Long Read Single-Molecule Real-Time Sequencing Elucidates Transcriptome-Wide Heterogeneity and Complexity in Esophageal Squamous Cells

The Application of Long-Read Sequencing to Cancer

Cancer is a multifaceted disease arising from numerous genomic aberrations that have been identified as a result of advancements in sequencing technologies. While next-generation sequencing (NGS), which uses short reads, has transformed cancer research and diagnostics, it is limited by read length. Third-generation sequencing (TGS), led by the Pacific Biosciences and Oxford Nanopore Technologies platforms, employs long-read sequences, which have marked a paradigm shift in cancer research. Cancer genomes often harbour complex events, and TGS, with its ability to span large genomic regions, has facilitated their characterisation, providing a better understanding of how complex rearrangements affect cancer initiation and progression. TGS has also characterised the entire transcriptome of various cancers, revealing cancer-associated isoforms that could serve as biomarkers or therapeutic targets. Furthermore, TGS has advanced cancer research by improving genome assemblies, detecting complex variants, and providing a more complete picture of transcriptomes and epigenomes. This review focuses on TGS and its growing role in cancer research. We investigate its advantages and limitations, providing a rigorous scientific analysis of its use in detecting previously hidden aberrations missed by NGS. This promising technology holds immense potential for both research and clinical applications, with far-reaching implications for cancer diagnosis and treatment.

FLIBase: a comprehensive repository of full-length isoforms across human cancers and tissues

Regulatory processes at the RNA transcript level play a crucial role in generating transcriptome diversity and proteome composition in human cells, impacting both physiological and pathological states. This study introduces FLIBase (www.FLIBase.org), a specialized database that focuses on annotating full-length isoforms using long-read sequencing techniques. We collected and integrated long-read (351 samples) and short-read (12 469 samples) RNA sequencing data from diverse normal and cancerous human tissues and cells. The current version of FLIBase comprises a total of 983 789 full-length spliced isoforms, identified through long-read sequences and verified using short-read exon-exon splice junctions. Of these, 188 248 isoforms have been annotated, while 795 541 isoforms remain unannotated. By overcoming the limitations of short-read RNA sequencing methods, FLIBase provides an accurate and comprehensive representation of full-length transcripts. These comprehensive annotations empower researchers to undertake various downstream analyses and investigations. Importantly, FLIBase exhibits a significant advantage in identifying a substantial number of previously unannotated isoforms and tumor-specific RNA transcripts. These tumor-specific RNA transcripts have the potential to serve as a source of immunogenic recurrent neoantigens. This remarkable discovery holds tremendous promise for advancing the development of tailored RNA-based diagnostic and therapeutic strategies for various types of human cancer.

Assessing the Expression of Long INterspersed Elements (LINEs) via Long-Read Sequencing in Diverse Human Tissues and Cell Lines

Transposable elements, such as Long INterspersed Elements (LINEs), are DNA sequences that can replicate within genomes. LINEs replicate using an RNA intermediate followed by reverse transcription and are typically a few kilobases in length. LINE activity creates genomic structural variants in human populations and leads to somatic alterations in cancer genomes. Long-read RNA sequencing technologies, including Oxford Nanopore and PacBio, can directly sequence relatively long transcripts, thus providing the opportunity to examine full-length LINE transcripts. This study focuses on the development of a new bioinformatics pipeline for the identification and quantification of active, full-length LINE transcripts in diverse human tissues and cell lines. In our pipeline, we utilized RepeatMasker to identify LINE-1 (L1) transcripts from long-read transcriptome data and incorporated several criteria, such as transcript start position, divergence, and length, to remove likely false positives. Comparisons between cancerous and normal cell lines, as well as human tissue samples, revealed elevated expression levels of young LINEs in cancer, particularly at intact L1 loci. By employing bioinformatics methodologies on long-read transcriptome data, this study demonstrates the landscape of L1 expression in tissues and cell lines.

The transcriptional landscape of endogenous retroelements delineates esophageal adenocarcinoma subtypes

Most cancer types exhibit aberrant transcriptional activity, including derepression of retrotransposable elements (RTEs). However, the degree, specificity and potential consequences of RTE transcriptional activation may differ substantially among cancer types and subtypes. Representing one extreme of the spectrum, we characterize the transcriptional activity of RTEs in cohorts of esophageal adenocarcinoma (EAC) and its precursor Barrett's esophagus (BE) from the OCCAMS (Oesophageal Cancer Clinical and Molecular Stratification) consortium, and from TCGA (The Cancer Genome Atlas). We found exceptionally high RTE inclusion in the EAC transcriptome, driven primarily by transcription of genes incorporating intronic or adjacent RTEs, rather than by autonomous RTE transcription. Nevertheless, numerous chimeric transcripts straddling RTEs and genes, and transcripts from stand-alone RTEs, particularly KLF5- and SOX9-controlled HERVH proviruses, were overexpressed specifically in EAC. Notably, incomplete mRNA splicing and EAC-characteristic intronic RTE inclusion was mirrored by relative loss of the respective fully-spliced, functional mRNA isoforms, consistent with compromised cellular fitness. Defective RNA splicing was linked with strong transcriptional activation of a HERVH provirus on Chr Xp22.32 and defined EAC subtypes with distinct molecular features and prognosis. Our study defines distinguishable RTE transcriptional profiles of EAC, reflecting distinct underlying processes and prognosis, thus providing a framework for targeted studies.

