2020
DOI: 10.1111/1755-0998.13136
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Applying genomic data in wildlife monitoring: Development guidelines for genotyping degraded samples with reduced single nucleotide polymorphism panels

Abstract: The genomic era has led to an unprecedented increase in the availability of genomewide data for a broad range of taxa. Wildlife management strives to make use of these vast resources to enable refined genetic assessments that enhance biodiversity conservation. However, as new genomic platforms emerge, problems remain in adapting the usually complex approaches for genotyping of noninvasively collected wildlife samples. Here, we provide practical guidelines for the standardized development of reduced single nucl… Show more

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Cited by 72 publications
(72 citation statements)
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“…RAD‐sequencing (RAD‐seq) methods also do not require reference genomes and can generate an order of magnitude more loci than UCE‐based methods; this dense genomic sampling enables investigation of both neutral and adaptive differentiation (Hohenlohe et al., 2010), which is particularly important for defining conservation units (Funk et al., 2012). However, for inferences regarding population structure and gene flow, it has been shown that fewer than 100 informative SNP loci are sufficient (von Thaden et al., 2020) and here we analysed 1,794 independent SNPs. Additionally, the average heterozygosity of our UCE‐derived SNPs is 0.23, similar to that reported in RAD‐seq studies of other small mammal populations, including mice of the genera Apodemus (0.28; Cerezo et al., 2020) and Peromyscus (0.148–0.239; Garcia‐Elfring et al., 2019).…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…RAD‐sequencing (RAD‐seq) methods also do not require reference genomes and can generate an order of magnitude more loci than UCE‐based methods; this dense genomic sampling enables investigation of both neutral and adaptive differentiation (Hohenlohe et al., 2010), which is particularly important for defining conservation units (Funk et al., 2012). However, for inferences regarding population structure and gene flow, it has been shown that fewer than 100 informative SNP loci are sufficient (von Thaden et al., 2020) and here we analysed 1,794 independent SNPs. Additionally, the average heterozygosity of our UCE‐derived SNPs is 0.23, similar to that reported in RAD‐seq studies of other small mammal populations, including mice of the genera Apodemus (0.28; Cerezo et al., 2020) and Peromyscus (0.148–0.239; Garcia‐Elfring et al., 2019).…”
Section: Discussionmentioning
confidence: 99%
“…RADsequencing (RAD-seq) methods also do not require reference genomes and can generate an order of magnitude more loci than UCE-based methods; this dense genomic sampling enables investigation of both neutral and adaptive differentiation (Hohenlohe et al, 2010), which is particularly important for defining conservation units (Funk et al, 2012). However, for inferences regarding population structure and gene flow, it has been shown that fewer than 100 informative SNP loci are sufficient (von Thaden et al, 2020) and here we analysed 1,794 independent SNPs.…”
Section: Uces For Fine-scale Population Genomicsmentioning
confidence: 99%
“…Multiple genomic tools are available for targeted monitoring of large sets of loci (e.g. 92,93) and could be used to track adaptive evolution and potential in the form of genetic diversity (44). However, before management decisions are made for specific genes further work should first identify favoured alleles and functional fitness effects for the genes we found in linkage with our genotyped SNP markers (Supplemental Table S4) .…”
Section: Conservation Implicationsmentioning
confidence: 99%
“…(2020) illustrate how reduced‐representation sequencing can be used to improve threatened species management, while also highlighting its limitations von Thaden et al. (2020), and (Wright et al., 2020) provide guidance on developing SNP panels from degraded samples in order to monitor endangered species.…”
Section: Associate Editors and Reviewersmentioning
confidence: 99%