Nanopore long-read RNAseq reveals widespread transcriptional variation among the surface receptors of individual B cells

Isoform-resolution single-cell RNA sequencing reveals the transcriptional panorama of adult Baoshan pig testis cells

BACKGROUND

As the primary organ of the male reproductive system, the testis facilitates spermatogenesis and androgen secretion. Due to the complexity of spermatogenesis, elucidating cellular heterogeneity and gene expression dynamics within the porcine testis is critical for advancing reproductive biology. Nevertheless, the cellular composition and regulatory mechanisms of porcine testes remain insufficiently characterized. In this study, we applied integrated long-read (Nanopore) and short-read (Illumina) scRNA-seq to Baoshan pig testes, establishing a comprehensive transcriptional profile to delineate cellular heterogeneity and molecular regulation.

RESULTS

Through systematic analysis of testicular architecture and the temporal progression of spermatogenesis, we characterized 11,520 single cells and 23,402 genes, delineating germ cell developmental stages: proliferative-phase spermatogonia (SPG), early-stage spermatocytes (Early SPC) and late-stage spermatocytes (Late SPC) during meiosis, and spermiogenic-phase round spermatids (RS) followed by elongating/elongated spermatids (ES), culminating in mature spermatozoa (Sperm). We further identified nine distinct testicular cell types, with germ cells spanning all developmental stages and somatic components comprising Sertoli cells, macrophages, and peritubular myoid cells as microenvironmental constituents, revealing the cellular heterogeneity of testicular tissue and dynamic characteristics of spermatogenesis. We obtained the dynamic expression changes of 16 vital marker genes during spermatogenesis and performed immunofluorescence validation on 7 marker genes. Gene ontology analysis revealed that germ cells at various stages were involved in specific biological processes, while cell communication networks highlighted eight pivotal signaling pathways, including MIF, NRG, WNT, VEGF, BMP, CCL, PARs, and ENHO pathways. Long-read sequencing further captured the full integrity and diversity of RNA transcripts, identifying 60% of the novel annotated isoforms and revealing that FSM isoforms exhibited longer transcript lengths, longer coding sequences, longer open reading frames, and a great number of exons, suggesting the complexity of isoforms within the testicular microenvironment.

CONCLUSIONS

Our results provide insight into the cellular heterogeneity, intercellular communication, and gene expression/transcript diversity in porcine testes, and offer a valuable resource for understanding the molecular mechanisms of porcine spermatogenesis.

Sequencing technologies to measure translation in single cells

Translation is one of the most energy-intensive processes in a cell and, accordingly, is tightly regulated. Genome-wide methods to measure translation and the translatome and to study the complex regulation of protein synthesis have enabled unprecedented characterization of this crucial step of gene expression. However, technological limitations have hampered our understanding of translation control in multicellular tissues, rare cell types and dynamic cellular processes. Recent optimizations, adaptations and new techniques have enabled these measurements to be made at single-cell resolution. In this Progress, we discuss single-cell sequencing technologies to measure translation, including ribosome profiling, ribosome affinity purification and spatial translatome methods.

A novel splicing graph allows a direct comparison between exon-based and splice junction-based approaches to alternative splicing detection

There are primarily two computational approaches to alternative splicing (AS) detection using short reads: splice junction-based and exon-based approaches. Despite their shared goal of addressing the same biological problem, these approaches have not been reconciled before. We devised a novel graph structure and algorithm aimed at mapping between the exonic parts and splicing events detected by the two different methods. Through simulations, we demonstrated disparities in sensitivity and specificity between splice junction-based and exon-based methods. When applied to empirical data, there were large discrepancies in the results, suggesting that the methods are complementary. With the discrepancies localized to individual events and exonic parts, we were able to gain insights into the strengths and weaknesses inherent in each approach. Finally, we integrated the results to generate a comprehensive list of both common and unique AS events detected by both methodologies.

Heterogeneous and novel transcript expression in single cells of patient-derived clear cell renal cell carcinoma organoids

Splicing is often dysregulated in cancer, leading to alterations in the expression of canonical and alternatively spliced isoforms. We used the multiplexed arrays sequencing (MAS-seq) protocol of PacBio to sequence full-length transcripts in patient-derived organoid (PDO) cells of clear cell renal cell carcinoma (ccRCC). The sequencing revealed a heterogeneous dysregulation of splicing across 2599 single ccRCC cells. The majority of novel transcripts could be removed with stringent filtering criteria. The remaining 31,531 transcripts (36.6% of the 86,182 detected transcripts on average) were previously uncharacterized. In contrast to known transcripts, many of the novel transcripts have cell-specific expression. Novel transcripts common to ccRCC cells belong to genes involved in ccRCC-related pathways, such as hypoxia and oxidative phosphorylation. A novel transcript of the ccRCC-related gene nicotinamide N-methyltransferase is validated using PCR. Moreover, >50% of novel transcripts possess a predicted complete protein-coding open reading frame. An analysis of the most dominant transcript-switching events between ccRCC and non-ccRCC cells shows many switching events that are cell- and sample-specific, underscoring the heterogeneity of alternative splicing events in ccRCC. Overall, our study elucidates the intricate transcriptomic architecture of ccRCC, underlying its aggressive phenotype and providing insights into its molecular complexity.

A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines

The human genome contains instructions to transcribe more than 200,000 RNAs. However, many RNA transcripts are generated from the same gene, resulting in alternative isoforms that are highly similar and that remain difficult to quantify. To evaluate the ability to study RNA transcript expression, we profiled seven human cell lines with five different RNA-sequencing protocols, including short-read cDNA, Nanopore long-read direct RNA, amplification-free direct cDNA and PCR-amplified cDNA sequencing, and PacBio IsoSeq, with multiple spike-in controls, and additional transcriptome-wide N6-methyladenosine profiling data. We describe differences in read length, coverage, throughput and transcript expression, reporting that long-read RNA sequencing more robustly identifies major isoforms. We illustrate the value of the SG-NEx data to identify alternative isoforms, novel transcripts, fusion transcripts and N6-methyladenosine RNA modifications. Together, the SG-NEx data provide a comprehensive resource enabling the development and benchmarking of computational methods for profiling complex transcriptional events at isoform-level resolution.

Fraxinellone-mediated targeting of cathepsin B leakage from lysosomes induces ferroptosis in fibroblasts to inhibit hypertrophic scar formation

BACKGROUND

Hypertrophic scar (HS) is a common fibrotic skin disorder characterized by the excessive deposition of extracellular matrix (ECM). Fibroblasts are the most important effector cells involved in HS formation. Currently no satisfactory treatment has been developed.

METHODS

The impact of fraxinellone (FRA) on the proliferation and migration capacity of human hypertrophic scar-derived fibroblasts (HSFs) was assessed by EdU proliferation, wound healing and transwell assays. Quantitative real-time PCR (qRT‒PCR), Western blot (WB), immunofluorescence staining and collagen gel contraction assays were performed to evaluate the collagen production and activation capacity of HSFs. Oxford Nanopore Technologies long-read RNA sequencing (ONT long-read RNA-seq) revealed the occurrence of ferroptosis in HSF and ferroptosis executioner-cathepsin B (CTSB). The mechanisms underlying FRA-induced HSF ferroptosis were examined through fluorescence staining, qRT‒PCR, WB and molecular docking study. The therapeutic efficacy of FRA was further validated in vivo using a rabbit ear scar model.

