Comprehensive transcriptome analysis using synthetic long-read sequencing reveals molecular co-association of distant splicing events

Long-read RNA sequencing reveals allele-specific N6-methyladenosine modifications

Long-read sequencing technology enables highly accurate detection of allele-specific RNA expression, providing insights into the effects of genetic variation on splicing and RNA abundance. Furthermore, the ability to directly sequence RNA promises the detection of RNA modifications in tandem with ascertaining the allelic origin of each molecule. Here, we leverage these advantages to determine allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNA. We utilized human and mouse cells with known genetic variants to assign allelic origin of each mRNA molecule combined with a supervised machine learning model to detect read-level m6A modification ratios. Our analyses revealed the importance of sequences adjacent to the DRACH-motif in determining m6A deposition, in addition to allelic differences that directly alter the motif. Moreover, we discovered allele-specific m6A modification (ASM) events with no genetic variants in close proximity to the differentially modified nucleotide, demonstrating the unique advantage of using long reads and surpassing the capabilities of antibody-based short-read approaches. This technological advancement promises to advance our understanding of the role of genetics in determining mRNA modifications.

Targeted DNA-seq and RNA-seq of Reference Samples with Short-read and Long-read Sequencing

Next-generation sequencing (NGS) has revolutionized genomic research by enabling high-throughput, cost-effective genome and transcriptome sequencing accelerating personalized medicine for complex diseases, including cancer. Whole genome/transcriptome sequencing (WGS/WTS) provides comprehensive insights, while targeted sequencing is more cost-effective and sensitive. In comparison to short-read sequencing, which still dominates the field due to high speed and cost-effectiveness, long-read sequencing can overcome alignment limitations and better discriminate similar sequences from alternative transcripts or repetitive regions. Hybrid sequencing combines the best strengths of different technologies for a more comprehensive view of genomic/transcriptomic variations. Understanding each technology's strengths and limitations is critical for translating cutting-edge technologies into clinical applications. In this study, we sequenced DNA and RNA libraries of reference samples using various targeted DNA and RNA panels and the whole transcriptome on both short-read and long-read platforms. This study design enables a comprehensive analysis of sequencing technologies, targeting protocols, and library preparation methods. Our expanded profiling landscape establishes a reference point for assessing current sequencing technologies, facilitating informed decision-making in genomic research and precision medicine.

Comparative transcriptomics identifies genes underlying growth performance of the Pacific black-lipped pearl oyster Pinctada margaritifera

BACKGROUND

In bivalves, the rate at which organisms grow is a major functional trait underlying many aspects of their commercial production. Growth is a highly polygenic trait, which is typically regulated by many genes with small to moderate effects. Due to its complexity, growth variability in such shellfish remains poorly understood. In this study, we aimed to investigate differential gene expression among spat of the pearl oyster Pinctada margaritifera with distinct growth phenotypes.

RESULTS

We selected two groups of P. margaritifera spat belonging to the same F2 cohort based on their growth performance at 5.5 months old. Transcriptome profile analysis identified a total of 394 differentially expressed genes between these Fast-growing (F) and Slow-growing (S) phenotypes. According to functional enrichment analysis, S oysters overexpressed genes associated with stress-pathways and regulation of innate immune responses. In contrast, F oysters up-regulated genes associated with cytoskeleton activity, cell proliferation, and apoptosis. Analysis of genome polymorphism identified 16 single nucleotide polymorphisms (SNPs) significantly associated with the growth phenotypes. SNP effect categorization revealed one SNP identified for high effect and annotated for a stop codon gained mutation. Interestingly, this SNP is located within a gene annotated for scavenger receptor class F member 1 (SRF1), which is known to modulate apoptosis. Our analyses also revealed that all F oysters showed up-regulation for this gene and were homozygous for the stop-codon mutation. Conversely, S oysters had a heterozygous genotype and a reduced expression of this gene.

CONCLUSIONS

Altogether, our findings suggest that differences in growth among the same oyster cohort may be explained by contrasted metabolic allocation between regulatory pathways for growth and the immune system. This study provides a valuable contribution towards our understanding of the molecular components associated with growth performance in the pearl oyster P. margaritifera and bivalves in general.

Single-cell long-read sequencing-based mapping reveals specialized splicing patterns in developing and adult mouse and human brain

RNA isoforms influence cell identity and function. However, a comprehensive brain isoform map was lacking. We analyze single-cell RNA isoforms across brain regions, cell subtypes, developmental time points and species. For 72% of genes, full-length isoform expression varies along one or more axes. Splicing, transcription start and polyadenylation sites vary strongly between cell types, influence protein architecture and associate with disease-linked variation. Additionally, neurotransmitter transport and synapse turnover genes harbor cell-type variability across anatomical regions. Regulation of cell-type-specific splicing is pronounced in the postnatal day 21-to-postnatal day 28 adolescent transition. Developmental isoform regulation is stronger than regional regulation for the same cell type. Cell-type-specific isoform regulation in mice is mostly maintained in the human hippocampus, allowing extrapolation to the human brain. Conversely, the human brain harbors additional cell-type specificity, suggesting gain-of-function isoforms. Together, this detailed single-cell atlas of full-length isoform regulation across development, anatomical regions and species reveals an unappreciated degree of isoform variability across multiple axes.

Mapping medically relevant RNA isoform diversity in the aged human frontal cortex with deep long-read RNA-seq

Determining whether the RNA isoforms from medically relevant genes have distinct functions could facilitate direct targeting of RNA isoforms for disease treatment. Here, as a step toward this goal for neurological diseases, we sequenced 12 postmortem, aged human frontal cortices (6 Alzheimer disease cases and 6 controls; 50% female) using one Oxford Nanopore PromethION flow cell per sample. We identified 1,917 medically relevant genes expressing multiple isoforms in the frontal cortex where 1,018 had multiple isoforms with different protein-coding sequences. Of these 1,018 genes, 57 are implicated in brain-related diseases including major depression, schizophrenia, Parkinson's disease and Alzheimer disease. Our study also uncovered 53 new RNA isoforms in medically relevant genes, including several where the new isoform was one of the most highly expressed for that gene. We also reported on five mitochondrially encoded, spliced RNA isoforms. We found 99 differentially expressed RNA isoforms between cases with Alzheimer disease and controls.

Human brain small extracellular vesicles contain selectively packaged, full-length mRNA

Brain cells release and take up small extracellular vesicles (sEVs) containing bioactive nucleic acids. sEV exchange is hypothesized to contribute to stereotyped spread of neuropathological changes in the diseased brain. We assess mRNA from sEVs of postmortem brain from non-diseased (ND) individuals and those with Alzheimer's disease (AD) using short- and long-read sequencing. sEV transcriptomes are distinct from those of bulk tissue, showing enrichment for genes including mRNAs encoding ribosomal proteins and transposable elements such as human-specific LINE-1 (L1Hs). AD versus ND sEVs show enrichment of inflammation-related mRNAs and depletion of synaptic signaling mRNAs. sEV mRNAs from cultured murine primary neurons, astrocytes, or microglia show similarities to human brain sEVs and reveal cell-type-specific packaging. Approximately 80% of neural sEV transcripts sequenced using long-read sequencing are full length. Motif analyses of sEV-enriched isoforms elucidate RNA-binding proteins that may be associated with sEV loading. Collectively, we show that mRNA in brain sEVs is intact, selectively packaged, and altered in disease.

