Comprehensive characterization of transcript isoform in mouse retina with ONT long read single-cell RNA sequencing
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1075146 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:The retina, a complex neural tissue, encompasses a vast diversity of over 100 distinct cell types, each characterized by unique features such as morphology, function, location, and transcriptomic profiles. However, the extent of mRNA alternative splicing within individual cell types in the retina remains largely uncharted territory. To bridge this knowledge gap, we employed single-cell RNA sequencing, utilizing both short-read and long-read high-throughput technologies. Our comprehensive analysis profiled the transcriptomes of 29,191 mouse retina cells, resulting in a dataset comprising 1.54 billion Illumina short reads and 1.40 billion Oxford Nanopore long reads. Remarkably, this exploration unveiled a staggering 44,325 transcript isoforms, with 38% of them representing entirely novel discoveries and 17% exhibiting cell-class-specific expression patterns. Intriguingly, while many isoforms were expressed across various cell types, their distribution often displayed variability among them. This research substantially enriches the catalog of transcript isoforms, laying the groundwork for further investigations into the role of alternative splicing in retinal biology and its implications for related diseases. It represents a crucial step toward unraveling the intricacies of retinal function and offers promising insights into the molecular mechanisms underlying retinal disorders.
2024-11-04 | GSE255520 | GEO
Project description:Dynamics and consequences of widespread transcript isoform changes during neuronal differentiation [ONT-Seq]
| PRJNA1027834 | ENA
Project description:Sacharomyces cerevisiae Transcript Isoform mapping (set2)
| PRJNA488283 | ENA
Project description:Analysis of isoform expression dynamics during in vitro neuronal differentiation
2024-04-10 | GSE245324 | GEO
Project description:Static gene expression programs have been extensively characterized in stem cells and mature human cells. However, the dynamics of RNA isoform change upon cell-state transitions during cell differentiation, and the determinants and functional consequences have largely remained unclear. Here, we used an improved model for human neurogenesis in vitro that we show is amenable for systems-wide analyses of gene expression. Our multi-omics analysis reveals that the pronounced alterations in cell morphology correlate strongly with widespread changes in RNA isoform expression. Our approach identifies thousands of new RNA isoforms that are expressed at distinct stages during neurogenesis. RNA isoforms mainly arise from the alternative usage of transcription start sites and poly-adenylation sites as well as the skipping of individual exons during human neurogenesis. The transcript isoform changes can remodel the abundance and functions of protein isoforms. Finally, our study identifies a set of RNA-binding proteins as a likely determinant of differentiation stage-specific global isoform changes.
2024-04-11 | PXD046084 | Pride
Project description:Extensive transcriptional heterogeneity revealed by isoform profiling Application of TIF-Seq (Transcript IsoForm Sequencing) to S.cerevisiae. The method was applied to simultaneously identify the 5' capped mRNA transcription start site and the 3' polyadenylation site in different conditions: WT cells grown in glucose media [ypd, 2 biological replicates (bio) and 3 independent library preparations, technical replicates(lib)], WT cells grown in galactose media [ypgal, 4 biological replicates (bio) and 3 independent library preparations, technical replicates(lib)]. A modified protocol designed to enrich in long mRNA molecules was performed for WT cells grown in glucose media [ypd, 2 biological replicates (bio)] and in galactose media [ypgal, 2 biological replicates (bio)] conditions. Finally, control samples performed with a modified protocol designed to identify non-capped but polyadenylated molecules was performed in WT cells grown both in glucose (nypd) and galactose (nypgal) media.
