A bioinformatic pipeline for identifying informative SNP panels for parentage assignment from RADseq data.

The development of high-throughput sequencing technologies is dramatically increasing the use of single nucleotide polymorphisms (SNPs) across the field of genetics, but most parentage studies of wild populations still rely on microsatellites. We developed a bioinformatic pipeline for identifying SNP panels that are informative for parentage analysis from restriction site-associated DNA sequencing (RADseq) data. This pipeline includes options for analysis with or without a reference genome, and provides methods to maximize genotyping accuracy and select sets of unlinked loci that have high statistical power. We test this pipeline on small populations of Mexican gray wolf and bighorn sheep, for which parentage analyses are expected to be challenging due to low genetic diversity and the presence of many closely related individuals. We compare the results of parentage analysis across SNP panels generated with or without the use of a reference genome, and between SNPs and microsatellites. For Mexican gray wolf, we conducted parentage analyses for 30 pups from a single cohort where samples were available from 64% of possible mothers and 53% of possible fathers, and the accuracy of parentage assignments could be estimated because true identities of parents were known a priori based on field data. For bighorn sheep, we conducted maternity analyses for 39 lambs from five cohorts where 77% of possible mothers were sampled, but true identities of parents were unknown. Analyses with and without a reference genome produced SNP panels with ≥95% parentage assignment accuracy for Mexican gray wolf, outperforming microsatellites at 78% accuracy. Maternity assignments were completely consistent across all SNP panels for the bighorn sheep, and were 74.4% consistent with assignments from microsatellites. Accuracy and consistency of parentage analysis were not reduced when using as few as 284 SNPs for Mexican gray wolf and 142 SNPs for bighorn sheep, indicating our pipeline can be used to develop SNP genotyping assays for parentage analysis with relatively small numbers of loci.

Local extinction and unintentional rewilding of bighorn sheep (Ovis canadensis) on a desert island.

Bighorn sheep (Ovis canadensis) were not known to live on Tiburón Island, the largest island in the Gulf of California and Mexico, prior to the surprisingly successful introduction of 20 individuals as a conservation measure in 1975. Today, a stable island population of ∼500 sheep supports limited big game hunting and restocking of depleted areas on the Mexican mainland. We discovered fossil dung morphologically similar to that of bighorn sheep in a dung mat deposit from Mojet Cave, in the mountains of Tiburón Island. To determine the origin of this cave deposit we compared pellet shape to fecal pellets of other large mammals, and extracted DNA to sequence mitochondrial DNA fragments at the 12S ribosomal RNA and control regions. The fossil dung was 14C-dated to 1476-1632 calendar years before present and was confirmed as bighorn sheep by morphological and ancient DNA (aDNA) analysis. 12S sequences closely or exactly matched known bighorn sheep sequences; control region sequences exactly matched a haplotype described in desert bighorn sheep populations in southwest Arizona and southern California and showed subtle differentiation from the extant Tiburón population. Native desert bighorn sheep previously colonized this land-bridge island, most likely during the Pleistocene, when lower sea levels connected Tiburón to the mainland. They were extirpated sometime in the last ∼1500 years, probably due to inherent dynamics of isolated populations, prolonged drought, and (or) human overkill. The reintroduced population is vulnerable to similar extinction risks. The discovery presented here refutes conventional wisdom that bighorn sheep are not native to Tiburón Island, and establishes its recent introduction as an example of unintentional rewilding, defined here as the introduction of a species without knowledge that it was once native and has since gone locally extinct.

Effective population size, genetic variation, and their relevance for conservation: the bighorn sheep in Tiburon Island and comparisons with managed artiodactyls.

The amount of genetic diversity in a finite biological population mostly depends on the interactions among evolutionary forces and the effective population size (N(e)) as well as the time since population establishment. Because the N(e) estimation helps to explore population demographic history, and allows one to predict the behavior of genetic diversity through time, N(e) is a key parameter for the genetic management of small and isolated populations. Here, we explored an N(e)-based approach using a bighorn sheep population on Tiburon Island, Mexico (TI) as a model. We estimated the current (N(crnt)) and ancestral stable (N(stbl)) inbreeding effective population sizes as well as summary statistics to assess genetic diversity and the demographic scenarios that could explain such diversity. Then, we evaluated the feasibility of using TI as a source population for reintroduction programs. We also included data from other bighorn sheep and artiodactyl populations in the analysis to compare their inbreeding effective size estimates. The TI population showed high levels of genetic diversity with respect to other managed populations. However, our analysis suggested that TI has been under a genetic bottleneck, indicating that using individuals from this population as the only source for reintroduction could lead to a severe genetic diversity reduction. Analyses of the published data did not show a strict correlation between H(E) and N(crnt) estimates. Moreover, we detected that ancient anthropogenic and climatic pressures affected all studied populations. We conclude that the estimation of N(crnt) and N(stbl) are informative genetic diversity estimators and should be used in addition to summary statistics for conservation and population management planning.