ScISOr-ATAC reveals convergent and divergent splicing and chromatin specificities between matched cell types across cortical regions, evolution, and in Alzheimer's Disease

Multimodal measurements have become widespread in genomics, however measuring open chromatin accessibility and splicing simultaneously in frozen brain tissues remains unconquered. Hence, we devised Single-Cell-ISOform-RNA sequencing coupled with the Assay-for-Transposase-Accessible-Chromatin (ScISOr-ATAC). We utilized ScISOr-ATAC to assess whether chromatin and splicing alterations in the brain convergently affect the same cell types or divergently different ones. We applied ScISOr-ATAC to three major conditions: comparing (i) the Rhesus macaque (Macaca mulatta) prefrontal cortex (PFC) and visual cortex (VIS), (ii) cross species divergence of Rhesus macaque versus human PFC, as well as (iii) dysregulation in Alzheimer's disease in human PFC. We found that among cortical-layer biased excitatory neuron subtypes, splicing is highly brain-region specific for L3-5/L6 IT_RORB neurons, moderately specific in L2-3 IT_CUX2.RORB neurons and unspecific in L2-3 IT_CUX2 neurons. In contrast, at the chromatin level, L2-3 IT_CUX2.RORB neurons show the highest brain-region specificity compared to other subtypes. Likewise, when comparing human and macaque PFC, strong evolutionary divergence on one molecular modality does not necessarily imply strong such divergence on another molecular level in the same cell type. Finally, in Alzheimer's disease, oligodendrocytes show convergently high dysregulation in both chromatin and splicing. However, chromatin and splicing dysregulation most strongly affect distinct oligodendrocyte subtypes. Overall, these results indicate that chromatin and splicing can show convergent or divergent results depending on the performed comparison, justifying the need for their concurrent measurement to investigate complex systems. Taken together, ScISOr-ATAC allows for the characterization of single-cell splicing and chromatin patterns and the comparison of sample groups in frozen brain samples.

Using long-read CAGE sequencing to profile cryptic-promoter-derived transcripts and their contribution to the immunopeptidome

Recent studies have shown that the noncoding genome can produce unannotated proteins as antigens that induce immune response. One major source of this activity is the aberrant epigenetic reactivation of transposable elements (TEs). In tumors, TEs often provide cryptic or alternate promoters, which can generate transcripts that encode tumor-specific unannotated proteins. Thus, TE-derived transcripts (TE transcripts) have the potential to produce tumor-specific, but recurrent, antigens shared among many tumors. Identification of TE-derived tumor antigens holds the promise to improve cancer immunotherapy approaches; however, current genomics and computational tools are not optimized for their detection. Here we combined CAGE technology with full-length long-read transcriptome sequencing (long-read CAGE, or LRCAGE) and developed a suite of computational tools to significantly improve immunopeptidome detection by incorporating TE and other tumor transcripts into the proteome database. By applying our methods to human lung cancer cell line H1299 data, we show that long-read technology significantly improves mapping of promoters with low mappability scores and that LRCAGE guarantees accurate construction of uncharacterized 5' transcript structure. Augmenting a reference proteome database with newly characterized transcripts enabled us to detect noncanonical antigens from HLA-pulldown LC-MS/MS data. Lastly, we show that epigenetic treatment increased the number of noncanonical antigens, particularly those encoded by TE transcripts, which might expand the pool of targetable antigens for cancers with low mutational burden.

Using deep long-read RNAseq in Alzheimer's disease brain to assess medical relevance of RNA isoform diversity

Due to alternative splicing, human protein-coding genes average over eight RNA isoforms, resulting in nearly four distinct protein coding sequences per gene. Long-read RNAseq (IsoSeq) enables more accurate quantification of isoforms, shedding light on their specific roles. To assess the medical relevance of measuring RNA isoform expression, we sequenced 12 aged human frontal cortices (6 Alzheimer's disease cases and 6 controls; 50% female) using one Oxford Nanopore PromethION flow cell per sample. Our study uncovered 53 new high-confidence RNA isoforms in medically relevant genes, including several where the new isoform was one of the most highly expressed for that gene. Specific examples include WDR4 (61%; microcephaly), MYL3 (44%; hypertrophic cardiomyopathy), and MTHFS (25%; major depression, schizophrenia, bipolar disorder). Other notable genes with new high-confidence isoforms include CPLX2 (10%; schizophrenia, epilepsy) and MAOB (9%; targeted for Parkinson's disease treatment). We identified 1,917 medically relevant genes expressing multiple isoforms in human frontal cortex, where 1,018 had multiple isoforms with different protein coding sequences, demonstrating the need to better understand how individual isoforms from a single gene body are involved in human health and disease, if at all. Exactly 98 of the 1,917 genes are implicated in brain-related diseases, including Alzheimer's disease genes such as APP (Aβ precursor protein; five), MAPT (tau protein; four), and BIN1 (eight). As proof of concept, we also found 99 differentially expressed RNA isoforms between Alzheimer's cases and controls, despite the genes themselves not exhibiting differential expression. Our findings highlight the significant knowledge gaps in RNA isoform diversity and their medical relevance. Deep long-read RNA sequencing will be necessary going forward to fully comprehend the medical relevance of individual isoforms for a "single" gene.

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.

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.

Integrative omics approaches to advance rare disease diagnostics

Over the past decade high-throughput DNA sequencing approaches, namely whole exome and whole genome sequencing became a standard procedure in Mendelian disease diagnostics. Implementation of these technologies greatly facilitated diagnostics and shifted the analysis paradigm from variant identification to prioritisation and evaluation. The diagnostic rates vary widely depending on the cohort size, heterogeneity and disease and range from around 30% to 50% leaving the majority of patients undiagnosed. Advances in omics technologies and computational analysis provide an opportunity to increase these unfavourable rates by providing evidence for disease-causing variant validation and prioritisation. This review aims to provide an overview of the current application of several omics technologies including RNA-sequencing, proteomics, metabolomics and DNA-methylation profiling for diagnostics of rare genetic diseases in general and inborn errors of metabolism in particular.

Identification of Splice Variants and Isoforms in Transcriptomics and Proteomics

Alternative splicing is pivotal to the regulation of gene expression and protein diversity in eukaryotic cells. The detection of alternative splicing events requires specific omics technologies. Although short-read RNA sequencing has successfully supported a plethora of investigations on alternative splicing, the emerging technologies of long-read RNA sequencing and top-down mass spectrometry open new opportunities to identify alternative splicing and protein isoforms with less ambiguity. Here, we summarize improvements in short-read RNA sequencing for alternative splicing analysis, including percent splicing index estimation and differential analysis. We also review the computational methods used in top-down proteomics analysis regarding proteoform identification, including the construction of databases of protein isoforms and statistical analyses of search results. While many improvements in sequencing and computational methods will result from emerging technologies, there should be future endeavors to increase the effectiveness, integration, and proteome coverage of alternative splicing events.

