ScAPAdb: a comprehensive database of alternative polyadenylation at single-cell resolution.
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ABSTRACT:
SUBMITTER: Zhu S
PROVIDER: S-EPMC8728153 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Alternative polyadenylation (APA) has been discovered to play regulatory roles in the development of many cancer cells through preferential addition of a poly(A) tail at specific sites of pre-mRNA. A recent study found that APA was involved in the mediation of acute myeloid leukaemia (AML). However, unlike gene expression heterogeneity, little attention has been directed toward variations in single-cell APA for different cell types during AML development. Here, we used single-cell RNA-seq data of a massive population of 16,843 bone marrow mononuclear cells (BMMCs) from healthy and AML patient samples to investigate dynamic APA usage in different cell types. Abnormalities of APA dynamics in the BMMCs from AML patient samples were uncovered compared to the stable APA dynamics in samples from healthy individuals, as well as lower APA diversity between eight cell types in AML patients. Genes with APA dynamics specific to the AML samples were significantly enriched in cellular signal transduction pathways that contribute to AML development. Moreover, many leukaemic cell marker genes such as NF-κB, GATA2 and IAP-Family genes exhibited APA dynamics that specifically affected abnormal proliferation and differentiation of leukemic BMMCs. Additionally, mature erythroid cells displayed greater APA dynamics and global 3' UTR shortening compared with other cell types. Our results revealed extensive involvement of APA regulation in leukemia development and erythropoiesis at the single-cell level, providing a high-resolution atlas to navigate cellular mRNA processing landscapes of differentiated cells in AML.
| S-EPMC6546370 | biostudies-literature
Project description: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.
| S-EPMC7200215 | biostudies-literature
Project description:BackgroundAlternative polyadenylation (APA) is emerging as an important mechanism in the post-transcriptional regulation of gene expression across eukaryotic species. Recent studies have shown that APA plays key roles in biological processes, such as cell proliferation and differentiation. Single-cell RNA-seq technologies are widely used in gene expression heterogeneity studies; however, systematic studies of APA at the single-cell level are still lacking.ResultsHere, we described a novel computational framework, SAPAS, that utilizes 3'-tag-based scRNA-seq data to identify novel poly(A) sites and quantify APA at the single-cell level. Applying SAPAS to the scRNA-seq data of phenotype characterized GABAergic interneurons, we identified cell type-specific APA events for different GABAergic neuron types. Genes with cell type-specific APA events are enriched for synaptic architecture and communications. In further, we observed a strong enrichment of heritability for several psychiatric disorders and brain traits in altered 3' UTRs and coding sequences of cell type-specific APA events. Finally, by exploring the modalities of APA, we discovered that the bimodal APA pattern of Pak3 could classify chandelier cells into different subpopulations that are from different laminar positions.ConclusionsWe established a method to characterize APA at the single-cell level. When applied to a scRNA-seq dataset of GABAergic interneurons, the single-cell APA analysis not only identified cell type-specific APA events but also revealed that the modality of APA could classify cell subpopulations. Thus, SAPAS will expand our understanding of cellular heterogeneity.
| S-EPMC8299648 | biostudies-literature
Project description:Within the tumour microenvironment, cells exhibit different behaviours driven by fine-tuning of gene regulation. Identification of cellular-specific gene regulatory networks will deepen the understanding of disease pathology at single-cell resolution and contribute to the development of precision medicine. Here, we describe a database, LnCeCell (http://www.bio-bigdata.net/LnCeCell/ or http://bio-bigdata.hrbmu.edu.cn/LnCeCell/), which aims to document cellular-specific long non-coding RNA (lncRNA)-associated competing endogenous RNA (ceRNA) networks for personalised characterisation of diseases based on the 'One Cell, One World' theory. LnCeCell is curated with cellular-specific ceRNA regulations from >94 000 cells across 25 types of cancers and provides >9000 experimentally supported lncRNA biomarkers, associated with tumour metastasis, recurrence, prognosis, circulation, drug resistance, etc. For each cell, LnCeCell illustrates a global map of ceRNA sub-cellular locations, which have been manually curated from the literature and related data sources, and portrays a functional state atlas for a single cancer cell. LnCeCell also provides several flexible tools to infer ceRNA functions based on a specific cellular background. LnCeCell serves as an important resource for investigating the gene regulatory networks within a single cell and can help researchers understand the regulatory mechanisms underlying complex microbial ecosystems and individual phenotypes.
| S-EPMC7778920 | biostudies-literature
Project description:The emerging discoveries on the link between polyadenylation and disease states underline the need to fully characterize genome-wide polyadenylation states. Here, we report comprehensive maps of global polyadenylation events in human and yeast generated using refinements to the Direct RNA Sequencing technology. This direct approach provides a quantitative view of genome-wide polyadenylation states in a strand-specific manner and requires only attomole RNA quantities. The polyadenylation profiles revealed an abundance of unannotated polyadenylation sites, alternative polyadenylation patterns, and regulatory element-associated poly(A)(+) RNAs. We observed differences in sequence composition surrounding canonical and noncanonical human polyadenylation sites, suggesting novel noncoding RNA-specific polyadenylation mechanisms in humans. Furthermore, we observed the correlation level between sense and antisense transcripts to depend on gene expression levels, supporting the view that overlapping transcription from opposite strands may play a regulatory role. Our data provide a comprehensive view of the polyadenylation state and overlapping transcription.
