Transcriptional landscape analysis using direct RNA sequencing

The Saccharomyces cerevisiae strain CEN.PK113-7D is used extensively in academic and industrial research due to a combination of ease of genetic manipulation and a fast growth rate. In order to provide detailed insight into this organism, researchers at the University of Arkansas first utilised nanopore sequencing to create a complete genome assembly, using long reads to improve upon the existing, fragmented short-read based assembly1. The team then performed direct RNA sequencing to determine gene expression patterns under two different growth conditions (diauxic growth). Examining the data revealed distinctive gene expression profiles for yeast replicates grown on glucose versus ethanol (Figure 1). As expected, organisms using ethanol as a growth substrate had significant increases in transcripts related to ethanol metabolism and cellular stresses, while up-regulated genes in the glucose group were associated with rapid growth processes and ethanol fermentation.

The team found that approximately 70% of the reads provided by direct RNA sequencing corresponded to full-length transcripts and, in addition, full-length transcripts over 5 kb could be detected. A comparison of direct RNA sequencing using nanopore technology with data obtained using a short-read sequencing technology revealed that, while the total amount of data was approximately half of that achieved using short reads, the mean coverage depth was comparable (Figure 2). Furthermore, there was evidence to suggest that the nanopore reads exhibited lower GC-bias than short-read RNA analysis technology2. Long-read, direct RNA sequencing also allowed the identification of many polyadenylated non-coding RNAs, including rRNA, telomerase RNA, and long non-coding RNA (lncRNA)1. Summarising, the team stated: ‘We believe that direct RNA sequencing will become a versatile tool for transcriptome analysis in the “complete genome era” of the future’.

Figure 1: Direct RNA sequencing allowed the identification of distinctive gene expression profiles for yeast replicates grown on glucose (blue) or ethanol (yellow). Image courtesy of Dr. Intawat Nookaew, University of Arkansas, USA.

Figure 2: The dynamic range of transcripts generated from 500 Mb of direct RNA sequencing data was similar to that obtained from 1,000 Mb of short-read sequencing technology data as shown by the mean coverage depth box plot. Image courtesy of Dr. Intawat Nookaew, University of Arkansas, USA.
  1. Jenjaroenpun, P. et al. Complete genomic and transcriptional landscape analysis using third-generation sequencing: a case study of Saccharomyces cerevisiae CEN.PK113- 7D. Nucleic Acids Res. 6(7):e38 (2018).
  2. Nookaew, I. Transcriptional landscapes analysis through direct RNA sequencing. Presentation.