Cardiac splicing as a diagnostic and therapeutic target

Despite advances in therapeutics for heart failure and arrhythmias, a substantial proportion of patients with cardiomyopathy do not respond to interventions, indicating a need to identify novel modifiable myocardial pathobiology. Human genetic variation associated with severe forms of cardiomyopathy and arrhythmias has highlighted the crucial role of alternative splicing in myocardial health and disease, given that it determines which mature RNA transcripts drive the mechanical, structural, signalling and metabolic properties of the heart. In this Review, we discuss how the analysis of cardiac isoform expression has been facilitated by technical advances in multiomics and long-read and single-cell sequencing technologies. The resulting insights into the regulation of alternative splicing - including the identification of cardiac splice regulators as therapeutic targets and the development of a translational pipeline to evaluate splice modulators in human engineered heart tissue, animal models and clinical trials - provide a basis for improved diagnosis and therapy. Finally, we consider how the medical and scientific communities can benefit from facilitated acquisition and interpretation of splicing data towards improved clinical decision-making and patient care.

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.

Cochlear transcript diversity and its role in auditory functions implied by an otoferlin short isoform

Isoforms of a gene may contribute to diverse biological functions. In the cochlea, the repertoire of alternative isoforms remains unexplored. We integrated single-cell short-read and long-read RNA sequencing techniques and identified 236,012 transcripts, 126,612 of which were unannotated in the GENCODE database. Then we analyzed and verified the unannotated transcripts using RNA-seq, RT-PCR, Sanger sequencing, and MS-based proteomics approaches. To illustrate the importance of identifying spliced isoforms, we investigated otoferlin, a key protein involved in synaptic transmission in inner hair cells (IHCs). Upon deletion of the canonical otoferlin isoform, the identified short isoform is able to support normal hearing thresholds but with reduced sustained exocytosis of IHCs, and further revealed otoferlin functions in endocytic membrane retrieval that was not well-addressed previously. Furthermore, we found that otoferlin isoforms are associated with IHC functions and auditory phenotypes. This work expands our mechanistic understanding of auditory functions at the level of isoform resolution.

Splicing complexity as a pivotal feature of alternative exons in mammalian species

BACKGROUND

As a significant process of post-transcriptional gene expression regulation in eukaryotic cells, alternative splicing (AS) of exons greatly contributes to the complexity of the transcriptome and indirectly enriches the protein repertoires. A large number of studies have focused on the splicing inclusion of alternative exons and have revealed the roles of AS in organ development and maturation. Notably, AS takes place through a change in the relative abundance of the transcript isoforms produced by a single gene, meaning that exons can have complex splicing patterns. However, the commonly used percent spliced-in (Ψ) values only define the usage rate of exons, but lose information about the complexity of exons' linkage pattern. To date, the extent and functional consequence of splicing complexity of alternative exons in development and evolution is poorly understood.

RESULTS

By comparing splicing complexity of exons in six tissues (brain, cerebellum, heart, liver, kidney, and testis) from six mammalian species (human, chimpanzee, gorilla, macaque, mouse, opossum) and an outgroup species (chicken), we revealed that exons with high splicing complexity are prevalent in mammals and are closely related to features of genes. Using traditional machine learning and deep learning methods, we found that the splicing complexity of exons can be moderately predicted with features derived from exons, among which length of flanking exons and splicing strength of downstream/upstream splice sites are top predictors. Comparative analysis among human, chimpanzee, gorilla, macaque, and mouse revealed that, alternative exons tend to evolve to an increased level of splicing complexity and higher tissue specificity in splicing complexity. During organ development, not only developmentally regulated exons, but also 10-15% of non-developmentally regulated exons show dynamic splicing complexity.

CONCLUSIONS

Our analysis revealed that splicing complexity is an important metric to characterize the splicing dynamics of alternative exons during the development and evolution of mammals.

Single-cell long-read mRNA isoform regulation is pervasive across mammalian brain regions, cell types, and development

RNA isoforms influence cell identity and function. Until recently, technological limitations prevented a genome-wide appraisal of isoform influence on cell identity in various parts of the brain. Using enhanced long-read single-cell isoform sequencing, we comprehensively analyze RNA isoforms in multiple mouse brain regions, cell subtypes, and developmental timepoints from postnatal day 14 (P14) to adult (P56). For 75% of genes, full-length isoform expression varies along one or more axes of phenotypic origin, underscoring the pervasiveness of isoform regulation across multiple scales. As expected, splicing varies strongly between cell types. However, certain gene classes including neurotransmitter release and reuptake as well as synapse turnover, harbor significant variability in the same cell type across anatomical regions, suggesting differences in network activity may influence cell-type identity. Glial brain-region specificity in isoform expression includes strong poly(A)-site regulation, whereas neurons have stronger TSS regulation. Furthermore, developmental patterns of cell-type specific splicing are especially pronounced in the murine adolescent transition from P21 to P28. The same cell type traced across development shows more isoform variability than across adult anatomical regions, indicating a coordinated modulation of functional programs dictating neural development. As most cell-type specific exons in P56 mouse hippocampus behave similarly in newly generated data from human hippocampi, these principles may be extrapolated to human brain. However, human brains have evolved additional cell-type specificity in splicing, suggesting gain-of-function isoforms. Taken together, we present a detailed single-cell atlas of full-length brain isoform regulation across development and anatomical regions, providing a previously unappreciated degree of isoform variability across multiple scales of the brain.

Dynamic chromatin accessibility tuning by the long noncoding RNA ELDR accelerates chondrocyte senescence and osteoarthritis

Epigenetic reprogramming plays a critical role in chondrocyte senescence during osteoarthritis (OA) pathology, but the underlying molecular mechanisms remain to be elucidated. Here, using large-scale individual datasets and genetically engineered (Col2a1-CreER^T2;Eldr^flox/flox and Col2a1-CreER^T2;ROSA26-LSL-Eldr^+/+ knockin) mouse models, we show that a novel transcript of long noncoding RNA ELDR is essential for the development of chondrocyte senescence. ELDR is highly expressed in chondrocytes and cartilage tissues of OA. Mechanistically, exon 4 of ELDR physically mediates a complex consisting of hnRNPL and KAT6A to regulate histone modifications of the promoter region of IHH, thereby activating hedgehog signaling and promoting chondrocyte senescence. Therapeutically, GapmeR-mediated silencing of ELDR in the OA model substantially attenuates chondrocyte senescence and cartilage degradation. Clinically, ELDR knockdown in cartilage explants from OA-affected individuals decreased the expression of senescence markers and catabolic mediators. Taken together, these findings uncover an lncRNA-dependent epigenetic driver in chondrocyte senescence, highlighting that ELDR could be a promising therapeutic avenue for OA.

Full-length transcriptome from different life stages of cobia (Rachycentron canadum, Rachycentridae)

Cobia (Rachycentron canadum, Rachycentridae) is one of the prospective species for mariculture. The transcriptome-based study on cobia was hampered by an inadequate reference genome and a lack of full-length cDNAs. We used a long-read based sequencing technology (PacBio Sequel II Iso-Seq3 SMRT) to obtain complete transcriptome sequences from larvae, juveniles, and various tissues of adult cobia, and a single SMRTcell generated 99 gigabytes of data and 51,205,946,694 bases. A total of 8609435, 7441673 and 9140164 subreads were generated from the larval, juvenile, and adult sample pools, with mean sub-read lengths of 2109.9, 1988.2 and 1996.2 bp, respectively. All samples were combined to increase transcript recovery and clustered into 35661 high-quality reads. This is the first report on a full-length transcriptome from R. canadum. Our results illustrate a significant increase in the identified amount of cobia LncRNAs and alternatively spliced transcripts, which will help improve genome annotation. Furthermore, this information will be beneficial for nutrigenomics and functional studies on cobia and other commercially important mariculture species.

