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Exploring differential exon usage via short- and long-read RNA sequencing strategies

Alternative splicing produces various mRNAs, and thereby various protein products, from one gene, impacting a wide range of cellular activities. However, accurate reconstruction and quantification of full-length transcripts using short-reads is limited, due to their length. Long-reads sequencing tec...

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Detalles Bibliográficos
Autores principales: Leshkowitz, Dena, Kedmi, Merav, Fried, Yael, Pilzer, David, Keren-Shaul, Hadas, Ainbinder, Elena, Dassa, Bareket
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9516339/
https://www.ncbi.nlm.nih.gov/pubmed/36168804
http://dx.doi.org/10.1098/rsob.220206
Descripción
Sumario:Alternative splicing produces various mRNAs, and thereby various protein products, from one gene, impacting a wide range of cellular activities. However, accurate reconstruction and quantification of full-length transcripts using short-reads is limited, due to their length. Long-reads sequencing technologies may provide a solution by sequencing full-length transcripts. We explored the use of both Illumina short-reads and two long Oxford Nanopore Technology (cDNA and Direct RNA) RNA-Seq reads for detecting global differential splicing during mouse embryonic stem cell differentiation, applying several bioinformatics strategies: gene-based, isoform-based and exon-based. We detected the strongest similarity among the sequencing platforms at the gene level compared to exon-based and isoform-based. Furthermore, the exon-based strategy discovered many differential exon usage (DEU) events, mostly in a platform-dependent manner and in non-differentially expressed genes. Thus, the platforms complemented each other in the ability to detect DEUs (i.e. long-reads exhibited an advantage in detecting DEUs at the UTRs, and short-reads detected more DEUs). Exons within 20 genes, detected in one or more platforms, were here validated by PCR, including key differentiation genes, such as Mdb3 and Aplp1. We provide an important analysis resource for discovering transcriptome changes during stem cell differentiation and insights for analysing such data.