Pitfalls and recommendations for large-scale SNP genotyping in a non-model endangered species: the southern damselflies (Coenagrion mercuriale) as a case study.

Genomic markers are essential tools for studying species of conservation concern, yet non-model species often lack a genome reference. Here we describe a methodology for identifying and genotyping thousands of SNP loci in the southern damselfly (Coenagrion mercuriale), a bioindicator of freshwater stream quality classified as near-threatened, with locally declining populations. We used a hybrid approach combining reduced representation sequencing and target enrichment. First, we identified putative SNP loci using ddRADseq and de novo assembly. Then, single primer enrichment technology targeted 6,000 of these SNPs across 1,920 individuals. Challenges encountered included sequence recapture failure, coverage depth discrepancies, and aberrant FIS values. We provide recommendations to address such issues. After multiple filtering, we retained 2,092 SNPs. We used them to characterise rear-edge populations of the southern damselfly in Northern France, a region where populations are sparsely distributed. Previous surveys utilising microsatellite markers allowed comparison of genetic diversity and differentiation estimates. Consistent with prior findings, genetic diversity estimates were similar across the studied populations that showed no sign of inbreeding. SNP markers exhibited greater resolution in detecting fine-scaled genetic structure, identifying two putative hybrids in adjacent populations, a feat unattainable with microsatellite loci. Altogether, this study highlighted the ongoing challenge of large-scale SNP genotyping using target sequencing techniques in non-model species to set conservation guidelines. Nonetheless, these new markers showed greater statistical power in identifying conservation units and offered the promise of greater precision in the identification of admixture events or the estimation of key population parameters such as effective population size.