ARTDeco: automatic readthrough transcription detection.
Gene expression
Next-generation sequencing analysis
Readthrough transcription
Transcription termination
Transcriptomics
Journal
BMC bioinformatics
ISSN: 1471-2105
Titre abrégé: BMC Bioinformatics
Pays: England
ID NLM: 100965194
Informations de publication
Date de publication:
26 May 2020
26 May 2020
Historique:
received:
06
02
2020
accepted:
18
05
2020
entrez:
28
5
2020
pubmed:
28
5
2020
medline:
24
7
2020
Statut:
epublish
Résumé
Mounting evidence suggests several diseases and biological processes target transcription termination to misregulate gene expression. Disruption of transcription termination leads to readthrough transcription past the 3' end of genes, which can result in novel transcripts, changes in epigenetic states and altered 3D genome structure. We developed Automatic Readthrough Transcription Detection (ARTDeco), a tool to detect and analyze multiple features of readthrough transcription from RNA-seq and other next-generation sequencing (NGS) assays that profile transcriptional activity. ARTDeco robustly quantifies the global severity of readthrough phenotypes, and reliably identifies individual genes that fail to terminate (readthrough genes), are aberrantly transcribed due to upstream termination failure (read-in genes), and novel transcripts created as a result of readthrough (downstream of gene or DoG transcripts). We used ARTDeco to characterize readthrough transcription observed during influenza A virus (IAV) infection, validating its specificity and sensitivity by comparing its performance in samples infected with a mutant virus that fails to block transcription termination. We verify ARTDeco's ability to detect readthrough as well as identify read-in genes from different experimental assays across multiple experimental systems with known defects in transcriptional termination, and show how these results can be leveraged to improve the interpretation of gene expression and downstream analysis. Applying ARTDeco to a gene expression data set from IAV-infected monocytes from different donors, we find strong evidence that read-in gene-associated expression quantitative trait loci (eQTLs) likely regulate genes upstream of read-in genes. This indicates that taking readthrough transcription into account is important for the interpretation of eQTLs in systems where transcription termination is blocked. ARTDeco aids researchers investigating readthrough transcription in a variety of systems and contexts.
Sections du résumé
BACKGROUND
BACKGROUND
Mounting evidence suggests several diseases and biological processes target transcription termination to misregulate gene expression. Disruption of transcription termination leads to readthrough transcription past the 3' end of genes, which can result in novel transcripts, changes in epigenetic states and altered 3D genome structure.
RESULTS
RESULTS
We developed Automatic Readthrough Transcription Detection (ARTDeco), a tool to detect and analyze multiple features of readthrough transcription from RNA-seq and other next-generation sequencing (NGS) assays that profile transcriptional activity. ARTDeco robustly quantifies the global severity of readthrough phenotypes, and reliably identifies individual genes that fail to terminate (readthrough genes), are aberrantly transcribed due to upstream termination failure (read-in genes), and novel transcripts created as a result of readthrough (downstream of gene or DoG transcripts). We used ARTDeco to characterize readthrough transcription observed during influenza A virus (IAV) infection, validating its specificity and sensitivity by comparing its performance in samples infected with a mutant virus that fails to block transcription termination. We verify ARTDeco's ability to detect readthrough as well as identify read-in genes from different experimental assays across multiple experimental systems with known defects in transcriptional termination, and show how these results can be leveraged to improve the interpretation of gene expression and downstream analysis. Applying ARTDeco to a gene expression data set from IAV-infected monocytes from different donors, we find strong evidence that read-in gene-associated expression quantitative trait loci (eQTLs) likely regulate genes upstream of read-in genes. This indicates that taking readthrough transcription into account is important for the interpretation of eQTLs in systems where transcription termination is blocked.
CONCLUSIONS
CONCLUSIONS
ARTDeco aids researchers investigating readthrough transcription in a variety of systems and contexts.
Identifiants
pubmed: 32456667
doi: 10.1186/s12859-020-03551-0
pii: 10.1186/s12859-020-03551-0
pmc: PMC7249449
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
214Subventions
Organisme : NIGMS NIH HHS
ID : R01 GM134366
Pays : United States
Organisme : NIAID NIH HHS
ID : U19 AI135972
Pays : United States
Organisme : NIGMS NIH HHS
ID : R01 GM129523
Pays : United States
Références
Mol Cell. 1998 Jun;1(7):991-1000
pubmed: 9651582
Cell. 2018 Sep 6;174(6):1522-1536.e22
pubmed: 30146161
Cell. 2016 Oct 20;167(3):643-656.e17
pubmed: 27768888
Genome Biol. 2014;15(12):550
pubmed: 25516281
Cell. 2015 Apr 23;161(3):526-540
pubmed: 25910207
Elife. 2015 Nov 17;4:
pubmed: 26575290
J Virol. 2009 Feb;83(4):1742-53
pubmed: 19073731
Cell Rep. 2018 May 15;23(7):2119-2129.e3
pubmed: 29768209
Cell Rep. 2017 Nov 28;21(9):2433-2446
pubmed: 29186682
Mol Cell. 2010 May 28;38(4):576-89
pubmed: 20513432
Mol Cell. 2015 Jun 18;58(6):1101-12
pubmed: 26028540
Mol Cell. 2015 Aug 6;59(3):437-48
pubmed: 26166703
BMC Genomics. 2018 Aug 8;19(1):597
pubmed: 30089468
Bioinformatics. 2009 Aug 15;25(16):2078-9
pubmed: 19505943
Science. 2013 Jun 28;340(6140):1577-80
pubmed: 23812715
Nat Commun. 2015 May 20;6:7126
pubmed: 25989971
Trends Genet. 2005 Jun;21(6):339-45
pubmed: 15922833
Genes Dev. 2009 Jun 1;23(11):1247-69
pubmed: 19487567
Bioinformatics. 2012 Aug 15;28(16):2184-5
pubmed: 22743226
Proc Natl Acad Sci U S A. 2017 Oct 3;114(40):E8362-E8371
pubmed: 28928151
Genes Dev. 2008 Apr 15;22(8):1082-92
pubmed: 18413718
Bioinformatics. 2012 Jul 15;28(14):1919-20
pubmed: 22576172
PLoS Comput Biol. 2012;8(2):e1002386
pubmed: 22359495
PLoS Pathog. 2018 Mar 26;14(3):e1006954
pubmed: 29579120
PLoS One. 2019 Apr 8;14(4):e0206715
pubmed: 30958820
Mol Cell. 2002 May;9(5):1101-11
pubmed: 12049745
Nature. 2004 Nov 25;432(7016):522-5
pubmed: 15565158
Nat Genet. 2000 May;25(1):25-9
pubmed: 10802651
Nat Struct Mol Biol. 2018 Sep;25(9):885-893
pubmed: 30177761
Nature. 2004 Nov 25;432(7016):517-22
pubmed: 15565157
PLoS Comput Biol. 2012;8(5):e1002514
pubmed: 22615551
Mol Cell. 2015 Aug 6;59(3):449-61
pubmed: 26190259
EMBO J. 1998 Aug 17;17(16):4771-9
pubmed: 9707436
Mol Cell Biol. 2018 Aug 28;38(18):
pubmed: 29967245