High-resolution transcriptome analysis with long-read RNA sequencing

TL;DR

This study compares short-read and long-read RNA sequencing, demonstrating that longer reads improve transcriptome analysis accuracy, especially in detecting regulatory and splicing variations, despite higher costs.

Contribution

It provides a systematic comparison of read lengths in RNA-seq, highlighting the advantages of long-read sequencing for transcriptome analysis.

Findings

Longer reads reduce mapping bias and ambiguity.

Long-read sequencing improves detection of allele-specific expression.

Benefits outweigh costs for detailed transcriptome insights.

Abstract

RNA sequencing (RNA-seq) enables characterization and quantification of individual transcriptomes as well as detection of patterns of allelic expression and alternative splicing. Current RNA-seq protocols depend on high-throughput short-read sequencing of cDNA. However, as ongoing advances are rapidly yielding increasing read lengths, a technical hurdle remains in identifying the degree to which differences in read length influence various transcriptome analyses. In this study, we generated two paired-end RNA-seq datasets of differing read lengths (2x75 bp and 2x262 bp) for lymphoblastoid cell line GM12878 and compared the effect of read length on transcriptome analyses, including read-mapping performance, gene and transcript quantification, and detection of allele-specific expression (ASE) and allele-specific alternative splicing (ASAS) patterns. Our results indicate that, while the current long-read protocol is considerably more expensive than short-read sequencing, there are important benefits that can only be achieved with longer read length, including lower mapping bias and reduced ambiguity in assigning reads to genomic elements, such as mRNA transcript. We show that these benefits ultimately lead to improved detection of cis-acting regulatory and splicing variation effects within individuals.