Therefore, InPACT represents a powerful tool for the accurate characterization of IPA from RNA-seq data.

Poly(A) tale: From A to A; RNA polyadenylation in prokaryotes and eukaryotes

Most eukaryotic mRNAs and different non-coding RNAs undergo a form of 3' end processing known as polyadenylation. Polyadenylation machinery is present in almost all organisms except few species. In bacteria, the machinery has evolved from PNPase, which adds heteropolymeric tails, to a poly(A)-specific polymerase. Differently, a complex machinery for accurate polyadenylation and several non-canonical poly(A) polymerases are developed in eukaryotes. The role of poly(A) tail has also evolved from serving as a degradative signal to a stabilizing modification that also regulates translation. In this review, we discuss poly(A) tail emergence in prokaryotes and its development into a stable, yet dynamic feature at the 3' end of mRNAs in eukaryotes. We also describe how appearance of novel poly(A) polymerases gives cells flexibility to shape poly(A) tail. We explain how poly(A) tail dynamics help regulate cognate RNA metabolism in a context-dependent manner, such as during oocyte maturation. Finally, we describe specific mRNAs in metazoans that bear stem-loops instead of poly(A) tails. We conclude with how recent discoveries about poly(A) tail can be applied to mRNA technology. This article is categorized under: RNA Evolution and Genomics > RNA and Ribonucleoprotein Evolution RNA Processing > 3' End Processing RNA Turnover and Surveillance > Regulation of RNA Stability.

TDP-43 loss induces extensive cryptic polyadenylation in ALS/FTD

Nuclear depletion and cytoplasmic aggregation of the RNA-binding protein TDP-43 is the hallmark of ALS, occurring in over 97% of cases. A key consequence of TDP-43 nuclear loss is the de-repression of cryptic exons. Whilst TDP-43 regulated cryptic splicing is increasingly well catalogued, cryptic alternative polyadenylation (APA) events, which define the 3' end of last exons, have been largely overlooked, especially when not associated with novel upstream splice junctions. We developed a novel bioinformatic approach to reliably identify distinct APA event types: alternative last exons (ALE), 3'UTR extensions (3'Ext) and intronic polyadenylation (IPA) events. We identified novel neuronal cryptic APA sites induced by TDP-43 loss of function by systematically applying our pipeline to a compendium of publicly available and in house datasets. We find that TDP-43 binding sites and target motifs are enriched at these cryptic events and that TDP-43 can have both repressive and enhancing action on APA. Importantly, all categories of cryptic APA can also be identified in ALS and FTD post mortem brain regions with TDP-43 proteinopathy underlining their potential disease relevance. RNA-seq and Ribo-seq analyses indicate that distinct cryptic APA categories have different downstream effects on transcript and translation. Intriguingly, cryptic 3'Exts occur in multiple transcription factors, such as ELK1, SIX3, and TLX1, and lead to an increase in wild-type protein levels and function. Finally, we show that an increase in RNA stability leading to a higher cytoplasmic localisation underlies these observations. In summary, we demonstrate that TDP-43 nuclear depletion induces a novel category of cryptic RNA processing events and we expand the palette of TDP-43 loss consequences by showing this can also lead to an increase in normal protein translation.

scTEA-db: a comprehensive database of novel terminal exon isoforms identified from human single cell transcriptomes

The usage of alternative terminal exons results in messenger RNA (mRNA) isoforms that differ in their 3' untranslated regions (3' UTRs) and often also in their protein-coding sequences. Alternative 3' UTRs contain different sets of cis-regulatory elements known to regulate mRNA stability, translation and localization, all of which are vital to cell identity and function. In previous work, we revealed that ∼25 percent of the experimentally observed RNA 3' ends are located within regions currently annotated as intronic, indicating that many 3' end isoforms remain to be uncovered. Also, the inclusion of not yet annotated terminal exons is more tissue specific compared to the already annotated ones. Here, we present the single cell-based Terminal Exon Annotation database (scTEA-db, www.scTEA-db.org) that provides the community with 12 063 so far not yet annotated terminal exons and associated transcript isoforms identified by analysing 53 069 publicly available single cell transcriptomes. Our scTEA-db web portal offers an array of features to find and explore novel terminal exons belonging to 5538 human genes, 110 of which are known cancer drivers. In summary, scTEA-db provides the foundation for studying the biological role of large numbers of so far not annotated terminal exon isoforms in cell identity and function.