RESULTS

FRA treatment significantly suppressed the proliferation, migration, collagen production and activation capacity of HSFs. ONT long-read RNA-seq discovered that FRA modulated the expression of transcripts related to ferroptosis and lysosomes. Mechanistically, FRA treatment reduced the protein expression level of glutathione peroxidase 4 (GPX4) and induced the release of CTSB from lysosomes into the cytoplasm. CTSB further induced ferroptosis via spermidine/spermine-N1-acetyltransferase (SAT1)-mediated lipid peroxidation, mitochondrial damage and mitogen-activated protein kinase (MAPK) signalling pathway activation, eventually affecting the function of HSFs. Moreover, FRA treatment attenuated the formation of HS in rabbit ears via CTSB-mediated ferroptosis. The antifibrotic effects of FRA were abrogated by pretreatment with a CTSB inhibitor (CA-074-me).

CONCLUSIONS

This study reveals that FRA ameliorates HS by inducing CTSB leakage from lysosomes, causing SAT1-mediated lipid peroxidation, mitochondrial damage and MAPK signalling pathway activation, thus mediating HSF ferroptosis. Therefore, FRA could be a promising therapeutic agent for treating HS.

Neuronal cell adhesion molecule (NRCAM) variant defined by microexon skipping is an essential, antigenically distinct, and targetable proteoform in high-grade glioma

To overcome the paucity of known tumor-specific surface antigens in pediatric high-grade glioma (pHGG), we contrasted splicing patterns in pHGGs and normal brain samples. Among alternative splicing events affecting extracellular protein domains, the most pervasive alteration was the skipping of ≤30 nucleotide-long microexons. Several of these skipped microexons mapped to L1-IgCAM family members, such as NRCAM . Bulk and single-nuclei short- and long-read RNA-seq revealed uniform skipping of NRCAM microexons 5 and 19 in virtually every pHGG sample. Importantly, the Δex5Δex19 (but not the full-length) NRCAM proteoform was essential for pHGG cell migration and invasion in vitro and tumor growth in vivo. We developed a monoclonal antibody selective for Δex5Δex19 NRCAM and demonstrated that "painting" of pHGG cells with this antibody enables killing by T cells armed with an FcRI-based universal immune receptor. Thus, pHGG-specific NRCAM and possibly other L1-IgCAM proteoforms are promising and highly selective targets for adoptive immunotherapies.

Statement of significance

Existing targets for chimeric antigen receptors (CAR)-armed T cells are often shared by CNS tumors and normal tissues, creating the potential for on-target/off-tumor toxicities. Here we demonstrate that in CNS tumors of glial origin, cell adhesion molecules have alternatively spliced proteoforms, which could be targeted by highly selective therapeutic antibodies.

Advances in forensic genetics: Exploring the potential of long read sequencing

DNA-based technologies have been used in forensic practice since the mid-1980s. While PCR-based STR genotyping using Capillary Electrophoresis remains the gold standard for generating DNA profiles in routine casework worldwide, the research community is continually seeking alternative methods capable of providing additional information to enhance discrimination power or contribute with new investigative leads. Oxford Nanopore Technologies (ONT) and PacBio third-generation sequencing have revolutionized the field, offering real-time capabilities, single-molecule resolution, and long-read sequencing (LRS). ONT, the pioneer of nanopore sequencing, uses biological nanopores to analyze nucleic acids in real-time. Its devices have revolutionized sequencing and may represent an interesting alternative for forensic research and routine casework, given that it offers unparalleled flexibility in a portable size: it enables sequencing approaches that range widely from PCR-amplified short target regions (e.g., CODIS STRs) to PCR-free whole transcriptome or even ultra-long whole genome sequencing. Despite its higher error rate compared to Illumina sequencing, it can significantly improve accuracy in read alignment against a reference genome or de novo genome assembly. This is achieved by generating long contiguous sequences that correctly assemble repetitive sections and regions with structural variation. Moreover, it allows real-time determination of DNA methylation status from native DNA without the need for bisulfite conversion. LRS enables the analysis of thousands of markers at once, providing phasing information and eliminating the need for multiple assays. This maximizes the information retrieved from a single invaluable sample. In this review, we explore the potential use of LRS in different forensic genetics approaches.

Steering research on mRNA splicing in cancer towards clinical translation

Splicing factors are affected by recurrent somatic mutations and copy number variations in several types of haematologic and solid malignancies, which is often seen as prima facie evidence that splicing aberrations can drive cancer initiation and progression. However, numerous spliceosome components also 'moonlight' in DNA repair and other cellular processes, making their precise role in cancer difficult to pinpoint. Still, few would deny that dysregulated mRNA splicing is a pervasive feature of most cancers. Correctly interpreting these molecular fingerprints can reveal novel tumour vulnerabilities and untapped therapeutic opportunities. Yet multiple technological challenges, lingering misconceptions, and outstanding questions hinder clinical translation. To start with, the general landscape of splicing aberrations in cancer is not well defined, due to limitations of short-read RNA sequencing not adept at resolving complete mRNA isoforms, as well as the shallow read depth inherent in long-read RNA-sequencing, especially at single-cell level. Although individual cancer-associated isoforms are known to contribute to cancer progression, widespread splicing alterations could be an equally important and, perhaps, more readily actionable feature of human cancers. This is to say that in addition to 'repairing' mis-spliced transcripts, possible therapeutic avenues include exacerbating splicing aberration with small-molecule spliceosome inhibitors, targeting recurrent splicing aberrations with synthetic lethal approaches, and training the immune system to recognize splicing-derived neoantigens.

Challenges in identifying mRNA transcript starts and ends from long-read sequencing data

Long-read sequencing (LRS) technologies have the potential to revolutionize scientific discoveries in RNA biology through the comprehensive identification and quantification of full-length mRNA isoforms. Despite great promise, challenges remain in the widespread implementation of LRS technologies for RNA-based applications, including concerns about low coverage, high sequencing error, and robust computational pipelines. Although much focus has been placed on defining mRNA exon composition and structure with LRS data, less careful characterization has been done of the ability to assess the terminal ends of isoforms, specifically, transcription start and end sites. Such characterization is crucial for completely delineating full mRNA molecules and regulatory consequences. However, there are substantial inconsistencies in both start and end coordinates of LRS reads spanning a gene, such that LRS reads often fail to accurately recapitulate annotated or empirically derived terminal ends of mRNA molecules. Here, we describe the specific challenges of identifying and quantifying mRNA terminal ends with LRS technologies and how these issues influence biological interpretations of LRS data. We then review recent experimental and computational advances designed to alleviate these problems, with ideal use cases for each approach. Finally, we outline anticipated developments and necessary improvements for the characterization of terminal ends from LRS data.

Understanding isoform expression by pairing long-read sequencing with single-cell and spatial transcriptomics

RNA isoform diversity, produced via alternative splicing, and alternative usage of transcription start and poly(A) sites, results in varied transcripts being derived from the same gene. Distinct isoforms can play important biological roles, including by changing the sequences or expression levels of protein products. The first single-cell approaches to RNA sequencing-and later, spatial approaches-which are now widely used for the identification of differentially expressed genes, rely on short reads and offer the ability to transcriptomically compare different cell types but are limited in their ability to measure differential isoform expression. More recently, long-read sequencing methods have been combined with single-cell and spatial technologies in order to characterize isoform expression. In this review, we provide an overview of the emergence of single-cell and spatial long-read sequencing and discuss the challenges associated with the implementation of these technologies and interpretation of these data. We discuss the opportunities they offer for understanding the relationships between the distinct variable elements of transcript molecules and highlight some of the ways in which they have been used to characterize isoforms' roles in development and pathology. Single-nucleus long-read sequencing, a special case of the single-cell approach, is also discussed. We attempt to cover both the limitations of these technologies and their significant potential for expanding our still-limited understanding of the biological roles of RNA isoforms.

