ggsashimi: Sashimi plot revised for browser- and annotation-independent splicing visualization

Garrido-Martín, Diego; Palumbo, Emilio; Guigó, Roderic; Breschi, Alessandra

doi:10.1371/journal.pcbi.1006360

Cited by 191 publications

(149 citation statements)

References 7 publications

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“…These counts were either combined with a count matrix of the human genes quantified by STAR and TMM/CPM normalized with edgeR ( Figure S1D) or normalized by the total number of viral junctionspanning reads per time point ( Figure S1E) [93]. Coverage plots were made from merged STAR-mapped BAM files, or from Bowtie-mapped small RNA-seq BAM files using ggsashimi [94]. This workflow was implemented with custom Python scripts in a Snakemake pipeline [95].…”

Section: Viral Rna-seq Analysismentioning

confidence: 99%

Bulk and single-cell gene expression profiling of SARS-CoV-2 infected human cell lines identifies molecular targets for therapeutic intervention

Wyler

Mösbauer

Franke

et al. 2020

Preprint

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The coronavirus disease 2019 pandemic, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is an ongoing global health threat with more than two million infected people since its emergence in late 2019. Detailed knowledge of the molecular biology of the infection is indispensable for understanding of the viral replication, host responses, and disease progression. We provide gene expression profiles of SARS-CoV and SARS-CoV-2 infections in three human cell lines (H1299, Caco-2 and Calu-3 cells), using bulk and single-cell transcriptomics. Small RNA profiling showed strong expression of the immunity and inflammation-associated microRNA miRNA-155 upon infection with both viruses. SARS-CoV-2 elicited approximately two-fold higher stimulation of the interferon response compared to SARS-CoV in the permissive human epithelial cell line Calu-3, and induction of cytokines such as CXCL10 or IL6. Single cell RNA sequencing data showed that canonical interferon stimulated genes such as IFIT2 or OAS2 were broadly induced, whereas interferon beta (IFNB1) and lambda (IFNL1-4) were expressed only in a subset of infected cells. In addition, temporal resolution of transcriptional responses suggested interferon regulatory factors (IRFs) activities precede that of nuclear factor-κB (NF-κB). Lastly, we identified heat shock protein 90 (HSP90) as a protein relevant for the infection. Inhibition of the HSP90 charperone activity by Tanespimycin/17-N-allylamino-17-demethoxygeldanamycin (17-AAG) resulted in a reduction of viral replication, and of TNF and IL1B mRNA levels. In summary, our study established in vitro cell culture models to study SARS-CoV-2 infection and identified HSP90 protein as potential drug target for therapeutic intervention of SARS-CoV-2 infection.

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Section: Viral Rna-seq Analysismentioning

confidence: 99%

Bulk and single-cell gene expression profiling of SARS-CoV-2 infected human cell lines identifies molecular targets for therapeutic intervention

Wyler

Mösbauer

Franke

et al. 2020

Preprint

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“…Heatmaps and charts were visualized using Cummerbund (Trapnell et al, 2012), and Integrative Genomics Viewer (Thorvaldsdottir et al, 2013) was used for visualization of read depths and alignments. Sashimi plots were generated with ggsashimi using the alignment files generated with TopHat2 and hg19 annotation (Garrido-Martin et al, 2018).…”

Section: Rna-seqmentioning

confidence: 99%

Pleiotropic requirements for human TDP-43 in the regulation of cell and organelle homeostasis

Roczniak-Ferguson

Ferguson

2019

Preprint

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TDP-43 is an RNA-binding protein that forms cytoplasmic aggregates in multiple neurodegenerative diseases. Although the loss of normal TDP-43 functions likely contributes to disease pathogenesis, the cell biological consequences of human TDP-43 depletion are not well understood. We therefore generated human TDP-43 knockout cells and subjected them to parallel cell biological and transcriptomic analyses. These efforts yielded three important discoveries. First, complete loss of TDP-43 resulted in widespread morphological defects related to multiple organelles including: Golgi, endosomes, lysosomes, mitochondria and the nuclear envelope. Second, we identified a new role for TDP-43 in controlling mRNA splicing of Nup188 (nuclear pore protein). Third, analysis of multiple amyotrophic lateral sclerosis (ALS) causing TDP-43 mutations revealed a broad ability to support splicing of TDP-43 target genes. However, as some TDP-43 disease causing mutants failed to support the regulation of specific target transcripts, our results raise the possibility of mutation-specific loss-of-function contributions to disease pathology.