| S-EPMC3022516 | biostudies-literature
Project description:BackgroundAlternative polyadenylation (APA) is emerging as a major post-transcriptional mechanism for gene regulation, and dysregulation of APA contributes to several human diseases. However, the functional consequences of APA in human cancer are not fully understood. Particularly, there is no large-scale analysis in cancer cell lines.MethodsWe characterized the global APA profiles of 6398 patient samples across 17 cancer types from The Cancer Genome Atlas and 739 cancer cell lines from the Cancer Cell Line Encyclopedia. We built a linear regression model to explore the correlation between APA factors and APA events across different cancer types. We used Spearman correlation to assess the effects of APA events on drug sensitivity and the Wilcoxon rank-sum test or Cox proportional hazards model to identify clinically relevant APA events.ResultsWe revealed a striking global 3'UTR shortening in cancer cell lines compared with tumor samples. Our analysis further suggested PABPN1 as the master regulator in regulating APA profile across different cancer types. Furthermore, we showed that APA events could affect drug sensitivity, especially of drugs targeting chromatin modifiers. Finally, we identified 1971 clinically relevant APA events, as well as alterations of APA in clinically actionable genes, suggesting that analysis of the complexity of APA profiles could have clinical utility.ConclusionsOur study highlights important roles for APA in human cancer, including reshaping cellular pathways and regulating specific gene expression, exemplifying the complex interplay between APA and other biological processes and yielding new insights into the action mechanism of cancer drugs.
| S-EPMC6059203 | biostudies-literature
Project description:Alternative polyadenylation (APA) is emerging as an important layer of gene regulation because the majority of mammalian protein-coding genes contain multiple polyadenylation (pA) sites in their 3' UTR. By alteration of 3' UTR length, APA can considerably affect post-transcriptional gene regulation. Yet, our understanding of APA remains rudimentary. Novel single-cell RNA sequencing (scRNA-seq) techniques allow molecular characterization of different cell types to an unprecedented degree. Notably, the most popular scRNA-seq protocols specifically sequence the 3' end of transcripts. Building on this property, we implemented a method for analysing patterns of APA regulation from such data. Analyzing multiple datasets from diverse tissues, we identified widespread modulation of APA in different cell types resulting in global 3' UTR shortening/lengthening and enhanced cleavage at intronic pA sites. Our results provide a proof-of-concept demonstration that the huge volume of scRNA-seq data that accumulates in the public domain offers a unique resource for the exploration of APA based on a very broad collection of cell types and biological conditions.
| S-EPMC6821429 | biostudies-literature
Project description: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.
| S-EPMC9329739 | biostudies-literature
Project description:Alternative polyadenylation (APA) is a widespread mechanism that contributes to the sophisticated dynamics of gene regulation. Approximately 50% of all protein-coding human genes harbor multiple polyadenylation (PA) sites; their selective and combinatorial use gives rise to transcript variants with differing length of their 3' untranslated region (3'UTR). Shortened variants escape UTR-mediated regulation by microRNAs (miRNAs), especially in cancer, where global 3'UTR shortening accelerates disease progression, dedifferentiation and proliferation. Here we present APADB, a database of vertebrate PA sites determined by 3' end sequencing, using massive analysis of complementary DNA ends. APADB provides (A)PA sites for coding and non-coding transcripts of human, mouse and chicken genes. For human and mouse, several tissue types, including different cancer specimens, are available. APADB records the loss of predicted miRNA binding sites and visualizes next-generation sequencing reads that support each PA site in a genome browser. The database tables can either be browsed according to organism and tissue or alternatively searched for a gene of interest. APADB is the largest database of APA in human, chicken and mouse. The stored information provides experimental evidence for thousands of PA sites and APA events. APADB combines 3' end sequencing data with prediction algorithms of miRNA binding sites, allowing to further improve prediction algorithms. Current databases lack correct information about 3'UTR lengths, especially for chicken, and APADB provides necessary information to close this gap. Database URL: http://tools.genxpro.net/apadb/.
| S-EPMC4105710 | biostudies-literature
Project description:Cleavage and polyadenylation are essential processes that can impact many aspects of mRNA fate. Most eukaryotic genes have alternative polyadenylation (APA) events. While the heterogeneity of mRNA polyadenylation isoform choice has been studied in specific tissues, less attention has been paid to the neuronal heterogeneity of APA selection at single-nucleus resolution. APA is highly controlled during development and neuronal activation, however, to what extent APA events vary in a specific neuronal cell population and the regulatory mechanisms are still unclear. In this paper, we investigated dynamic APA usage in different cell types using snRNA-seq data of 1424 human brain cells generated by single-cell 3' RNA sequencing. We found that distal APA sites are not only favored by global neuronal cells, but that their usage also varies between the principal types of neuronal cell populations (excitatory neurons and inhibitory neurons). A motif analysis and a gene functional analysis indicated the enrichment of RNA-binding protein (RBP) binding sites and neuronal functions for the set of genes with neuron-enhanced distal PAS usage. Our results revealed the extensive involvement of APA regulation in neuronal populations at the single-nucleus level, providing new insights into roles for APA in specific neuronal cell populations, as well as utility in future functional studies.
| S-EPMC7349645 | biostudies-literature