Meta-Analysis Suggests That Intron Retention Can Affect Quantification of Transposable Elements from RNA-Seq Data.
RNA-seq
bioinformatics
intron retention
technical bias
transcriptomic
transposable elements expression quantification
Journal
Biology
ISSN: 2079-7737
Titre abrégé: Biology (Basel)
Pays: Switzerland
ID NLM: 101587988
Informations de publication
Date de publication:
27 May 2022
27 May 2022
Historique:
received:
15
04
2022
revised:
20
05
2022
accepted:
26
05
2022
entrez:
24
6
2022
pubmed:
25
6
2022
medline:
25
6
2022
Statut:
epublish
Résumé
Transposable elements (TEs), also known as "jumping genes", are repetitive sequences with the capability of changing their location within the genome. They are key players in many different biological processes in health and disease. Therefore, a reliable quantification of their expression as transcriptional units is crucial to distinguish between their independent expression and the transcription of their sequences as part of canonical transcripts. TEs quantification faces difficulties of different types, the most important one being low reads mappability due to their repetitive nature preventing an unambiguous mapping of reads originating from their sequences. A large fraction of TEs fragments localizes within introns, which led to the hypothesis that intron retention (IR) can be an additional source of bias, potentially affecting accurate TEs quantification. IR occurs when introns, normally removed from the mature transcript by the splicing machinery, are maintained in mature transcripts. IR is a widespread mechanism affecting many different genes with cell type-specific patterns. We hypothesized that, in an RNA-seq experiment, reads derived from retained introns can introduce a bias in the detection of overlapping, independent TEs RNA expression. In this study we performed meta-analysis using public RNA-seq data from lymphoblastoid cell lines and show that IR can impact TEs quantification using established tools with default parameters. Reads mapped on intronic TEs were indeed associated to the expression of TEs and influence their correct quantification as independent transcriptional units. We confirmed these results using additional independent datasets, demonstrating that this bias does not appear in samples where IR is not present and that differential TEs expression does not impact on IR quantification. We concluded that IR causes the over-quantification of intronic TEs and differential IR might be confused with differential TEs expression. Our results should be taken into account for a correct quantification of TEs expression from RNA-seq data, especially in samples in which IR is abundant.
Identifiants
pubmed: 35741347
pii: biology11060826
doi: 10.3390/biology11060826
pmc: PMC9220773
pii:
doi:
Types de publication
Journal Article
Langues
eng
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