
@article {65295,
	title = {Empowering conservation practice with efficient and economical genotyping from poor quality samples.},
	journal = {Methods Ecol Evol},
	volume = {10},
	year = {2019},
	month = {2019 Jun},
	pages = {853-859},
	abstract = {<p>Moderate- to high-density genotyping (100 + SNPs) is widely used to determine and measure individual identity, relatedness, fitness, population structure and migration in wild populations.However, these important tools are difficult to apply when high-quality genetic material is unavailable. Most genomic tools are developed for high-quality DNA sources from laboratory or medical settings. As a result, most genetic data from market or field settings is limited to easily amplified mitochondrial DNA or a few microsatellites.To enable genotyping in conservation contexts, we used next-generation sequencing of multiplex PCR products from very low-quality DNA extracted from faeces, hair and cooked samples. We demonstrated utility and wide-ranging potential application in endangered wild tigers and tracking commercial trade in Caribbean queen conch.We genotyped 100 SNPs from degraded tiger samples to identify individuals, discern close relatives and detect population differentiation. Co-occurring carnivores do not amplify (e.g. Indian wild dog/dhole) or are monomorphic (e.g. leopard). Sixty-two SNPs from conch fritters and field-collected samples were used to test relatedness and detect population structure.We provide proof of concept for a rapid, simple, cost-effective and scalable method (for both samples and number of loci), a framework that can be applied to other conservation scenarios previously limited by low-quality DNA samples. These approaches provide a critical advance for wildlife monitoring and forensics, open the door to field-ready testing, and will strengthen the use of science in policy decisions and wildlife trade.</p>
},
	issn = {2041-210X},
	doi = {10.1111/2041-210X.13173},
	author = {Natesh, Meghana and Taylor, Ryan W and Truelove, Nathan K and Hadly, Elizabeth A and Palumbi, Stephen R and Petrov, Dmitri A and Ramakrishnan, Uma}
}