A comprehensive review of the applications of RNA sequencing in celiac disease research

RNA sequencing (RNA-seq) has undergone substantial advancements in recent decades and has emerged as a vital technique for profiling the transcriptome. The transition from bulk sequencing to single-cell and spatial approaches has facilitated the achievement of higher precision at cell resolution. It provides valuable biological knowledge about individual immune cells and aids in the discovery of the molecular mechanisms that contribute to the development of autoimmune diseases. Celiac disease (CeD) is an autoimmune disorder characterized by a strong immune response to gluten consumption. RNA-seq has led to significantly advanced research in multiple fields, particularly in CeD research. It has been instrumental in studies involving comparative transcriptomics, nutritional genomics and wheat research, cancer research in the context of CeD, genetic and noncoding RNA-mediated epigenetic insights, disease monitoring and biomarker discovery, regulation of mitochondrial functions, therapeutic target identification and drug mechanism of action, dietary factors, immune cell profiling and the immune landscape. This review offers a comprehensive examination of recent RNA-seq technology research in the field of CeD, highlighting future challenges and opportunities for its application.

NanoTrans: an integrated computational framework for comprehensive transcriptome analysis with nanopore direct RNA sequencing

Nanopore direct RNA sequencing (DRS) provides the direct access to native RNA strands with full-length information, shedding light on rich qualitative and quantitative properties of gene expression profiles. Here with NanoTrans, we present an integrated computational framework that comprehensively covers all major DRS-based application scopes, including isoform clustering and quantification, poly(A) tail length estimation, RNA modification profiling, and fusion gene detection. In addition to its merit in providing such a streamlined one-stop solution, NanoTrans also shines in its workflow-orientated modular design, batch processing capability, all-in-one tabular and graphic report output, as well as automatic installation and configuration supports. Finally, by applying NanoTrans to real DRS datasets of yeast, Arabidopsis, as well as human embryonic kidney and cancer cell lines, we further demonstrate its utility, effectiveness, and efficacy across a wide range of DRS-based application settings.

The alternative splicing landscape of infarcted mouse heart identifies isoform level therapeutic targets

Alternative splicing is an important process that contributes to highly diverse transcripts and protein products, which can affect the development of disease in various organisms. Cardiovascular disease (CVD) represents one of the greatest global threats to humans, particularly acute myocardial infarction (MI) and subsequent ischemic reperfusion (IR) injury, which involve complex transcriptomic changes in heart tissues associated with metabolic reshaping and immunological response. In this study, we used a newly developed ONT full-length transcriptomic approach and performed transcript-resolved differential expression profiling in murine models of MI and IR. We built an analytical pipeline to reliably identify and quantify alternative splicing products (isoforms), expanding on the currently available catalog of isoforms described in mice. The updated alternative splicing landscape included transcripts, genes, and pathways that were differentially regulated during IR and MI. Our study establishes a pipeline to profile highly diverse isoforms using state-of-the-art long-read sequencing, builds a landscape of alternative splicing in the mouse heart during MI and IR.

Simultaneous profiling of RNA isoforms and chromatin accessibility of single cells of human retinal organoids

Single-cell multi-omics sequencing is a powerful approach to analyze complex mechanisms underlying neuronal development and regeneration. However, current methods lack the ability to simultaneously profile RNA alternative splicing and chromatin accessibility at the single-cell level. We develop a technique, single-cell RNA isoform and chromatin accessibility sequencing (scRICA-seq), which demonstrates higher sensitivity and cost-effectiveness compared to existing methods. scRICA-seq can profile both isoforms and chromatin accessibility for up to 10,000 single cells in a single run. Applying this method to human retinal organoids, we construct a multi-omic cell atlas and reveal associations between chromatin accessibility, isoform expression of fate-determining factors, and alternative splicing events in their binding sites. This study provides insights into integrating epigenetics, transcription, and RNA splicing to elucidate the mechanisms underlying retinal neuronal development and fate determination.

Estimates of Sequences with Ultralong and Short CDR3s in the Bovine IgM B Cell Receptor Repertoire Using the Long-read Oxford Nanopore MinION Platform

Cattle produce Abs with an H chain ultralong CDR3 (40-70 aa). These Abs have been shown to have features such as broad neutralization of viruses and are investigated as human therapeutics. A common issue in sequencing the bovine BCR repertoire is the sequence length required to capture variable (V) and isotype gene information. This study aimed to assess the use of Oxford Nanopore Technologies' MinION platform to perform IgM BCR repertoire sequencing to assess variation in the percentage of ultralong CDR3s among dairy cattle. Blood was collected from nine Holstein heifers. B cells were isolated using magnetic bead-based separation, RNA was extracted, and IgM+ transcripts were amplified using PCR and sequenced using a MinION R10.4 flow cell. The distribution of CDR3 lengths was trimodal, and the percentage of ultralong CDR3s ranged among animals from 2.32 to 20.13% in DNA sequences and 1.56% to 17.02% in productive protein sequences. V segment usage varied significantly among heifers. Segment IGHV1-7, associated with ultralong CDR3s, was used in 5.8-24.2% of sequences; usage was positively correlated with ultralong CDR3 production (r = 0.99, p < 0.01). To our knowledge, this is the first study to sequence the bovine BCR repertoire using Oxford Nanopore Technologies and demonstrates the potential for cost-efficient long-read repertoire sequencing in cattle without assembly. Findings from this study support literature describing the distribution of length and percentage of ultralong CDR3s. Future studies will investigate changes in the bovine BCR repertoire associated with age, antigenic exposure, and genetics.

Long-Read MDM4 Sequencing Reveals Aberrant Isoform Landscape in Metastatic Melanomas

MDM4 is upregulated in the majority of melanoma cases and has been described as a "key therapeutic target in cutaneous melanoma". Numerous isoforms of MDM4 exist, with few studies examining their specific expression in human tissues. The changes in splicing of MDM4 during human melanomagenesis are critical to p53 activity and represent potential therapeutic targets. Compounding this, studies relying on short reads lose "connectivity" data, so full transcripts are frequently only inferred from the presence of splice junction reads. To address this problem, long-read nanopore sequencing was utilized to read the entire length of transcripts. Here, MDM4 transcripts, both alternative and canonical, are characterized in a pilot cohort of human melanoma specimens. RT-PCR was first used to identify the presence of novel splice junctions in these specimens. RT-qPCR then quantified the expression of major MDM4 isoforms observed during sequencing. The current study both identifies and quantifies MDM4 isoforms present in melanoma tumor samples. In the current study, we observed high expression levels of MDM4-S, MDM4-FL, MDM4-A, and the previously undescribed Ensembl transcript MDM4-209. A novel transcript lacking both exons 6 and 9 is observed and named MDM4-A/S for its resemblance to both MDM4-A and MDM4-S isoforms.

Single-cell long-read targeted sequencing reveals transcriptional variation in ovarian cancer

Single-cell RNA sequencing predominantly employs short-read sequencing to characterize cell types, states and dynamics; however, it is inadequate for comprehensive characterization of RNA isoforms. Long-read sequencing technologies enable single-cell RNA isoform detection but are hampered by lower throughput and unintended sequencing of artifacts. Here we develop Single-cell Targeted Isoform Long-Read Sequencing (scTaILoR-seq), a hybridization capture method which targets over a thousand genes of interest, improving the median number of on-target transcripts per cell by 29-fold. We use scTaILoR-seq to identify and quantify RNA isoforms from ovarian cancer cell lines and primary tumors, yielding 10,796 single-cell transcriptomes. Using long-read variant calling we reveal associations of expressed single nucleotide variants (SNVs) with alternative transcript structures. Phasing of SNVs across transcripts enables the measurement of allelic imbalance within distinct cell populations. Overall, scTaILoR-seq is a long-read targeted RNA sequencing method and analytical framework for exploring transcriptional variation at single-cell resolution.

