IsoVis - a webserver for visualization and annotation of alternative RNA isoforms.

Genes commonly express multiple RNA products (RNA isoforms), which differ in exonic content and can have different functions. Making sense of the plethora of known and novel RNA isoforms being identified by transcriptomic approaches requires a user-friendly way to visualize gene isoforms and how they differ in exonic content, expression levels and potential functions. Here we introduce IsoVis, a freely available webserver that accepts user-supplied transcriptomic data and visualizes the expressed isoforms in a clear, intuitive manner. IsoVis contains numerous features, including the ability to visualize all RNA isoforms of a gene and their expression levels; the annotation of known isoforms from external databases; mapping of protein domains and features to exons, allowing changes to protein sequence and function between isoforms to be established; and extensive species compatibility. Datasets visualised on IsoVis remain private to the user, allowing analysis of sensitive data. IsoVis visualisations can be downloaded to create publication-ready figures. The IsoVis webserver enables researchers to perform isoform analyses without requiring programming skills, is free to use, and available at https://isomix.org/isovis/.

Whole-genome landscapes of major melanoma subtypes.

Melanoma of the skin is a common cancer only in Europeans, whereas it arises in internal body surfaces (mucosal sites) and on the hands and feet (acral sites) in people throughout the world. Here we report analysis of whole-genome sequences from cutaneous, acral and mucosal subtypes of melanoma. The heavily mutated landscape of coding and non-coding mutations in cutaneous melanoma resolved novel signatures of mutagenesis attributable to ultraviolet radiation. However, acral and mucosal melanomas were dominated by structural changes and mutation signatures of unknown aetiology, not previously identified in melanoma. The number of genes affected by recurrent mutations disrupting non-coding sequences was similar to that affected by recurrent mutations to coding sequences. Significantly mutated genes included BRAF, CDKN2A, NRAS and TP53 in cutaneous melanoma, BRAF, NRAS and NF1 in acral melanoma and SF3B1 in mucosal melanoma. Mutations affecting the TERT promoter were the most frequent of all; however, neither they nor ATRX mutations, which correlate with alternative telomere lengthening, were associated with greater telomere length. Most melanomas had potentially actionable mutations, most in components of the mitogen-activated protein kinase and phosphoinositol kinase pathways. The whole-genome mutation landscape of melanoma reveals diverse carcinogenic processes across its subtypes, some unrelated to sun exposure, and extends potential involvement of the non-coding genome in its pathogenesis.

Multiomic analysis elucidates Complex I deficiency caused by a deep intronic variant in NDUFB10.

The diagnosis of Mendelian disorders following uninformative exome and genome sequencing remains a challenging and often unmet need. Following uninformative exome and genome sequencing of a family quartet including two siblings with suspected mitochondrial disorder, RNA sequencing (RNAseq) was pursued in one sibling. Long-read amplicon sequencing was used to determine and quantify transcript structure. Immunoblotting studies and quantitative proteomics were performed to demonstrate functional impact. Differential expression analysis of RNAseq data identified significantly decreased expression of the mitochondrial OXPHOS Complex I subunit NDUFB10 associated with a cryptic exon in intron 1 of NDUFB10, that included an in-frame stop codon. The cryptic exon contained a rare intronic variant that was homozygous in both affected siblings. Immunoblot and quantitative proteomic analysis of fibroblasts revealed decreased abundance of Complex I subunits, providing evidence of isolated Complex I deficiency. Through multiomic analysis we present data implicating a deep intronic variant in NDUFB10 as the cause of mitochondrial disease in two individuals, providing further support of the gene-disease association. This study highlights the importance of transcriptomic and proteomic analyses as complementary diagnostic tools in patients undergoing genome-wide diagnostic evaluation.

Molecular biomarkers for chronological age in animal ecology.

