Content area
Nanopore-technology offers real-time sequencing opportunities, providing rapid access to sequenced data and allowing researchers to manage the sequencing process efficiently, resulting in cost-effective strategies. Here, we present focused case studies demonstrating the versatility of real-time transcriptomics analysis in rapid quality control for long-read RNA-seq. We illustrate its utility through three experimental setups: 1) transcriptome profiling of distinct human cellular populations, 2) identification of experimentally enriched transcripts, and 3) identification of experimentally manipulated genes (knockout and overexpression) in several yeast strains. We show how to perform multiple layers of quality control as soon as sequencing has started, addressing both the quality of the experimental and sequencing traits. Real-time quality control measures comprise assessing sample/condition variability and determining the number of identified genes per sample/condition. Furthermore, real-time differential gene/transcript expression analysis can be conducted at various time points post-sequencing initiation (PSI), revealing dynamic changes in gene/transcript expression between two conditions. Using real-time analysis, which occurs in parallel to the sequencing run, we identified differentially expressed genes/transcripts as early as 1-hour PSI. These changes were consistently observed throughout the entire sequencing process. We discuss the new possibilities offered by real-time data analysis, which have the potential to serve as a valuable tool for rapid and cost-effective quality checks in specific experimental settings and can be potentially integrated into clinical applications in the future.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
* We revised the manuscript, addressing two key points: 1) Replicate number: We expanded the HEK293 vs HeLa transcriptomics analysis to include 10 replicates per condition (Figure 2 revised). Our results show consistent performance and reproducibility, even when compared to the initial experiment with only 2 replicates per condition. 2) Biological relevance: To increase the biological significance, we conducted heat-shock experiments, demonstrating NanopoReaTA's ability to accurately identify condition-specific differentially expressed genes (DEGs) in a relevant biological context (added Figure 4). 3) Figure 5 and 6 were updated providing a clearer and more realistic comparison between mutant and wild-type conditions in the main figure. 4) We have separated the supplementary figures document into 5 supplementary documents containing the relevant supplementary figures to each experimental setup in an organized manner. We think it is important to showcase the type of insights NanopoReaTA can deliver, particularly the dynamic changes observed at each time point.