An age-progressive platelet differentiation path from hematopoietic stem cells causes exacerbated thrombosis

Platelet dysregulation is drastically increased with advanced age and contributes to making cardiovascular disorders the leading cause of death of elderly humans. Here, we reveal a direct differentiation pathway from hematopoietic stem cells into platelets that is progressively propagated upon aging. Remarkably, the aging-enriched platelet path is decoupled from all other hematopoietic lineages, including erythropoiesis, and operates as an additional layer in parallel with canonical platelet production. This results in two molecularly and functionally distinct populations of megakaryocyte progenitors. The age-induced megakaryocyte progenitors have a profoundly enhanced capacity to engraft, expand, restore, and reconstitute platelets in situ and upon transplantation and produce an additional platelet population in old mice. The two pools of co-existing platelets cause age-related thrombocytosis and dramatically increased thrombosis in vivo. Strikingly, aging-enriched platelets are functionally hyper-reactive compared with the canonical platelet populations. These findings reveal stem cell-based aging as a mechanism for platelet dysregulation and age-induced thrombosis.

Advances in single-cell long-read sequencing technologies

With an increase in accuracy and throughput of long-read sequencing technologies, they are rapidly being assimilated into the single-cell sequencing pipelines. For transcriptome sequencing, these techniques provide RNA isoform-level information in addition to the gene expression profiles. Long-read sequencing technologies not only help in uncovering complex patterns of cell-type specific splicing, but also offer unprecedented insights into the origin of cellular complexity and thus potentially new avenues for drug development. Additionally, single-cell long-read DNA sequencing enables high-quality assemblies, structural variant detection, haplotype phasing, resolving high-complexity regions, and characterization of epigenetic modifications. Given that significant progress has primarily occurred in single-cell RNA isoform sequencing (scRiso-seq), this review will delve into these advancements in depth and highlight the practical considerations and operational challenges, particularly pertaining to downstream analysis. We also aim to offer a concise introduction to complementary technologies for single-cell sequencing of the genome, epigenome and epitranscriptome. We conclude by identifying certain key areas of innovation that may drive these technologies further and foster more widespread application in biomedical science.

A normalization method that controls for total RNA abundance affects the identification of differentially expressed genes, revealing bias toward morning-expressed responses

RNA-Sequencing is widely used to investigate changes in gene expression at the transcription level in plants. Most plant RNA-Seq analysis pipelines base the normalization approaches on the assumption that total transcript levels do not vary between samples. However, this assumption has not been demonstrated. In fact, many common experimental treatments and genetic alterations affect transcription efficiency or RNA stability, resulting in unequal transcript abundance. The addition of synthetic RNA controls is a simple correction that controls for variation in total mRNA levels. However, adding spike-ins appropriately is challenging with complex plant tissue, and carefully considering how they are added is essential to their successful use. We demonstrate that adding external RNA spike-ins as a normalization control produces differences in RNA-Seq analysis compared to traditional normalization methods, even between two times of day in untreated plants. We illustrate the use of RNA spike-ins with 3' RNA-Seq and present a normalization pipeline that accounts for differences in total transcriptional levels. We evaluate the effect of normalization methods on identifying differentially expressed genes in the context of identifying the effect of the time of day on gene expression and response to chilling stress in sorghum.

Computational approaches and challenges in the analysis of circRNA data

Circular RNAs (circRNA) are a class of non-coding RNA, forming a single-stranded covalently closed loop structure generated via back-splicing. Advancements in sequencing methods and technologies in conjunction with algorithmic developments of bioinformatics tools have enabled researchers to characterise the origin and function of circRNAs, with practical applications as a biomarker of diseases becoming increasingly relevant. Computational methods developed for circRNA analysis are predicated on detecting the chimeric back-splice junction of circRNAs whilst mitigating false-positive sequencing artefacts. In this review, we discuss in detail the computational strategies developed for circRNA identification, highlighting a selection of tool strengths, weaknesses and assumptions. In addition to circRNA identification tools, we describe methods for characterising the role of circRNAs within the competing endogenous RNA (ceRNA) network, their interactions with RNA-binding proteins, and publicly available databases for rich circRNA annotation.

Improved sensitivity for detection of pathogenic variants in familial NF2-related schwannomatosis

PURPOSE

To determine the impact of additional genetic screening techniques on the rate of detection of pathogenic variants leading to familial NF2-related schwannomatosis.

METHODS

We conducted genetic screening of a cohort of 168 second-generation individuals meeting the clinical criteria for NF2-related schwannomatosis. In addition to the current clinical screening techniques, targeted next-generation sequencing (NGS) and multiplex ligation-dependent probe amplification analysis, we applied additional genetic screening techniques, including karyotype and RNA analysis. For characterisation of a complex structural variant, we also performed long-read sequencing analysis.

RESULTS

Additional genetic analysis resulted in increased sensitivity of detection of pathogenic variants from 87% to 95% in our second-generation NF2-related schwannomatosis cohort. A number of pathogenic variants identified through extended analysis had been previously observed after NGS analysis but had been overlooked or classified as variants of uncertain significance.

CONCLUSION

Our study indicates there is added value in performing additional genetic analysis for detection of pathogenic variants that are difficult to identify with current clinical genetic screening methods. In particular, RNA analysis is valuable for accurate classification of non-canonical splicing variants. Karyotype analysis and whole genome sequencing analysis are of particular value for identification of large and/or complex structural variants, with additional advantages in the use of long-read sequencing techniques.

Experimental and analytical pipeline for sub-genomic RNA landscape of coronavirus by Nanopore sequencer

Coronaviruses (CoVs), including severe acute respiratory syndrome coronavirus 2, can infect a variety of mammalian and avian hosts with significant medical and economic consequences. During the life cycle of CoV, a coordinated series of subgenomic RNAs, including canonical subgenomic messenger RNA and non-canonical defective viral genomes (DVGs), are generated with different biological implications. Studies that adopted the Nanopore sequencer (ONT) to investigate the landscape and dynamics of viral RNA subgenomic transcriptomes applied arbitrary bioinformatics parameters without justification or experimental validation. The current study used bovine coronavirus (BCoV), which can be performed under biosafety level 2 for library construction and experimental validation using traditional colony polymerase chain reaction and Sanger sequencing. Four different ONT protocols, including RNA direct and cDNA direct sequencing with or without exonuclease treatment, were used to generate RNA transcriptomic libraries from BCoV-infected cell lysates. Through rigorously examining the k-mer, gap size, segment size, and bin size, the optimal cutoffs for the bioinformatic pipeline were determined to remove the sequence noise while keeping the informative DVG reads. The sensitivity and specificity of identifying DVG reads using the proposed pipeline can reach 82.6% and 99.6% under the k-mer size cutoff of 15. Exonuclease treatment reduced the abundance of RNA transcripts; however, it was not necessary for future library preparation. Additional recovery of clipped BCoV nucleotide sequences with experimental validation expands the landscape of the CoV discontinuous RNA transcriptome, whose biological function requires future investigation. The results of this study provide the benchmarks for library construction and bioinformatic parameters for studying the discontinuous CoV RNA transcriptome.IMPORTANCEFunctional defective viral genomic RNA, containing all the cis-acting elements required for translation or replication, may play different roles in triggering cell innate immune signaling, interfering with the canonical subgenomic messenger RNA transcription/translation or assisting in establishing persistence infection. This study does not only provide benchmarks for library construction and bioinformatic parameters for studying the discontinuous coronavirus RNA transcriptome but also reveals the complexity of the bovine coronavirus transcriptome, whose functional assays will be critical in future studies.

