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Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms
Published on: May 9, 2017
Evaluating characteristics of de novo assembly software on 454 transcriptome data: a simulation approach
Marvin Mundry1, Erich Bornberg-Bauer, Michael Sammeth
1Evolutionary Bioinformatics, Institute for Evolution and Biodiversity, Westfaelische-Wilhelms-University, Muenster, Germany.
Plos One
|March 3, 2012
Summary
This study evaluated transcriptome assembly software for non-model organisms using a novel simulation approach. MIRA and Newbler showed contrasting performance, with MIRA being conservative and Newbler more liberal in merging reads.
Area of Science:
- Bioinformatics
- Genomics
- Computational Biology
Background:
- Transcriptome data for non-model organisms is rapidly increasing.
- Sequence read assembly is a critical bioinformatics challenge.
- Evaluating assembly software is essential for best practices.
Purpose of the Study:
- To evaluate transcriptome assembly software performance using a simulation approach.
- To compare basic assembly metrics against a known optimal solution.
- To assess assembly ambiguity and contig characteristics.
Main Methods:
- Adapted a simulation approach to evaluate assembly programs (CAP3, MIRA, Newbler, Oases) on 454 data.
- Calculated a model assembly as a reference point for comparison.
- Traced reads to their correct placement and mapped them to assembled contigs.
Main Results:
- MIRA and CAP3 were conservative, producing many short contigs and low chimeric rates but high redundancy.
- Newbler produced longer contigs with less redundancy but a higher proportion of chimeric contigs.
- Oases generated the shortest assembly and performed poorly on 454 reads.
Conclusions:
- MIRA and Newbler slightly outperformed other programs, exhibiting contrasting conservative and liberal read-merging strategies.
- The choice of assembly software should consider downstream analysis needs.
- Understanding assembler characteristics is crucial for effective transcriptome assembly.
Related Concept Videos
03:36Genome Annotation and Assembly
The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
03:21RNA-seq
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...