The chronological age of an individual animal predicts many of its biological characteristics, and these in turn influence population-level ecological processes. Animal age information can therefore be valuable in ecological research, but many species have no external features that allow age to be reliably determined. Molecular age biomarkers provide a potential solution to this problem. Research in this area of molecular ecology has so far focused on a limited range of age biomarkers. The most commonly tested molecular age biomarker is change in average telomere length, which predicts age well in a small number of species and tissues, but performs poorly in many other situations. Epigenetic regulation of gene expression has recently been shown to cause age-related modifications to DNA and to cause changes in abundance of several RNA types throughout animal lifespans. Age biomarkers based on these epigenetic changes, and other new DNA-based assays, have already been applied to model organisms, humans and a limited number of wild animals. There is clear potential to apply these marker types more widely in ecological studies. For many species, these new approaches will produce age estimates where this was previously impractical. They will also enable age information to be gathered in cross-sectional studies and expand the range of demographic characteristics that can be quantified with molecular methods. We describe the range of molecular age biomarkers that have been investigated to date and suggest approaches for developing the newer marker types as age assays in nonmodel animal species.

Pervasive effects of RNA degradation on Nanopore direct RNA sequencing.

Oxford Nanopore direct RNA sequencing (DRS) is capable of sequencing complete RNA molecules and accurately measuring gene and isoform expression. However, as DRS is designed to profile intact RNA, expression quantification may be more heavily dependent upon RNA integrity than alternative RNA sequencing methodologies. It is currently unclear how RNA degradation impacts DRS or whether it can be corrected for. To assess the impact of RNA integrity on DRS, we performed a degradation time series using SH-SY5Y neuroblastoma cells. Our results demonstrate that degradation is a significant and pervasive factor that can bias DRS measurements, including a reduction in library complexity resulting in an overrepresentation of short genes and isoforms. Degradation also biases differential expression analyses; however, we find that explicit correction can almost fully recover meaningful biological signal. In addition, DRS provided less biased profiling of partially degraded samples than Nanopore PCR-cDNA sequencing. Overall, we find that samples with RNA integrity number (RIN) > 9.5 can be treated as undegraded and samples with RIN > 7 can be utilized for DRS with appropriate correction. These results establish the suitability of DRS for a wide range of samples, including partially degraded in vivo clinical and post-mortem samples, while limiting the confounding effect of degradation on expression quantification.

Identification of cell barcodes from long-read single-cell RNA-seq with BLAZE.

Long-read single-cell RNA sequencing (scRNA-seq) enables the quantification of RNA isoforms in individual cells. However, long-read scRNA-seq using the Oxford Nanopore platform has largely relied upon matched short-read data to identify cell barcodes. We introduce BLAZE, which accurately and efficiently identifies 10x cell barcodes using only nanopore long-read scRNA-seq data. BLAZE outperforms the existing tools and provides an accurate representation of the cells present in long-read scRNA-seq when compared to matched short reads. BLAZE simplifies long-read scRNA-seq while improving the results, is compatible with downstream tools accepting a cell barcode file, and is available at https://github.com/shimlab/BLAZE .

Long-Read RNA Sequencing Identifies Polyadenylation Elongation and Differential Transcript Usage of Host Transcripts During SARS-CoV-2 In Vitro Infection.

Better methods to interrogate host-pathogen interactions during Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infections are imperative to help understand and prevent this disease. Here we implemented RNA-sequencing (RNA-seq) using Oxford Nanopore Technologies (ONT) long-reads to measure differential host gene expression, transcript polyadenylation and isoform usage within various epithelial cell lines permissive and non-permissive for SARS-CoV-2 infection. SARS-CoV-2-infected and mock-infected Vero (African green monkey kidney epithelial cells), Calu-3 (human lung adenocarcinoma epithelial cells), Caco-2 (human colorectal adenocarcinoma epithelial cells) and A549 (human lung carcinoma epithelial cells) were analyzed over time (0, 2, 24, 48 hours). Differential polyadenylation was found to occur in both infected Calu-3 and Vero cells during a late time point (48 hpi), with Gene Ontology (GO) terms such as viral transcription and translation shown to be significantly enriched in Calu-3 data. Poly(A) tails showed increased lengths in the majority of the differentially polyadenylated transcripts in Calu-3 and Vero cell lines (up to ~101 nt in mean poly(A) length, padj = 0.029). Of these genes, ribosomal protein genes such as RPS4X and RPS6 also showed downregulation in expression levels, suggesting the importance of ribosomal protein genes during infection. Furthermore, differential transcript usage was identified in Caco-2, Calu-3 and Vero cells, including transcripts of genes such as GSDMB and KPNA2, which have previously been implicated in SARS-CoV-2 infections. Overall, these results highlight the potential role of differential polyadenylation and transcript usage in host immune response or viral manipulation of host mechanisms during infection, and therefore, showcase the value of long-read sequencing in identifying less-explored host responses to disease.