Telomere-specific regulation of TERRA and its impact on telomere stability

TERRA is a class of telomeric repeat-containing RNAs that are expressed from telomeres in multiple organisms. TERRA transcripts play key roles in telomere maintenance and their physiological levels are essential to maintain the integrity of telomeric DNA. Indeed, deregulated TERRA expression or its altered localization can impact telomere stability by multiple mechanisms including fueling transcription-replication conflicts, promoting resection of chromosome ends, altering the telomeric chromatin, and supporting homologous recombination. Therefore, a fine-tuned control of TERRA is important to maintain the integrity of the genome. Several studies have reported that different cell lines express substantially different levels of TERRA. Most importantly, TERRA levels markedly vary among telomeres of a given cell type, indicating the existence of telomere-specific regulatory mechanisms which may help coordinate TERRA functions. TERRA molecules contain distinct subtelomeric sequences, depending on their telomere of origin, which may instruct specific post-transcriptional modifications or mediate distinct functions. In addition, all TERRA transcripts share a repetitive G-rich sequence at their 3' end which can form DNA:RNA hybrids and fold into G-quadruplex structures. Both structures are involved in TERRA functions and can critically affect telomere stability. In this review, we examine the mechanisms controlling TERRA levels and the impact of their telomere-specific regulation on telomere stability. We compare evidence obtained in different model organisms, discussing recent advances as well as controversies in the field. Furthermore, we discuss the importance of DNA:RNA hybrids and G-quadruplex structures in the context of TERRA biology and telomere maintenance.

Single-cell and spatial transcriptomics: Bridging current technologies with long-read sequencing

Single-cell technologies have transformed biomedical research over the last decade, opening up new possibilities for understanding cellular heterogeneity, both at the genomic and transcriptomic level. In addition, more recent developments of spatial transcriptomics technologies have made it possible to profile cells in their tissue context. In parallel, there have been substantial advances in sequencing technologies, and the third generation of methods are able to produce reads that are tens of kilobases long, with error rates matching the second generation short reads. Long reads technologies make it possible to better map large genome rearrangements and quantify isoform specific abundances. This further improves our ability to characterize functionally relevant heterogeneity. Here, we show how researchers have begun to combine single-cell, spatial transcriptomics, and long-read technologies, and how this is resulting in powerful new approaches to profiling both the genome and the transcriptome. We discuss the achievements so far, and we highlight remaining challenges and opportunities.

Noncontiguous operon atlas for the Staphylococcus aureus genome

Bacteria synchronize the expression of genes with related functions by organizing genes into operons so that they are cotranscribed together in a single polycistronic messenger RNA. However, some cellular processes may benefit if the simultaneous production of the operon proteins coincides with the inhibition of the expression of an antagonist gene. To coordinate such situations, bacteria have evolved noncontiguous operons (NcOs), a subtype of operons that contain one or more genes that are transcribed in the opposite direction to the other operon genes. This structure results in overlapping transcripts whose expression is mutually repressed. The presence of NcOs cannot be predicted computationally and their identification requires a detailed knowledge of the bacterial transcriptome. In this study, we used direct RNA sequencing methodology to determine the NcOs map in the Staphylococcus aureus genome. We detected the presence of 18 NcOs in the genome of S. aureus and four in the genome of the lysogenic prophage 80α. The identified NcOs comprise genes involved in energy metabolism, metal acquisition and transport, toxin-antitoxin systems, and control of the phage life cycle. Using the menaquinone operon as a proof of concept, we show that disarrangement of the NcO architecture results in a reduction of bacterial fitness due to an increase in menaquinone levels and a decrease in the rate of oxygen consumption. Our study demonstrates the significance of NcO structures in bacterial physiology and emphasizes the importance of combining operon maps with transcriptomic data to uncover previously unnoticed functional relationships between neighbouring genes.

Challenges in the discovery of tumor-specific alternative splicing-derived cell-surface antigens in glioma

Despite advancements in cancer immunotherapy, solid tumors remain formidable challenges. In glioma, profound inter- and intra-tumoral heterogeneity of antigen landscape hampers therapeutic development. Therefore, it is critical to consider alternative sources to expand the repertoire of targetable (neo-)antigens and improve therapeutic outcomes. Accumulating evidence suggests that tumor-specific alternative splicing (AS) could be an untapped reservoir of antigens. In this study, we investigated tumor-specific AS events in glioma, focusing on those predicted to generate major histocompatibility complex (MHC)-presentation-independent, cell-surface antigens that could be targeted by antibodies and chimeric antigen receptor-T cells. We systematically analyzed bulk RNA-sequencing datasets comparing 429 tumor samples (from The Cancer Genome Atlas) and 9166 normal tissue samples (from the Genotype-Tissue Expression project), and identified 13 AS events in 7 genes predicted to be expressed in more than 10% of the patients, including PTPRZ1 and BCAN, which were corroborated by an external RNA-sequencing dataset. Subsequently, we validated our predictions and elucidated the complexity of the isoforms using full-length transcript amplicon sequencing on patient-derived glioblastoma cells. However, analyses of the RNA-sequencing datasets of spatially mapped and longitudinally collected clinical tumor samples unveiled remarkable spatiotemporal heterogeneity of the candidate AS events. Furthermore, proteomics analysis did not reveal any peptide spectra matching the putative antigens. Our investigation illustrated the diverse characteristics of the tumor-specific AS events and the challenges of antigen exploration due to their notable spatiotemporal heterogeneity and elusive nature at the protein levels. Redirecting future efforts toward intracellular, MHC-presented antigens could offer a more viable avenue.

Oarfish: Enhanced probabilistic modeling leads to improved accuracy in long read transcriptome quantification

Motivation

Long read sequencing technology is becoming an increasingly indispensable tool in genomic and transcriptomic analysis. In transcriptomics in particular, long reads offer the possibility of sequencing full-length isoforms, which can vastly simplify the identification of novel transcripts and transcript quantification. However, despite this promise, the focus of much long read method development to date has been on transcript identification, with comparatively little attention paid to quantification. Yet, due to differences in the underlying protocols and technologies, lower throughput (i.e. fewer reads sequenced per sample compared to short read technologies), as well as technical artifacts, long read quantification remains a challenge, motivating the continued development and assessment of quantification methods tailored to this increasingly prevalent type of data.

Results

We introduce a new method and software tool for long read transcript quantification called oarfish. Our model incorporates a novel and innovative coverage score, which affects the conditional probability of fragment assignment in the underlying probabilistic model. We demonstrate that by accounting for this coverage information, oarfish is able to produce more accurate quantification estimates than existing long read quantification methods, particularly when one considers the primary isoforms present in a particular cell line or tissue type.

Availability and Implementation

Oarfish is implemented in the Rust programming language, and is made available as free and open-source software under the BSD 3-clause license. The source code is available at https://www.github.com/COMBINE-lab/oarfish.

Light controls mesophyll-specific post-transcriptional splicing of photoregulatory genes by AtPRMT5

Light plays a central role in plant growth and development, providing an energy source and governing various aspects of plant morphology. Previous study showed that many polyadenylated full-length RNA molecules within the nucleus contain unspliced introns (post-transcriptionally spliced introns, PTS introns), which may play a role in rapidly responding to changes in environmental signals. However, the mechanism underlying post-transcriptional regulation during initial light exposure of young, etiolated seedlings remains elusive. In this study, we used FLEP-seq2, a Nanopore-based sequencing technique, to analyze nuclear RNAs in Arabidopsis (Arabidopsis thaliana) seedlings under different light conditions and found numerous light-responsive PTS introns. We also used single-nucleus RNA sequencing (snRNA-seq) to profile transcripts in single nucleus and investigate the distribution of light-responsive PTS introns across distinct cell types. We established that light-induced PTS introns are predominant in mesophyll cells during seedling de-etiolation following exposure of etiolated seedlings to light. We further demonstrated the involvement of the splicing-related factor A. thaliana PROTEIN ARGININE METHYLTRANSFERASE 5 (AtPRMT5), working in concert with the E3 ubiquitin ligase CONSTITUTIVE PHOTOMORPHOGENIC 1 (COP1), a critical repressor of light signaling pathways. We showed that these two proteins orchestrate light-induced PTS events in mesophyll cells and facilitate chloroplast development, photosynthesis, and morphogenesis in response to ever-changing light conditions. These findings provide crucial insights into the intricate mechanisms underlying plant acclimation to light at the cell-type level.

