Next-generation sequencing of transcriptomes (RNA-Seq) is being used increasingly in studies of nonmodel organisms. Here, we evaluate the effectiveness of normalising cDNA libraries prior to sequencing in a small-scale study of the zebra finch. We find that assemblies produced from normalised libraries had a larger number of contigs but used fewer reads compared to unnormalised libraries. Considerably more genes were also detected using the contigs produced from normalised cDNA, and microsatellite discovery was up to 73% more efficient in these. There was a positive correlation between the detected expression level of genes in normalised and unnormalised cDNA, and there was no difference in the number of genes identified as being differentially expressed between blood and spleen for the normalised and unnormalised libraries. We conclude that normalised cDNA libraries are preferable for many applications of RNA-Seq and that these can also be used in quantitative gene expression studies. 1. Introduction Next-generation sequencing (NGS) has revolutionised biological research and opened up the field of genomics for small-scale projects in nonmodel organisms [1–3]. A practical approach for studies of species with no prior genomics information available, and where budgets are limited, is to sequence only the expressed parts of the genomes (transcriptomes). This method, known as RNA-Seq [4], has the advantage that sequence characterisation is focused on functionally important regions of the genomes. An additional benefit is that information is obtained not only about gene sequence variation but also regarding gene expression levels [5]. While most publications on transcriptome characterisation in nonmodel organisms remain rather descriptive, question-oriented papers are also emerging in a number of fields, including speciation [6], conservation [7], and local adaptation [8]. The Roche 454 sequencing technology is probably still the most widely used NGS method for de novo characterisation of transcriptomes of nonmodel organisms, but other methods such as Illumina/Solexa and ABI SOLiD are becoming increasingly popular [9, 10]. Data from small-scale RNA-Seq studies are routinely used for a number of different purposes such as gene finding, marker identification, and expression studies [1]. Data from related species, genomic reference species [11], are often utilised to annotate whole-transcriptome sequence datasets or to identify specific genes of interest. Molecular markers such as microsatellites, indels, and SNPs can be efficiently mined from NGS transcriptome
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