Multi-omics approach to identifying isoform variants as therapeutic targets in cancer patients

Cancer-specific alternatively spliced events (ASE) play a role in cancer pathogenesis and can be targeted by immunotherapy, oligonucleotide therapy, and small molecule inhibition. However, identifying actionable ASE targets remains challenging due to the uncertainty of its protein product, structure impact, and proteoform (protein isoform) function. Here we argue that an integrated multi-omics profiling strategy can overcome these challenges, allowing us to mine this untapped source of targets for therapeutic development. In this review, we will provide an overview of current multi-omics strategies in characterizing ASEs by utilizing the transcriptome, proteome, and state-of-art algorithms for protein structure prediction. We will discuss limitations and knowledge gaps associated with each technology and informatics analytics. Finally, we will discuss future directions that will enable the full integration of multi-omics data for ASE target discovery.

Bridging the splicing gap in human genetics with long-read RNA sequencing: finding the protein isoform drivers of disease

Aberrant splicing underlies many human diseases, including cancer, cardiovascular diseases and neurological disorders. Genome-wide mapping of splicing quantitative trait loci (sQTLs) has shown that genetic regulation of alternative splicing is widespread. However, identification of the corresponding isoform or protein products associated with disease-associated sQTLs is challenging with short-read RNA-seq, which cannot precisely characterize full-length transcript isoforms. Furthermore, contemporary sQTL interpretation often relies on reference transcript annotations, which are incomplete. Solutions to these issues may be found through integration of newly emerging long-read sequencing technologies. Long-read sequencing offers the capability to sequence full-length mRNA transcripts and, in some cases, to link sQTLs to transcript isoforms containing disease-relevant protein alterations. Here, we provide an overview of sQTL mapping approaches, the use of long-read sequencing to characterize sQTL effects on isoforms, the linkage of RNA isoforms to protein-level functions and comment on future directions in the field. Based on recent progress, long-read RNA sequencing promises to be part of the human disease genetics toolkit to discover and treat protein isoforms causing rare and complex diseases.

Transcriptome variation in human tissues revealed by long-read sequencing

Regulation of transcript structure generates transcript diversity and plays an important role in human disease1-7. The advent of long-read sequencing technologies offers the opportunity to study the role of genetic variation in transcript structure8-16. In this Article, we present a large human long-read RNA-seq dataset using the Oxford Nanopore Technologies platform from 88 samples from Genotype-Tissue Expression (GTEx) tissues and cell lines, complementing the GTEx resource. We identified just over 70,000 novel transcripts for annotated genes, and validated the protein expression of 10% of novel transcripts. We developed a new computational package, LORALS, to analyse the genetic effects of rare and common variants on the transcriptome by allele-specific analysis of long reads. We characterized allele-specific expression and transcript structure events, providing new insights into the specific transcript alterations caused by common and rare genetic variants and highlighting the resolution gained from long-read data. We were able to perturb the transcript structure upon knockdown of PTBP1, an RNA binding protein that mediates splicing, thereby finding genetic regulatory effects that are modified by the cellular environment. Finally, we used this dataset to enhance variant interpretation and study rare variants leading to aberrant splicing patterns.

Identifying Terpenoid Biosynthesis Genes in Euphorbia maculata via Full-Length cDNA Sequencing

The annual herb Euphorbia maculata L. produces anti-inflammatory and biologically active substances such as triterpenoids, tannins, and polyphenols, and it is used in traditional Chinese medicine. Of these bioactive compounds, terpenoids, also called isoprenoids, are major secondary metabolites in E. maculata. Full-length cDNA sequencing was carried out to characterize the transcripts of terpenoid biosynthesis reference genes and determine the copy numbers of their isoforms using PacBio SMRT sequencing technology. The Illumina short-read sequencing platform was also employed to identify differentially expressed genes (DEGs) in the secondary metabolite pathways from leaves, roots, and stems. PacBio generated 62 million polymerase reads, resulting in 81,433 high-quality reads. From these high-quality reads, we reconstructed a genome of 20,722 genes, in which 20,246 genes (97.8%) did not have paralogs. About 33% of the identified genes had two or more isoforms. DEG analysis revealed that the expression level differed among gene paralogs in the leaf, stem, and root. Whole sets of paralogs and isoforms were identified in the mevalonic acid (MVA), methylerythritol phosphate (MEP), and terpenoid biosynthesis pathways in the E. maculata L. The nucleotide information will be useful for identifying orthologous genes in other terpenoid-producing medicinal plants.

Single-nuclei isoform RNA sequencing unlocks barcoded exon connectivity in frozen brain tissue

Single-nuclei RNA sequencing characterizes cell types at the gene level. However, compared to single-cell approaches, many single-nuclei cDNAs are purely intronic, lack barcodes and hinder the study of isoforms. Here we present single-nuclei isoform RNA sequencing (SnISOr-Seq). Using microfluidics, PCR-based artifact removal, target enrichment and long-read sequencing, SnISOr-Seq increased barcoded, exon-spanning long reads 7.5-fold compared to naive long-read single-nuclei sequencing. We applied SnISOr-Seq to adult human frontal cortex and found that exons associated with autism exhibit coordinated and highly cell-type-specific inclusion. We found two distinct combination patterns: those distinguishing neural cell types, enriched in TSS-exon, exon-polyadenylation-site and non-adjacent exon pairs, and those with multiple configurations within one cell type, enriched in adjacent exon pairs. Finally, we observed that human-specific exons are almost as tightly coordinated as conserved exons, implying that coordination can be rapidly established during evolution. SnISOr-Seq enables cell-type-specific long-read isoform analysis in human brain and in any frozen or hard-to-dissociate sample.

Poly(A) capture full length cDNA sequencing improves the accuracy and detection ability of transcript quantification and alternative splicing events

The full-length double-strand cDNA sequencing, one of the RNA-Seq methods, is a powerful method used to investigate the transcriptome status of a gene of interest, such as its transcription level and alternative splicing variants. Furthermore, full-length double-strand cDNA sequencing has the advantage that it can create a library from a small amount of sample and the library can be applied to long-read sequencers in addition to short-read sequencers. Nevertheless, one of our previous studies indicated that the full-length double-strand cDNA sequencing yields non-specific genomic DNA amplification, affecting transcriptome analysis, such as transcript quantification and alternative splicing analysis. In this study, it was confirmed that it is possible to produce the RNA-Seq library from only genomic DNA and that the full-length double-strand cDNA sequencing of genomic DNA yielded non-specific genomic DNA amplification. To avoid non-specific genomic DNA amplification, two methods were examined, which are the DNase I-treated full-length double-strand cDNA sequencing and poly(A) capture full-length double-strand cDNA sequencing. Contrary to expectations, the non-specific genomic DNA amplification was increased and the number of the detected expressing genes was reduced in DNase I-treated full-length double-strand cDNA sequencing. On the other hand, in the poly(A) capture full-length double-strand cDNA sequencing, the non-specific genomic DNA amplification was significantly reduced, accordingly the accuracy and the number of detected expressing genes and splicing events were increased. The expression pattern and percentage spliced in index of splicing events were highly correlated. Our results indicate that the poly(A) capture full-length double-strand cDNA sequencing improves transcript quantification accuracy and the detection ability of alternative splicing events. It is also expected to contribute to the determination of the significance of DNA variants to splicing events.

