mountainClimber Identifies Alternative Transcription Start and Polyadenylation Sites in RNA-Seq

Pan-cancer transcriptome analysis reveals widespread regulation through alternative tandem transcription initiation

Abnormal transcription initiation from alternative first exon has been reported to promote tumorigenesis. However, the prevalence and impact of gene expression regulation mediated by alternative tandem transcription initiation were mostly unknown in cancer. Here, we developed a robust computational method to analyze alternative tandem transcription start site (TSS) usage from standard RNA sequencing data. Applying this method to pan-cancer RNA sequencing datasets, we observed widespread dysregulation of tandem TSS usage in tumors, many of which were independent of changes in overall expression level or alternative first exon usage. We showed that the dynamics of tandem TSS usage was associated with epigenomic modulation. We found that significant 5' untranslated region shortening of gene TIMM13 contributed to increased protein production, and up-regulation of TIMM13 by CRISPR-mediated transcriptional activation promoted proliferation and migration of lung cancer cells. Our findings suggest that dysregulated tandem TSS usage represents an addtional layer of cancer-associated transcriptome alterations.

(Alternative) transcription start sites as regulators of RNA processing

Alternative transcription start site usage (ATSS) is a widespread regulatory strategy that enables genes to choose between multiple genomic loci for initiating transcription. This mechanism is tightly controlled during development and is often altered in disease states. In this review, we examine the growing evidence highlighting a role for transcription start sites (TSSs) in the regulation of mRNA isoform selection during and after transcription. We discuss how the choice of transcription initiation sites influences RNA processing and the importance of this crosstalk for cell identity and organism function. We also speculate on possible mechanisms underlying the integration of transcriptional and post-transcriptional processes.

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.

Alternative Transcripts Diversify Genome Function for Phenome Relevance to Health and Diseases

Manipulation using alternative exon splicing (AES), alternative transcription start (ATS), and alternative polyadenylation (APA) sites are key to transcript diversity underlying health and disease. All three are pervasive in organisms, present in at least 50% of human protein-coding genes. In fact, ATS and APA site use has the highest impact on protein identity, with their ability to alter which first and last exons are utilized as well as impacting stability and translation efficiency. These RNA variants have been shown to be highly specific, both in tissue type and stage, with demonstrated importance to cell proliferation, differentiation and the transition from fetal to adult cells. While alternative exon splicing has a limited effect on protein identity, its ubiquity highlights the importance of these minor alterations, which can alter other features such as localization. The three processes are also highly interwoven, with overlapping, complementary, and competing factors, RNA polymerase II and its CTD (C-terminal domain) chief among them. Their role in development means dysregulation leads to a wide variety of disorders and cancers, with some forms of disease disproportionately affected by specific mechanisms (AES, ATS, or APA). Challenges associated with the genome-wide profiling of RNA variants and their potential solutions are also discussed in this review.

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.

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.

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.

RNA modification writers influence tumor microenvironment in gastric cancer and prospects of targeted drug therapy

Background: RNA adenosine modifications are crucial for regulating RNA levels. N6-methyladenosine (m6A), N1-methyladenosine (m1A), adenosine-to-inosine RNA editing, and alternative polyadenylation (APA) are four major RNA modification types. Methods: We evaluated the altered mRNA expression profiles of 27 RNA modification enzymes and compared the differences in tumor microenvironment (TME) and clinical prognosis between two RNA modification patterns using unsupervised clustering. Then, we constructed a scoring system, WM_score, and quantified the RNA modifications in patients of gastric cancer (GC), associating WM_score with TME, clinical outcomes, and effectiveness of targeted therapies. Results: RNA adenosine modifications strongly correlated with TME and could predict the degree of TME cell infiltration, genetic variation, and clinical prognosis. Two modification patterns were identified according to high and low WM_scores. Tumors in the WM_score-high subgroup were closely linked with survival advantage, CD4[Formula: see text] T-cell infiltration, high tumor mutation burden, and cell cycle signaling pathways, whereas those in the WM_score-low subgroup showed strong infiltration of inflammatory cells and poor survival. Regarding the immunotherapy response, a high WM_score showed a significant correlation with PD-L1 expression, predicting the effect of PD-L1 blockade therapy. Conclusion: The WM_scoring system could facilitate scoring and prediction of GC prognosis.

Widespread occurrence of hybrid internal-terminal exons in human transcriptomes

Messenger RNA isoform differences are predominantly driven by alternative first, internal, and last exons. Despite the importance of classifying exons to understand isoform structure, few tools examine isoform-specific exon usage. We recently observed that alternative transcription start sites often arise near internal exons, often creating “hybrid” first/internal exons. To systematically detect hybrid exons, we built the hybrid-internal-terminal (HIT) pipeline to classify exons depending on their isoform-specific usage. On the basis of splice junction reads in RNA sequencing data and probabilistic modeling, the HIT index identified thousands of previously misclassified hybrid first-internal and internal-last exons. Hybrid exons are enriched in long genes and genes involved in RNA splicing and have longer flanking introns and strong splice sites. Their usage varies considerably across human tissues. By developing the first method to classify exons according to isoform contexts, our findings document the occurrence of hybrid exons, a common quirk of the human transcriptome.

Understanding small ORF diversity through a comprehensive transcription feature classification

Small open reading frames (small ORFs/sORFs/smORFs) are potentially coding sequences smaller than 100 codons that have historically been considered junk DNA by gene prediction software and in annotation screening; however, the advent of next-generation sequencing has contributed to the deeper investigation of junk DNA regions and their transcription products, resulting in the emergence of smORFs as a new focus of interest in systems biology. Several smORF peptides were recently reported in noncanonical mRNAs as new players in numerous biological contexts; however, their relevance is still overlooked in coding potential analysis. Hence, this review proposes a smORF classification based on transcriptional features, discussing the most promising approaches to investigate smORFs based on their different characteristics. First, smORFs were divided into nonexpressed (intergenic) and expressed (genic) smORFs. Second, genic smORFs were classified as smORFs located in noncoding RNAs (ncRNAs) or canonical mRNAs. Finally, smORFs in ncRNAs were further subdivided into sequences located in small or long RNAs, whereas smORFs located in canonical mRNAs were subdivided into several specific classes depending on their localization along the gene. We hope that this review provides new insights into large-scale annotations and reinforces the role of smORFs as essential components of a hidden coding DNA world.

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.

APAlyzer: a bioinformatics package for analysis of alternative polyadenylation isoforms

SUMMARY

Most eukaryotic genes produce alternative polyadenylation (APA) isoforms. APA is dynamically regulated under different growth and differentiation conditions. Here, we present a bioinformatics package, named APAlyzer, for examining 3'UTR APA, intronic APA and gene expression changes using RNA-seq data and annotated polyadenylation sites in the PolyA_DB database. Using APAlyzer and data from the GTEx database, we present APA profiles across human tissues.

AVAILABILITY AND IMPLEMENTATION

APAlyzer is freely available at https://bioconductor.org/packages/release/bioc/html/APAlyzer.html as an R/Bioconductor package.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.