The peptide woods are lovely, dark and deep: Hunting for novel cancer antigens

Harnessing the patient's immune system to control a tumor is a proven avenue for cancer therapy. T cell therapies as well as therapeutic vaccines, which target specific antigens of interest, are being explored as treatments in conjunction with immune checkpoint blockade. For these therapies, selecting the best suited antigens is crucial. Most of the focus has thus far been on neoantigens that arise from tumor-specific somatic mutations. Although there is clear evidence that T-cell responses against mutated neoantigens are protective, the large majority of these mutations are not immunogenic. In addition, most somatic mutations are unique to each individual patient and their targeting requires the development of individualized approaches. Therefore, novel antigen types are needed to broaden the scope of such treatments. We review high throughput approaches for discovering novel tumor antigens and some of the key challenges associated with their detection, and discuss considerations when selecting tumor antigens to target in the clinic.

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.

Context-specific regulation and function of mRNA alternative polyadenylation

Alternative cleavage and polyadenylation (APA) is a widespread mechanism to generate mRNA isoforms with alternative 3' untranslated regions (UTRs). The expression of alternative 3' UTR isoforms is highly cell type specific and is further controlled in a gene-specific manner by environmental cues. In this Review, we discuss how the dynamic, fine-grained regulation of APA is accomplished by several mechanisms, including cis-regulatory elements in RNA and DNA and factors that control transcription, pre-mRNA cleavage and post-transcriptional processes. Furthermore, signalling pathways modulate the activity of these factors and integrate APA into gene regulatory programmes. Dysregulation of APA can reprogramme the outcome of signalling pathways and thus can control cellular responses to environmental changes. In addition to the regulation of protein abundance, APA has emerged as a major regulator of mRNA localization and the spatial organization of protein synthesis. This role enables the regulation of protein function through the addition of post-translational modifications or the formation of protein-protein interactions. We further discuss recent transformative advances in single-cell RNA sequencing and CRISPR-Cas technologies, which enable the mapping and functional characterization of alternative 3' UTRs in any biological context. Finally, we discuss new APA-based RNA therapeutics, including compounds that target APA in cancer and therapeutic genome editing of degenerative diseases.

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.

Leveraging omic features with F3UTER enables identification of unannotated 3'UTRs for synaptic genes

There is growing evidence for the importance of 3' untranslated region (3'UTR) dependent regulatory processes. However, our current human 3'UTR catalogue is incomplete. Here, we develop a machine learning-based framework, leveraging both genomic and tissue-specific transcriptomic features to predict previously unannotated 3'UTRs. We identify unannotated 3'UTRs associated with 1,563 genes across 39 human tissues, with the greatest abundance found in the brain. These unannotated 3'UTRs are significantly enriched for RNA binding protein (RBP) motifs and exhibit high human lineage-specificity. We find that brain-specific unannotated 3'UTRs are enriched for the binding motifs of important neuronal RBPs such as TARDBP and RBFOX1, and their associated genes are involved in synaptic function. Our data is shared through an online resource F3UTER ( https://astx.shinyapps.io/F3UTER/ ). Overall, our data improves 3'UTR annotation and provides additional insights into the mRNA-RBP interactome in the human brain, with implications for our understanding of neurological and neurodevelopmental diseases.

Shortening of 3' UTRs in most cell types composing tumor tissues implicates alternative polyadenylation in protein metabolism

During pre-mRNA maturation 3' end processing can occur at different polyadenylation sites in the 3' untranslated region (3' UTR) to give rise to transcript isoforms that differ in the length of their 3' UTRs. Longer 3' UTRs contain additional cis-regulatory elements that impact the fate of the transcript and/or of the resulting protein. Extensive alternative polyadenylation (APA) has been observed in cancers, but the mechanisms and roles remain elusive. In particular, it is unclear whether the APA occurs in the malignant cells or in other cell types that infiltrate the tumor. To resolve this, we developed a computational method, called SCUREL, that quantifies changes in 3' UTR length between groups of cells, including cells of the same type originating from tumor and control tissue. We used this method to study APA in human lung adenocarcinoma (LUAD). SCUREL relies solely on annotated 3' UTRs and on control systems such as T cell activation, and spermatogenesis gives qualitatively similar results at much greater sensitivity compared to the previously published scAPA method. In the LUAD samples, we find a general trend toward 3' UTR shortening not only in cancer cells compared to the cell type of origin, but also when comparing other cell types from the tumor vs. the control tissue environment. However, we also find high variability in the individual targets between patients. The findings help in understanding the extent and impact of APA in LUAD, which may support improvements in diagnosis and treatment.