Highly efficient clustering of long-read transcriptomic data with GeLuster

MOTIVATION

The advancement of long-read RNA sequencing technologies leads to a bright future for transcriptome analysis, in which clustering long reads according to their gene family of origin is of great importance. However, existing de novo clustering algorithms require plenty of computing resources.

RESULTS

We developed a new algorithm GeLuster for clustering long RNA-seq reads. Based on our tests on one simulated dataset and nine real datasets, GeLuster exhibited superior performance. On the tested Nanopore datasets it ran 2.9-17.5 times as fast as the second-fastest method with less than one-seventh of memory consumption, while achieving higher clustering accuracy. And on the PacBio data, GeLuster also had a similar performance. It sets the stage for large-scale transcriptome study in future.

AVAILABILITY AND IMPLEMENTATION

GeLuster is freely available at https://github.com/yutingsdu/GeLuster.

Long-Read DNA and RNA Sequencing to Streamline Clinical Genetic Testing and Reduce Barriers to Comprehensive Genetic Testing

BACKGROUND

Obtaining a precise molecular diagnosis through clinical genetic testing provides information about disease prognosis or progression, allows accurate counseling about recurrence risk, and empowers individuals to benefit from precision therapies or take part in N-of-1 trials. Unfortunately, more than half of individuals with a suspected Mendelian condition remain undiagnosed after a comprehensive clinical evaluation, and the results of any individual clinical genetic test ordered during a typical evaluation may take weeks or months to return. Furthermore, commonly used technologies, such as short-read sequencing, are limited in the types of disease-causing variation they can identify. New technologies, such as long-read sequencing (LRS), are poised to solve these problems.

CONTENT

Recent technical advances have improved accuracy, increased throughput, and decreased the costs of commercially available LRS technologies. This has resolved many historical concerns about the use of LRS in the clinical environment and opened the door to widespread clinical adoption of LRS. Here, we review LRS technology, how it has been used in the research setting to clarify complex variants or identify disease-causing variation missed by prior clinical testing, and how it may be used clinically in the near future.

SUMMARY

LRS is unique in that, as a single data source, it has the potential to replace nearly every other clinical genetic test offered today. When analyzed in a stepwise fashion, LRS will simplify laboratory processes, reduce barriers to comprehensive genetic testing, increase the rate of genetic diagnoses, and shorten the amount of time required to make a molecular diagnosis.

Technologies to Study Genetics and Molecular Pathways

Over the last few decades, the study of congenital heart disease (CHD) has benefited from various model systems and the development of molecular biological techniques enabling the analysis of single gene as well as global effects. In this chapter, we first describe different models including CHD patients and their families, animal models ranging from invertebrates to mammals, and various cell culture systems. Moreover, techniques to experimentally manipulate these models are discussed. Second, we introduce cardiac phenotyping technologies comprising the analysis of mouse and cell culture models, live imaging of cardiogenesis, and histological methods for fixed hearts. Finally, the most important and latest molecular biotechniques are described. These include genotyping technologies, different applications of next-generation sequencing, and the analysis of transcriptome, epigenome, proteome, and metabolome. In summary, the models and technologies presented in this chapter are essential to study the function and development of the heart and to understand the molecular pathways underlying CHD.

Long-Read Sequencing Reveals Alternative Splicing-Driven, Shared Immunogenic Neoepitopes Regardless of SF3B1 Status in Uveal Melanoma

Tumor-specific neoepitopes are promising targets in cancer immunotherapy. However, the identification of functional tumor-specific neoepitopes remains challenging. In addition to the most common source, single-nucleotide variants (SNV), alternative splicing (AS) represents another rich source of neoepitopes and can be utilized in cancers with low SNVs such as uveal melanoma (UM). UM, the most prevalent adult ocular malignancy, has poor clinical outcomes due to a lack of effective therapies. Recent studies have revealed the promise of harnessing tumor neoepitopes to treat UM. Previous studies have focused on neoepitope targets associated with mutations in splicing factor 3b subunit 1 (SF3B1), a key splicing factor; however, little is known about the neoepitopes that are commonly shared by patients independent of SF3B1 status. To identify the AS-derived neoepitopes regardless of SF3B1 status, we herein used a comprehensive nanopore long-read-sequencing approach to elucidate the landscape of AS and novel isoforms in UM. We also performed high-resolution mass spectrometry to further validate the presence of neoepitope candidates and analyzed their structures using the AlphaFold2 algorithm. We experimentally evaluated the antitumor effects of these neoepitopes and found they induced robust immune responses by stimulating interferon (IFN)γ production and activating T cell-based UM tumor killing. These results provide novel insights into UM-specific neoepitopes independent of SF3B1 and lay the foundation for developing therapies by targeting these actionable neoepitopes.

Challenges in the discovery of tumor-specific alternative splicing-derived cell-surface antigens in glioma

Background

Despite advancements in cancer immunotherapy, solid tumors remain formidable challenges. In glioma, profound inter-and intra-tumoral heterogeneity of antigen landscape hampers therapeutic development. Therefore, it is critical to consider alternative sources to expand the repertoire of targetable (neo-)antigens and improve therapeutic outcomes. Accumulating evidence suggests that tumor-specific alternative splicing (AS) could be an untapped reservoir of neoantigens.

Results

In this study, we investigated tumor-specific AS events in glioma, focusing on those predicted to generate major histocompatibility complex (MHC)-presentation-independent, cell-surface neoantigens that could be targeted by antibodies and chimeric antigen receptor (CAR)-T cells. We systematically analyzed bulk RNA-sequencing datasets comparing 429 tumor samples (from The Cancer Genome Atlas [TCGA]) and 9,166 normal tissue samples (from the Genotype-Tissue Expression project [GTEx]), and identified 13 AS events in 7 genes predicted to be expressed in more than 10% of the patients, including PTPRZ1 and BCAN , which were corroborated by an external RNA-sequencing dataset. Subsequently, we validated our predictions and elucidated the complexity of the isoforms using full-length transcript amplicon sequencing on patient-derived glioblastoma cells. However, analyses of the RNA-sequencing datasets of spatially mapped and longitudinally collected clinical tumor samples unveiled remarkable spatiotemporal heterogeneity of the candidate AS events. Furthermore, proteomics analysis did not reveal any peptide spectra matching the putative neoantigens.

Conclusions

Our investigation illustrated the diverse characteristics of the tumor-specific AS events and the challenges of antigen exploration due to their notable spatiotemporal heterogeneity and elusive nature at the protein levels. Redirecting future efforts toward intracellular, MHC-presented antigens could offer a more viable avenue.

Benchmarking long-read RNA-sequencing analysis tools using in silico mixtures

The lack of benchmark data sets with inbuilt ground-truth makes it challenging to compare the performance of existing long-read isoform detection and differential expression analysis workflows. Here, we present a benchmark experiment using two human lung adenocarcinoma cell lines that were each profiled in triplicate together with synthetic, spliced, spike-in RNAs (sequins). Samples were deeply sequenced on both Illumina short-read and Oxford Nanopore Technologies long-read platforms. Alongside the ground-truth available via the sequins, we created in silico mixture samples to allow performance assessment in the absence of true positives or true negatives. Our results show that StringTie2 and bambu outperformed other tools from the six isoform detection tools tested, DESeq2, edgeR and limma-voom were best among the five differential transcript expression tools tested and there was no clear front-runner for performing differential transcript usage analysis between the five tools compared, which suggests further methods development is needed for this application.