Splicing factor TRA2A contributes to esophageal cancer progression via a noncanonical role in lncRNA m6 A methylation

Transformer 2 alpha homolog (TRA2A), a member of the serine/arginine-rich splicing factor family, has been shown to control mRNA splicing in development and cancers. However, it remains unclear whether TRA2A is involved in lncRNA regulation. In the present study, we found that TRA2A was upregulated and correlated with poor prognosis in esophageal cancer. Downregulation of TRA2A suppressed the tumor growth in xenograft nude mice. Epitranscriptomic microarray showed that depletion of TRA2A affected global lncRNA methylation similarly to the key m⁶ A methyltransferase, METTL3, by silencing. MeRIP-qPCR, RNA pull-down, CLIP analyses, and stability assays indicated that ablation of TRA2A reduced m⁶ A-modification of the oncogenic lncRNA MALAT1, thus inducing structural alterations and reduced stability. Furthermore, Co-IP experiments showed TRA2A directly interacted with METTL3 and RBMX, which also affected the writer KIAA1429 expression. Knockdown of TRA2A inhibited cell proliferation in a manner restored by RBMX/KIAA1429 overexpression. Clinically, MALAT1, RBMX, and KIAA1429 were prognostic factors of worse survival in ESCA patients. Structural similarity-based virtual screening in FDA-approved drugs repurposed nebivolol, a β₁ -adrenergic receptor antagonist, as a potent compound to suppress the proliferation of esophageal cancer cells. Cellular thermal shift and RIP assay indicated that nebivolol may compete with MALAT1 to bind TRA2A. In conclusion, our study revealed the noncanonical function of TRA2A, which coordinates with multiple methylation proteins to promote oncogenic MALAT1 during ESCA carcinogenesis.

DELongSeq for efficient detection of differential isoform expression from long-read RNA-seq data

Conventional gene expression quantification approaches, such as microarrays or quantitative PCR, have similar variations of estimates for all genes. However, next-generation short-read or long-read sequencing use read counts to estimate expression levels with much wider dynamic ranges. In addition to the accuracy of estimated isoform expression, efficiency, which measures the degree of estimation uncertainty, is also an important factor for downstream analysis. Instead of read count, we present DELongSeq, which employs information matrix of EM algorithm to quantify uncertainty of isoform expression estimates to improve estimation efficiency. DELongSeq uses random-effect regression model for the analysis of DE isoform, in that within-study variation represents variable precision in isoform expression estimation and between-study variation represents variation in isoform expression levels across samples. More importantly, DELongSeq allows 1 case versus 1 control comparison of differential expression, which has specific application scenarios in precision medicine (such as before versus after treatment, or tumor versus stromal tissues). Through extensive simulations and analysis of several RNA-Seq datasets, we show that the uncertainty quantification approach is computationally reliable, and can improve the power of differential expression (DE) analysis of isoforms or genes. In summary, DELongSeq allows for efficient detection of differential isoform/gene expression from long-read RNA-Seq data.

Epigenetic and transcriptional activation of the secretory kinase FAM20C as an oncogene in glioma

Gliomas are the most prevalent and aggressive malignancies of the nervous system. Previous bioinformatic studies have revealed the crucial role of the secretory pathway kinase FAM20C in the prediction of glioma invasion and malignancy. However, little is known about the pathogenesis of FAM20C in the regulation of glioma. Here, we construct the full-length transcriptome atlas in paired gliomas and observe that 22 genes are upregulated by full-length transcriptome and differential APA analysis. Analysis of ATAC-seq data reveals that both FAM20C and NPTN are the hub genes with chromatin openness and differential expression. Further, in vitro and in vivo studies suggest that FAM20C stimulates the proliferation and metastasis of glioma cells. Meanwhile, NPTN, a novel cancer suppressor gene, counteracts the function of FAM20C by inhibiting both the proliferation and migration of glioma. The blockade of FAM20C by neutralizing antibodies results in the regression of xenograft tumors. Moreover, MAX, BRD4, MYC, and REST are found to be the potential trans-active factors for the regulation of FAM20C. Taken together, our results uncover the oncogenic role of FAM20C in glioma and shed new light on the treatment of glioma by abolishing FAM20C.

Recent advances in cancer fusion transcript detection

Extensive investigation of gene fusions in cancer has led to the discovery of novel biomarkers and therapeutic targets. To date, most studies have neglected chromosomal rearrangement-independent fusion transcripts and complex fusion structures such as double or triple-hop fusions, and fusion-circRNAs. In this review, we untangle fusion-related terminology and propose a classification system involving both gene and transcript fusions. We highlight the importance of RNA-level fusions and how long-read sequencing approaches can improve detection and characterization. Moreover, we discuss novel bioinformatic tools to identify fusions in long-read sequencing data and strategies to experimentally validate and functionally characterize fusion transcripts.

