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Transcriptome profiling of mouse samples using nanopore sequencing of cDNA and RNA molecules
- Source :
- Scientific Reports, Vol 9, Iss 1, Pp 1-12 (2019), Scientific Reports, Scientific Reports, Nature Publishing Group, 2019, 9 (1), pp.14908. ⟨10.1038/s41598-019-51470-9⟩, Scientific Reports, 2019, 9 (1), pp.14908. ⟨10.1038/s41598-019-51470-9⟩
- Publication Year :
- 2019
- Publisher :
- Nature Publishing Group, 2019.
-
Abstract
- Our vision of DNA transcription and splicing has changed dramatically with the introduction of short-read sequencing. These high-throughput sequencing technologies promised to unravel the complexity of any transcriptome. Generally gene expression levels are well-captured using these technologies, but there are still remaining caveats due to the limited read length and the fact that RNA molecules had to be reverse transcribed before sequencing. Oxford Nanopore Technologies has recently launched a portable sequencer which offers the possibility of sequencing long reads and most importantly RNA molecules. Here we generated a full mouse transcriptome from brain and liver using the Oxford Nanopore device. As a comparison, we sequenced RNA (RNA-Seq) and cDNA (cDNA-Seq) molecules using both long and short reads technologies and tested the TeloPrime preparation kit, dedicated to the enrichment of full-length transcripts. Using spike-in data, we confirmed that expression levels are efficiently captured by cDNA-Seq using short reads. More importantly, Oxford Nanopore RNA-Seq tends to be more efficient, while cDNA-Seq appears to be more biased. We further show that the cDNA library preparation of the Nanopore protocol induces read truncation for transcripts containing internal runs of T’s. This bias is marked for runs of at least 15 T’s, but is already detectable for runs of at least 9 T’s and therefore concerns more than 20% of expressed transcripts in mouse brain and liver. Finally, we outline that bioinformatics challenges remain ahead for quantifying at the transcript level, especially when reads are not full-length. Accurate quantification of repeat-associated genes such as processed pseudogenes also remains difficult, and we show that current mapping protocols which map reads to the genome largely over-estimate their expression, at the expense of their parent gene. The entire dataset is available from http://www.genoscope.cns.fr/externe/ONT_mouse_RNA.
- Subjects :
- DNA, Complementary
Pseudogene
[SDV]Life Sciences [q-bio]
0206 medical engineering
Datasets as Topic
lcsh:Medicine
02 engineering and technology
Computational biology
Biology
Article
Transcriptome
Mice
03 medical and health sciences
Complementary DNA
Animals
RNA-Seq
lcsh:Science
Gene
ComputingMilieux_MISCELLANEOUS
Gene Library
030304 developmental biology
0303 health sciences
cDNA library
lcsh:R
Brain
High-Throughput Nucleotide Sequencing
RNA
RNA sequencing
Sequence Analysis, DNA
Computational biology and bioinformatics
Nanopore Sequencing
Liver
RNA splicing
lcsh:Q
Nanopore sequencing
[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]
020602 bioinformatics
Subjects
Details
- Language :
- English
- ISSN :
- 20452322
- Volume :
- 9
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Scientific Reports
- Accession number :
- edsair.doi.dedup.....e26427d330f5cf2645271f5e11fb9747
- Full Text :
- https://doi.org/10.1038/s41598-019-51470-9