HycDemux: a hybrid unsupervised approach for accurate barcoded sample demultiplexing in nanopore sequencing

DNA barcodes enable Oxford Nanopore sequencing to sequence multiple barcoded DNA samples on a single flow cell. DNA sequences with the same barcode need to be grouped together through demultiplexing. As the number of samples increases, accurate demultiplexing becomes difficult. We introduce HycDemux, which incorporates a GPU-parallelized hybrid clustering algorithm that uses nanopore signals and DNA sequences for accurate data clustering, alongside a voting-based module to finalize the demultiplexing results. Comprehensive experiments demonstrate that our approach outperforms unsupervised tools in short sequence fragment clustering and performs more robustly than current state-of-the-art demultiplexing tools for complex multi-sample sequencing data.

Full-length transcript alterations in human bronchial epithelial cells with U2AF1 S34F mutations

U2AF1 is one of the most recurrently mutated splicing factors in lung adenocarcinoma and has been shown to cause transcriptome-wide pre-mRNA splicing alterations; however, the full-length altered mRNA isoforms associated with the mutation are largely unknown. To better understand the impact U2AF1 has on full-length isoform fate and function, we conducted high-throughput long-read cDNA sequencing from isogenic human bronchial epithelial cells with and without a U2AF1 S34F mutation. We identified 49,366 multi-exon transcript isoforms, more than half of which did not match GENCODE or short-read-assembled isoforms. We found 198 transcript isoforms with significant expression and usage changes relative to WT, only 68% of which were assembled by short reads. Expression of isoforms from immune-related genes is largely down-regulated in mutant cells and without observed splicing changes. Finally, we reveal that isoforms likely targeted by nonsense-mediated decay are down-regulated in U2AF1 S34F cells, suggesting that isoform changes may alter the translational output of those affected genes. Altogether, our work provides a resource of full-length isoforms associated with U2AF1 S34F in lung cells.

Profiling the polyadenylated transcriptome of extracellular vesicles with long-read nanopore sequencing

BACKGROUND

While numerous studies have described the transcriptomes of extracellular vesicles (EVs) in different cellular contexts, these efforts have typically relied on sequencing methods requiring RNA fragmentation, which limits interpretations on the integrity and isoform diversity of EV-targeted RNA populations. It has been assumed that mRNA signatures in EVs are likely to be fragmentation products of the cellular mRNA material, and the extent to which full-length mRNAs are present within EVs remains to be clarified.

RESULTS

Using long-read nanopore RNA sequencing, we sought to characterize the full-length polyadenylated (poly-A) transcriptome of EVs released by human chronic myelogenous leukemia K562 cells. We detected 443 and 280 RNAs that were respectively enriched or depleted in EVs. EV-enriched poly-A transcripts consist of a variety of biotypes, including mRNAs, long non-coding RNAs, and pseudogenes. Our analysis revealed that 10.58% of all EV reads, and 18.67% of all cellular (WC) reads, corresponded to known full-length transcripts, with mRNAs representing the largest biotype for each group (EV = 58.13%, WC = 43.93%). We also observed that for many well-represented coding and non-coding genes, diverse full-length transcript isoforms were present in EV specimens, and these isoforms were reflective-of but often in different ratio compared to cellular samples.

CONCLUSION

This work provides novel insights into the compositional diversity of poly-A transcript isoforms enriched within EVs, while also underscoring the potential usefulness of nanopore sequencing to interrogate secreted RNA transcriptomes.

Long-read sequencing reveals the landscape of aberrant alternative splicing and novel therapeutic target in colorectal cancer

BACKGROUND

Alternative splicing complexity plays a vital role in carcinogenesis and cancer progression. Improved understanding of novel splicing events and the underlying regulatory mechanisms may contribute new insights into developing new therapeutic strategies for colorectal cancer (CRC).

METHODS

Here, we combined long-read sequencing technology with short-read RNA-seq methods to investigate the transcriptome complexity in CRC. By using experiment assays, we explored the function of newly identified splicing isoform TIMP1 Δ4-5. Moreover, a CRISPR/dCasRx-based strategy to induce the TIMP1 exon 4-5 exclusion was introduced to inhibit neoplasm growth.

RESULTS

A total of 90,703 transcripts were identified, of which > 62% were novel compared with current transcriptome annotations. These novel transcripts were more likely to be sample specific, expressed at relatively lower levels with more exons, and oncogenes displayed a characteristic to generate more transcripts in CRC. Clinical outcome data analysis showed that 1472 differentially expressed alternative splicing events (DEAS) were tightly associated with CRC patients' prognosis, and many novel isoforms were likely to be important determinants for patient survival. Among these, newly identified splicing isoform TIMP1 Δ4-5 was significantly downregulated in CRC. Further in vitro and in vivo assays demonstrated that ectopic expression of TIMP1 Δ4-5 significantly suppresses tumor cell growth and metastasis. Serine/arginine-rich splicing factor 1 (SRSF1) acts as a onco-splicing regulator through sustaining the inclusion of TIMP1 exon 4-5. Furthermore, CRISPR/dCasRx-based strategies designed to induce TIMP1 exon 4-5 exclusion have the potential to restrain the CRC growth.

CONCLUSIONS

This data provides a rich resource for deeper studies of gastrointestinal malignancies. Newly identified splicing isoform TIMP1 Δ4-5 plays an important role in mediating CRC progression and may be a potential therapy target in CRC.

Development of Nanopore sequencing-based full-length transcriptome database toward functional genome annotation of the Pacific oyster, Crassostrea gigas

The Pacific oyster (Crassostrea gigas) is a widely cultivated shellfish in the world, while its transcriptome diversity remains less unexplored due to the limitation of short reads. In this study, we used Oxford Nanopore sequencing to develop the full-length transcriptome database of C. gigas. We identified 77,920 full-length transcripts from 21,523 genes, and uncovered 9668 alternative splicing events and 87,468 alternative polyadenylation sites. Notably, a total of 16,721 novel transcripts were annotated in this work. Furthermore, integrative analysis of 25 publicly available RNA-seq datasets revealed the transcriptome diversity involved in post-transcriptional regulation in C. gigas. We further developed a Drupal based webserver, Cgtdb, which can be used for transcriptome visualization, sequence alignment, and functional genome annotation analyses. This work provides valuable resources and a useful tool for integrative analysis of various transcriptome datasets in C. gigas, which will serve as an essential reference for functional annotation of the oyster genome.

Hemin availability induces coordinated DNA methylation and gene expression changes in Porphyromonas gingivalis

Periodontal disease is a chronic inflammatory disease in which the oral pathogen Porphyromonas gingivalis plays an important role. Porphyromonas gingivalis expresses virulence determinants in response to higher hemin concentrations, but the underlying regulatory processes remain unclear. Bacterial DNA methylation has the potential to fulfil this mechanistic role. We characterized the methylome of P. gingivalis, and compared its variation to transcriptome changes in response to hemin availability. Porphyromonas gingivalis W50 was grown in chemostat continuous culture with excess or limited hemin, prior to whole-methylome and transcriptome profiling using Nanopore and Illumina RNA-Seq. DNA methylation was quantified for Dam/Dcm motifs and all-context N6-methyladenine (6mA) and 5-methylcytosine (5mC). Of all 1,992 genes analyzed, 161 and 268 were respectively over- and under-expressed with excess hemin. Notably, we detected differential DNA methylation signatures for the Dam "GATC" motif and both all-context 6mA and 5mC in response to hemin availability. Joint analyses identified a subset of coordinated changes in gene expression, 6mA, and 5mC methylation that target genes involved in lactate utilization and ABC transporters. The results identify altered methylation and expression responses to hemin availability in P. gingivalis, with insights into mechanisms regulating its virulence in periodontal disease. IMPORTANCE DNA methylation has important roles in bacteria, including in the regulation of transcription. Porphyromonas gingivalis, an oral pathogen in periodontitis, exhibits well-established gene expression changes in response to hemin availability. However, the regulatory processes underlying these effects remain unknown. We profiled the novel P. gingivalis epigenome, and assessed epigenetic and transcriptome variation under limited and excess hemin conditions. As expected, multiple gene expression changes were detected in response to limited and excess hemin that reflect health and disease, respectively. Notably, we also detected differential DNA methylation signatures for the Dam "GATC" motif and both all-context 6mA and 5mC in response to hemin. Joint analyses identified coordinated changes in gene expression, 6mA, and 5mC methylation that target genes involved in lactate utilization and ABC transporters. The results identify novel regulatory processes underlying the mechanism of hemin regulated gene expression in P. gingivalis, with phenotypic impacts on its virulence in periodontal disease.