Corrigendum: Isoform Age - Splice Isoform Profiling Using Long-Read Technologies.

[This corrects the article DOI: 10.3389/fmolb.2021.711733.].

Isoform Age - Splice Isoform Profiling Using Long-Read Technologies.

Alternative splicing (AS) of RNA is a key mechanism that results in the expression of multiple transcript isoforms from single genes and leads to an increase in the complexity of both the transcriptome and proteome. Regulation of AS is critical for the correct functioning of many biological pathways, while disruption of AS can be directly pathogenic in diseases such as cancer or cause risk for complex disorders. Current short-read sequencing technologies achieve high read depth but are limited in their ability to resolve complex isoforms. In this review we examine how long-read sequencing (LRS) technologies can address this challenge by covering the entire RNA sequence in a single read and thereby distinguish isoform changes that could impact RNA regulation or protein function. Coupling LRS with technologies such as single cell sequencing, targeted sequencing and spatial transcriptomics is producing a rapidly expanding suite of technological approaches to profile alternative splicing at the isoform level with unprecedented detail. In addition, integrating LRS with genotype now allows the impact of genetic variation on isoform expression to be determined. Recent results demonstrate the potential of these techniques to elucidate the landscape of splicing, including in tissues such as the brain where AS is particularly prevalent. Finally, we also discuss how AS can impact protein function, potentially leading to novel therapeutic targets for a range of diseases.

The long and the short of it: unlocking nanopore long-read RNA sequencing data with short-read differential expression analysis tools.

Application of Oxford Nanopore Technologies' long-read sequencing platform to transcriptomic analysis is increasing in popularity. However, such analysis can be challenging due to the high sequence error and small library sizes, which decreases quantification accuracy and reduces power for statistical testing. Here, we report the analysis of two nanopore RNA-seq datasets with the goal of obtaining gene- and isoform-level differential expression information. A dataset of synthetic, spliced, spike-in RNAs ('sequins') as well as a mouse neural stem cell dataset from samples with a null mutation of the epigenetic regulator Smchd1 was analysed using a mix of long-read specific tools for preprocessing together with established short-read RNA-seq methods for downstream analysis. We used limma-voom to perform differential gene expression analysis, and the novel FLAMES pipeline to perform isoform identification and quantification, followed by DRIMSeq and limma-diffSplice (with stageR) to perform differential transcript usage analysis. We compared results from the sequins dataset to the ground truth, and results of the mouse dataset to a previous short-read study on equivalent samples. Overall, our work shows that transcriptomic analysis of long-read nanopore data using long-read specific preprocessing methods together with short-read differential expression methods and software that are already in wide use can yield meaningful results.

Transcriptional and epi-transcriptional dynamics of SARS-CoV-2 during cellular infection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uses subgenomic RNA (sgRNA) to produce viral proteins for replication and immune evasion. We apply long-read RNA and cDNA sequencing to in vitro human and primate infection models to study transcriptional dynamics. Transcription-regulating sequence (TRS)-dependent sgRNA upregulates earlier in infection than TRS-independent sgRNA. An abundant class of TRS-independent sgRNA consisting of a portion of open reading frame 1ab (ORF1ab) containing nsp1 joins to ORF10, and the 3' untranslated region (UTR) upregulates at 48 h post-infection in human cell lines. We identify double-junction sgRNA containing both TRS-dependent and -independent junctions. We find multiple sites at which the SARS-CoV-2 genome is consistently more modified than sgRNA and that sgRNA modifications are stable across transcript clusters, host cells, and time since infection. Our work highlights the dynamic nature of the SARS-CoV-2 transcriptome during its replication cycle.

