Abstract
BackgroundThe possibility of generating large RNA-sequencing datasets has led to development of various reference-based and de novo transcriptome assemblers with their own strengths and limitations. While reference-based tools are widely used in various transcriptomic studies, their application is limited to the organisms with finished and well-annotated genomes. De novo transcriptome reconstruction from short reads remains an open challenging problem, which is complicated by the varying expression levels across different genes, alternative splicing, and paralogous genes.ResultsHerein we describe the novel transcriptome assembler rnaSPAdes, which has been developed on top of the SPAdes genome assembler and explores computational parallels between assembly of transcriptomes and single-cell genomes. We also present quality assessment reports for rnaSPAdes assemblies, compare it with modern transcriptome assembly tools using several evaluation approaches on various RNA-sequencing datasets, and briefly highlight strong and weak points of different assemblers.ConclusionsBased on the performed comparison between different assembly methods, we infer that it is not possible to detect the absolute leader according to all quality metrics and all used datasets. However, rnaSPAdes typically outperforms other assemblers by such important property as the number of assembled genes and isoforms, and at the same time has higher accuracy statistics on average comparing to the closest competitors.
Highlights
While reference-based methods for RNA-Seq analysis [5,7,10,11,16,23] currently dominate transcriptome studies, they are subjected to the following constraints: (i) they are not applicable in the case when the genome is unknown, (ii) their performance deteriorates when the genome sequence or annotation are incomplete, and (iii) they may miss unusual transcripts even when the reference genome is available
De novo transcriptome assemblers [6,15,19,20,25] have emerged as a viable complement to the reference-based tools
While the transcriptome assembly may seem to be a simpler problem than the genome assembly, RNA-Seq assemblers have to address the complications arising from highly uneven read coverage depth caused by variations in gene expression levels
Summary
While reference-based methods for RNA-Seq analysis [5,7,10,11,16,23] currently dominate transcriptome studies, they are subjected to the following constraints: (i) they are not applicable in the case when the genome is unknown, (ii) their performance deteriorates when the genome sequence or annotation are incomplete, and (iii) they may miss unusual transcripts (such as fusion genes or genes with short unannotated exons) even when the reference genome is available To address these constraints, de novo transcriptome assemblers [6,15,19,20,25] have emerged as a viable complement to the reference-based tools. Even though SPAdes is a genome assembler and was not optimized for RNA-seq data, in some cases it generated decent assemblies of quality comparable to the state-of-the-art transcriptome assemblers
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