A massively parallel strategy for STR marker development, capture, and genotyping

Abstract Short tandem repeat (STRs or microsatellites) variants, are highly polymorphic markers that facilitate powerful, high-precision population genetic analyses. STRs are especially valuable in conservation and ecological genetic research, yielding detailed information on population structure and short-term demographic flux. However, STR marker development and analysis by conventional PCR-based methods imposes a workflow bottleneck and is suboptimal for noninvasive sampling strategies such as fecal DNA recovery. While massively parallel sequencing has not previously been leveraged for scalable, efficient STR recovery, here we present a pipeline for developing STR markers directly from high-throughput shotgun sequencing data without requiring a reference genome assembly, and a methodological approach for highly parallel recovery of enriched STR loci. We first employed our approach to design and capture a panel of 5,000 STR loci from a test group of diademed sifakas ( Propithecus diadema , n=3), endangered Malagasy rainforest lemurs, and we report extremely efficient recovery of targeted loci—97.3-99.6% of STRs characterized with ≥10x non-redundant coverage. Second, we tested our STR capture strategy on a P. diadema fecal DNA preparation, and report robust initial results and methodological suggestions for future implementations. In addition to STR targets, this approach also generates large, genome-wide single nucleotide polymorphism (SNP) panels from regions flanking the STR loci. Our method provides a cost-effective and highly scalable solution for rapid recovery of large STR and SNP datasets in any species without need for a reference genome, and can be used even with suboptimal DNA, which is more easily acquired in conservation and ecological genetic studies. Data Deposition Raw sequencing data are available under Study Accession numbers SRP073167 (genomic shotgun data for Oberon and Tatiana) and SRP076225 (targeted re-sequencing data) from the NCBI Sequence Read Archive. BaitSTR software is available at Github (core BaitSTR programs: https://github.com/aakrosh/BaitSTR ; BaitSTR_type.pl companion script for genotyping and block manipulation: https://github.com/lkistler/BaitSTR_type ).