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

The role of alternative polyadenylation in breast cancer

Breast cancer (BC), as a highly prevalent malignant tumor worldwide, is still unclear in its pathogenesis and has poor therapeutic outcomes. Alternative polyadenylation (APA) is a post-transcriptional regulatory mechanism widely found in eukaryotes. Precursor mRNA (pre-mRNA) undergoes the APA process to generate multiple mRNA isoforms with different coding regions or 3'UTRs, thereby greatly increasing the diversity and complexity of the eukaryotic transcriptome and proteome. Studies have shown that APA is involved in the progression of various diseases, including cancer, and plays a crucial role. Therefore, clarifying the biological mechanisms of APA and its regulators in breast cancer will help to comprehensively understand the pathogenesis of breast cancer and provide new ideas for its prevention and treatment.

Gene expression investigation of four key regulators of polyadenylation and alternative adenylation in the periphery of late-onset Alzheimer's disease patients

BACKGROUND

Alzheimer's disease (AD) is a genetic and sporadic neurodegenerative disease considered by an archetypal cognitive impairment and a decrease in less common cognitive impairment. Notably, the discovery of goals in this paradigm is still a challenge, and understanding basic mechanisms is an important step toward improving disease management. Polyadenylation (PA) and alternative polyadenylation (APA) are two of the most critical RNA processing stages in 3'UTRs that influence various AD-related genes.

METHODS

In this study, we assessed Cleavage and polyadenylation specificity factors 1 and 6 (CPSF1 and CPSF6), cleavage stimulation factor 1 (CSTF1), and WD Repeat Domain 33 (WDR33) genes expression in the periphery of 50 AD patients and 50 healthy individuals with age and gender-matched by quantitative real-time PCR.

RESULTS

Comparing AD patients with healthy people using expression analysis revealed a substantial increase in CSTF1 (posterior beta = 0.773, adjusted P-value = 0.042). Significant positive correlations were found between CSTF1 and CPSF1 (r = 0.365, P < 0.001), WDR33 (r = 0.506, P < 0.001), and CPSF6 (r = 0.446, P < 0.001) expression levels.

CONCLUSION

Although further research is required to determine their potential contribution to AD, our findings offer a fresh perspective on molecular regulatory pathways associated with AD pathogenic mechanisms associated with PA and APA.

Omics Technologies Improving Breast Cancer Research and Diagnostics

Breast cancer (BC) has yielded approximately 2.26 million new cases and has caused nearly 685,000 deaths worldwide in the last two years, making it the most common diagnosed cancer type in the world. BC is an intricate ecosystem formed by both the tumor microenvironment and malignant cells, and its heterogeneity impacts the response to treatment. Biomedical research has entered the era of massive omics data thanks to the high-throughput sequencing revolution, quick progress and widespread adoption. These technologies-liquid biopsy, transcriptomics, epigenomics, proteomics, metabolomics, pharmaco-omics and artificial intelligence imaging-could help researchers and clinicians to better understand the formation and evolution of BC. This review focuses on the findings of recent multi-omics-based research that has been applied to BC research, with an introduction to every omics technique and their applications for the different BC phenotypes, biomarkers, target therapies, diagnosis, treatment and prognosis, to provide a comprehensive overview of the possibilities of BC research.

Modeling cross-talk of RNA modification enzymes reveals tumor microenvironment-associated clinical significance and immunotherapy prediction in hepatobiliary malignancy

RNA modification includes four main types, N6-methyladenosine, N1-methyladenosine, alternative polyadenylation (APA), and adenosine-to-inosine (A-to-I) RNA editing, involving 41 enzymes that serve as "writers", "readers" and "erasers". By collecting RNA modifying enzyme information in 1759 hepatobiliary malignancy (HBM) samples from 11 datasets, an RNA modification HBM Score (RH_score) was established based on unsupervised cluster analysis of RNA modification-associated differentially expressed genes (DEGs). We identified the imbalanced expression of 41 RNA modification enzymes in HBM, which was scientifically categorized into two groups: RH_Score high and RH_Score low. A high RH_Score was associated with a worse prognosis and more immature immune cells in the tumor microenvironment (TME), while a low RH_Score was associated with a better prognosis and more mature immune cells in the TME. Further analysis using single-cell databases showed that the high RH_Score was immune exhaustion in the TME. RH_Score was involved in transcriptional regulation and post-transcriptional events in HBM. Additionally, resistant and sensitive drugs were selected based on RNA modification, and anti-PD-L1 therapy responded better with low RH_Score. In conclusion, our study comprehensively analyzes RNA modification in HBM, which induces TME changes and transcriptional and posttranscriptional events, implying potential guiding significance in prognosis prediction and treatment options.

