Bookend

Bookend assembles full-length transcripts from RNA sequencing (RNA-seq) data by integrating short-read, long-read, and end-capture datasets to improve identification and annotation of RNA 5' and 3' ends.

Key Features:

• End-aware assembly: Identifies and utilizes RNA 5' and 3' ends to improve transcript boundary precision.
• Multi-platform integration: Combines short-read, long-read, and end-capture RNA-seq datasets for hybrid assembly.
• Single-cell end-labeled reads: Incorporates full-length single-cell RNA-seq datasets that include end-labeled reads to enhance single-cell transcript assembly accuracy.
• Hybrid assembly approach: Performs hybrid assembly across diverse RNA-seq types to generate full-length transcripts.
• Meta-assembly support: Supports meta-assembly of RNA-seq data from single cells, including single mouse embryonic stem cells.
• Reference-quality annotation demonstrated: Applied to Arabidopsis thaliana to produce reference-quality end-to-end transcript annotations.

Scientific Applications:

• Improved transcript annotation: Refines transcript start and end annotations for more precise gene models.
• Single-cell transcriptomics: Enhances full-length transcript assembly and boundary resolution in single-cell RNA-seq datasets.
• Reference transcriptome generation: Produces end-to-end transcript annotations for model organisms such as Arabidopsis thaliana.
• Meta-analysis of single-cell data: Enables meta-assembly across single mouse embryonic stem cell datasets to build comprehensive transcriptome maps.

Methodology:

Computational steps include identification of transcript start and end sites, integration of short-read, long-read, and end-capture RNA-seq datasets, incorporation of end-labeled full-length single-cell RNA-seq reads, and hybrid/meta-assembly to produce end-to-end transcript annotations.