Age estimation in a long-lived seabird (Ardenna tenuirostris) using DNA methylation-based biomarkers.

Age structure is a fundamental aspect of animal population biology. Age is strongly related to individual physiological condition, reproductive potential and mortality rate. Currently, there are no robust molecular methods for age estimation in birds. Instead, individuals must be ringed as chicks to establish known-age populations, which is a labour-intensive and expensive process. The estimation of chronological age using DNA methylation (DNAm) is emerging as a robust approach in mammals including humans, mice and some non-model species. Here, we quantified DNAm in whole blood samples from a total of 71 known-age Short-tailed shearwaters (Ardenna tenuirostris) using digital restriction enzyme analysis of methylation (DREAM). The DREAM method measures DNAm levels at thousands of CpG dinucleotides throughout the genome. We identified seven CpG sites with DNAm levels that correlated with age. A model based on these relationships estimated age with a mean difference of 2.8 years to known age, based on validation estimates from models created by repeated sampling of training and validation data subsets. Longitudinal observation of individuals re-sampled over 1 or 2 years generally showed an increase in estimated age (6/7 cases). For the first time, we have shown that epigenetic changes with age can be detected in a wild bird. This approach should be of broad interest to researchers studying age biomarkers in non-model species and will allow identification of markers that can be assessed using targeted techniques for accurate age estimation in large population studies.

Multiple endocrine neoplasia type 1: clinical correlates of MEN1 gene methylation.

Multiple endocrine neoplasia type 1 (MEN 1) has marked severity variation between individuals with the same mutation. To investigate any relationship between promoter methylation and clinical features, blood and tissue samples were collected from 16 members of the Tasman 1 MEN 1 kindred carrying a common splice site mutation and 7 patients with sporadic MEN 1. Methylation at 39 CpGs in the MEN1 promoter were assessed in formalin fixed, paraffin embedded parathyroid tissue. Clinical disease severity markers included age at first parathyroid operation, parathyroid hormone level and corrected serum calcium levels. Six patients with sporadic hyperparathyroidism were used for comparison. Minimal methylation was observed in all patients across CpG sites 1-23. In contrast, hypermethylation was observed at CpG sites 24-31 in MEN 1 patients, a pattern not observed in patients with non-MEN 1 parathyroid disease. Mean methylation at sites 24-31 was significantly correlated with age at first parathyroid operation (r = 0.652, p = 0.041). A permutation test, utilising the mean correlation coefficient (r = -0.401) revealed a possible association between relative PHPT severity and methylation score for each significant CpG site (p < 0.103). This novel study reveals evidence supporting a possible association between altered MEN1 promoter methylation and clinical severity of disease.

Measuring Animal Age with DNA Methylation: From Humans to Wild Animals.

DNA methylation (DNAm) is a key mechanism for regulating gene expression in animals and levels are known to change with age. Recent studies have used DNAm changes as a biomarker to estimate chronological age in humans and these techniques are now also being applied to domestic and wild animals. Animal age is widely used to track ongoing changes in ecosystems, however chronological age information is often unavailable for wild animals. An ability to estimate age would lead to improved monitoring of (i) population trends and status and (ii) demographic properties such as age structure and reproductive performance. Recent studies have revealed new examples of DNAm age association in several new species increasing the potential for developing DNAm age biomarkers for a broad range of wild animals. Emerging technologies for measuring DNAm will also enhance our ability to study age-related DNAm changes and to develop new molecular age biomarkers.

DNA methylation levels in candidate genes associated with chronological age in mammals are not conserved in a long-lived seabird.