ScisorWiz: Visualizing Differential Isoform Expression in Single-Cell Long-Read Data

Summary

RNA isoforms contribute to the diverse functionality of the proteins they encode within the cell. Visualizing how isoform expression differs across cell types and brain regions can inform our understanding of disease and gain or loss of functionality caused by alternative splicing with potential negative impacts. However, the extent to which this occurs in specific cell types and brain regions is largely unknown. This is the kind of information that ScisorWiz plots can provide in an informative and easily communicable manner. ScisorWiz affords its user the opportunity to visualize specific genes across any number of cell types, and provides various sorting options for the user to gain different ways to understand their data. ScisorWiz provides a clear picture of differential isoform expression through various clustering methods and highlights features such as alternative exons and single-nucleotide variants. Tools like ScisorWiz are key for interpreting single-cell isoform sequencing data. This tool applies to any single-cell long-read RNA sequencing data in any cell type, tissue or species.

Availability and implementation

Source code is available at http://github.com/ans4013/ScisorWiz. No new data were generated for this publication. Data used to generate figures was sourced from GEO accession token GSE158450 and available on GitHub as example data.

SCN1A overexpression, associated with a genomic region marked by a risk variant for a common epilepsy, raises seizure susceptibility

Mesial temporal lobe epilepsy with hippocampal sclerosis and a history of febrile seizures is associated with common variation at rs7587026, located in the promoter region of SCN1A. We sought to explore possible underlying mechanisms. SCN1A expression was analysed in hippocampal biopsy specimens of individuals with mesial temporal lobe epilepsy with hippocampal sclerosis who underwent surgical treatment, and hippocampal neuronal cell loss was quantitatively assessed using immunohistochemistry. In healthy individuals, hippocampal volume was measured using MRI. Analyses were performed stratified by rs7587026 type. To study the functional consequences of increased SCN1A expression, we generated, using transposon-mediated bacterial artificial chromosome transgenesis, a zebrafish line expressing exogenous scn1a, and performed EEG analysis on larval optic tecta at 4 day post-fertilization. Finally, we used an in vitro promoter analysis to study whether the genetic motif containing rs7587026 influences promoter activity. Hippocampal SCN1A expression differed by rs7587026 genotype (Kruskal-Wallis test P = 0.004). Individuals homozygous for the minor allele showed significantly increased expression compared to those homozygous for the major allele (Dunn's test P = 0.003), and to heterozygotes (Dunn's test P = 0.035). No statistically significant differences in hippocampal neuronal cell loss were observed between the three genotypes. Among 597 healthy participants, individuals homozygous for the minor allele at rs7587026 displayed significantly reduced mean hippocampal volume compared to major allele homozygotes (Cohen's D = - 0.28, P = 0.02), and to heterozygotes (Cohen's D = - 0.36, P = 0.009). Compared to wild type, scn1lab-overexpressing zebrafish larvae exhibited more frequent spontaneous seizures [one-way ANOVA F(4,54) = 6.95 (P < 0.001)]. The number of EEG discharges correlated with the level of scn1lab overexpression [one-way ANOVA F(4,15) = 10.75 (P < 0.001]. Finally, we showed that a 50 bp promoter motif containing rs7587026 exerts a strong regulatory role on SCN1A expression, though we could not directly link this to rs7587026 itself. Our results develop the mechanistic link between rs7587026 and mesial temporal lobe epilepsy with hippocampal sclerosis and a history of febrile seizures. Furthermore, we propose that quantitative precision may be important when increasing SCN1A expression in current strategies aiming to treat seizures in conditions involving SCN1A haploinsufficiency, such as Dravet syndrome.

A comparison of mRNA sequencing (RNA-Seq) library preparation methods for transcriptome analysis

BACKGROUND

mRNA sequencing is a powerful technique, which is used to investigate the transcriptome status of a gene of interest, such as its transcription level and splicing variants. Presently, several RNA sequencing (RNA-Seq) methods have been developed; however, the relative advantage of each method has remained unknown. Here we used three commercially available RNA-Seq library preparation kits; the traditional method (TruSeq), in addition to full-length double-stranded cDNA methods (SMARTer and TeloPrime) to investigate the advantages and disadvantages of these three approaches in transcriptome analysis.

RESULTS

We observed that the number of expressed genes detected from the TeloPrime sequencing method was fewer than that obtained using the TruSeq and SMARTer. We also observed that the expression patterns between TruSeq and SMARTer correlated strongly. Alternatively, SMARTer and TeloPrime methods underestimated the expression of relatively long transcripts. Moreover, genes having low expression levels were undetected stochastically regardless of any three methods used. Furthermore, although TeloPrime detected a significantly higher proportion at the transcription start site (TSS), its coverage of the gene body was not uniform. SMARTer is proposed to be yielded for nonspecific genomic DNA amplification. In contrast, the detected splicing event number was highest in the TruSeq. The percent spliced in index (PSI) of the three methods was highly correlated.

CONCLUSIONS

TruSeq detected transcripts and splicing events better than the other methods and measured expression levels of genes, in addition to splicing events accurately. However, although detected transcripts and splicing events in TeloPrime were fewer, the coverage at TSS was highest. Additionally, SMARTer was better than TeloPrime with regards to the detected number of transcripts and splicing events among the understudied full-length double-stranded cDNA methods. In conclusion, for short-read sequencing, TruSeq has relative advantages for use in transcriptome analysis.

acorde unravels functionally interpretable networks of isoform co-usage from single cell data

Alternative splicing (AS) is a highly-regulated post-transcriptional mechanism known to modulate isoform expression within genes and contribute to cell-type identity. However, the extent to which alternative isoforms establish co-expression networks that may be relevant in cellular function has not been explored yet. Here, we present acorde, a pipeline that successfully leverages bulk long reads and single-cell data to confidently detect alternative isoform co-expression relationships. To achieve this, we develop and validate percentile correlations, an innovative approach that overcomes data sparsity and yields accurate co-expression estimates from single-cell data. Next, acorde uses correlations to cluster co-expressed isoforms into a network, unraveling cell type-specific alternative isoform usage patterns. By selecting same-gene isoforms between these clusters, we subsequently detect and characterize genes with co-differential isoform usage (coDIU) across cell types. Finally, we predict functional elements from long read-defined isoforms and provide insight into biological processes, motifs, and domains potentially controlled by the coordination of post-transcriptional regulation. The code for acorde is available at https://github.com/ConesaLab/acorde .

