MAAPER: model-based analysis of alternative polyadenylation using 3' end-linked reads.
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ABSTRACT:
SUBMITTER: Li WV
PROVIDER: S-EPMC8356463 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The position of a poly(A) site of eukaryotic mRNA is determined by sequence signals in pre-mRNA and a group of polyadenylation factors. To reveal rice poly(A) signals at a genome level, we constructed a dataset of 55 742 authenticated poly(A) sites and characterized the poly(A) signals. This resulted in identifying the typical tripartite cis-elements, including FUE, NUE and CE, as previously observed in Arabidopsis. The average size of the 3'-UTR was 289 nucleotides. When mapped to the genome, however, 15% of these poly(A) sites were found to be located in the currently annotated intergenic regions. Moreover, an extensive alternative polyadenylation profile was evident where 50% of the genes analyzed had more than one unique poly(A) site (excluding microheterogeneity sites), and 13% had four or more poly(A) sites. About 4% of the analyzed genes possessed alternative poly(A) sites at their introns, 5'-UTRs, or protein coding regions. The authenticity of these alternative poly(A) sites was partially confirmed using MPSS data. Analysis of nucleotide profile and signal patterns indicated that there may be a different set of poly(A) signals for those poly(A) sites found in the coding regions. Based on the features of rice poly(A) signals, an updated algorithm termed PASS-Rice was designed to predict poly(A) sites.
| S-EPMC2396415 | biostudies-literature
Project description:BACKGROUND: One of the major open challenges in next generation sequencing (NGS) is the accurate identification of structural variants such as insertions and deletions (indels). Current methods for indel calling assign scores to different types of evidence or counter-evidence for the presence of an indel, such as the number of split read alignments spanning the boundaries of a deletion candidate or reads that map within a putative deletion. Candidates with a score above a manually defined threshold are then predicted to be true indels. As a consequence, structural variants detected in this manner contain many false positives. RESULTS: Here, we present a machine learning based method which is able to discover and distinguish true from false indel candidates in order to reduce the false positive rate. Our method identifies indel candidates using a discriminative classifier based on features of split read alignment profiles and trained on true and false indel candidates that were validated by Sanger sequencing. We demonstrate the usefulness of our method with paired-end Illumina reads from 80 genomes of the first phase of the 1001 Genomes Project ( http://www.1001genomes.org) in Arabidopsis thaliana. CONCLUSION: In this work we show that indel classification is a necessary step to reduce the number of false positive candidates. We demonstrate that missing classification may lead to spurious biological interpretations. The software is available at: http://agkb.is.tuebingen.mpg.de/Forschung/SV-M/.
| S-EPMC3614465 | biostudies-other
Project description:This SuperSeries is composed of the SubSeries listed below.
2024-03-21 | GSE212425 | GEO
Project description:BackgroundAlternative polyadenylation (APA) has emerged as a pervasive mechanism that contributes to the transcriptome complexity and dynamics of gene regulation. The current tsunami of whole genome poly(A) site data from various conditions generated by 3' end sequencing provides a valuable data source for the study of APA-related gene expression. Cluster analysis is a powerful technique for investigating the association structure among genes, however, conventional gene clustering methods are not suitable for APA-related data as they fail to consider the information of poly(A) sites (e.g., location, abundance, number, etc.) within each gene or measure the association among poly(A) sites between two genes.ResultsHere we proposed a computational framework, named PASCCA, for clustering genes from replicated or unreplicated poly(A) site data using canonical correlation analysis (CCA). PASCCA incorporates multiple layers of gene expression data from both the poly(A) site level and gene level and takes into account the number of replicates and the variability within each experimental group. Moreover, PASCCA characterizes poly(A) sites in various ways including the abundance and relative usage, which can exploit the advantages of 3' end deep sequencing in quantifying APA sites. Using both real and synthetic poly(A) site data sets, the cluster analysis demonstrates that PASCCA outperforms other widely-used distance measures under five performance metrics including connectivity, the Dunn index, average distance, average distance between means, and the biological homogeneity index. We also used PASCCA to infer APA-specific gene modules from recently published poly(A) site data of rice and discovered some distinct functional gene modules. We have made PASCCA an easy-to-use R package for APA-related gene expression analyses, including the characterization of poly(A) sites, quantification of association between genes, and clustering of genes.ConclusionsBy providing a better treatment of the noise inherent in repeated measurements and taking into account multiple layers of poly(A) site data, PASCCA could be a general tool for clustering and analyzing APA-specific gene expression data. PASCCA could be used to elucidate the dynamic interplay of genes and their APA sites among various biological conditions from emerging 3' end sequencing data to address the complex biological phenomenon.
