Accurate annotation of transcript isoforms is crucial for functional genomics research, but automated methods for reconstructing full-length transcripts from RNA sequencing (RNA-seq) data are imprecise. We developed a generalized transcript assembly framework called Bookend that incorporates data from multiple modes of RNA-seq, with a focus on identifying, labeling, and deconvoluting RNA 5′ and 3′ ends. Through end-guided assembly with Bookend we demonstrate that correctly modeling transcript start and end sites is essential for precise transcript assembly. Furthermore, we discover that reads from full-length single-cell RNA-seq (scRNA-seq) methods are sparsely end-labeled, and that these ends are sufficient to dramatically improve precision of assembly in single cells. Finally, we show that hybrid assembly across short-read, long-read, and end-capture RNA-seq in the model plant Arabidopsis and meta-assembly of single mouse embryonic stem cells (mESCs) are both capable of producing tissue-specific end-to-end transcript annotations of comparable or superior quality to existing reference isoforms.