Sequencing of individual barcoded cDNAs using Pacific Biosciences and Oxford Nanopore Technologies reveals platform-specific error patterns

Long-read transcriptomics require understanding error sources inherent to technologies. Current approaches cannot compare methods for an individual RNA molecule. Here, we present a novel platform-comparison method that combines barcoding strategies and long-read sequencing to sequence cDNA copies representing an individual RNA molecule on both Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT). We compare these long-read pairs in terms of sequence content and isoform patterns. Although individual read pairs show high similarity, we find differences in (1) aligned length, (2) transcription start site (TSS), (3) polyadenylation site (poly(A)-site) assignment, and (4) exon-intron structures. Overall, 25% of read pairs disagree on either TSS, poly(A)-site, or splice site. Intron-chain disagreement typically arises from alignment errors of microexons and complicated splice sites. Our single-molecule technology comparison reveals that inconsistencies are often caused by sequencing error-induced inaccurate ONT alignments, especially to downstream GUNNGU donor motifs. However, annotation-disagreeing upstream shifts in NAGNAG acceptors in ONT are often confirmed by PacBio and are thus likely real. In both barcoded and nonbarcoded ONT reads, we find that intron number and proximity of GU/AGs better predict inconsistencies with the annotation than read quality alone. We summarize these findings in an annotation-based algorithm for spliced alignment correction that improves subsequent transcript construction with ONT reads.

Single-Cell Transcriptomics Reveals Splicing Features of Adult Neural Stem Cells in the Subventricular Zone

The central nervous system has enormously complex cellular diversity with hundreds of distinct cell types, yet alternative splicing features in single cells of important cell types at neurogenic regions are not well understood. By employing in silico analysis, we systematically identified 3,611 alternative splicing events from 1,908 genes in 28 single-cell transcriptomic data of adult mouse ependymal and subependymal regions, and found that single-cell RNA-seq has the advantage in uncovering rare splicing isoforms compared to bulk RNA-seq at the population level. We uncovered that the simultaneous presence of multiple isoforms from the same gene in a single cell is prevalent, and quiescent stem cells, activated stem cells, and neuroblast cells exhibit high heterogeneity of splicing variants. Furthermore, we also demonstrated the existence of novel bicistronic transcripts in quiescent stem cells.

Nanopore sequencing of RNA and cDNA molecules in Escherichia coli

High-throughput sequencing dramatically changed our view of transcriptome architectures and allowed for ground-breaking discoveries in RNA biology. Recently, sequencing of full-length transcripts based on the single-molecule sequencing platform from Oxford Nanopore Technologies (ONT) was introduced and is widely used to sequence eukaryotic and viral RNAs. However, experimental approaches implementing this technique for prokaryotic transcriptomes remain scarce. Here, we present an experimental and bioinformatic workflow for ONT RNA-seq in the bacterial model organism Escherichia coli, which can be applied to any microorganism. Our study highlights critical steps of library preparation and computational analysis and compares the results to gold standards in the field. Furthermore, we comprehensively evaluate the applicability and advantages of different ONT-based RNA sequencing protocols, including direct RNA, direct cDNA, and PCR-cDNA. We find that (PCR)-cDNA-seq offers improved yield and accuracy compared to direct RNA sequencing. Notably, (PCR)-cDNA-seq is suitable for quantitative measurements and can be readily used for simultaneous and accurate detection of transcript 5' and 3' boundaries, analysis of transcriptional units, and transcriptional heterogeneity. In summary, based on our comprehensive study, we show nanopore RNA-seq to be a ready-to-use tool allowing rapid, cost-effective, and accurate annotation of multiple transcriptomic features. Thereby nanopore RNA-seq holds the potential to become a valuable alternative method for RNA analysis in prokaryotes.

SMRT sequencing of full-length transcriptome and gene expression analysis in two chemical types of Pogostemon cablin (Blanco) Benth

BACKGROUND

Pogostemon cablin (Blanco) Benth. also called patchouli, is a traditional medicinal and aromatic plant that grows mainly in Southeast Asia and China. In China, P. cablin is divided into two chemical types: the patchouliol-type and the pogostone-type. Patchouliol-type patchouli usually grow taller, with thicker stems and bigger leaves, and produce more aromatic oil.

METHODS

To better understand the genetic differences between the two chemical types that contribute to their differences in morphology and biosynthetic capabilities, we constructed de novo transcriptomes from both chemical types using the Pacific Biosciences (PacBio) Sequel platform and performed differential expression analysis of multiple tissues using Illumina short reads.

RESULTS

In this study, using single-molecule real-time (SMRT) long-read sequencing, we obtained 22.07 GB of clean data and 134,647 nonredundant transcripts from two chemical types. Additionally, we identified 126,576 open reading frames (ORFs), 100,638 coding sequences (CDSs), 4,106 long noncoding RNAs (lncRNAs) and 6,829 transcription factors (TFs) from two chemical types of P. cablin. We adopted PacBio and Illumina sequencing to identify differentially expressed transcripts (DEGs) in three tissues of the two chemical types. More DEGs were observed in comparisons of different tissues collected from the same chemical type relative to comparisons of the same tissue collected from different chemical types. Furthormore, using KEGG enrichment analysis of DEGs, we found that the most enriched biosynthetic pathways of secondary metabolites of the two chemical types were "terpenoid backbone biosynthesis", "phenylpropanoid biosynthesis", "plant hormone signal transduction", "sesquiterpenoid and triterpenoid biosynthesis", "ubiquinone and other terpenoid-quinone biosynthesis", "flavonoid biosynthesis", and "flavone and flavonol biosynthesis". However, the main pathways of the patchouliol-type also included "diterpene biosynthesis" and "monoterpene biosynthesis". Additionally, by comparing the expression levels of the three tissues verified by qRT-PCR, more DEGs in the roots were upregulated in the mevalonate (MVA) pathway in the cytoplasm, but more DEGs in the leaves were upregulated in the methylerythritol phosphate (MEP) pathway in the plastid, both of which are important pathways for terpenoids biosynthesis. These findings promote the study of further genome annotation and transcriptome research in P. cablin.

Single-molecule long-read sequencing reveals the potential impact of posttranscriptional regulation on gene dosage effects on the avian Z chromosome

Background

Mammalian sex chromosomes provide dosage compensation, but avian lack a global mechanism of dose compensation. Herein, we employed nanopore sequencing to investigate the genetic basis of gene expression and gene dosage effects in avian Z chromosomes at the posttranscriptional level.

Results

In this study, the gonad and head skin of female and male duck samples (n = 4) were collected at 16 weeks of age for Oxford nanopore sequencing. Our results revealed a dosage effect and local regulation of duck Z chromosome gene expression. Additionally, AS and APA achieve tissue-specific gene expression, and male-biased lncRNA regulates its Z-linked target genes, with a positive regulatory role for gene dosage effects on the duck Z chromosome. In addition, GO enrichment and KEGG pathway analysis showed that the dosage effects of Z-linked genes were mainly associated with the cellular response to hormone stimulus, melanin biosynthetic, metabolic pathways, and melanogenesis, resulting in sex differences.

Conclusions

Our data suggested that post transcriptional regulation (AS, APA and lncRNA) has a potential impact on the gene expression effects of avian Z chromosomes. Our study provides a new view of gene regulation underlying the dose effects in avian Z chromosomes at the RNA post transcriptional level.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08360-8.

A comprehensive long-read isoform analysis platform and sequencing resource for breast cancer

Tumors display widespread transcriptome alterations, but the full repertoire of isoform-level alternative splicing in cancer is unknown. We developed a long-read (LR) RNA sequencing and analytical platform that identifies and annotates full-length isoforms and infers tumor-specific splicing events. Application of this platform to breast cancer samples identifies thousands of previously unannotated isoforms; ~30% affect protein coding exons and are predicted to alter protein localization and function. We performed extensive cross-validation with -omics datasets to support transcription and translation of novel isoforms. We identified 3059 breast tumor–specific splicing events, including 35 that are significantly associated with patient survival. Of these, 21 are absent from GENCODE and 10 are enriched in specific breast cancer subtypes. Together, our results demonstrate the complexity, cancer subtype specificity, and clinical relevance of previously unidentified isoforms and splicing events in breast cancer that are only annotatable by LR-seq and provide a rich resource of immuno-oncology therapeutic targets.

