Benchmarking Next-Generation Transcriptome Sequencing for Functional and Evolutionary Genomics

Abstract

Next-generation sequencing has opened the door to genomic analysis of nonmodel organisms. Technologies generating long-sequence reads (200-400 bp) are increasingly used in evolutionary studies of nonmodel organisms, but the short-sequence reads (30-50 bp) that can be produced at lower cost are thought to be of limited utility for de novo sequencing applications. Here, we tested this assumption by short-read sequencing the transcriptomes of the tropical disease vectors Aedes aegypti and Anopheles gambiae, for which complete genome sequences are available. Comparison of our results to the reference genomes allowed us to accurately evaluate the quantity, quality, and functional and evolutionary information content of our "test" data. We produced more than 0.7 billion nucleotides of sequenced data per species that assembled into more than 21,000 test contigs larger than 100 bp per species and covered approximately 27% of the Aedes reference transcriptome. Remarkably, the substitution error rate in the test contigs was approximately 0.25% per site, with very few indels or assembly errors. Test contigs of both species were enriched for genes involved in energy production and protein synthesis and underrepresented in genes involved in transcription and differentiation. Ortholog prediction using the test contigs was accurate across hundreds of millions of years of evolution. Our results demonstrate the considerable utility of short-read transcriptome sequencing for genomic studies of nonmodel organisms and suggest an approach for assessing the information content of next-generation data for evolutionary studies.

Transcriptomics of salinity tolerance capacity in Arctic charr (Salvelinus alpinus): a comparison of gene expression profiles between divergent QTL genotypes

“…The final dataset used for de novo transcriptome assembly was 38.9% of its original size. The number of contigs in each assembly, spanning k-mers 33 to 89, was inversely related to k-mer size (Table 2), which is consistent with previous observations (17,18,21,28). The optimum k-mer sizes appeared to be 57 and 65, which had the highest values for most metrics typically used to assess assembly quality (e.g., mean and median contig lengths, N50, and N90), maximum contig length the exception.…”

Genome-wide transcriptome analysis between Small-tail Han sheep and the Surabaya fur sheep using high-throughput RNA sequencing

“…Recently, de novo transcriptome analyses, that is, de novo assembly of short reads from mRNA without genome reference, have emerged. Several studies have reported the transcriptome sequencing of various non-model species using next-generation sequencing technologies (Gibbons et al 2009, Wolf et al 2010. Although many studies are based on the long-read sequence data using 454 pyrosequencing or used a hybrid approach, the de novo assembly of transcriptome employing short reads (Illumina or SOLiD) has also received extensive attention because of its relatively low cost.…”

“…Recent methods and experimental advances have made it possible to perform at de novo sequence projects (Li et al 2009). Many previous pioneering works have suggested that nextgeneration sequencing technologies provide a massive amount of useful information for the transcriptome analysis in non-model organisms (Gibbons et al 2009, Wolf et al 2010. As a powerful tool to explore the expression levels of thousands of genes simultaneously in cell or tissue, the microarray technology was discussed and reviewed in livestock species.…”

Phototransduction and clock gene expression in the troglobiont beetlePtomaphagus hirtusof Mammoth cave

“…Our study suggests that next-generation sequencing methods will continue to serve as powerful facilitators in this endeavor. The recovery of over 5000 high confidence Drosophila and Tribolium orthologs in the adult head transcriptome of P. hirtus by RNA sequencing underlines the promise of nextgeneration sequencing for exploring the genetic organization of nonmodel organisms, by capitalizing on model species' genome sequences as a reference for assembly and annotation (Gibbons et al, 2009;Juan et al, 2010). The sensitivity of this approach is most impressively highlighted by the detection of circadian rhythm gene transcripts.…”