Binding Pattern Reconstructions of FGF-FGFR Budding-Inducing Signaling in Reef-Building Corals

Reef-building corals play an important role in marine ecosystems. However, owing to climate change, ocean acidification, and predation by invasive crown-of-thorns starfish, these corals are declining. As marine animals comprise polyps, reproduction by asexual budding is pivotal in scleractinian coral growth. The fibroblast growth factor (FGF) signaling pathway is essential in coral budding morphogenesis. Here, we sequenced the full-length transcriptomes of four common and frequently dominant reef-building corals and screened out the budding-related FGF and FGFR genes. Thereafter, three-dimensional (3D) models of FGF and FGFR proteins as well as FGF-FGFR binding models were reconstructed. Based on our findings, the FGF8-FGFR3 binding models in Pocillopora damicornis, Montipora capricornis, and Acropora muricata are typical receptor tyrosine kinase-signaling pathways that are similar to the Kringelchen (FGFR) in hydra. However, in P. verrucosa, FGF8 is not the FGFR3 ligand, which is found in other hydrozoan animals, and its FGFR3 must be activated by other tyrosine kinase-type ligands. Overall, this study provides background on the potentially budding propagation signaling pathway activated by the applications of biological agents in reef-building coral culture that could aid in the future restoration of coral reefs.

Long non-coding RNAs associated with infection and vaccine-induced immunity

The immune system responds to infection or vaccination through a dynamic and complex process that involves several molecular and cellular factors. Among these factors, long non-coding RNAs (lncRNAs) have emerged as significant players in all areas of biology, particularly in immunology. Most of the mammalian genome is transcribed in a highly regulated manner, generating a diversity of lncRNAs that impact the differentiation and activation of immune cells and affect innate and adaptive immunity. Here, we have reviewed the range of functions and mechanisms of lncRNAs in response to infectious disease, including pathogen recognition, interferon (IFN) response, and inflammation. We describe examples of lncRNAs exploited by pathogenic agents during infection, which indicate that lncRNAs are a fundamental part of the arms race between hosts and pathogens. We also discuss lncRNAs potentially implicated in vaccine-induced immunity and present examples of lncRNAs associated with the antibody response of subjects receiving Influenza or Yellow Fever vaccines. Elucidating the widespread involvement of lncRNAs in the immune system will improve our understanding of the factors affecting immune response to different pathogenic agents, to better prevent and treat disease.

Accurate transcriptome assembly by Nanopore RNA sequencing reveals novel functional transcripts in hepatocellular carcinoma

The long reads of Nanopore sequencing permit accurate transcript assembly and ease in discovering novel transcripts with potentially important functions in cancers. The wide adoption of Nanopore sequencing for transcript quantification, however, is largely limited by high costs. To address this issue, we developed a bioinformatics software, NovelQuant, that can specifically quantify long-read-assembled novel transcripts with short-read sequencing data. Nanopore Direct RNA Sequencing was carried out on three hepatocellular carcinoma (HCC) patients' tumor, matched portal vein tumor thrombus, and peritumor to reconstruct the HCC transcriptome. Then, based on the reconstructed transcriptome, NovelQuant was applied on Illumina RNA sequencing data of 59 HCC patients' tumor and paired peritumor to quantify novel transcripts. Our further analysis revealed 361 novel transcripts dysregulated in HCC and that 101 of them were significantly associated with prognosis. There were 19 novel prognostic transcripts predicted to be long noncoding RNAs (lncRNAs), and some of them had regulatory targets that were reported to be associated with HCC. Additionally, 42 novel prognostic transcripts were predicted to be protein-coding mRNAs, and many of them could be involved in xenobiotic metabolism. Moreover, the tumor-suppressive roles of two representative novel prognostic transcripts, CDO1-novel (lncRNA) and CYP2A6-novel (protein-coding mRNA), were further functionally validated during HCC progression. Overall, the current study shows a possibility of combining long- and short-read sequencing to explore functionally important novel transcripts in HCC with accuracy and cost-efficiency, which expands the pool of molecular biomarkers that could enhance our understanding of the molecular mechanisms of HCC.

LIQA: long-read isoform quantification and analysis

Long-read RNA sequencing (RNA-seq) technologies can sequence full-length transcripts, facilitating the exploration of isoform-specific gene expression over short-read RNA-seq. We present LIQA to quantify isoform expression and detect differential alternative splicing (DAS) events using long-read direct mRNA sequencing or cDNA sequencing data. LIQA incorporates base pair quality score and isoform-specific read length information in a survival model to assign different weights across reads, and uses an expectation-maximization algorithm for parameter estimation. We apply LIQA to long-read RNA-seq data from the Universal Human Reference, acute myeloid leukemia, and esophageal squamous epithelial cells and demonstrate its high accuracy in profiling alternative splicing events.