Overview of ESPRESSO. Science Advances, 2023.

Although extensively used, short-read RNA sequencing (RNA-seq) only examines fragments of full-length transcripts. Thus, protein products that correspond to identified RNA processing events often cannot be reliably inferred. Although long-read RNA-seq is an ideal tool for resolving full-length transcript structures, it is under-utilized for human transcriptome analysis due to its methodological and computational challenges. Our lab has made and continues to make multiple advances to overcome these limitations:

To account for the relatively high sequencing base error rate of long-read RNA-seq, we developed ESPRESSO (Error Statistics PRomoted Evaluator of Splice Site Options), a computational tool for robust discovery and quantification of transcript isoforms from error-prone long-read RNA-seq data. 

Overview of TEQUILA-seq. Nature Communications, 2023.

We further tackled long-read RNA-seq challenges by addressing the lower throughput of long-read sequencing platforms. We developed TEQUILA-seq (Transcript Enrichment and Quantification Utilizing Isothermally Linear-Amplified probes in conjunction with long-read sequencing), a versatile, easy-to-implement, and low-cost method for targeted long-read RNA-seq. TEQUILA-seq has multiple usage applications, including for RNA-guided genetic diagnosis and for precision oncology.

An additional key technology developed by our lab for long-read analysis is isoCirc, a novel strategy for sequencing full-length circRNA isoforms using rolling circle amplification followed by nanopore long-read sequencing. In ongoing parallel work, we are developing single-cell long-read sequencing methods, including methods to acquire transcript-level information on individual cells.