A blood drop through the pore: nanopore sequencing in hematology

The development of new sequencing platforms, technologies, and bioinformatics tools in the past decade fostered key discoveries in human genomics. Among the most recent sequencing technologies, nanopore sequencing (NS) has caught the interest of researchers for its intriguing potential and flexibility. This up-to-date review highlights the recent application of NS in the hematology field, focusing on progress and challenges of the technological approaches employed for the identification of pathologic alterations. The molecular and analytic pipelines developed for the analysis of the whole-genome, target regions, and transcriptomics provide a proof of evidence of the unparalleled amount of information that could be retrieved by an innovative approach based on long-read sequencing.

Technical challenges in defining RNA modifications

It is well established that DNA base modifications play a key role in gene regulation during development and in response to environmental stress. This type of epigenetic control of development and environmental responses has been intensively studied over the past few decades. Similar to DNA, various RNA species also undergo modifications that play important roles in, for example, RNA splicing, protein translation, and the avoidance of immune surveillance by host. More than 160 different types of RNA modifications have been identified. In addition to base modifications, RNA modification also involves splicing of pre-mRNAs, leading to as many as tens of transcript isoforms from a single pre-RNA, especially in higher organisms. However, the function, prevalence and distribution of RNA modifications are poorly understood. The lack of a suitable method for the reliable identification of RNA modifications constitutes a significant challenge to studying their functions. This review focuses on the technologies that enable de novo identification of RNA base modifications and the alternatively spliced mRNA transcripts.

Transcript-targeted analysis reveals isoform alterations and double-hop fusions in breast cancer

Although transcriptome alteration is an essential driver of carcinogenesis, the effects of chromosomal structural alterations on the cancer transcriptome are not yet fully understood. Short-read transcript sequencing has prevented researchers from directly exploring full-length transcripts, forcing them to focus on individual splice sites. Here, we develop a pipeline for Multi-Sample long-read Transcriptome Assembly (MuSTA), which enables construction of a transcriptome from long-read sequence data. Using the constructed transcriptome as a reference, we analyze RNA extracted from 22 clinical breast cancer specimens. We identify a comprehensive set of subtype-specific and differentially used isoforms, which extended our knowledge of isoform regulation to unannotated isoforms including a short form TNS3. We also find that the exon-intron structure of fusion transcripts depends on their genomic context, and we identify double-hop fusion transcripts that are transcribed from complex structural rearrangements. For example, a double-hop fusion results in aberrant expression of an endogenous retroviral gene, ERVFRD-1, which is normally expressed exclusively in placenta and is thought to protect fetus from maternal rejection; expression is elevated in several TCGA samples with ERVFRD-1 fusions. Our analyses provide direct evidence that full-length transcript sequencing of clinical samples can add to our understanding of cancer biology and genomics in general.

Impact of human gene annotations on RNA-seq differential expression analysis

BACKGROUND

Differential expression (DE) analysis of RNA-seq data typically depends on gene annotations. Different sets of gene annotations are available for the human genome and are continually updated-a process complicated with the development and application of high-throughput sequencing technologies. However, the impact of the complexity of gene annotations on DE analysis remains unclear.

RESULTS

Using "mappability", a metric of the complexity of gene annotation, we compared three distinct human gene annotations, GENCODE, RefSeq, and NONCODE, and evaluated how mappability affected DE analysis. We found that mappability was significantly different among the human gene annotations. We also found that increasing mappability improved the performance of DE analysis, and the impact of mappability mainly evident in the quantification step and propagated downstream of DE analysis systematically.

CONCLUSIONS

We assessed how the complexity of gene annotations affects DE analysis using mappability. Our findings indicate that the growth and complexity of gene annotations negatively impact the performance of DE analysis, suggesting that an approach that excludes unnecessary gene models from gene annotations improves the performance of DE analysis.

A look into retinal organoids: methods, analytical techniques, and applications

Inherited retinal diseases (IRDs) cause progressive loss of light-sensitive photoreceptors in the eye and can lead to blindness. Gene-based therapies for IRDs have shown remarkable progress in the past decade, but the vast majority of forms remain untreatable. In the era of personalised medicine, induced pluripotent stem cells (iPSCs) emerge as a valuable system for cell replacement and to model IRD because they retain the specific patient genome and can differentiate into any adult cell type. Three-dimensional (3D) iPSCs-derived retina-like tissue called retinal organoid contains all major retina-specific cell types: amacrine, bipolar, horizontal, retinal ganglion cells, Müller glia, as well as rod and cone photoreceptors. Here, we describe the main applications of retinal organoids and provide a comprehensive overview of the state-of-art analysis methods that apply to this model system. Finally, we will discuss the outlook for improvements that would bring the cellular model a step closer to become an established system in research and treatment development of IRDs.

Full-length transcriptome analysis and identification of transcript structures in Eimeria necatrix from different developmental stages by single-molecule real-time sequencing

Background

Eimeria necatrix is one of the most pathogenic parasites, causing high mortality in chickens. Although its genome sequence has been published, the sequences and complete structures of its mRNA transcripts remain unclear, limiting exploration of novel biomarkers, drug targets and genetic functions in E. necatrix.

Methods

Second-generation merozoites (MZ-2) of E. necatrix were collected using Percoll density gradients, and high-quality RNA was extracted from them. Single-molecule real-time (SMRT) sequencing and Illumina sequencing were combined to generate the transcripts of MZ-2. Combined with the SMRT sequencing data of sporozoites (SZ) collected in our previous study, the transcriptome and transcript structures of E. necatrix were studied.

Results

SMRT sequencing yielded 21,923 consensus isoforms in MZ-2. A total of 17,151 novel isoforms of known genes and 3918 isoforms of novel genes were successfully identified. We also identified 2752 (SZ) and 3255 (MZ-2) alternative splicing (AS) events, 1705 (SZ) and 1874 (MZ-2) genes with alternative polyadenylation (APA) sites, 4019 (SZ) and 2588 (MZ-2) fusion transcripts, 159 (SZ) and 84 (MZ-2) putative transcription factors (TFs) and 3581 (SZ) and 2039 (MZ-2) long non-coding RNAs (lncRNAs). To validate fusion transcripts, reverse transcription-PCR was performed on 16 candidates, with an accuracy reaching up to 87.5%. Sanger sequencing of the PCR products further confirmed the authenticity of chimeric transcripts. Comparative analysis of transcript structures revealed a total of 3710 consensus isoforms, 815 AS events, 1139 genes with APA sites, 20 putative TFs and 352 lncRNAs in both SZ and MZ-2.

Conclusions

We obtained many long-read isoforms in E. necatrix SZ and MZ-2, from which a series of lncRNAs, AS events, APA events and fusion transcripts were identified. Information on TFs will improve understanding of transcriptional regulation, and fusion event data will greatly improve draft versions of gene models in E. necatrix. This information offers insights into the mechanisms governing the development of E. necatrix and will aid in the development of novel strategies for coccidiosis control.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-021-05015-7.

