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Raw sequencing data and ngsfilters for snow track eDNA samples

Cite this dataset

De Barba, Marta et al. (2023). Raw sequencing data and ngsfilters for snow track eDNA samples [Dataset]. Dryad. https://doi.org/10.5061/dryad.9kd51c5q1

Abstract

Continued advancements in environmental DNA (eDNA) research have made it possible to access intraspecific variation from eDNA samples, opening new opportunities to expand non-invasive genetic studies of wildlife populations. However, the use of eDNA samples for individual genotyping, as typically performed in non-invasive genetics, still remains elusive. We present the first successful individual genotyping of eDNA obtained from snow tracks of three large carnivores: brown bear (Ursus arctos), European lynx (Lynx lynx) and wolf (Canis lupus). DNA was extracted using a protocol for isolating water eDNA and genotyped using amplicon sequencing of short tandem repeats (STR) and, for brown bear, a sex marker, on a high-throughput sequencing platform. Individual genotypes were obtained for all species, but genotyping performance differed among samples and species. The proportion of samples genotyped to individuals was higher for brown bear samples (5/7) than for wolf (7/10) and lynx (4/9), but locus genotyping success was greater for brown bear (0.88). Results for three species show that reliable individual genotyping, including sex identification, is now possible from eDNA in snow tracks, underlining its vast potential to complement the non-invasive genetic methods used for wildlife. To fully leverage the application of snow track eDNA, improved understanding of the ideal species- and site-specific sampling conditions, as well as laboratory methods promoting genotyping success are needed. This will also inform efforts to retrieve and type nuclear DNA from other eDNA samples, thereby advancing eDNA–based individual and population-level studies.

README: Raw sequencing data and ngsfilters for snow track eDNA samples

https://doi.org/10.5061/dryad.9kd51c5q1

Description of the data and file structure

The dataset contains four libraries with STR amplicons for three carnivore species: DIVJA088 (brown bear), DIVJA089 (brown bear), DAB074 (brown bear, wolf and lynx), LF22 (wolf). Besides raw reads, the ngsfilter file is attached to each library. Ngsfilter is used for further data processing and contains information about sample name, sample position on plate, primers and tags sequences. More details about mulitplexing concept can be found in De Barba et al., 2017.

De Barba, M., Miquel, C., Lobréaux, S., Quenette, P. Y., Swenson, J. E., & Taberlet, P. (2017). High-throughput microsatellite genotyping in ecology: Improved accuracy, efficiency, standardization and success with low-quantity and degraded DNA. Molecular Ecology Resources, 17(3), 492–507.

Code/Software

To process the data see the description of the pipeline in https://github.com/PazhenkovaEA/ngs_pipelines.py

Methods

Snow tracks of brown bear, lynx and wolf were collected opportunistically during winter in 2019, 2020 and 2022 in the Slovenian Alps and Dinaric Mountains (seven brown bear samples and nine lynx samples) and in the French Alps (ten wolf samples). For genotyping of each species, we used a set of STR markers designed for optimal multiplex amplification and HTS genotyping. The brown bear set includes 13 STR recently described and used for individual profiling from fecal DNA, with the addition of a sex-specific marker. For wolf and lynx, we used 13 new STRs. We performed sequencing on a NovaSeq platform (2x150 bp) (libraries with id DIVJA088, DIVJA089, DAB074) and on a Miniseq platform (2x150 bp) (library LF22). Amplicons were sequenced in multiplexes, and necessary information for demultiplexing is in .ngsfilter files.

Funding

European Commission, Award: LIFE16 NAT/SI/000634

European Commission, Award: LIFE18 NAT/IT/000972, LIFE WolfAlps EU

Slovenian Research Agency, Award: P1-0184

Federal Office for the Environment