Leveraging targeted sequencing for non-model species: a step-by-step guide to obtain a reduced SNP set and a pipeline to automate data processing in the Antarctic Midge, Belgica antarctica.

Abstract

The sequencing of whole or partial (e.g. reduced representation) genomes are commonly employed in molecular ecology and conservation genetics studies. However, due to sequencing costs, a trade-off between the number of samples and genome coverage can hinder research for non-model organisms. Furthermore, the processing of raw sequences requires familiarity with coding and bioinformatic tools that are not always available. Here, we present a guide for isolating a set of short, SNP-containing genomic regions for use with targeted amplicon sequencing protocols. We also present a python pipeline--PypeAmplicon-- that facilitates processing of reads to individual genotypes. We demonstrate the applicability of our method by generating an informative set of amplicons for genotyping of the Antarctic midge, Belgica antarctica, an endemic dipteran species of the Antarctic Peninsula. Our pipeline analyzed raw sequences produced by a combination of high-multiplexed PCR and next-generation sequencing. A total of 38 out of 47 (81%) amplicons designed by our panel were recovered, allowing successful genotyping of 42 out of 55 (76%) targeted SNPs. The sequencing of [~]150 bp around the targeted SNPs also uncovered 80 new SNPs, which complemented our analyses. By comparing overall patterns of genetic diversity and population structure of amplicon data with the low-coverage, whole-genome re-sequencing (lcWGR) data used to isolate the informative amplicons, we were able to demonstrate that amplicon sequencing produces information and results similar to that of lcWGR. Our methods will benefit other research programs where rapid development of population genetic data is needed but yet prevented due to high expense and a lack of bioinformatic experience.