Circular RNAs and Untranslated Regions in Acute Myeloid Leukemia

Before the advent of next-generation sequencing, research on acute myeloid leukemia (AML) mostly centered on protein-coding genes. In recent years, breakthroughs in RNA sequencing technologies and whole transcriptome analysis have led to the discovery that approximately 97.5% of the human genome is transcribed into non-coding RNAs (ncRNAs). This paradigm shift has led to an explosion of research interest in different classes of non-coding RNAs, such as circular RNAs (circRNAs) as well as non-coding untranslated regions (UTRs) of protein-coding messenger RNAs. The critical roles of circRNAs and UTRs in AML pathogenesis have become increasingly apparent. In this review, we discuss the cellular mechanisms of circRNAs and summarize recent studies that reveal their biological roles in AML. Furthermore, we also review the contribution of 3'UTRs to disease progression. Finally, we discuss the potential of circRNAs and 3'UTRs as new biomarkers for disease stratification and/or the prediction of treatment response and targets for the development of RNA-directed therapeutic applications.

Regulation and function of alternative polyadenylation in development and differentiation

Alternative processing of nascent mRNAs is widespread in eukaryotic organisms and greatly impacts the output of gene expression. Specifically, alternative cleavage and polyadenylation (APA) is a co-transcriptional molecular process that switches the polyadenylation site (PAS) at which a nascent mRNA is cleaved, resulting in mRNA isoforms with different 3'UTR length and content. APA can potentially affect mRNA translation efficiency, localization, stability, and mRNA seeded protein-protein interactions. APA naturally occurs during development and cellular differentiation, with around 70% of human genes displaying APA in particular tissues and cell types. For example, neurons tend to express mRNAs with long 3'UTRs due to preferential processing at PASs more distal than other PASs used in other cell types. In addition, changes in APA mark a variety of pathological states, including many types of cancer, in which mRNAs are preferentially cleaved at more proximal PASs, causing expression of mRNA isoforms with short 3'UTRs. Although APA has been widely reported, both the function of APA in development and the mechanisms that regulate the choice of 3'end cut sites in normal and pathogenic conditions are still poorly understood. In this review, we summarize current understanding of how APA is regulated during development and cellular differentiation and how the resulting change in 3'UTR content affects multiple aspects of gene expression. With APA being a widespread phenomenon, the advent of cutting-edge scientific techniques and the pressing need for in-vivo studies, there has never been a better time to delve into the intricate mechanisms of alternative cleavage and polyadenylation.

Association of RNA-modification "writer" genes with prognosis and response to immunotherapy in patients with low-grade glioma

RNA modification is a key regulatory mechanism involved in tumorigenesis, tumor progression, and the immune response. However, the potential role of RNA modification "writer" genes in the immune microenvironment of gliomas and their effect on the response to immunotherapy remains unclear. The purpose of this study was to evaluate the role of RNA modification "writer" gene in the prognosis and immunotherapy response of low-grade glioma (LGG). The consensus non-negative matrix factorization (CNMF) method was used to identify different RNA modification subtypes. We used a novel eigengene screening method, the variable neighborhood learning Harris Hawks optimizer (VNLHHO), to screen for eigengenes among the RNA modification subtypes. We constructed a principal components analysis score(PCA_score)-based prognostic prediction model and validated it using an independent cohort. We also analyzed the association between PCA_score and the immune and molecular features of LGG. The results suggested that LGG can be divided into two different RNA modification-based subtypes with distinct prognostic and molecular features. High PCA_score was significantly associated with a poor prognosis in LGG and was an independent prognostic factor. A nomogram containing PCA_score and clinical features was constructed, and it showed a significant predictive value. PCA_score was negatively correlated with tumor purity and the abundance of CD4+ T cells in LGG patients. LGG patients with high PCA_score had lower Tumor Immune Dysfunction and Exclusion scores and showed an immunotherapy response. In conclusion, we report a novel RNA modification-based prognostic model for LGG that lays the foundation for evaluating LGG prognosis and developing more effective therapeutic strategies for these tumors.

scAPAmod: Profiling Alternative Polyadenylation Modalities in Single Cells from Single-Cell RNA-Seq Data