Most seabirds do not have any outward identifiers of their chronological age, so estimation of seabird population age structure generally requires expensive, long-term banding studies. We investigated the potential to use a molecular age biomarker to estimate age in short-tailed shearwaters (Ardenna tenuirostris). We quantified DNA methylation in several A. tenuirostris genes that have shown age-related methylation changes in mammals. In birds ranging from chicks to 21 years of age, bisulphite treated blood and feather DNA was sequenced and methylation levels analysed in 67 CpG sites in 13 target gene regions. From blood samples, five of the top relationships with age were identified in KCNC3 loci (CpG66: R2 = 0.325, p = 0.019). In feather samples ELOVL2 (CpG42: R2 = 0.285, p = 0.00048) and EDARADD (CpG46: R2 = 0.168, p = 0.0067) were also weakly correlated with age. However, the majority of markers had no clear association with age (of 131 comparisons only 12 had a p-value < 0.05) and statistical analysis using a penalised lasso approach did not produce an accurate ageing model. Our data indicate that some age-related signatures identified in orthologous mammalian genes are not conserved in the long-lived short tailed shearwater. Alternative molecular approaches will be required to identify a reliable biomarker of chronological age in these seabirds.

Comparison of whole-exome sequencing of matched fresh and formalin fixed paraffin embedded melanoma tumours: implications for clinical decision making.

The identification of recurrent driver mutations by whole-exome sequencing (WES) of fresh-frozen human cancers and the subsequent development of novel targeted therapies have recently transformed the treatment of many cancers including melanoma. In routine clinical practice, fresh-frozen tissue is rarely available and mutation testing usually needs to be carried out on archival formalin fixed, paraffin embedded (FFPE) tissue, from which DNA is typically fragmented, cross-linked and of lower quality. In this study we aimed to determine whether WES data generated from genomic DNA (gDNA) extracted from FFPE tissues can be produced reliably and of clinically-actionable standard. In this study of ten melanoma patients, we compared WES data produced from analysis of gDNA isolated from FFPE tumour tissue with that isolated from fresh-frozen tumour tissue from the same specimen. FFPE samples were sequenced using both Illumina's Nextera and NimbleGen SeqCap exome capture kits. To examine mutations between the two tissue sources and platforms, somatic mutations in the FFPE exomes were called using the matched fresh tissue sequence as a reference. Of the 10 FFPE DNA samples, seven Nextera and four SeqCap samples passed library preparation. On average, there were 5341 and 2246 variants lost in FFPE compared to matched fresh tissue utilising Nextera and SeqCap kits, respectively. In order to explore the feasibility of future clinical implementation of WES, FFPE variants in 27 genes of important clinical relevance in melanoma were assessed. The average concordance rate was 43.2% over a total of 1299 calls for the chosen genes in the FFPE DNA. For the current clinically most important melanoma mutations, 0/3 BRAF and 6/8 (75%) NRAS FFPE calls were concordant with the fresh tissue result, which was confirmed using a Sequenom OncoCarta Panel. The poor performance of FFPE WES indicates that specialised library construction to account for low quality DNA and further refinements will be necessary before this approach could be used for routine clinical decision making over currently preferred techniques.

Combining BET and HDAC inhibitors synergistically induces apoptosis of melanoma and suppresses AKT and YAP signaling.

Histone acetylation marks have an important role in controlling gene expression and are removed by histone deacetylases (HDACs). These marks are read by bromodomain and extra-terminal (BET) proteins and novel inhibitiors of these proteins are currently in clinical development. Inhibitors of HDAC and BET proteins have individually been shown to cause apoptosis and reduce growth of melanoma cells. Here we show that combining the HDAC inhibitor LBH589 and BET inhibitor I-BET151 synergistically induce apoptosis of melanoma cells but not of melanocytes. Induction of apoptosis proceeded through the mitochondrial pathway, was caspase dependent and involved upregulation of the BH3 pro-apoptotic protein BIM. Analysis of signal pathways in melanoma cell lines resistant to BRAF inhibitors revealed that treatment with the combination strongly downregulated anti-apoptotic proteins and proteins in the AKT and Hippo/YAP signaling pathways. Xenograft studies showed that the combination of inhibitors was more effective than single drug treatment and confirmed upregulation of BIM and downregulation of XIAP as seen in vitro. These results support the combination of these two classes of epigenetic regulators in treatment of melanoma including those resistant to BRAF inhibitors.

