Securing genetic integrity in freshwater pearl mussel propagation and captive breeding.

Securing genetic integrity is of key importance in conservation-oriented captive breeding programs releasing juveniles into the wild. This is particularly true for species such as the endangered freshwater pearl mussel (Margaritifera margaritifera) for which a number of captive breeding facilities has been established in Europe. The core objective of this study was to compare the genetic constitution of 29 cohorts of captive-bred freshwater pearl mussels from five different breeding facilities in Austria, France, Luxembourg and Germany, with their original 14 source populations from nine major European drainages, based on microsatellite markers. Captive-bred mussels represented 11 different genetic clusters, suggesting an important contribution of the breeding stations to securing the genetic diversity of the species. In almost all cases, the cultured offspring closely resembled the genetic constitution of the source mussels as revealed from the STRUCTURE analysis and the generally high assignment of offspring to the original source populations. The majority of captive-bred cohorts had an increased inbreeding coefficient and decreased genetic variability compared to their source populations as measured by AR and HO. Highest numbers of deformed juveniles coincided with very low levels of HO < 0.05. Since erosion of genetic diversity in captive breeding was mostly evident in individual year-cohorts, long-term breeding over multiple years can minimize such effects. The systematic selection of priority populations for conservation, effective breeding strategies avoiding effects of in- and outbreeding by genetically informed selection of parent individuals, and a network of collaboration among the different breeding facilities would be very useful to increase resilience and effectiveness.

Fast and cost-effective single nucleotide polymorphism (SNP) detection in the absence of a reference genome using semideep next-generation Random Amplicon Sequencing (RAMseq).

Biodiversity has suffered a dramatic global decline during the past decades, and monitoring tools are urgently needed providing data for the development and evaluation of conservation efforts both on a species and on a genetic level. However, in wild species, the assessment of genetic diversity is often hampered by the lack of suitable genetic markers. In this article, we present Random Amplicon Sequencing (RAMseq), a novel approach for fast and cost-effective detection of single nucleotide polymorphisms (SNPs) in nonmodel species by semideep sequencing of random amplicons. By applying RAMseq to the Eurasian otter (Lutra lutra), we identified 238 putative SNPs after quality filtering of all candidate loci and were able to validate 32 of 77 loci tested. In a second step, we evaluated the genotyping performance of these SNP loci in noninvasive samples, one of the most challenging genotyping applications, by comparing it with genotyping results of the same faecal samples at microsatellite markers. We compared (i) polymerase chain reaction (PCR) success rate, (ii) genotyping errors and (iii) Mendelian inheritance (population parameters). SNPs produced a significantly higher PCR success rate (75.5% vs. 65.1%) and lower mean allelic error rate (8.8% vs. 13.3%) than microsatellites, but showed a higher allelic dropout rate (29.7% vs. 19.8%). Genotyping results showed no deviations from Mendelian inheritance in any of the SNP loci. Hence, RAMseq appears to be a valuable tool for the detection of genetic markers in nonmodel species, which is a common challenge in conservation genetic studies.

Targeted resequencing of coding DNA sequences for SNP discovery in nonmodel species.

Targeted capture coupled with high-throughput sequencing can be used to gain information about nuclear sequence variation at hundreds to thousands of loci. Divergent reference capture makes use of molecular data of one species to enrich target loci in other (related) species. This is particularly valuable for nonmodel organisms, for which often no a priori knowledge exists regarding these loci. Here, we have used targeted capture to obtain data for 809 nuclear coding DNA sequences (CDS) in a nonmodel organism, the Eurasian lynx Lynx lynx, using baits designed with the help of the published genome of a related model organism (the domestic cat Felis catus). Using this approach, we were able to survey intraspecific variation at hundreds of nuclear loci in L. lynx across the species' European range. A large set of biallelic candidate SNPs was then evaluated using a high-throughput SNP genotyping platform (Fluidigm), which we then reduced to a final 96 SNP-panel based on assay performance and reliability; validation was carried out with 100 additional Eurasian lynx samples not included in the SNP discovery phase. The 96 SNP-panel developed from CDS performed very successfully in the identification of individuals and in population genetic structure inference (including the assignment of individuals to their source population). In keeping with recent studies, our results show that genic SNPs can be valuable for genetic monitoring of wildlife species.

A single-nucleotide polymorphism-based approach for rapid and cost-effective genetic wolf monitoring in Europe based on noninvasively collected samples.

Noninvasive genetics based on microsatellite markers has become an indispensable tool for wildlife monitoring and conservation research over the past decades. However, microsatellites have several drawbacks, such as the lack of standardisation between laboratories and high error rates. Here, we propose an alternative single-nucleotide polymorphism (SNP)-based marker system for noninvasively collected samples, which promises to solve these problems. Using nanofluidic SNP genotyping technology (Fluidigm), we genotyped 158 wolf samples (tissue, scats, hairs, urine) for 192 SNP loci selected from the Affymetrix v2 Canine SNP Array. We carefully selected an optimised final set of 96 SNPs (and discarded the worse half), based on assay performance and reliability. We found rates of missing data in this SNP set of <10% and genotyping error of ~1%, which improves genotyping accuracy by nearly an order of magnitude when compared to published data for other marker types. Our approach provides a tool for rapid and cost-effective genotyping of noninvasively collected wildlife samples. The ability to standardise genotype scoring combined with low error rates promises to constitute a major technological advancement and could establish SNPs as a standard marker for future wildlife monitoring.