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Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms
Published on: May 9, 2017
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Comparing de novo and reference-based transcriptome assembly strategies by applying them to the blood-sucking bug
A Marchant1, F Mougel2, V Mendonça3
1UMR EGCE (Laboratoire Evolution, Génomes, Comportement, Ecologie), Univ. Paris-Sud, CNRS, IRD, IDEEV, Univ. Paris-Saclay, Avenue de la Terrasse, Bâtiment 13, BP1 - 91198 Gif-sur-Yvette, France.
Insect Biochemistry and Molecular Biology
|May 26, 2015
Summary
Comparing transcriptome assembly methods for Rhodnius prolixus, reference-based strategies proved superior to de novo assembly alone. A combined approach yielded the most comprehensive transcript catalog, revealing novel isoforms and fragmented transcripts.
Area of Science:
- Genomics
- Bioinformatics
- Transcriptomics
Background:
- High Throughput Sequencing facilitates transcriptome assembly, but quality is crucial for comprehensive transcript catalogs and further experiments.
- No consensus exists on optimal sequencing technologies and assembly tools for transcriptome assembly.
- Many non-model organisms lack reference genomes, necessitating de novo assembly, while others, like Rhodnius prolixus, have reference genomes enabling reference-based assembly.
Purpose of the Study:
- To compare the effectiveness of reference-based versus de novo transcriptome assembly strategies.
- To evaluate different sequencing datasets (454, Illumina, combined) and assembly software.
- To establish criteria for assessing transcriptome assembly quality, including transcript number, chimeric transcripts, and completeness.
Main Methods:
- Utilized three distinct datasets: 454, Illumina, and a combination of both.
- Employed various assembly software for both de novo and reference-based strategies.
- Assessed assembly quality using metrics such as transcript size distribution, chimeric transcript proportion, and completeness (CEGMA, R. prolixus proteome fraction).
Main Results:
- Reference-based assemblies, particularly after genome annotation, significantly outperformed de novo strategies alone.
- Reference-based methods identified novel transcripts and isoforms not predicted by automatic genome annotation.
- A hybrid approach combining de novo and reference-based strategies delivered the best overall results, successfully assembling fragmented transcripts.
Conclusions:
- Reference-based transcriptome assembly is superior to de novo assembly for organisms with a reference genome.
- Combining de novo and reference-based strategies offers the most robust approach for comprehensive transcriptome assembly.
- This study provides valuable insights for optimizing transcriptome assembly in insects and other organisms, particularly for discovering novel transcripts and isoforms.
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