Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Accurate isoform quantification by joint short- and long-read RNA-sequencing

ABSTRACT: This SuperSeries is composed of the SubSeries listed below.

ORGANISM(S): Homo sapiens

PROVIDER: GSE271530 | GEO | 2024/07/10

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Accurate isoform quantification by joint short- and long-read RNA-sequencing [short reads]

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

Accurate isoform quantification by joint short- and long-read RNA-sequencing [long reads]

2024-07-10 | GSE271527 | GEO

Accurate long-read transcript discovery and quantification at single-cell resolution with Isosceles

Project description:This SuperSeries is composed of the SubSeries listed below.

2023-11-27 | GSE248118 | GEO

LocusMasterTE: long-read assisted short-read TE quantification [short]

Project description:With an ability to compromise genome integrity, transposable elements (TEs) have significant associations with human diseases. Short-read sequencing has been used to study the expression of TEs; however, the highly repetitive nature of these elements makes multimapping a critical issue. Here we implement LocusMasterTE, an improved quantification method by integrating long-read sequencing. Introducing computed transcript per million(TPM) counts from long-read sequencing as prior distribution during Expectation-Maximization(EM) model in short-read TE quantification, multi-mapped reads are re-assigned to correct expression values. Based on simulated short reads, LocusMasterTE outperforms current quantitative approaches and is significantly favorable in capturing newly inserted TEs. We also verified that TEs quantified by LocusMasterTE clearly related to euchromatins and heterochromatins in cell line samples. With LocusMasterTE we anticipate that more accurate quantification can be performed, allowing novel functions of TEs to be uncovered.

2023-09-01 | GSE225380 | GEO

LIQA: long-read isoform quantification and analysis.

Project description: Not available

| S-EPMC8212471 | biostudies-literature

LocusMasterTE: long-read assisted short-read RNA-seq TE quantification [long]

2023-09-01 | GSE225377 | GEO

MSIQ: JOINT MODELING OF MULTIPLE RNA-SEQ SAMPLES FOR ACCURATE ISOFORM QUANTIFICATION.

Project description: Not available

| S-EPMC5935499 | biostudies-literature

LoopSeq Synthetic Long Read Sequencing Uncovers Isoform Modulation in the progression of Colon Cancer

Project description:This SuperSeries is composed of the SubSeries listed below.

2021-05-05 | GSE155921 | GEO

Long-read and short-read isoform sequencing in breast cancer

Project description:The goal of this project was to perform long-read RNA sequencing (LR-seq, PacBio) in combination with short-read RNA-seq for systematic characterization of the isoform diversity in primary breast tumor samples. We sequenced the full-length transcriptomes of 26 breast tumors and 4 normal breast samples.

| EGAS00001004819 | EGA

Ultralow-input single-tube linked-read library method enables short-read second-generation sequencing systems to routinely generate highly accurate and economical long-range sequencing information.

Project description: Not available

| S-EPMC7370886 | biostudies-literature