PacBio Single-Molecule Long-Read Sequencing Provides New Light on the Complexity of Full-Length Transcripts in Cattle

Cattle (Bos taurus) is one of the most widely distributed livestock species in the world, and provides us with high-quality milk and meat which have a huge impact on the quality of human life. Therefore, accurate and complete transcriptome and genome annotation are of great value to the research of cattle breeding. In this study, we used error-corrected PacBio single-molecule real-time (SMRT) data to perform whole-transcriptome profiling in cattle. Then, 22.5 Gb of subreads was generated, including 381,423 circular consensus sequences (CCSs), among which 276,295 full-length non-chimeric (FLNC) sequences were identified. After correction by Illumina short reads, we obtained 22,353 error-corrected isoforms. A total of 305 alternative splicing (AS) events and 3,795 alternative polyadenylation (APA) sites were detected by transcriptome structural analysis. Furthermore, we identified 457 novel genes, 120 putative transcription factors (TFs), and 569 novel long non-coding RNAs (lncRNAs). Taken together, this research improves our understanding and provides new insights into the complexity of full-length transcripts in cattle.

Nanopore Assay Reveals Cell-Type-Dependent Gene Expression of Vesicular Stomatitis Indiana Virus and Differential Host Cell Response

Vesicular stomatitis Indiana virus (VSIV) of genus Vesiculovirus, species IndianaVesiculovirus (formerly as Vesicular stomatitis virus, VSV) causes a disease in livestock that is very similar to the foot and mouth disease, thereby an outbreak may lead to significant economic loss. Long-read sequencing (LRS) -based approaches already reveal a hidden complexity of the transcriptomes in several viruses. This technique has been utilized for the sequencing of the VSIV genome, but our study is the first for the application of this technique for the profiling of the VSIV transcriptome. Since LRS is able to sequence full-length RNA molecules, it thereby provides more accurate annotation of the transcriptomes than the traditional short-read sequencing methods. The objectives of this study were to assemble the complete transcriptome of using nanopore sequencing, to ascertain cell-type specificity and dynamics of viral gene expression, and to evaluate host gene expression changes induced by the viral infection. We carried out a time-course analysis of VSIV gene expression in human glioblastoma and primate fibroblast cell lines using a nanopore-based LRS approach and applied both amplified and direct cDNA sequencing (as well as cap-selection) for a fraction of samples. Our investigations revealed that, although the VSIV genome is simple, it generates a relatively complex transcriptomic architecture. In this study, we also demonstrated that VSIV transcripts vary in structure and exhibit differential gene expression patterns in the two examined cell types.

HITAC-seq enables high-throughput cost-effective sequencing of plasmids and DNA fragments with identity

DNA sequencing is vital for many aspects of biological research and diagnostics. Despite the development of second and third generation sequencing technologies, Sanger sequencing has long been the only choice when required to precisely track each sequenced plasmids or DNA fragments. Here, we report a complete set of novel barcoding and assembling system, Highly-parallel Indexed Tagmentation-reads Assembled Consensus sequencing (HITAC-seq), that could massively sequence and track the identities of each individual sequencing sample. With the cost of much less than that of single read of Sanger sequencing, HITAC-seq can generate high-quality contiguous sequences of up to 10 kilobases or longer. The capability of HITAC-seq was confirmed through large-scale sequencing of thousands of plasmid clones and hundreds of amplicon fragments using approximately 100 pg of input DNAs. Due to its long synthetic length, HITAC-seq was effective in detecting relatively large structural variations, as demonstrated by the identification of a ∼1.3 kb Copia retrotransposon insertion in the upstream of a likely maize domestication gene. Besides being a practical alternative to traditional Sanger sequencing, HITAC-seq is suitable for many high-throughput sequencing and genotyping applications.

Single-molecule, full-length transcript isoform sequencing reveals disease-associated RNA isoforms in cardiomyocytes

Alternative splicing generates differing RNA isoforms that govern phenotypic complexity of eukaryotes. Its malfunction underlies many diseases, including cancer and cardiovascular diseases. Comparative analysis of RNA isoforms at the genome-wide scale has been difficult. Here, we establish an experimental and computational pipeline that performs de novo transcript annotation and accurately quantifies transcript isoforms from cDNA sequences with a full-length isoform detection accuracy of 97.6%. We generate a searchable, quantitative human transcriptome annotation with 31,025 known and 5,740 novel transcript isoforms ( http://steinmetzlab.embl.de/iBrowser/ ). By analyzing the isoforms in the presence of RNA Binding Motif Protein 20 (RBM20) mutations associated with aggressive dilated cardiomyopathy (DCM), we identify 121 differentially expressed transcript isoforms in 107 cardiac genes. Our approach enables quantitative dissection of complex transcript architecture instead of mere identification of inclusion or exclusion of individual exons, as exemplified by the discovery of IMMT isoforms mis-spliced by RBM20 mutations. Thereby we achieve a path to direct differential expression testing independent of an existing annotation of transcript isoforms, providing more immediate biological interpretation and higher resolution transcriptome comparisons.

Sequoia: an interactive visual analytics platform for interpretation and feature extraction from nanopore sequencing datasets

Background

Direct-sequencing technologies, such as Oxford Nanopore’s, are delivering long RNA reads with great efficacy and convenience. These technologies afford an ability to detect post-transcriptional modifications at a single-molecule resolution, promising new insights into the functional roles of RNA. However, realizing this potential requires new tools to analyze and explore this type of data.

Result

Here, we present Sequoia, a visual analytics tool that allows users to interactively explore nanopore sequences. Sequoia combines a Python-based backend with a multi-view visualization interface, enabling users to import raw nanopore sequencing data in a Fast5 format, cluster sequences based on electric-current similarities, and drill-down onto signals to identify properties of interest. We demonstrate the application of Sequoia by generating and analyzing ~ 500k reads from direct RNA sequencing data of human HeLa cell line. We focus on comparing signal features from m6A and m5C RNA modifications as the first step towards building automated classifiers. We show how, through iterative visual exploration and tuning of dimensionality reduction parameters, we can separate modified RNA sequences from their unmodified counterparts. We also document new, qualitative signal signatures that characterize these modifications from otherwise normal RNA bases, which we were able to discover from the visualization.

Conclusions

Sequoia’s interactive features complement existing computational approaches in nanopore-based RNA workflows. The insights gleaned through visual analysis should help users in developing rationales, hypotheses, and insights into the dynamic nature of RNA. Sequoia is available at https://github.com/dnonatar/Sequoia.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07791-z.

Direct long-read RNA sequencing identifies a subset of questionable exitrons likely arising from reverse transcription artifacts

Resistance to CD19-directed immunotherapies in lymphoblastic leukemia has been attributed, among other factors, to several aberrant CD19 pre-mRNA splicing events, including recently reported excision of a cryptic intron embedded within CD19 exon 2. While "exitrons" are known to exist in hundreds of human transcripts, we discovered, using reporter assays and direct long-read RNA sequencing (dRNA-seq), that the CD19 exitron is an artifact of reverse transcription. Extending our analysis to publicly available datasets, we identified dozens of questionable exitrons, dubbed "falsitrons," that appear only in cDNA-seq, but never in dRNA-seq. Our results highlight the importance of dRNA-seq for transcript isoform validation.

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.