Improved SNV Discovery in Barcode-Stratified scRNA-seq Alignments

Currently, the detection of single nucleotide variants (SNVs) from 10 x Genomics single-cell RNA sequencing data (scRNA-seq) is typically performed on the pooled sequencing reads across all cells in a sample. Here, we assess the gaining of information regarding SNV assessments from individual cell scRNA-seq data, wherein the alignments are split by cellular barcode prior to the variant call. We also reanalyze publicly available data on the MCF7 cell line during anticancer treatment. We assessed SNV calls by three variant callers—GATK, Strelka2, and Mutect2, in combination with a method for the cell-level tabulation of the sequencing read counts bearing variant alleles–SCReadCounts (single-cell read counts). Our analysis shows that variant calls on individual cell alignments identify at least a two-fold higher number of SNVs as compared to the pooled scRNA-seq; these SNVs are enriched in novel variants and in stop-codon and missense substitutions. Our study indicates an immense potential of SNV calls from individual cell scRNA-seq data and emphasizes the need for cell-level variant detection approaches and tools, which can contribute to the understanding of the cellular heterogeneity and the relationships to phenotypes, and help elucidate somatic mutation evolution and functionality.

QuantifyPoly(A): reshaping alternative polyadenylation landscapes of eukaryotes with weighted density peak clustering

The dynamic choice of different polyadenylation sites in a gene is referred to as alternative polyadenylation, which functions in many important biological processes. Large-scale messenger RNA 3' end sequencing has revealed that cleavage sites for polyadenylation are presented with microheterogeneity. To date, the conventional determination of polyadenylation site clusters is subjective and arbitrary, leading to inaccurate annotations. Here, we present a weighted density peak clustering method, QuantifyPoly(A), to accurately quantify genome-wide polyadenylation choices. Applying QuantifyPoly(A) on published 3' end sequencing datasets from both animals and plants, their polyadenylation profiles are reshaped into myriads of novel polyadenylation site clusters. Most of these novel polyadenylation site clusters show significantly dynamic usage across different biological samples or associate with binding sites of trans-acting factors. Upstream sequences of these clusters are enriched with polyadenylation signals UGUA, UAAA and/or AAUAAA in a species-dependent manner. Polyadenylation site clusters also exhibit species specificity, while plants ones generally show higher microheterogeneity than that of animals. QuantifyPoly(A) is broadly applicable to any types of 3' end sequencing data and species for accurate quantification and construction of the complex and dynamic polyadenylation landscape and enables us to decode alternative polyadenylation events invisible to conventional methods at a much higher resolution.

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.

Role of Arginine Methylation in Alternative Polyadenylation of VEGFR-1 (Flt-1) pre-mRNA

Mature mRNA is generated by the 3ʹ end cleavage and polyadenylation of its precursor pre-mRNA. Eukaryotic genes frequently have multiple polyadenylation sites, resulting in mRNA isoforms with different 3ʹ-UTR lengths that often encode different C-terminal amino acid sequences. It is well-known that this form of post-transcriptional modification, termed alternative polyadenylation, can affect mRNA stability, localization, translation, and nuclear export. We focus on the alternative polyadenylation of pre-mRNA for vascular endothelial growth factor receptor-1 (VEGFR-1), the receptor for VEGF. VEGFR-1 is a transmembrane protein with a tyrosine kinase in the intracellular region. Secreted forms of VEGFR-1 (sVEGFR-1) are also produced from the same gene by alternative polyadenylation, and sVEGFR-1 has a function opposite to that of VEGFR-1 because it acts as a decoy receptor for VEGF. However, the mechanism that regulates the production of sVEGFR-1 by alternative polyadenylation remains poorly understood. In this review, we introduce and discuss the mechanism of alternative polyadenylation of VEGFR-1 mediated by protein arginine methylation.