Alternative polyadenylation (APA) is a key layer of gene expression regulation, and APA choice is finely modulated in cells. Advances in single-cell RNA-seq (scRNA-seq) have provided unprecedented opportunities to study APA in cell populations. However, existing studies that investigated APA in single cells were either confined to a few cells or focused on profiling APA dynamics between cell types or identifying APA sites. The diversity and pattern of APA usages on a genomic scale in single cells remains unappreciated. Here, we proposed an analysis framework based on a Gaussian mixture model, scAPAmod, to identify patterns of APA usage from homogeneous or heterogeneous cell populations at the single-cell level. We systematically evaluated the performance of scAPAmod using simulated data and scRNA-seq data. The results show that scAPAmod can accurately identify different patterns of APA usages at the single-cell level. We analyzed the dynamic changes in the pattern of APA usage using scAPAmod in different cell differentiation and developmental stages during mouse spermatogenesis and found that even the same gene has different patterns of APA usages in different differentiation stages. The preference of patterns of usages of APA sites in different genomic regions was also analyzed. We found that patterns of APA usages of the same gene in 3′ UTRs (3′ untranslated region) and non-3′ UTRs are different. Moreover, we analyzed cell-type-specific APA usage patterns and changes in patterns of APA usages across cell types. Different from the conventional analysis of single-cell heterogeneity based on gene expression profiling, this study profiled the heterogeneous pattern of APA isoforms, which contributes to revealing the heterogeneity of single-cell gene expression with higher resolution.

Alternative polyadenylation: An enigma of transcript length variation in health and disease

Alternative polyadenylation (APA) is a molecular mechanism during a pre-mRNA processing that involves usage of more than one polyadenylation site (PA-site) generating transcripts of varying length from a single gene. The location of a PA-site affects transcript length and coding potential of an mRNA contributing to both mRNA and protein diversification. This variation in the transcript length affects mRNA stability and translation, mRNA subcellular and tissue localization, and protein function. APA is now considered as an important regulatory mechanism in the pathophysiology of human diseases. An important consequence of the changes in the length of 3'-untranslated region (UTR) from disease-induced APA is altered protein expression. Yet, the relationship between 3'-UTR length and protein expression remains a paradox in a majority of diseases. Here, we review occurrence of APA, mechanism of PA-site selection, and consequences of transcript length variation in different diseases. Emerging evidence reveals coordinated involvement of core RNA processing factors including poly(A) polymerases in the PA-site selection in diseases-associated APAs. Targeting such APA regulators will be therapeutically significant in combating drug resistance in cancer and other complex diseases. This article is categorized under: RNA Processing > 3' End Processing RNA in Disease and Development > RNA in Disease Translation > Regulation.

Analysis of alternative polyadenylation from single-cell RNA-seq using scDaPars reveals cell subpopulations invisible to gene expression

Alternative polyadenylation (APA) is a major mechanism of post-transcriptional regulation in various cellular processes including cell proliferation and differentiation, but the APA heterogeneity among single cells remains largely unknown. Single-cell RNA sequencing (scRNA-seq) has been extensively used to define cell subpopulations at the transcription level. Yet, most scRNA-seq data have not been analyzed in an "APA-aware" manner. Here, we introduce scDaPars (Dynamic Analysis of Alternative PolyAdenylation from Single-cell RNA-seq), a bioinformatics algorithm to accurately quantify APA events at both single-cell and single-gene resolution using either 3' end (10x Chromium) or full-length (Smart-seq2) scRNA-seq data. Validations in both real and simulated data indicate that scDaPars can robustly recover missing APA events caused by the low amounts of mRNA sequenced in single cells. When applied to cancer and human endoderm differentiation data, scDaPars not only revealed cell type-specific APA regulation but also identified cell subpopulations that are otherwise invisible to conventional gene expression analysis. Thus, scDaPars will enable us to understand cellular heterogeneity at the post-transcriptional APA level.

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.

Single cell RNA sequencing for breast cancer: present and future

Breast cancer is one of the most common malignant tumors in women. It is a heterogeneous disease related to genetic and environmental factors. Presently, the treatment of breast cancer still faces challenges due to recurrence and metastasis. The emergence of single-cell RNA sequencing (scRNA-seq) technology has brought new strategies to deeply understand the biological behaviors of breast cancer. By analyzing cell phenotypes and transcriptome differences at the single-cell level, scRNA-seq reveals the heterogeneity, dynamic growth and differentiation process of cells. This review summarizes the application of scRNA-seq technology in breast cancer research, such as in studies on cell heterogeneity, cancer cell metastasis, drug resistance, and prognosis. scRNA-seq technology is of great significance to deeply analyze the mechanism of breast cancer occurrence and development, identify new therapeutic targets and develop new therapeutic approaches for breast cancer.

