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Updated: May 9, 2026

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
Published on: May 28, 2021
De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and
Brian J Haas1, Alexie Papanicolaou2, Moran Yassour1,3
1Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, MA, 02142, USA.
This study presents the Trinity platform for de novo transcriptome assembly from RNA-seq data, enabling genome-independent analysis. It offers tools for transcript abundance, differential expression, and protein-coding gene identification in non-model organisms.
Area of Science:
- Genomics
- Bioinformatics
- Transcriptomics
Background:
- De novo transcriptome assembly from RNA-seq data allows gene expression studies without a reference genome.
- This approach is crucial for non-model organisms, cancer research, and microbiome studies.
Purpose of the Study:
- To describe the Trinity platform for de novo transcriptome assembly from RNA-seq data in non-model organisms.
- To present companion utilities for downstream transcriptomic analyses.
Main Methods:
- Utilized the Trinity platform for de novo transcriptome assembly.
- Employed RSEM for transcript abundance estimation.
- Applied R/Bioconductor packages for differential gene expression analysis and protein-coding gene identification.
Main Results:
- Provided a workflow for genome-independent transcriptome analysis using the Trinity platform.
- Demonstrated the processing of an example dataset in under 5 hours.
- Trinity software, documentation, and demonstrations are freely available online.
Conclusions:
- The Trinity platform offers a comprehensive solution for de novo transcriptome assembly and downstream analysis.
- This workflow facilitates transcriptomic research, particularly in organisms lacking a reference genome.
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