In the Netherlands we have a situation where the introduced Italian crested newt is locally replacing the native Northern crested newt. As the Northern crested newt is a threatened species, conservationists would like to try and remove Italian crested newts from the wild. A complication is that the two species hybridize and backcross, resulting in a mix of individuals that are hard to distinguish from natives based on morphology, but that do possess alien alleles. Genetic approaches are required to identify such newts.

Example for one of the nuclear markers genotyped with our ‘SNPline’ protocol. During PCR two differently fluorescence-labelled tags can be built in, one matching the native allele and the other matching the alien allele. The axes here reflect the level of fluorescence after PCR for each tag. The red cloud reflects individuals with two native copies and the blue cloud individuals with two alien copies, while the green cloud consists of individuals that possess both a native and an invasive allele for this particular marker.

In a previous study we documented the Dutch situation using our Triturus Ion Torrent protocol. The aim of a follow-up study, now published in the journal Conservation Genetics Resources, was to use our existing knowledge on the newt case and design a quick, cheap and easy pipeline to genotype newts on a large scale. Hence, the data required to stop the gradual replacement of the Northern crested newt by the Italian crested newt can now be collected efficiently. Our methodology can also be applied to other cases where the Italian crested newt has been introduced inside the range of the Northern crested newt, known from the UK, Germany and the Swiss/France border.

Reference: Wielstra, B., Burke, T., Butlin, R.K., Schaap, O., Shaffer, H.B., Vrieling, K., Arntzen, J.W. (2016). Efficient screening for ‘genetic pollution’ in an anthropogenic crested newt hybrid zone. Conservation Genetics Resources 8(4): 553-560.

I initiated this work as a Newton International Fellow. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 655487.