Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “long-read RNA-seq”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

9 recordsLinked to original sources
PubMed2026

NextLongIso: a comprehensive Nextflow pipeline for multi-dimensional long-read RNA-seq analysis.

SUMMARY: Long-read RNA sequencing technologies, including Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT), enable direct characterization of full-length transcripts and transcriptome complexity. However, analysis of long-read RNA-seq data remains fragmented across multiple tools, limiting the ability to obtain a unified view of transcript structure, expression, and regulatory variation in long-read transcriptomes. We present NextLongIso, a scalable and reproducible Nextflow pipeline that enables coordinated analysis of multiple layers of transcript regulation. Rather than focusing solely on transcript reconstruction, NextLongIso integrates transcript discovery with downstream regulatory analyses to jointly characterize alternative splicing, isoform switching, transcript boundary dynamics (including alternative promoters and polyadenylation), and transposable element-associated transcription from both PacBio and ONT datasets. By eliminating complex cross-tool data harmonization, this unified framework facilitates the transition from transcript identification to functional interpretation of transcriptomic variation. AVAILABILITY AND IMPLEMENTATION: NextLongIso is implemented in Nextflow and is freely available at github: https://github.com/YidanSunResearchLab/nf-LongIso.git and Zenodo: https://doi.org/10.5281/zenodo.21049837.

Software↗
PubMed2026

Dysregulation of U12-Type Splicing in Lupus Neutrophils.

OBJECTIVE: Neutrophil dysfunction is a hallmark of systemic lupus erythematosus (SLE), but its molecular basis remains unclear. This study explores transcriptional and posttranscriptional changes in low-density granulocytes (LDGs), a proinflammatory neutrophil subset expanded in SLE, focusing on NADPH oxidase (Nox) function and minor intron splicing. METHODS: LDGs and normal-density granulocytes (NDGs) were isolated from patients with SLE and healthy controls (HCs). CYBA (p22phox) expression was evaluated at transcript and protein levels. Nox activity was measured using luminol assays. Bulk RNA sequencing (RNA-seq) and rMATS software were used to assess alternative splicing, particularly of U12-type intron-containing genes. RESULTS: CYBA expression was reduced in SLE LDGs (n = 11) compared to SLE and HC NDGs (n = 6), with levels resembling those in chronic granulomatous disease neutrophils. SLE LDGs exhibited impaired Nox activity (n = 7 SLE, n = 12 HC). CYBA is a U12 intron-containing gene, and transcriptomic analysis revealed broad down-regulation of this gene class in SLE LDGs, suggesting minor spliceosome dysfunction. rMATS analysis showed increased U12-type intron retention and widespread splicing defects-including exon skipping and mutually exclusive exon use-in genes such as GBP5, MAEA, and STX10. These abnormalities were validated in an independent long-read RNA-seq data set from SLE peripheral blood mononuclear cells. Importantly, splicing disruptions correlated with disease activity and autoantibody profiles. CONCLUSION: Impaired U12-dependent splicing may contribute to neutrophil dysfunction in SLE, potentially via defective oxidative burst and altered immune regulation. These findings highlight the minor spliceosome as a novel player in lupus pathogenesis.

Humans↗
PubMed2025

Improving spliced alignment by modeling splice sites with deep learning.

MOTIVATION: Spliced alignment refers to the alignment of messenger RNA (mRNA) or protein sequences to eukaryotic genomes. It plays a critical role in gene annotation and the study of gene functions. Accurate spliced alignment demands sophisticated modeling of splice sites, but current aligners use simple models, which may affect their accuracy given dissimilar sequences. RESULTS: We implemented minisplice to learn splice signals with a one-dimensional convolutional neural network (1D-CNN) and trained a model with 7,026 parameters for vertebrate and insect genomes. It captures conserved splice signals across phyla and reveals GC-rich introns specific to mammals and birds. We used this model to estimate the empirical splicing probability for every GT and AG in genomes, and modified minimap2 and miniprot to leverage pre-computed splicing probability during alignment. Evaluation on human long-read RNA-seq data and cross-species protein datasets showed our method greatly improves the junction accuracy especially for noisy long RNA-seq reads and proteins of distant homology. AVAILABILITY AND IMPLEMENTATION: https://github.com/lh3/minisplice.

Journal Article↗
PubMed2024

An isoform-resolution transcriptomic atlas of colorectal cancer from long-read single-cell sequencing.