Tumour procurement, DNA extraction, coverage analysis and optimisation of mutation-detection algorithms for human melanoma genomes.

Whole genome sequencing (WGS) of cancer patients' tumours offers the most comprehensive method of identifying both novel and known clinically-actionable genomic targets. However, the practicalities of performing WGS on clinical samples are poorly defined.This study was designed to test sample preparation, sequencing specifications and bioinformatic algorithms for their effect on accuracy and cost-efficiency in a large WGS analysis of human melanoma samples.WGS was performed on melanoma cell lines (n = 15) and melanoma fresh frozen tumours (n = 222). The appropriate level of coverage and the optimal mutation detection algorithm for the project pipeline were determined.An incremental increase in sequencing coverage from 36X to 132X in melanoma tissue samples and 30X to 103X for cell lines only resulted in a small increase (1-2%) in the number of mutations detected, and the quality scores of the additional mutations indicated a low probability that the mutations were real. The results suggest that 60X coverage for melanoma tissue and 40X for melanoma cell lines empower the detection of 98-99% of informative single nucleotide variants (SNVs), a sensitivity level at which clinical decision making or landscape research projects can be carried out with a high degree of confidence in the results. Likewise the bioinformatic mutation analysis methodology strongly influenced the number and quality of SNVs detected. Detecting mutations in the blood genomes separate to the tumour genomes generated 41% more SNVs than if the blood and melanoma tissue genomes were analysed simultaneously. Therefore, simultaneous analysis should be employed on matched melanoma tissue and blood genomes to reduce errors in mutation detection.This study provided valuable insights into the accuracy of SNV with WGS at various coverage levels in human clinical cancer specimens. Additionally, we investigated the accuracy of the publicly available mutation detection algorithms to detect cancer specific SNVs which will aid researchers and clinicians in study design and implementation of WGS for the identification of somatic mutations in other cancers.

UV-Associated Mutations Underlie the Etiology of MCV-Negative Merkel Cell Carcinomas.

Merkel cell carcinoma (MCC) is an uncommon, but highly malignant, cutaneous tumor. Merkel cell polyoma virus (MCV) has been implicated in a majority of MCC tumors; however, viral-negative tumors have been reported to be more prevalent in some geographic regions subject to high sun exposure. While the impact of MCV and viral T-antigens on MCC development has been extensively investigated, little is known about the etiology of viral-negative tumors. We performed targeted capture and massively parallel DNA sequencing of 619 cancer genes to compare the gene mutations and copy number alterations in MCV-positive (n = 13) and -negative (n = 21) MCC tumors and cell lines. We found that MCV-positive tumors displayed very low mutation rates, but MCV-negative tumors exhibited a high mutation burden associated with a UV-induced DNA damage signature. All viral-negative tumors harbored mutations in RB1, TP53, and a high frequency of mutations in NOTCH1 and FAT1. Additional mutated or amplified cancer genes of potential clinical importance included PI3K (PIK3CA, AKT1, PIK3CG) and MAPK (HRAS, NF1) pathway members and the receptor tyrosine kinase FGFR2. Furthermore, looking ahead to potential therapeutic strategies encompassing immune checkpoint inhibitors such as anti-PD-L1, we also assessed the status of T-cell-infiltrating lymphocytes (TIL) and PD-L1 in MCC tumors. A subset of viral-negative tumors exhibited high TILs and PD-L1 expression, corresponding with the higher mutation load within these cancers. Taken together, this study provides new insights into the underlying biology of viral-negative MCC and paves the road for further investigation into new treatment opportunities.