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“…b) Exonic structure of the isoforms and location of exons 5, 6 and 7 (highlighted area). Compared to RBM23-001 (green), RBM23-002 (blue) lacks exon 6, and RBM23-003 (red), exons 4 and 6. c) Sashimi plot (corresponding to the highlighted area in b) displaying the mean exon inclusion of exon 6 of RBM23 across all brain cortex samples of each genotype group at rs2295682, obtained by ggsashimi 84 . The dashed line marks the location of the SNP.…”

Section: Introductionmentioning

confidence: 99%

“…Then, we employed REVIGO 75 79 (http://revigo.irb.hr/, with parameters: allowed similarity = 0.9, database = H. sapiens, semantic 80 metric = SimRel) to remove highly redundant terms and generate semantic similarity-based GO term 81 representations for sGenes and non-sGenes. 82 sQTL replication 83 To assess replication of GTEx sQTLs, we examined the p values for matched variant-gene pairs identified 84 as splicing QTLs by sQTLseekeR for three immune cell types (CD14 + monocytes, CD16 + neutrophils, and 85 naive CD4 + T cells) in the Blueprint Project (BP) 27 . Both studies have large differences in RNA sources 86 (tissues in GTEx vs cell types in Blueprint), library preparation (unstranded polyA + vs stranded Ribo-Zero), 87 sequencing strategy (e.g.…”

mentioning

confidence: 99%

Identification and analysis of splicing quantitative trait loci across multiple tissues in the human genome

Garrido-Martín

Borsari

Calvo

et al. 2020

Preprint

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We have developed an efficient and reproducible pipeline for the discovery of genetic variants affecting splicing (sQTLs), based on an approach that captures the intrinsically multivariate nature of this phenomenon. We employed it to analyze the multi-tissue transcriptome GTEx dataset, generating a comprehensive catalogue of sQTLs in the human genome. A core set of these sQTLs is shared across multiple tissues. Downstream analyses of this catalogue contribute to the understanding of the mechanisms underlying splicing regulation. We found that sQTLs often target the global splicing pattern of genes, rather than individual splicing events. Many of them also affect gene expression, but not always of the same gene, potentially uncovering regulatory loci that act on different genes through different mechanisms. sQTLs tend to be preferentially located in introns that are post-transcriptionally spliced, which would act as hotspots for splicing regulation. While many variants affect splicing patterns by directly altering the sequence of splice sites, many more modify the binding of RNA-binding proteins (RBPs) to target sequences within the transcripts. Genetic variants affecting splicing can have a phenotypic impact comparable or even stronger than variants affecting expression, with those that alter RBP binding playing a prominent role in disease. 33 splice sites, many more modify the binding of RNA-binding proteins (RBPs) to target sequences within 34 the transcripts. We have observed that sQTLs often impact GWAS traits and diseases more than variants 35 affecting only gene expression, confirming earlier reports which suggest that splicing mutations underlie 36 many hereditary diseases 15,19 . For many conditions, GWAS associations are particularly strong for sQTLs 37 3 altering RBP binding sites. 40 For sQTL mapping, we developed sQTLseekeR2, a software based on sQTLseekeR 20 , which identi-41 fies genetic variants associated with changes in the relative abundances of the transcript isoforms of a 42 given gene. sQTLseekeR uses the Hellinger distance to estimate the variability of isoform abundances 43 across observations, and Anderson's method 21,22 , a non-parametric analogue to multivariate analysis 44 of variance, to assess the significance of the associations (see Methods and Supplementary Note 1). 45 Among other enhancements, sQTLseekeR2 improves the accuracy and speed of the p value calcula-46 tion, and allows to account for additional covariates before testing for association with the genotype, 47 while maintaining the multivariate statistical test in sQTLseekeR. It also implements a multiple testing 48 correction scheme that empirically characterizes, for each gene, the distribution of p values expected un-49 der the null hypothesis of no association (see Methods and Supplementary Note 1). To ensure highly 50 parallel, portable and reproducible sQTL mapping, we embedded sQTLseekeR2 in a Nextflow 23 (plus 51 Docker, https://www.docker.com/) computational workflow named sqtlseeker2-nf, available at 52 https://gi...

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ggsashimi: Sashimi plot revised for browser- and annotation-independent splicing visualization

Cited by 191 publications

References 7 publications

Bulk and single-cell gene expression profiling of SARS-CoV-2 infected human cell lines identifies molecular targets for therapeutic intervention

Bulk and single-cell gene expression profiling of SARS-CoV-2 infected human cell lines identifies molecular targets for therapeutic intervention

Pleiotropic requirements for human TDP-43 in the regulation of cell and organelle homeostasis

Identification and analysis of splicing quantitative trait loci across multiple tissues in the human genome

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