Similar Datasets
Project description:Most pre-messenger RNA (pre-mRNA) undergo extensive processing to create distinct transcripts from the same gene. One of these processes, alternative polyadenylation, involves over twenty proteins to bind and cleave the pre-mRNA at poly(A) sites that can lie within the 3' UTR, introns, or exons; this can modulate protein function, but the effect of choosing a site internal to the gene vs. within the 3' UTR remains unclear. Here we show that reduced expression of CPSF6, one of the proteins involved in site selection, derails development in both humans and zebrafish by causing a bidirectional shift in poly(A) site usage. CPSF6 insufficiency favors the use of intronic poly(A) sites in neuronal genes, reducing mRNA and protein abundance, but promotes 3' UTR site usage in cardiovascular and skeletal genes, upregulating mRNA and protein.These data thus provide a long-sought link between APA and gene expression and shows that poly(A) site selection influences development.
2023-01-15 | GSE206557 | GEO
Project description:Most pre-messenger RNA (pre-mRNA) undergo extensive processing to create distinct transcripts from the same gene. One of these processes, alternative polyadenylation, involves over twenty proteins to bind and cleave the pre-mRNA at poly(A) sites that can lie within the 3' UTR, introns, or exons; this can modulate protein function, but the effect of choosing a site internal to the gene vs. within the 3' UTR remains unclear. Here we show that reduced expression of CPSF6, one of the proteins involved in site selection, derails development in both humans and zebrafish by causing a bidirectional shift in poly(A) site usage. CPSF6 insufficiency favors the use of intronic poly(A) sites in neuronal genes, reducing mRNA and protein abundance, but promotes 3' UTR site usage in cardiovascular and skeletal genes, upregulating mRNA and protein.These data thus provides a long-sought link between APA and gene expression and shows that poly(A) site selection influences development.
2023-01-15 | GSE206558 | GEO
Project description:Loss of CPSF6 causes developmental disease via bimodal changes in polyadenylation site usage and protein expression
| PRJNA851372 | ENA
Project description:Loss of CPSF6 causes developmental disease via bimodal changes in polyadenylation site usage and protein expression [Human]
| PRJNA851383 | ENA
Project description:Loss of CPSF6 causes developmental disease via bimodal changes in polyadenylation site usage and protein expression [Zebrafish]
| PRJNA851381 | ENA
Project description:Alternative polyadenylation (APA) is a crucial step in post-transcriptional regulation. Previous bioinformatic studies have mainly focused on the recognition of polyadenylation sites (PASs) in a given genomic sequence, which is a binary classification problem. Recently, computational methods for predicting the usage level of alternative PASs in the same gene have been proposed. However, all of them cast the problem as a non-quantitative pairwise comparison task and do not take the competition among multiple PASs into account. To address this, here we propose a deep learning architecture, Deep Regulatory Code and Tools for Alternative Polyadenylation (DeeReCT-APA), to quantitatively predict the usage of all alternative PASs of a given gene. To accommodate different genes with potentially different numbers of PASs, DeeReCT-APA treats the problem as a regression task with a variable-length target. Based on a convolutional neural network-long short-term memory (CNN-LSTM) architecture, DeeReCT-APA extracts sequence features with CNN layers, uses bidirectional LSTM to explicitly model the interactions among competing PASs, and outputs percentage scores representing the usage levels of all PASs of a gene. In addition to the fact that only our method can quantitatively predict the usage of all the PASs within a gene, we show that our method consistently outperforms other existing methods on three different tasks for which they are trained: pairwise comparison task, highest usage prediction task, and ranking task. Finally, we demonstrate that our method can be used to predict the effect of genetic variations on APA patterns and sheds light on future mechanistic understanding in APA regulation. Our code and data are available at https://github.com/lzx325/DeeReCT-APA-repo.
| S-EPMC9801043 | biostudies-literature
Project description:RNA-binding protein HuR modulates the stability and translational efficiency of messenger RNAs (mRNAs) encoding essential components of the cellular proliferation, growth and survival pathways. Consistent with these functions, HuR levels are often elevated in cancer cells and reduced in senescent and quiescent cells. However, the molecular mechanisms that control HuR expression are poorly understood. Here we show that HuR protein autoregulates its abundance through a negative feedback loop that involves interaction of the nuclear HuR protein with a GU-rich element (GRE) overlapping with the HuR major polyadenylation signal (PAS2). An increase in the cellular HuR protein levels stimulates the expression of long HuR mRNA species containing an AU-rich element (ARE) that destabilizes the mRNAs and thus reduces the protein production output. The PAS2 read-through occurs due to a reduced recruitment of the CstF-64 subunit of the pre-mRNA cleavage stimulation factor in the presence of the GRE-bound HuR. We propose that this mechanism maintains HuR homeostasis in proliferating cells. Since only the nuclear HuR is expected to contribute to the auto-regulation, our model may explain the longstanding observation that the increase in the total HuR expression in cancer cells often correlates with the accumulation of its substantial fraction in the cytoplasm.
