Abstract
De novo assembled transcriptomes, in combination with RNA-Seq, are powerful tools to explore gene sequence and expression level in organisms without reference genomes. Investigators must first choose which high throughput sequencing platforms will provide data most suitable for their experimental goals. In this study, we explore the utility of 454 and Illumina sequences for de novo transcriptome assembly and downstream RNA-Seq applications in a reproductive gland from a non-model bird species, the Japanese quail (Coturnix japonica). Four transcriptomes composed of either pure 454 or Illumina reads or mixtures of read types were assembled and evaluated for the same cost. Illumina assemblies performed best for de novo transcriptome characterization in terms of contig length, transcriptome coverage, and complete assembly of gene transcripts. Improvements over the Hybrid assembly were marginal, with the exception that the addition of 454 data significantly increased the number of genes annotated. The Illumina assembly provided the best reference to align an independent set of RNA-Seq data as ∼84% of reads mapped to single genes in the transcriptome. Contigs constructed solely from 454 data may impose problems for RNA-Seq as our 454 transcriptome revealed a high number of indels and many ambiguously mapped reads. Correcting the 454 transcriptome with Illumina reads was an effective strategy to deal with indel and frameshift errors inherent to the 454 transcriptome, but at the cost of transcriptome coverage. In the absence of a reference genome, we find that Illumina reads alone produced a high quality transcriptome appropriate for RNA-Seq gene expression analyses.
Highlights
Until recently, evolutionary and population-genomic research was restricted to the small number of taxa considered model organisms
The Illumina assembly displayed the highest values across most standard metrics of transcriptome quality, followed by the Hybrid assembly (Table 1)
Illumina or similar short-read data are currently the standard for RNA-Seq projects, and our results suggest that Illumina-based assemblies will be most appropriate for RNA-Seq experiments mapping to de novo assembled transcriptomes
Summary
Evolutionary and population-genomic research was restricted to the small number of taxa considered model organisms. The potential for largescale genomic investigations exists for virtually any study system [1,2,3,4]. One approach adopted by the non-model research community is shotgun-sequencing of transcriptomes [1,2,3,4]. With the advent of deep, parallel sequencing of cDNA (‘‘RNA-Seq’’) researchers can quantify expression variation in a high-throughput and cost-effective manner [5,6]. Given options in terms of sequencing platform and bioinformatics workflow, a pressing question is what is the optimal strategy to harness both the static (sequence-level) and dynamic (expression-level) nature of transcriptomes of non-model species
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