Anatomy and Neuroscience - Research Publications
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ItemPervasive effects of RNA degradation on Nanopore direct RNA sequencing(Oxford University Press, 2023-03-29)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.
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ItemIdentification of cell barcodes from long-read single-cell RNA-seq with BLAZE(BMC, 2023-04-06)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 .
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ItemNo Preview AvailableUsing long-read RNA sequencing to decipher the role of RNA isoforms in disease(Elsevier BV, 2022-03)Accurate quantification of genes and their mRNA products is essential to understanding health and disease. In humans, processes such as alternative splicing cause almost all genes to express multiple mRNA products (isoforms), which can have different functions. In addition, aberrant splicing is a common cause of disease. Standard short-read RNA sequencing (RNA-seq) methodologies have limitations in identifying isoforms. In contrast, long-read RNA-seq can address this challenge by covering the entire mRNA sequence in a single read and so identify and quantify the isoforms present. We have utilised long-read RNA-seq to characterise isoforms involved in disease risk, genetic disease and viral infection. Investigation of >30 neuropsychiatric disease risk genes in human brain identified hundreds of novel isoforms, including many genes where most expression was from previously undiscovered isoforms. Exemplifying this, the calcium channel CACNA1C expressed >200 novel isoforms with abundant splice variants modifying channel regions regulating activation voltage and channel conductance. The accurate characterisation of RNA isoforms enabled by long-read RNA-seq enables the translation of genomic findings into a pathophysiological understanding of disease.
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ItemLong-Read RNA Sequencing Identifies Polyadenylation Elongation and Differential Transcript Usage of Host Transcripts During SARS-CoV-2 In Vitro Infection(FRONTIERS MEDIA SA, 2022-04-06)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.
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ItemIsoform Age-Splice Isoform Profiling Using Long-Read Technologies (vol 8, 744, 2021)(FRONTIERS MEDIA SA, 2021-09-27)[This corrects the article DOI: 10.3389/fmolb.2021.711733.].
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ItemAge estimation in a long-lived seabird (Ardenna tenuirostris) using DNA methylation-based biomarkers(WILEY, 2019-03)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.
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ItemTranscriptional and epi-transcriptional dynamics of SARS-CoV-2 during cellular infection(CELL PRESS, 2021-05-11)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.
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ItemThe long and the short of it: unlocking nanopore long-read RNA sequencing data with short-read differential expression analysis tools(Oxford University Press, 2021-06-01)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.
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ItemMultiomic analysis elucidates Complex I deficiency caused by a deep intronic variant in NDUFB10(WILEY-HINDAWI, 2021-01)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.
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ItemPan-cancer analysis of whole genomes(NATURE PUBLISHING GROUP, 2020-02-06)Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1-3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10-18.