The article introduces Trinity, a method for de novo assembly of full-length transcripts from RNA-Seq data without a reference genome. Trinity consists of three software modules: Inchworm, Chrysalis, and Butterfly, which are applied sequentially to process large volumes of RNA-Seq reads. The method efficiently constructs and analyzes sets of de Bruijn graphs to fully reconstruct a large fraction of transcripts, including alternatively spliced isoforms and transcripts from recently duplicated genes. Compared to other de novo transcriptome assemblers, Trinity recovers more full-length transcripts across a broad range of expression levels, with a sensitivity similar to methods that rely on genome alignments. The authors evaluate Trinity on samples from fission yeast, mouse, and whitefly, demonstrating its effectiveness in reconstructing transcripts in the absence of a reference genome. Trinity provides a unified solution for transcriptome reconstruction in any sample, enhancing our understanding of transcriptomes in non-model organisms and improving genome annotation.The article introduces Trinity, a method for de novo assembly of full-length transcripts from RNA-Seq data without a reference genome. Trinity consists of three software modules: Inchworm, Chrysalis, and Butterfly, which are applied sequentially to process large volumes of RNA-Seq reads. The method efficiently constructs and analyzes sets of de Bruijn graphs to fully reconstruct a large fraction of transcripts, including alternatively spliced isoforms and transcripts from recently duplicated genes. Compared to other de novo transcriptome assemblers, Trinity recovers more full-length transcripts across a broad range of expression levels, with a sensitivity similar to methods that rely on genome alignments. The authors evaluate Trinity on samples from fission yeast, mouse, and whitefly, demonstrating its effectiveness in reconstructing transcripts in the absence of a reference genome. Trinity provides a unified solution for transcriptome reconstruction in any sample, enhancing our understanding of transcriptomes in non-model organisms and improving genome annotation.