Quantitative visualization of alternative exon expression from RNA-seq data

Katz, Yarden; Wang, Eric T.; Silterra, Jacob; Schwartz, Schraga; Wong, Bang; Thorvaldsdóttir, Helga; Robinson, James T.; Mesirov, Jill P.; Airoldi, Edoardo M.; Burge, Christopher B.

doi:10.1093/bioinformatics/btv034

Cited by 155 publications

(132 citation statements)

References 8 publications

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“…We used Sashimi plots (Katz et al, 2015) to visualize splicing changes in RNA-seq data, across sets of samples that had, or lacked, particular mutations.…”

Section: Methodsmentioning

confidence: 99%

Integrative Analysis Identifies Four Molecular and Clinical Subsets in Uveal Melanoma

Robertson¹,

Shih²,

Yau³

et al. 2017

Cancer Cell

711

712

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SUMMARY Comprehensive multiplatform analysis of 80 uveal melanomas (UM) identifies four molecularly distinct, clinically relevant subtypes: two associated with poor-prognosis monosomy 3 (M3) and two with better-prognosis disomy 3 (D3). We show that BAP1 loss follows M3 occurrence and correlates with a global DNA methylation state that is distinct from D3-UM. Poor-prognosis M3-UM divide into subsets with divergent genomic aberrations, transcriptional features, and clinical outcomes. We report change-of-function SRSF2 mutations. Within D3-UM, EIF1AX- and SRSF2/SF3B1 -mutant tumors have distinct somatic copy number alterations and DNA methylation profiles, providing insight into the biology of these low-versus intermediate-risk clinical mutation subtypes.

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“…We used Sashimi plots (Katz et al, 2015) to visualize splicing changes in RNA-seq data, across sets of samples that had, or lacked, particular mutations.…”

Section: Methodsmentioning

confidence: 99%

Integrative Analysis Identifies Four Molecular and Clinical Subsets in Uveal Melanoma

Robertson¹,

Shih²,

Yau³

et al. 2017

Cancer Cell

711

712

View full text Add to dashboard Cite

show abstract

“…RNA-seq datasets were first quality assessed using FastQC (Andrews, 2010), trimmed with BBDuk (parameters ktrim = r, k = 21, mink = 10, hdist = 1) (Bushnell, 2015), aligned using HISAT2 (option -U -S), and sorted and indexed with Samtools (Li et al, 2009). Splicing events were visualized in IGV (sashimi plot function) to enumerate the intron-spanning reads between avian exons 4, 5, and 6 (Katz et al, 2015). …”

Section: Star⋆methodsmentioning

confidence: 99%

Differential Splicing of ANP32A in Birds Alters Its Ability to Stimulate RNA Synthesis by Restricted Influenza Polymerase

2018

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SUMMARY Adaptation of viruses to their hosts can result in specialization and a restricted host range. Species specific polymorphisms in the influenza virus polymerase restrict its host range during transmission from birds to mammals. ANP32A was recently identified as a cellular co-factor affecting polymerase adaption and activity. Avian influenza polymerases require ANP32A containing an insertion resulting from an exon duplication uniquely encoded in birds. Here we find that natural splice variants surrounding this exon create avian ANP32A proteins with distinct effects on polymerase activity. We demonstrate species-independent direct interactions between all ANP32A variants and the PB2 polymerase subunit. This interaction is enhanced in the presence of viral genomic RNA. In contrast, only avian ANP32A restored ribonucleoprotein complex assembly for a restricted polymerase by enhancing RNA synthesis. Our data suggest that ANP32A splicing variation among birds differentially affects viral replication, polymerase adaption, and the potential of avian hosts to be reservoirs.

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“…(b) Densities of GC content of isoform-specific regions from genes with two isoforms when one or more reported differential expression, compared to GC content of random exons. (c) Sashimi plot 30 for GEUVADIS samples in a region of the USF2 gene containing the alternative exon distinguishing two isoforms, with the GC content of each exon listed below the gene model. Samples from center 1 had a drop-out in coverage on the high GC exons, including the alternative exon.…”

Section: Figurementioning

confidence: 99%

Modeling of RNA-seq fragment sequence bias reduces systematic errors in transcript abundance estimation

2016

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Quantitative visualization of alternative exon expression from RNA-seq data

Abstract: Software code and documentation freely available here: http://miso.readthedocs.org/en/fastmiso/sashimi.html

Cited by 155 publications

References 8 publications

Integrative Analysis Identifies Four Molecular and Clinical Subsets in Uveal Melanoma

Integrative Analysis Identifies Four Molecular and Clinical Subsets in Uveal Melanoma

Differential Splicing of ANP32A in Birds Alters Its Ability to Stimulate RNA Synthesis by Restricted Influenza Polymerase

Modeling of RNA-seq fragment sequence bias reduces systematic errors in transcript abundance estimation

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