PolyASite 2.0: a consolidated atlas of polyadenylation sites from 3' end sequencing

Generated by 3′ end cleavage and polyadenylation at alternative polyadenylation (poly(A)) sites, alternative terminal exons account for much of the variation between human transcript isoforms. More than a dozen protocols have been developed so far for capturing and sequencing RNA 3′ ends from a variety of cell types and species. In previous studies, we have used these data to uncover novel regulatory signals and cell type-specific isoforms. Here we present an update of the PolyASite (https://polyasite.unibas.ch) resource of poly(A) sites, constructed from publicly available human, mouse and worm 3′ end sequencing datasets by enforcing uniform quality measures, including the flagging of putative internal priming sites. Through integrated processing of all data, we identified and clustered sites that are closely spaced and share polyadenylation signals, as these are likely the result of stochastic variations in processing. For each cluster, we identified the representative - most frequently processed - site and estimated the relative use in the transcriptome across all samples. We have established a modern web portal for efficient finding, exploration and export of data. Database generation is fully automated, greatly facilitating incorporation of new datasets and the updating of underlying genome resources.

Discovery of alternative polyadenylation dynamics from single cell types

Alternative polyadenylation (APA) occurs in the process of mRNA maturation by adding a poly(A) tail at different locations, resulting increased diversity of mRNA isoforms and contributing to the complexity of gene regulatory network. Benefit from the development of high-throughput sequencing technologies, we could now delineate APA profiles of transcriptomes at an unprecedented pace. Especially the single cell RNA sequencing (scRNA-seq) technologies provide us opportunities to interrogate biological details of diverse and rare cell types. Despite increasing evidence showing that APA is involved in the cell type-specific regulation and function, efficient and specific laboratory methods for capturing poly(A) sites at single cell resolution are underdeveloped to date. In this review, we summarize existing experimental and computational methods for the identification of APA dynamics from diverse single cell types. A future perspective is also provided.

FilTar: using RNA-Seq data to improve microRNA target prediction accuracy in animals

MOTIVATION

MicroRNA (miRNA) target prediction algorithms do not generally consider biological context and therefore generic target prediction based on seed binding can lead to a high level of false-positive predictions. Here, we present FilTar, a method that incorporates RNA-Seq data to make miRNA target prediction specific to a given cell type or tissue of interest.

RESULTS

We demonstrate that FilTar can be used to: (i) provide sample specific 3'-UTR reannotation; extending or truncating default annotations based on RNA-Seq read evidence and (ii) filter putative miRNA target predictions by transcript expression level, thus removing putative interactions where the target transcript is not expressed in the tissue or cell line of interest. We test the method on a variety of miRNA transfection datasets and demonstrate increased accuracy versus generic miRNA target prediction methods.

AVAILABILITY AND IMPLEMENTATION

FilTar is freely available and can be downloaded from https://github.com/TBradley27/FilTar. The tool is implemented using the Python and R programming languages, and is supported on GNU/Linux operating systems.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Estimating the Allele-Specific Expression of SNVs From 10× Genomics Single-Cell RNA-Sequencing Data

With the recent advances in single-cell RNA-sequencing (scRNA-seq) technologies, the estimation of allele expression from single cells is becoming increasingly reliable. Allele expression is both quantitative and dynamic and is an essential component of the genomic interactome. Here, we systematically estimate the allele expression from heterozygous single nucleotide variant (SNV) loci using scRNA-seq data generated on the 10×Genomics Chromium platform. We analyzed 26,640 human adipose-derived mesenchymal stem cells (from three healthy donors), sequenced to an average of 150K sequencing reads per cell (more than 4 billion scRNA-seq reads in total). High-quality SNV calls assessed in our study contained approximately 15% exonic and >50% intronic loci. To analyze the allele expression, we estimated the expressed variant allele fraction (VAF_RNA) from SNV-aware alignments and analyzed its variance and distribution (mono- and bi-allelic) at different minimum sequencing read thresholds. Our analysis shows that when assessing positions covered by a minimum of three unique sequencing reads, over 50% of the heterozygous SNVs show bi-allelic expression, while at a threshold of 10 reads, nearly 90% of the SNVs are bi-allelic. In addition, our analysis demonstrates the feasibility of scVAF_RNA estimation from current scRNA-seq datasets and shows that the 3′-based library generation protocol of 10×Genomics scRNA-seq data can be informative in SNV-based studies, including analyses of transcriptional kinetics.

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.