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

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

Cross-talk of four types of RNA modification writers defines tumor microenvironment and pharmacogenomic landscape in colorectal cancer

Background

The four major RNA adenosine modifications, i.e., m⁶A, m¹A, alternative polyadenylation, and adenosine-to-inosine RNA editing, are mediated mostly by the “writer” enzymes and constitute critical mechanisms of epigenetic regulation in immune response and tumorigenesis. However, the cross-talk and potential roles of these “writers” in the tumor microenvironment (TME), drug sensitivity, and immunotherapy remain unknown.

Methods

We systematically characterized mRNA expression and genetic alterations of 26 RNA modification “writers” in colorectal cancer (CRC), and evaluated their expression pattern in 1697 CRC samples from 8 datasets. We used an unsupervised clustering method to assign the samples into two patterns of expression of RNA modification “writers”. Subsequently, we constructed the RNA modification “writer” Score (WM_Score) model based on differentially expressed genes (DEGs) responsible for the RNA modification patterns to quantify the RNA modification-related subtypes of individual tumors. Furthermore, we performed association analysis for WM_Score and characteristics of TME, consensus molecular subtypes (CMSs), clinical features, transcriptional and post-transcriptional regulation, drug response, and the efficacy of immunotherapy.

Results

We demonstrated that multi-layer alterations of RNA modification “writer” are associated with patient survival and TME cell-infiltrating characteristics. We identified two distinct RNA modification patterns, characterized by a high and a low WM_Score. The WM_Score-high group was associated with worse patient overall survival and with the infiltration of inhibitory immune cells, such as M2 macrophages, EMT activation, and metastasis, while the WM_Score-low group was associated with a survival advantage, apoptosis, and cell cycle signaling pathways. WM_Score correlated highly with the regulation of transcription and post-transcriptional events contributing to the development of CRC. In response to anti-cancer drugs, WM_Score highly negatively correlated (drug sensitive) with drugs which targeted oncogenic related pathways, such as MAPK, EGFR, and mTOR signaling pathways, positively correlated (drug resistance) with drugs which targeted in apoptosis and cell cycle. Importantly, the WM_Score was associated with the therapeutic efficacy of PD-L1 blockade, suggesting that the development of potential drugs targeting these “writers” to aid the clinical benefits of immunotherapy.

Conclusions

Our study is the first to provide a comprehensive analysis of four RNA modifications in CRC. We revealed the potential function of these writers in TME, transcriptional and post-transcriptional events, and identified their therapeutic liability in targeted therapy and immunotherapy. This work highlights the cross-talk and potential clinical utility of RNA modification “writers” in cancer therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12943-021-01322-w.

Immune-related genes with APA in microenvironment indicate risk stratification and clinical prognosis in grade II/III gliomas

Tumor microenvironment and alternative polyadenylation (APA) have drawn more attention in cancer research. However, their roles in grade II and III gliomas, termed as lower-grade glioma (LGG) in this study, remain to be fully elucidated. Here, we conducted this study and found that stromal and immune scores were elevated in higher grade and isocitrate dehydrogenase (IDH) wild-type glioma. Besides, higher stromal and immune scores indicated a poor prognosis in patients with LGG. APA events in immune-related genes were associated with overall survival, RNA expression, IDH mutation, and disease-free survival. Patients in the high-risk group had poor prognoses, and the risk score could be used to predict the survival rate. The risk score was positively correlated with the expression of immune checkpoints, inflammatory cytokines, and infiltrated immune cells. Moreover, risk stratification could predict the efficacy of radiotherapy and provide a reference for the treatment of grade III glioma. Our study revealed that immune-related genes with APA events in the microenvironment could predict risk stratification and clinical prognosis in patients with LGG.

Progress and Clinical Application of Single-Cell Transcriptional Sequencing Technology in Cancer Research

Cancer has been a daunting challenge for human beings because of its clonal heterogeneity and compositional complexity. Tumors are composed of cancer cells and a variety of non-cancer cells, which together with the extracellular matrix form the tumor microenvironment. These cancer-related cells and components and immune mechanisms can affect the development and progression of cancer and are associated with patient diagnosis, treatment and prognosis. As the first choice for the study of complex biological systems, single-cell transcriptional sequencing (scRNA-seq) has been widely used in cancer research. ScRNA-seq has made breakthrough discoveries in tumor heterogeneity, tumor evolution, metastasis and spread, development of chemoresistance, and the relationship between the tumor microenvironment and the immune system. These results will guide clinical cancer treatment and promote personalized and highly accurate cancer treatment. In this paper, we summarize the latest research progress of scRNA-seq and its guiding significance for clinical treatment.