Colorectal cancer (CRC) ranks as the second leading cause of cancer deaths globally. In recent years, short-read single-cell RNA sequencing (scRNA-seq) has been instrumental in deciphering tumor heterogeneities. However, these studies only enable gene-level quantification but neglect alterations in transcript structures arising from alternative end processing or splicing. In this study, we integrated short- and long-read scRNA-seq of CRC samples to build an isoform-resolution CRC transcriptomic atlas. We identified 394 dysregulated transcript structures in tumor epithelial cells, including 299 resulting from various combinations of splicing events. Second, we characterized genes and isoforms associated with epithelial lineages and subpopulations exhibiting distinct prognoses. Among 31,935 isoforms with novel junctions, 330 were supported by The Cancer Genome Atlas RNA-seq and mass spectrometry data. Finally, we built an algorithm that integrated novel peptides derived from open reading frames of recurrent tumor-specific transcripts with mass spectrometry data and identified recurring neoepitopes that may aid the development of cancer vaccines.

Colorectal Neoplasms↗
PubMed2026

Long-read transcriptomics corrects Trichomonas vaginalis intron annotations and refines transcript-end features.

BACKGROUND: Trichomonas vaginalis causes the most prevalent non-viral sexually transmitted infection worldwide. Despite its large genome (181.5 Mb; 36,310 predicted protein-coding genes in NYU_TvagG3_2), intron annotations remain limited and inconsistently validated. A recent short-read RNA-seq study reported 63 putative active introns, but short reads can misassign splice boundaries and cannot resolve complete transcript structures. METHODS: We integrated Oxford Nanopore direct RNA sequencing (DRS), ONT cDNA long-read sequencing, and Illumina RNA-seq to refine intron annotations, transcript-end features, and UTR boundaries in T. vaginalis. Candidate introns were validated by targeted PCR and Sanger sequencing, and representative splicing events were further assessed using public SRA datasets. RESULTS: Starting from 31 historically annotated introns, motif-guided long-read screening and orthogonal validation identified 17 additional validated introns, increasing the curated set to 48 confirmed introns. Among these 17 events, three were previously unrecognized in the current NYU_TvagG3_2 reference annotation. We also corrected five reported loci, including two false-positive introns, two splice-coordinate misannotations, and one gene-sequence error. DRS further supported transcript termination site mapping, UAAA polyadenylation-signal profiling relative to poly(A) addition sites, and single-molecule poly(A)-tail estimation. StringTie mixed-mode assemblies provided updated UTR boundaries for intron-bearing transcripts and transcripts without curated introns. CONCLUSIONS: This study provides a rigorously validated, long-read-refined resource of intron annotations, UTR boundaries, and UAAA-guided transcript-end features for T. vaginalis, together with a reproducible workflow for non-model protists. These refinements improve the current reference annotation and support future studies of functional genomics, parasite biology, pathogenesis, and diagnostic development.

Trichomonas vaginalis↗
PubMed2025

UMI-nea: a fast, robust tool for reference-free UMI deduplication and accurate quantification.

MOTIVATION: One of the key applications of Unique Molecular Identifiers (UMIs) in high-throughput sequencing is to correct for PCR amplification bias and removal of PCR duplicates, thereby improving quantification in DNA-seq and RNA-seq applications. Accurately grouping error-bearing UMIs that originate from the same input molecule through a UMI deduplication method is a critical step in this process. However, many existing UMI deduplication tools rely on simple Hamming distance comparisons or suboptimal clustering algorithms, often resulting in erroneous UMI groupings, particularly in error-prone long-read sequencing or ultra-high-depth short-read sequencing. RESULTS: We introduce UMI-nea, a tool that utilizes Levenshtein distance comparisons and a novel clustering approach to optimize multithreading workflows. Compared against three other indel-aware UMI deduplication tools, UMI-nea achieves more accurate UMI groupings with efficient run time. It demonstrates robust performance across diverse sequencing platforms, depths, and UMI lengths. Additionally, UMI-nea incorporates a data-guided adaptive UMI filter, further enhancing quantification accuracy. AVAILABILITY AND IMPLEMENTATION: UMI-nea is available on github https://github.com/Qiaseq-research/UMI-nea.git or Zenodo https://doi.org/10.5281/zenodo.16745758. Sequencing data are stored at https://qiagenpublic.blob.core.windows.net/umi-nea-datasets/.

High-Throughput Nucleotide Sequencing↗
PubMed2026

Isoform-Level Analysis Reveals Reproducible Early Changes in Transcript Usage During Human Vaccine Responses.