Allele-specific quantification of human leukocyte antigen transcript isoforms by nanopore sequencing

Introduction

While tens of thousands of HLA alleles have been identified by DNA sequencing, the contribution of alternative splicing to HLA diversity is not well characterized. In this study, we sought to determine if long-read sequencing could be used to accurately quantify allele-specific HLA transcripts in primary human lymphocytes.

Methods

cDNA libraries were prepared from peripheral blood lymphocytes from 12 donors and sequenced by nanopore long-read sequencing. HLA reads were aligned to donor-specific reference sequences based on the known type of each donor. Allele-specific exon utilization was calculated as the proportion of reads aligning to each allele containing known exons, and transcript isoforms were quantified based on patterns of exon utilization within individual reads.

Results

Splice variants were rare among class I HLA genes (median exon retention rate 99%-100%), except for several HLA-C alleles with exon 5 spliced out of up to 15% of reads. Splice variants were also rare among class II HLA genes (median exon retention rate 98%-100%), except for HLA-DQB1. Consistent with previous work, exon 5 of HLA-DQB1 was spliced out in alleles with a mutated splice acceptor site at rs28688207. Surprisingly, a 28% loss of exon 5 was also observed in HLA-DQB1 alleles with an intact splice acceptor site at rs28688207.

Discussion

We describe a simple bioinformatic workflow to quantify allele-specific expression of HLA transcript isoforms. Further studies are warranted to characterize the repertoire of HLA transcripts expressed in different cell types and tissues across diverse populations.

Beyond the exome: What's next in diagnostic testing for Mendelian conditions

Despite advances in clinical genetic testing, including the introduction of exome sequencing (ES), more than 50% of individuals with a suspected Mendelian condition lack a precise molecular diagnosis. Clinical evaluation is increasingly undertaken by specialists outside of clinical genetics, often occurring in a tiered fashion and typically ending after ES. The current diagnostic rate reflects multiple factors, including technical limitations, incomplete understanding of variant pathogenicity, missing genotype-phenotype associations, complex gene-environment interactions, and reporting differences between clinical labs. Maintaining a clear understanding of the rapidly evolving landscape of diagnostic tests beyond ES, and their limitations, presents a challenge for non-genetics professionals. Newer tests, such as short-read genome or RNA sequencing, can be challenging to order, and emerging technologies, such as optical genome mapping and long-read DNA sequencing, are not available clinically. Furthermore, there is no clear guidance on the next best steps after inconclusive evaluation. Here, we review why a clinical genetic evaluation may be negative, discuss questions to be asked in this setting, and provide a framework for further investigation, including the advantages and disadvantages of new approaches that are nascent in the clinical sphere. We present a guide for the next best steps after inconclusive molecular testing based upon phenotype and prior evaluation, including when to consider referral to research consortia focused on elucidating the underlying cause of rare unsolved genetic disorders.

ROGUE: an R Shiny app for RNA sequencing analysis and biomarker discovery

BACKGROUND

The growing power and ever decreasing cost of RNA sequencing (RNA-Seq) technologies have resulted in an explosion of RNA-Seq data production. Comparing gene expression values within RNA-Seq datasets is relatively easy for many interdisciplinary biomedical researchers; however, user-friendly software applications increase the ability of biologists to efficiently explore available datasets.

RESULTS

Here, we describe ROGUE (RNA-Seq Ontology Graphic User Environment, https://marisshiny.

RESEARCH

chop.edu/ROGUE/ ), a user-friendly R Shiny application that allows a biologist to perform differentially expressed gene analysis, gene ontology and pathway enrichment analysis, potential biomarker identification, and advanced statistical analyses. We use ROGUE to identify potential biomarkers and show unique enriched pathways between various immune cells.

CONCLUSIONS

User-friendly tools for the analysis of next generation sequencing data, such as ROGUE, will allow biologists to efficiently explore their datasets, discover expression patterns, and advance their research by allowing them to develop and test hypotheses.

Challenges in identifying mRNA transcript starts and ends from long-read sequencing data

Long-read sequencing (LRS) technologies have the potential to revolutionize scientific discoveries in RNA biology, especially by enabling the comprehensive identification and quantification of full length mRNA isoforms. However, inherently high error rates make the analysis of long-read sequencing data challenging. While these error rates have been characterized for sequence and splice site identification, it is still unclear how accurately LRS reads represent transcript start and end sites. Here, we systematically assess the variability and accuracy of mRNA terminal ends identified by LRS reads across multiple sequencing platforms. We find substantial inconsistencies in both the start and end coordinates of LRS reads spanning a gene, such that LRS reads often fail to accurately recapitulate annotated or empirically derived terminal ends of mRNA molecules. To address this challenge, we introduce an approach to condition reads based on empirically derived terminal ends and identified a subset of reads that are more likely to represent full-length transcripts. Our approach can improve transcriptome analyses by enhancing the fidelity of transcript terminal end identification, but may result in lower power to quantify genes or discover novel isoforms. Thus, it is necessary to be cautious when selecting sequencing approaches and/or interpreting data from long-read RNA sequencing.

A current and future perspective on T cell receptor repertoire profiling

T cell receptors (TCR) play a vital role in the immune system's ability to recognize and respond to foreign antigens, relying on the highly polymorphic rearrangement of TCR genes. The recognition of autologous peptides by adaptive immunity may lead to the development and progression of autoimmune diseases. Understanding the specific TCR involved in this process can provide insights into the autoimmune process. RNA-seq (RNA sequencing) is a valuable tool for studying TCR repertoires by providing a comprehensive and quantitative analysis of the RNA transcripts. With the development of RNA technology, transcriptomic data must provide valuable information to model and predict TCR and antigen interaction and, more importantly, identify or predict neoantigens. This review provides an overview of the application and development of bulk RNA-seq and single-cell (SC) RNA-seq to examine the TCR repertoires. Furthermore, discussed here are bioinformatic tools that can be applied to study the structural biology of peptide/TCR/MHC (major histocompatibility complex) and predict antigenic epitopes using advanced artificial intelligence tools.

From words to complete phrases: insight into single-cell isoforms using short and long reads

The profiling of gene expression patterns to glean biological insights from single cells has become commonplace over the last few years. However, this approach overlooks the transcript contents that can differ between individual cells and cell populations. In this review, we describe early work in the field of single-cell short-read sequencing as well as full-length isoforms from single cells. We then describe recent work in single-cell long-read sequencing wherein some transcript elements have been observed to work in tandem. Based on earlier work in bulk tissue, we motivate the study of combination patterns of other RNA variables. Given that we are still blind to some aspects of isoform biology, we suggest possible future avenues such as CRISPR screens which can further illuminate the function of RNA variables in distinct cell populations.