An evaluation of pool-sequencing transcriptome-based exon capture for population genomics of non-model species

Exon capture, as targeted sequence enrichment method, coupled with high-throughput sequencing technologies, represents a cost-effective technical solution to answer specific evolutionary biology questions by focusing on areas of the genome under selection. Transcriptome-based capture, which allows exon captures for non-model species, are particularly used in phylogenomics, but remain poorly developed for population genomics studies. Exon capture cost is still prohibitively high to sequence a large number of indexed individuals across multiple populations of one species. But many population genomics research questions can be addressed by the sole use of allele frequencies at the population scale. In this study, we evaluate the possibility of combining transcriptome-based capture and pool-seq as a cost-effective, generic and robust approach to estimate the population variant allelic frequencies of any species. We designed capture probes for ~5 Mb of randomly chosen de novo transcripts of the Asian ladybird (i.e. 5,717 transcripts). From a pool of non-indexed 36 individuals, ~300,000 bi-allelic coding SNPs were called among 4,700 coding genes. We found that capture efficacy was high, and that pool-seq was as effective and accurate as individual-seq in detecting variants and estimating allele frequencies. We also propose and evaluate an approach to simplify process read data, without assembling them, which consists of mapping reads directly to targeted de novo transcript sequences in order to obtain coding variants. This approach is effective and does not affect the estimation of SNPs9 allele frequencies but presents a small bias by predicting few false SNPs at certain exon ends. We demonstrate that this approach can also be used to efficiently predict a posteriori intron-exon boundaries of targeted transcripts, which may allow the genotyping bias to be cancelled at the exons ends.