Vaccine-induced transcriptional responses have been extensively characterized at the gene level, but whether vaccination also alters transcript isoform usage remains largely unexplored. Here, we reanalyzed longitudinal whole-blood RNA-seq data from a discovery cohort of mRNA COVID-19 vaccine recipients using the IsoformSwitchAnalyzeR framework and validated the findings in an independent cohort. Key findings were validated by full-length RNA long-read sequencing and extended to four additional vaccine cohorts covering distinct platforms and pathogens. mRNA vaccination induced a rapid and transient wave of differential transcript usage, peaking at 24 h post-vaccination with 131 isoforms significantly altered across 107 genes, before largely resolving by Day 14. Isoform switching events were reproducible across independent cohorts and confirmed by full-length RNA long-read sequencing. Structural annotation of switching transcripts, including RMI2, WARS1, and NT5C3A, revealed changes affecting predicted protein domains and signal peptides. Notably, highly concordant isoform switching patterns were observed across MVA-based SARS-CoV-2, influenza, and Ebola vaccine cohorts and showed dose-dependent modulation. Overall, differential transcript isoform usage is a rapid and transient feature of the early human immune response to vaccination that was observed across multiple vaccine platforms. These findings reveal an underappreciated layer of transcriptional regulation that complements conventional gene-level analyses and warrants integration into future vaccine immunogenicity studies.

Humans↗
PubMed2024

Chromosome-scale assembly with improved annotation provides insights into breed-wide genomic structure and diversity in domestic cats.

INTRODUCTION: Comprehensive genomic resources offer insights into biological features, including traits/disease-related genetic loci. The current reference genome assembly for the domestic cat (Felis catus), Felis_Catus_9.0 (felCat9), derived from sequences of the Abyssinian cat, may inadequately represent the general cat population, limiting the extent of deducible genetic variations. OBJECTIVES: The goal was to develop Anicom American Shorthair 1.0 (AnAms1.0), a reference-grade chromosome-scale cat genome assembly. METHODS: In contrast to prior assemblies relying on Abyssinian cat sequences, AnAms1.0 was constructed from the sequences of more popular American Shorthair breed, which is related to more breeds than the Abyssinian cat. By combining advanced genomics technologies, including PacBio long-read sequencing and Hi-C- and optical mapping data-based sequence scaffolding, we compared AnAms1.0 to existing Felidae genome assemblies (20 scaffolds, scaffolds N50 > 150 Mbp). Homology-based and ab initio gene annotation through Iso-Seq and RNA-Seq was used to identify new coding genes and splice variants. RESULTS: AnAms1.0 demonstrated superior contiguity and accuracy than existing Felidae genome assemblies. Using AnAms1.0, we identified over 1.5 thousand structural variants and 29 million repetitions compared to felCat9. Additionally, we identified > 1,600 novel protein-coding genes. Notably, olfactory receptor structural variants and cardiomyopathy-related variants were identified. CONCLUSION: AnAms1.0 facilitates the discovery of novel genes related to normal and disease phenotypes in domestic cats. The analyzed data are publicly accessible on Cats-I (https://cat.annotation.jp/), which we established as a platform for accumulating and sharing genomic resources to discover novel genetic traits and advance veterinary medicine.

Animals↗
PubMed2026

Long-read sequencing reveals widespread novel splicing and neojunction-derived neoantigens in nasopharyngeal carcinoma.

The widespread transcriptomic diversity driven by alternative splicing (AS) contributes to all hallmarks of cancer and represents a critical source of neoantigens for personalized immunotherapy. However, unlike other major malignancies, the full repertoire of AS in nasopharyngeal carcinoma (NPC) remains underexplored. Here, we employ long-read sequencing (LR-seq) to generate a high-resolution, isoform-level transcriptomic atlas from a cohort of 14 NPC tumor samples and four immortalized nasopharyngeal epithelial cell lines. We identify a substantial number of full-length novel transcripts (22,687; ∼44.38%), which reveal diverse splicing patterns and previously unannotated splicing events. By integrating short-read RNA-seq data to quantify isoform expression, we discover a subset of novel transcripts that are differentially expressed between tumor samples and immortalized nasopharyngeal epithelial cell lines. Furthermore, LR-seq enables precise identification of chimeric readthrough fusion transcripts, such as CLDN15-FIS1 and FOXRED2-TXN2 Finally, we develop a computational framework, tumor-specific splicing neoantigen detection (TS-SNAD), to predict neoantigens originating from novel exon-exon junctions (neojunctions) in tumor-specific novel transcripts. Using this framework, we identify neojunction-derived neoantigens and experimentally validate the immunogenicity of selected HLA-B*40:01-restricted neoantigens. These neojunction-derived peptides constitute a new class of noncanonical neoantigens with significant potential for developing personalized cancer vaccines for NPC.

Humans↗