Accuracy of allele frequency estimation using pooled RNA-Seq.

For nonmodel organisms, genome-wide information that describes functionally relevant variation may be obtained by RNA-Seq following de novo transcriptome assembly. While sequencing has become relatively inexpensive, the preparation of a large number of sequencing libraries remains prohibitively expensive for population genetic analyses of nonmodel species. Pooling samples may be then an attractive alternative. To test whether pooled RNA-Seq accurately predicts true allele frequencies, we analysed the liver transcriptomes of 10 bank voles. Each sample was sequenced both as an individually barcoded library and as a part of a pool. Equal amounts of total RNA from each vole were pooled prior to mRNA selection and library construction. Reads were mapped onto the de novo assembled reference transcriptome. High-quality genotypes for individual voles, determined for 23,682 SNPs, provided information on 'true' allele frequencies; allele frequencies estimated from the pool were then compared with these values. 'True' frequencies and those estimated from the pool were highly correlated. Mean relative estimation error was 21% and did not depend on expression level. However, we also observed a minor effect of interindividual variation in gene expression and allele-specific gene expression influencing allele frequency estimation accuracy. Moreover, we observed strong negative relationship between minor allele frequency and relative estimation error. Our results indicate that pooled RNA-Seq exhibits accuracy comparable with pooled genome resequencing, but variation in expression level between individuals should be assessed and accounted for. This should help in taking account the difference in accuracy between conservatively expressed transcripts and these which are variable in expression level.

Development, validation and high-throughput analysis of sequence markers in nonmodel species.

DNA sequences derived from multiple regions of the nuclear genome are essential for historical inferences in the fields of phylogeography and phylogenetics. The appropriate markers should be single-copy, variable, easy to amplify from multiple samples and easy to sequence using high-throughput technologies. This may be difficult to achieve for species lacking sequenced genomes and particularly challenging for species possessing large genomes, which consist mostly of repetitive sequences. Here, we present a cost-effective, broadly applicable framework for designing, validating and high-throughput sequencing of multiple markers in nonmodel species without sequenced genomes. We demonstrate its utility in two closely related species of newts, representatives of urodeles, a vertebrate group characterized by large genomes. We show that over 80 markers, c. 600 bp each, developed mainly from 3' untranslated transcript regions (3'UTR) may be effectively multiplexed and sequenced. Data are further processed using standard, freely available bioinformatic tools, producing phase-resolved sequences. The approach does not require barcoded PCR primers, and the cost of library preparation is independent of the number of markers investigated. We hope that this approach will be of broad interest for researchers working at the interface of population genetics and phylogenetics, exploring deep intraspecific genetic structure, species boundaries and phylogeographies of closely related species.