Factors influencing genotyping success and genotyping error rate of Eurasian otter (Lutra lutra) faeces collected in temperate Central Europe

Abstract

The use of non-invasively collected DNA source material for genetic and genomic applications is usually characterized by low target DNA concentration and quality, genotyping errors and cost-intensive lab procedures. However, for otters (Lutrinae) as elusive species of conservation concern, genetic non-invasive sampling has become an important tool to study their ecology and demography. To increase cost-efficiency of monitoring programmes and to promote the expansion of genomic approaches to non-invasive samples, we aimed to refine sample collection and preparation. Therefore, we examined the effects of intrinsic sample characteristics (including diet), environmental conditions in the field and sample treatment in the molecular laboratory on the success of genotyping and allelic dropout (ADO) rates using microsatellite markers in 1970 fresh Eurasian otter (Lutra lutra) scats. Using fresh samples only, we probably eliminated one of the most important impediments of genotyping DNA from otter faecal samples beforehand. But, we observed higher genotyping success and lower ADO rates for anal glad secretions and faecal samples containing high proportions of mucus. Moist conditions during sample collection may promote DNA degradation and PCR inhibition, leading to decreased genotyping success rates. ADO was further affected by the type of extraction kit. However, a high proportion of variance remaining unexplained by our models implied that additional parameters were acting (amount of PCR inhibitors, non-uniform distribution of intestinal cells, efficiency of PCRs, specific microclimate at marking sites). We summarized influential factors maximizing genotyping quality of otter scats and give recommendations for sample collection, storage and DNA extraction based on our results and current literature.

Species-specific SNP arrays for non-invasive genetic monitoring of a vulnerable bat

“…Microsatellite studies typically show a negative relationship between genotyping errors and amplification rate, with the rate of allelic dropout increasing with greater scat age (assumed to be a result of low DNA quantity and/or quality 4 ). The better performance of M. gigas scats could be due to environmental factors since caves provide a stable microclimate where scats are sheltered from UV light and rain compared to those exposed to ambient weather conditions 4 , 5 , 16 , 17 . In addition, we found an interaction between the DNA extraction method used and MassARRAY amplification rate with the QIAamp ® Fast DNA Stool Mini kit performing more poorly than the Omega Biotek Mag-Bind Stool DNA 96 kit, most likely due to the presence of EDTA in buffers interfering with MassARRAY multiplex PCR reactions.…”

“…Faecal genotyping with microsatellite markers has been applied successfully in wildlife monitoring for many years 5 , 15 , 16 . The benefit of microsatellite markers is that statistical power to identify individuals is achieved with relatively few markers but many alleles.…”

Taxonomic status of otter species in Nakai‐Nam Theun National Park, Lao PDR, based on DNA evidence

“…We collected about 5 g from each sample, selecting the outside layer of the feces where gut epithelial cells are more abundant. Spraints with anal gland secretions were also targeted due to higher DNA concentration and amplification success (Sittenthaler et al, 2021).…”

Identification of three Asian otter species (Aonyx cinereus, Lutra sumatrana, and Lutrogale perspicillata) using a novel noninvasive PCR‐RFLP analysis

“…Camera traps at latrine sites have provided valuable data on species, group size, and social behavior (Ben‐David et al, 1998 ; Green et al, 2015 ; Stevens & Serfass, 2008 ). Noninvasive molecular genetic sampling using spraints has been successfully employed in ecological and demographic studies of Eurasian and North American otters (Hájková et al, 2009 ; Jansman et al, 2001 ; Klütsch & Thomas, 2018 ; Sittenthaler et al, 2020 ). These methods increase the scope of population monitoring by providing data on otter presence and habitat use, including additional information such as individual identification by DNA analysis, which can be used to estimate population size and density.…”