Alternative Polyadenylation: a new frontier in post transcriptional regulation

Polyadenylation of pre-messenger RNA (pre-mRNA) specific sites and termination of their downstream transcriptions are signaled by unique sequence motif structures such as AAUAAA and its auxiliary elements. Alternative polyadenylation (APA) is an important post-transcriptional regulatory mechanism that processes RNA products depending on its 3'-untranslated region (3'-UTR) specific sequence signal. APA processing can generate several mRNA isoforms from a single gene, which may have different biological functions on their target gene. As a result, cellular genomic stability, proliferation capability, and transformation feasibility could all be affected. Furthermore, APA modulation regulates disease initiation and progression. APA status could potentially act as a biomarker for disease diagnosis, severity stratification, and prognosis forecast. While the advance of modern throughout technologies, such as next generation-sequencing (NGS) and single-cell sequencing techniques, have enriched our knowledge about APA, much of APA biological process is unknown and pending for further investigation. Herein, we review the current knowledge on APA and how its regulatory complex factors (CFI/IIm, CPSF, CSTF, and RBPs) work together to determine RNA splicing location, cell cycle velocity, microRNA processing, and oncogenesis regulation. We also discuss various APA experiment strategies and the future direction of APA research.

scAPAtrap: identification and quantification of alternative polyadenylation sites from single-cell RNA-seq data

Alternative polyadenylation (APA) generates diverse mRNA isoforms, which contributes to transcriptome diversity and gene expression regulation by affecting mRNA stability, translation and localization in cells. The rapid development of 3' tag-based single-cell RNA-sequencing (scRNA-seq) technologies, such as CEL-seq and 10x Genomics, has led to the emergence of computational methods for identifying APA sites and profiling APA dynamics at single-cell resolution. However, existing methods fail to detect the precise location of poly(A) sites or sites with low read coverage. Moreover, they rely on priori genome annotation and can only detect poly(A) sites located within or near annotated genes. Here we proposed a tool called scAPAtrap for detecting poly(A) sites at the whole genome level in individual cells from 3' tag-based scRNA-seq data. scAPAtrap incorporates peak identification and poly(A) read anchoring, enabling the identification of the precise location of poly(A) sites, even for sites with low read coverage. Moreover, scAPAtrap can identify poly(A) sites without using priori genome annotation, which helps locate novel poly(A) sites in previously overlooked regions and improve genome annotation. We compared scAPAtrap with two latest methods, scAPA and Sierra, using scRNA-seq data from different experimental technologies and species. Results show that scAPAtrap identified poly(A) sites with higher accuracy and sensitivity than competing methods and could be used to explore APA dynamics among cell types or the heterogeneous APA isoform expression in individual cells. scAPAtrap is available at https://github.com/BMILAB/scAPAtrap.

Dissecting the heterogeneity of the alternative polyadenylation profiles in triple-negative breast cancers

Background: Triple-negative breast cancer (TNBC) is an aggressive malignancy with high heterogeneity. However, the alternative polyadenylation (APA) profiles of TNBC remain unknown. Here, we aimed to define the characteristics of the APA events at post-transcription level among TNBCs. Methods: Using transcriptome microarray data, we analyzed APA profiles of 165 TNBC samples and 33 paired normal tissues. A pooled short hairpin RNA screen targeting 23 core cleavage and polyadenylation (C/P) genes was used to identify key C/P factors. Results: We established an unconventional APA subtyping system composed of four stable subtypes: 1) luminal androgen receptor (LAR), 2) mesenchymal-like immune-activated (MLIA), 3) basal-like (BL), 4) suppressed (S) subtypes. Patients in the S subtype had the worst disease-free survival comparing to other patients (log-rank p = 0.021). Enriched clinically actionable pathways and putative therapeutic APA events were analyzed among each APA subtype. Furthermore, CPSF1 and PABPN1 were identified as the master C/P factors in regulating APA events and TNBC proliferation. The depletion of CPSF1 or PABPN1 weakened cell proliferation, enhanced apoptosis, resulted in cell cycle redistribution and a reversion of APA events of genes associated with tumorigenesis, proliferation, metastasis and chemosensitivity in breast cancer. Conclusions: Our findings advance the understanding of tumor heterogeneity regulation in APA and yield new insights into therapeutic target identification in TNBC.

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

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

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.