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Transcriptome profiling of mouse samples using nanopore sequencing of cDNA and RNA molecules

Publication

Date: 17th October 2019 | Source: Scientific Reports

Authors: Camille Sessegolo, Corinne Cruaud, Corinne Da Silva, Marion Dubarry, Thomas Derrien, Vincent Lacroix, Jean-Marc Aury.

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.

Read the full text RNA sequencing white paper

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