Oxford Nanopore MinION Direct RNA-Seq for Systems Biology

SIMPLE SUMMARY: A new technology has been recently developed by Oxford Nanopore Technologies, enabling researchers to investigate the structure and relative abundance of specific molecules, ribonucleic acids. The ribonucleic acids carry information from the genes to proteins, which are responsible for virtually every process in the human organism, including disease progression and response to therapies. Special computational methods allow identification of various activated biological processes by analyzing the changes in concentrations of ribonucleic acids. This is of particular interest for precision medicine which aims at single-patient analysis. Here we evaluated whether ribonucleic acid abundances measured by new technology are suited for robust predictions of activated biological processes in single samples. We performed simulations varying the number of experimental replicates and analysed activated biological processes’ predictions using two algorithms. In brief, we found that at least two replicates are required to obtain reproducible results. We hope that our findings may be of interest to researchers planning their nanopore experiments and may stimulate further development of clinical applications of this technology. ABSTRACT: Long-read direct RNA sequencing developed by Oxford Nanopore Technologies (ONT) is quickly gaining popularity for transcriptome studies, while fast turnaround time and low cost make it an attractive instrument for clinical applications. There is a growing interest to utilize transcriptome data to unravel activated biological processes responsible for disease progression and response to therapies. This trend is of particular interest for precision medicine which aims at single-patient analysis. Here we evaluated whether gene abundances measured by MinION direct RNA sequencing are suited to produce robust estimates of pathway activation for single sample scoring methods. We performed multiple RNA-seq analyses for a single sample that originated from the HepG2 cell line, namely five ONT replicates, and three replicates using Illumina NovaSeq. Two pathway scoring methods were employed—ssGSEA and singscore. We estimated the ONT performance in terms of detected protein-coding genes and average pairwise correlation between pathway activation scores using an exhaustive computational scheme for all combinations of replicates. In brief, we found that at least two ONT replicates are required to obtain reproducible pathway scores for both algorithms. We hope that our findings may be of interest to researchers planning their ONT direct RNA-seq experiments.