| S-EPMC3258158 | biostudies-literature
Project description:BackgroundAlternative polyadenylation (APA) is an important mechanism of gene expression regulation through generation of RNA isoforms with distinct 3' termini. Increasing evidence has revealed that APA is actively involved in development and disease, including hepatocellular carcinoma (HCC). However, how APA functions in tumor formation and progression remains elusive. In this study, we investigated the role of cleavage factor I (CFIm) subunit CPSF6 in human hepatocellular carcinoma (HCC).MethodsExpression levels of CPSF6 in clinical tissues and cell lines were determined by qRT-PCR and western blot. Functional assays, including the cell number, MTT, colony formation and transwell, were used to determine the oncogenic role of CPSF6 in HCC. Animal experiments were used to determine the role of CPSF6 in HCC tumorigenicity in vivo. Deep sequencing-based 3 T-seq was used to profile the transcriptome-wide APA sites in both HCC cells and CPSF6 knockdown HCC cells. The function of CPSF6-affected target NQO1 with distinct 3'UTRs was characterized by metabolism assays.ResultsWe observed CPSF6 was upregulated in HCC and the high expression of CPSF6 was associated with poor prognosis in patients. Overexpression of CPSF6 promoted proliferation, migration and invasion of HCC cells in vitro and in vivo. Transcriptome-wide APA profiling analysis indicated that high expression of CPSF6 promoted the favorable usage of the proximal poly(A) site in the 3'UTR of NQO1. We demonstrated CPSF6-induced tumorigenic activities were mediated by the NQO1 isoform with short 3'UTR. Furthermore, we found that CPSF6 induced metabolic alterations in liver cells through NQO1.ConclusionCPSF6 plays a critical role in HCC progression by upregulating NQO1 expression through APA. These findings provide evidence to demonstrate that APA of NQO1 contributes to HCC progression and may have implications for developing new therapeutic strategy against this disease.
| S-EPMC7923339 | biostudies-literature
Project description:The genomic distribution of cleavage and polyadenylation (polyA) sites should be co-evolutionally optimized with the local gene structure. Otherwise, spurious polyadenylation can cause premature transcription termination and generate aberrant proteins. To obtain mechanistic insights into polyA site optimization across the human genome, we develop deep/machine learning models to identify genome-wide putative polyA sites at unprecedented nucleotide-level resolution and calculate their strength and usage in the genomic context. Our models quantitatively measure position-specific motif importance and their crosstalk in polyA site formation and cleavage heterogeneity. The intronic site expression is governed by the surrounding splicing landscape. The usage of alternative polyA sites in terminal exons is modulated by their relative locations and distance to downstream genes. Finally, we apply our models to reveal thousands of disease- and trait-associated genetic variants altering polyadenylation activity. Altogether, our models represent a valuable resource to dissect molecular mechanisms mediating genome-wide polyA site expression and characterize their functional roles in human diseases.
| S-EPMC10651852 | biostudies-literature
Project description:A defining property of circadian clocks is temperature compensation, characterized by the resilience of their near 24-hour free-running periods against changes in environmental temperature within the physiological range. While temperature compensation is evolutionary conserved across different taxa of life and has been studied within many model organisms, its molecular underpinnings remain elusive. Posttranscriptional regulations such as temperature-sensitive alternative splicing or phosphorylation have been described as underlying reactions. Here, we show that knockdown of cleavage and polyadenylation specificity factor subunit 6 (CPSF6), a key regulator of 3'-end cleavage and polyadenylation, significantly alters circadian temperature compensation in human U-2 OS cells. We apply a combination of 3'-end-RNA-seq and mass spectrometry-based proteomics to globally quantify changes in 3' UTR length as well as gene and protein expression between wild-type and CPSF6 knockdown cells and their dependency on temperature. Since changes in temperature compensation behavior should be reflected in alterations of temperature responses within one or all of the 3 regulatory layers, we statistically assess differential responses upon changes in ambient temperature between wild-type and CPSF6 knockdown cells. By this means, we reveal candidate genes underlying circadian temperature compensation, including eukaryotic translation initiation factor 2 subunit 1 (EIF2S1).
| S-EPMC10335657 | biostudies-literature