| S-EPMC6343338 | biostudies-literature
Project description:BACKGROUND:Typical experimental design advice for expression analyses using RNA-seq generally assumes that single-end reads provide robust gene-level expression estimates in a cost-effective manner, and that the additional benefits obtained from paired-end sequencing are not worth the additional cost. However, in many cases (e.g., with Illumina NextSeq and NovaSeq instruments), shorter paired-end reads and longer single-end reads can be generated for the same cost, and it is not obvious which strategy should be preferred. Using publicly available data, we test whether short-paired end reads can achieve more robust expression estimates and differential expression results than single-end reads of approximately the same total number of sequenced bases. RESULTS:At both the transcript and gene levels, 2?×?40 paired-end reads unequivocally provide expression estimates that are more highly correlated with 2?×?125 than 1?×?75 reads; in nearly all cases, those correlations are also greater than for 1?×?125, despite the greater total number of sequenced bases for the latter. Across an array of metrics, differential expression tests based upon 2?×?40 consistently outperform those using 1?×?75. CONCLUSION:Researchers seeking a cost-effective approach for gene-level expression analysis should prefer short paired-end reads over a longer single-end strategy. Short paired-end reads will also give reasonably robust expression estimates and differential expression results at the isoform level.
| S-EPMC7168855 | biostudies-literature
Project description:Complex organisms are able to generate differential gene expression through the same set of DNA sequences in distinct cells. The communication between chromatin and RNA regulates how cells behave in tissues. However, little is known about how chromatin, especially the histone modifications, regulates RNA polyadenylation. Here, we find that FUS is recruited to chromatin by H3K36me3 at gene bodies. Once H3K36me3 is abolished, FUS is dissociated from chromatin to increase the binding with RNA, resulting in increased distal polyadenylation selections that are far from the stop codon. The H3K36me3 recognition of FUS is mediated by the proline residues in ZNF domain, mutations of which lead to reduced chromatin association of FUS, increased RNA binding of FUS, and distal polyadenylation selections. Proline mutation, which corresponds to the mutation in amyotrophic lateral sclerosis, contributes to the hyperactivation of mitochondria and hyperdifferentiation in mouse embryonic stem cells. These findings reveal FUS as an H3K36me3 reader protein that links chromatin-mediated alternative polyadenylation to human disease.
2024-03-21 | GSE212424 | GEO
Project description:Complex organisms are able to generate differential gene expression through the same set of DNA sequences in distinct cells. The communication between chromatin and RNA regulates how cells behave in tissues. However, little is known about how chromatin, especially the histone modifications, regulates RNA polyadenylation. Here, we find that FUS is recruited to chromatin by H3K36me3 at gene bodies. Once H3K36me3 is abolished, FUS is dissociated from chromatin to increase the binding with RNA, resulting in increased distal polyadenylation selections that are far from the stop codon. The H3K36me3 recognition of FUS is mediated by the proline residues in ZNF domain, mutations of which lead to reduced chromatin association of FUS, increased RNA binding of FUS, and distal polyadenylation selections. Proline mutation, which corresponds to the mutation in amyotrophic lateral sclerosis, contributes to the hyperactivation of mitochondria and hyperdifferentiation in mouse embryonic stem cells. These findings reveal FUS as an H3K36me3 reader protein that links chromatin-mediated alternative polyadenylation to human disease.
2024-03-21 | GSE212423 | GEO
Project description:Complex organisms are able to generate differential gene expression through the same set of DNA sequences in distinct cells. The communication between chromatin and RNA regulates how cells behave in tissues. However, little is known about how chromatin, especially the histone modifications, regulates RNA polyadenylation. Here, we find that FUS is recruited to chromatin by H3K36me3 at gene bodies. Once H3K36me3 is abolished, FUS is dissociated from chromatin to increase the binding with RNA, resulting in increased distal polyadenylation selections that are far from the stop codon. The H3K36me3 recognition of FUS is mediated by the proline residues in ZNF domain, mutations of which lead to reduced chromatin association of FUS, increased RNA binding of FUS, and distal polyadenylation selections. Proline mutation, which corresponds to the mutation in amyotrophic lateral sclerosis, contributes to the hyperactivation of mitochondria and hyperdifferentiation in mouse embryonic stem cells. These findings reveal FUS as an H3K36me3 reader protein that links chromatin-mediated alternative polyadenylation to human disease.
2024-03-21 | GSE212422 | GEO
Project description:Expression of mature messenger RNAs (mRNAs) requires appropriate transcription initiation and termination, as well as pre-mRNA processing by capping, splicing, cleavage, and polyadenylation. A core 3'-end processing complex carries out the cleavage and polyadenylation reactions, but many proteins have been implicated in the selection of polyadenylation sites among the multiple alternatives that eukaryotic genes typically have. In recent years, high-throughput approaches to map both the 3'-end processing sites as well as the binding sites of proteins that are involved in the selection of cleavage sites and in the processing reactions have been developed. Here, we review these approaches as well as the insights into the mechanisms of polyadenylation that emerged from genome-wide studies of polyadenylation across a range of cell types and states.
| S-EPMC4282565 | 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