Discovery of 20,000 RAD–SNPs and development of a 52-SNP array for monitoring river otters

Abstract

Many North American river otter (Lontra canadensis) populations are threatened or recovering but are difficult to study because they occur at low densities, it is difficult to visually identify individuals, and they inhabit aquatic environments that accelerate degradation of biological samples. Single nucleotide polymorphisms (SNPs) can improve our ability to monitor demographic and genetic parameters of difficult to study species. We used restriction site associated DNA (RAD) sequencing to discover 20,772 SNPs present in Montana, USA, river otter populations, including 14,512 loci that were also variable in at least one other population range-wide. After applying careful filtering criteria meant to minimize ascertainment bias and identify high quality, highly heterozygous (H o = 0.2-0.50) SNPs, we developed and tested 52 independent SNP qPCR genotyping assays, including 41 that performed well with diluted DNA. The 41 loci provided high power for population assignment tests with only 1 misassignment (1.6 %) between closely neighboring populations. Our SNPs showed high power to differentiate individuals and assign them to population of origin, as well as strong concordance of genotypes from high and diluted concentrations of DNA, and between original RAD and the SNP qPCR array.

Applying genomic data in wildlife monitoring: Development guidelines for genotyping degraded samples with reduced single nucleotide polymorphism panels

“…An initial pool of candidate SNP loci for assay design may be filtered from genomic data according to the respective application purposes, such as high heterozygosities for individual identification (Kraus et al, ; Stetz et al, ), maximized F ST between species for hybridization or introgression assessments (Henriques et al, ; Nussberger, Greminger, Grossen, Keller, & Wandeler, ; Pritchard et al, ), and high minor allele frequencies for relatedness estimations (Andrews et al, ; Baetscher et al, ; Zhao et al, ), or for sex determination (Katzner et al, ; Norman, Street, & Spong, ; Nussberger, Wandeler, & Camenisch, ).…”

“…The genomics era has been accompanied by an ever increasing availability of whole genomes generated from high-throughput (Kraus et al, 2015;Stetz et al, 2016), maximized F ST between species for hybridization or introgression assessments (Henriques et al, 2018;Nussberger, Greminger, Grossen, Keller, & Wandeler, 2013;Pritchard et al, 2016), and high minor allele frequencies for relatedness estimations (Andrews et al, 2018;Baetscher et al, 2017;Zhao et al, 2018), or for sex determination (Katzner et al, 2017;Norman, Street, & Spong, 2013;Nussberger, Wandeler, & Camenisch, 2014a).…”

Whole‐genome sequencing approaches for conservation biology: Advantages, limitations and practical recommendations

“…A subset of these loci can be used for the development of cost-effective genotyping tools suitable for the assessment of diverse aspects of interest in conservation and management (e.g., taxonomic status, hybrids, sex, carriers of genetic diseases, population structure, individual assignment and population of origin, among others). These tools can be incorporated in conservation plans of threatened species (Norman, Street, & Spong, 2013;Muñoz et al, 2015;Ivy, Putnam, Navarro, Gurr, & Ryder, 2016;Stetz et al, 2016;Fussi et al, 2016;Vandergast, 2017;Grossen, Biebach, Angelone-Alasaad, Keller, & Croll, 2017) and in management plans of commercially valuable species (Martinsohn & Ogden, 2009;Habicht et al, 2012;Bekkevold et al, 2015;Bradbury et al, 2015;Aykanat, Lindqvist, Pritchard, & Primmer, 2016;Sinclair-Waters, 2017). The scarcity of genomic resources for most species under conservation concern coupled with the still high cost of high-throughput sequencing and the elevated demand for computing resources, however, have limited the implementation of WGR in conservation biology.…”

Conservation priorities for endangered Indian tigers through a genomic lens

“…Such data has helped identify African savannah ( Loxodonta africana ) and forest elephants ( Loxodonta cyclotis ) as separate species 4 , detect cryptic population structure in chimpanzees ( Pan troglodytes ) 5 , reveal local adaptation in giant panda ( Ailuropoda melanoleuca ) populations 6 and quantify genetic diversity in Tasmanian devils 7 ( Sarcophilus harrisii ). Genome-wide Single Nucleotide Polymorhphisms (SNPs) have been developed for monitoring populations in the wild, including bears 8 ( Ursus arctos ), wolves 9 ( Canis lupus ) and river otters 10 ( Lontra canadensis ). Several thousands of SNPs provide higher statistical power in comparison to examining a limited number of microsatellites, resulting in more robust population genetic inference 11 , 12 .…”