2013-05-06 | E-GEOD-39128 | biostudies-arrayexpress
Project description:Accurate quantification of transcript isoforms is crucial for understanding gene regulation, functional diversity, and cellular behavior. Existing methods using either short-read (SR) or long-read (LR) RNA sequencing have significant limitations: SR sequencing provides high depth but struggles with isoform deconvolution, while LR sequencing offers isoform resolution at the cost of lower depth, higher noise, and technical biases. Addressing this gap, we introduce Multi-Platform Aggregation and Quantification of Transcripts (MPAQT), a generative model that combines the complementary strengths of different sequencing platforms to achieve state-of-the-art isoform-resolved transcript quantification, as demonstrated by extensive simulations and experimental benchmarks. Applying MPAQT to an in vitro model of human embryonic stem cell differentiation into cortical neurons, followed by machine learning-based modeling of mRNA abundance determinants, reveals the role of untranslated regions (UTRs) in isoform regulation through isoform-specific interactions with RNA-binding proteins that modulate mRNA stability. These findings highlight MPAQT's potential to enhance our understanding of transcriptomic complexity and underline the role of splicing-independent post-transcriptional mechanisms in shaping the isoform and exon usage landscape of the cell.
2024-07-10 | GSE271528 | GEO
Project description:Accurate quantification of transcript isoforms is crucial for understanding gene regulation, functional diversity, and cellular behavior. Existing methods using either short-read (SR) or long-read (LR) RNA sequencing have significant limitations: SR sequencing provides high depth but struggles with isoform deconvolution, while LR sequencing offers isoform resolution at the cost of lower depth, higher noise, and technical biases. Addressing this gap, we introduce Multi-Platform Aggregation and Quantification of Transcripts (MPAQT), a generative model that combines the complementary strengths of different sequencing platforms to achieve state-of-the-art isoform-resolved transcript quantification, as demonstrated by extensive simulations and experimental benchmarks. Applying MPAQT to an in vitro model of human embryonic stem cell differentiation into cortical neurons, followed by machine learning-based modeling of mRNA abundance determinants, reveals the role of untranslated regions (UTRs) in isoform regulation through isoform-specific interactions with RNA-binding proteins that modulate mRNA stability. These findings highlight MPAQT's potential to enhance our understanding of transcriptomic complexity and underline the role of splicing-independent post-transcriptional mechanisms in shaping the isoform and exon usage landscape of the cell.
2024-07-10 | GSE271527 | GEO
Project description:Alternative splicing generates differing RNA isoforms that govern phenotypic complexity of eukaryotes. Its malfunction underlies many diseases, including cancer and cardiovascular diseases. Comparative analysis of RNA isoforms at the genome-wide scale has been difficult. Here, we established an experimental and computational pipeline that accurately quantifies transcript isoforms in their entire length from cDNA sequences with a full-length isoform detection accuracy of 97.6%. We generated a searchable, quantitative human transcriptome annotation with 31,025 known and 5,740 novel transcript isoforms (http://steinmetzlab.embl.de/iBrowser/). By analyzing the isoforms in the presence of RNA Binding Motif Protein 20 (RBM20) mutations associated with aggressive dilated cardiomyopathy (DCM), we identified 121 differentially expressed transcript isoforms in 107 cardiac genes. By establishing an isoform-differential expression test, our approach revealed that 11 of these genes displayed no detectable change in overall RNA expression. However, significant differences in the expression of specific isoforms in these genes was observed. These isoform specific effects demonstrate the need of analyzing RNA isoform expression levels rather than total gene expression levels.
2021-06-16 | E-MTAB-7334 | biostudies-arrayexpress
Project description:To address differences in splicing across brain regions (cerebellum, cortex, hippocampus, and striatum) and sexes, we used long-read Oxford Nanopore Technologies (ONT) RNA sequencing to sequence 40 wild-type mouse brain cDNA libraries from 10 mice and calculated differential expression and transcript usage. We found that there is differential gene expression, differential transcript expression, and differential transcript usage across all brain regions. We found that the brain region with the most differential expression and transcript usage is the cerebellum, potentially driven by differences in cell type composition. Additionally, our findings suggest there is much differential splicing across brain regions and to a lesser extent, within brain regions across sexes.
2024-01-31 | GSE246705 | GEO