Long-read and short-read isoform sequencing in breast cancer
Ontology highlight
ABSTRACT:
PROVIDER: EGAS00001004819 | EGA |
REPOSITORIES: EGA
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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.
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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.
| EGAD00001006596 | EGA
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.
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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.
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Project description:Transcription and translation are intertwined processes where mRNA isoforms are crucial intermediaries. However, methodological limitations in analyzing translation at the mRNA isoform level have impaired our ability to comprehensively establish links between the full-length transcripts and the translatome. This has left gaps in our understanding of critical biological processes, regulatory mechanisms, and disease progression. To address this, we develop an integrated computational and experimental framework called long-read Ribo-STAMP (LR-Ribo-STAMP). LR-Ribo-STAMP capitalizes on advancements in long-read sequencing and RNA-base editing-mediated technologies to simultaneously and scalably profile translation and transcription at both gene and mRNA isoform levels for the first time. In this report, we show agreement between gene-level translation profiles obtained with LR-Ribo-STAMP and those from previously validated short-read Ribo-STAMP data in unperturbed cells. At the mRNA isoform level, we show that LR-Ribo-STAMP successfully profiles translation in unperturbed cells and links mRNA isoforms and regulatory features, such as upstream ORFs (uORFs) and regulatory sequences, to translation measurements. We further demonstrate the method’s effectiveness in profiling disease models by profiling translation at gene and isoform levels in a triple-negative breast cancer cell line under normoxia and hypoxia. Here, we find that LR-Ribo-STAMP effectively delineates orthogonal transcriptional and translation shifts between conditions at gene and isoform levels. At the isoform level, LR-Ribo-STAMP uniquely identifies key regulatory elements and shifts in mRNA isoform transcription that correlate with changes in translational, providing an example of insight that can inform the development of novel therapeutics. Overall, LR-Ribo-STAMP is a significant advancement in translation methods and can have profound implications for basic research and clinical applications.
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Project description:Long-read sequencing technologies such as Iso-Seq (PacBio Inc.) generate highly accurate sequences of full-length mRNA transcript isoforms. Long-read transcriptomics may be especially useful in the context of lymphocyte functional plasticity as it relates to human health and disease. However, no long-read isoform-aware reference transcriptomes of human circulating lymphocytes seem to be publicly available despite being valuable as benchmarks in a variety of transcriptomic studies. To begin to fill this gap, we purified four lymphocyte subsets (CD4 T, CD8 T, NK, and Pan B cells) from the peripheral blood of a healthy male donor and obtained high-quality RNA (RIN>8) for PacBio Iso-Seq analysis and parallel RNA-Seq analysis.
2022-09-16 | GSE202327 | GEO
Project description:Single-cell RNA sequencing analysis has recently provided snapshots of gene expression of specific cell types and enabled cell types classification within an heterogenous population. As well as transcriptional changes, alternative splicing events and modifications of components of splicing machinery actively contributes in shaping cellular phenotype as well as ageing process and diseases occurence. Current high-throughput single-cell RNA sequencing methods may lack information on cell-specific isoform expression, missing key aspects of cell biology. In the present work we introduce a novel approach using the 10X Genomics Chromium to generate short-read (Illumina) and long-read (Pacific Biosciences Sequel II) RNA-sequencing libraries from the same single cells. This approach produced single cell parallel transcriptional and splicing profiling that demonstrates for the first time cell-type specific isoform expression and alterations at transcriptional levels associated with ageing in haematopoietic stem and progenitor cells
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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
Project description:Deregulated gene expression is a hallmark of cancer, however most studies to date have analyzed short-read RNA-sequencing data with inherent limitations. Here, we combine PacBio long-read isoform sequencing (Iso-Seq) and Illumina paired-end short read RNA sequencing to comprehensively survey the transcriptome of gastric cancer (GC), a leading cause of global cancer mortality. We performed full-length transcriptome analysis across 10 GC cell lines covering four major GC molecular subtypes (chromosomal unstable, Epstein-Barr positive, genome stable and microsatellite unstable). We identify 60,239 non-redundant full-length transcripts, of which >66% are novel compared to current transcriptome databases. Novel isoforms are more likely to be cell-line and subtype specific, expressed at lower levels with larger number of exons, with longer isoform/coding sequence lengths. Most novel isoforms utilize an alternate first exon, and compared to other alternative splicing categories are expressed at higher levels and exhibit higher variability. Collectively, we observe alternate promoter usage in 25% of detected genes, with the majority (84.2%) of known/novel promoter pairs exhibiting potential changes in their coding sequences. Mapping these alternate promoters to TCGA GC samples, we identify several cancer-associated isoforms, including novel variants of oncogenes. Tumor-specific transcript isoforms tend to alter protein coding sequences to a larger extent than other isoforms. Analysis of outcome data suggests that novel isoforms may impart additional prognostic information. Our results provide a rich resource of full-length transcriptome data for deeper studies of GC and other gastrointestinal malignancies.
2021-02-02 | PXD023373 | Pride