Native RNA or cDNA Sequencing for Transcriptomic Analysis: A Case Study on Saccharomyces cerevisiae

Abstract

Direct sequencing of single molecules through nanopores allows for accurate quantification and full-length characterization of native RNA or complementary DNA (cDNA) without amplification. Both nanopore-based native RNA and cDNA approaches involve complex transcriptome procedures at a lower cost. However, there are several differences between the two approaches. In this study, we perform matched native RNA sequencing and cDNA sequencing to enable relevant comparisons and evaluation. Using Saccharomyces cerevisiae, a eukaryotic model organism widely used in industrial biotechnology, two different growing conditions are considered for comparison, including the poly-A messenger RNA isolated from yeast cells grown in minimum media under respirofermentative conditions supplemented with glucose (glucose growth conditions) and from cells that had shifted to ethanol as a carbon source (ethanol growth conditions). Library preparation for direct RNA sequencing is shorter than that for direct cDNA sequencing. The sequence characteristics of the two methods were different, such as sequence yields, quality score of reads, read length distribution, and mapped on reference ability of reads. However, differential gene expression analyses derived from the two approaches are comparable. The unique feature of direct RNA sequencing is RNA modification; we found that the RNA modification at the 5′ end of a transcript was underestimated due to the 3′ bias behavior of the direct RNA sequencing. Our comprehensive evaluation from this work could help researchers make informed choices when selecting an appropriate long-read sequencing method for understanding gene functions, pathways, and detailed functional characterization.

Benchmarking long-read RNA-sequencing analysis tools usingin silicomixtures

“…For instance, Soneson et al . [9] and Wongsurawat et al[10] compared Oxford Nanopore Technologies (ONT) direct RNA-seq to direct cDNA-seq and Sessegolo et al[11] compared ONT PCR cDNA-seq to direct RNA-seq. In the recent Singapore Nanopore Expression Project (SG-NEx), Chen et al .…”

“…Several benchmark studies for long-read bulk RNA-seq have focused on the comparison of sequencing protocols by analysing data from matched samples. For instance, Soneson et al [9] and Wongsurawat et al [10] compared Oxford Nanopore Technologies (ONT) direct RNA-seq to direct cDNA-seq and Sessegolo et al [11] compared ONT PCR cDNA-seq to direct RNA-seq. In the recent Singapore Nanopore Expression Project (SG-NEx), Chen et al [12] generated a dataset containing 5 human cancer cell lines sequenced by 4 different protocols: ONT direct RNA-seq, direct cDNA-seq, PCR cDNA-seq and Illumina RNA-seq.…”

“…[9] and Wongsurawat et al . [10] compared Oxford Nanopore Technologies (ONT) direct RNA-seq to direct cDNA-seq and Sessegolo et al . [11] compared ONT PCR cDNA-seq to direct RNA-seq.…”

Enhancing transcriptome expression quantification through accurate assignment of long RNA sequencing reads with TranSigner

“…We’ll approximate the 5’ end and 3’ end positions of a read in a transcript as the positions where the read alignment starts and ends on that transcript, respectively. Different long-read RNA-seq technologies show various biases towards the ends of the transcripts (Amarasinghe et al, 2020; Chen et al, 2021; Grünberger et al, 2022; Wongsurawat et al, 2022). Nonetheless, long reads are more likely to cover all bases of a transcript, compared to the short reads, which are generated from fragments of the transcript.…”

Merging short and stranded long reads improves transcript assembly

“…For long-read RNA-seq, RNA was polyadenylated for use with polyT primers, then subjected to library preparation using the Oxford Nanopore direct cDNA sequencing kit, and run on a MinION sequencer. We chose the cDNA sequencing platform as it has higher yield than the direct RNA sequencing platform [45]. We obtained ~1.2M and 3M reads for HAP1 replicates, and ~1.8M and 2.5M reads for HL1 replicates and subjected them to our analysis pipeline (S1 Table ).…”