ABSTRACT
Identifying sex-linked markers in genomic datasets is important because their presence in supposedly neutral autosomal datasets can result in incorrect estimates of genetic diversity, population structure and parentage. However, detecting sex-linked loci can be challenging, and available scripts neglect some categories of sex-linked variation. Here, we present new R functions to (1) identify and separate sex-linked loci in ZW and XY sex determination systems and (2) infer the genetic sex of individuals based on these loci. We tested these functions on genomic data for two bird and one mammal species and compared the biological inferences made before and after removing sex-linked loci using our function. We found that our function identified autosomal loci with ≥98.8% accuracy and sex-linked loci with an average accuracy of 87.8%. We showed that standard filters, such as low read depth and call rate, failed to remove up to 54.7% of sex-linked loci. This led to (i) overestimation of population FIS by up to 24%, and the number of private alleles by up to 8%; (ii) wrongly inferring significant sex differences in heterozygosity; (iii) obscuring genetic population structure and (iv) inferring ~11% fewer correct parentages. We discuss how failure to remove sex-linked markers can lead to incorrect biological inferences (e.g. sex-biased dispersal and cryptic population structure) and misleading management recommendations. For reduced-representation datasets with at least 15 known-sex individuals of each sex, our functions offer convenient resources to remove sex-linked loci and to sex the remaining individuals (freely available at https://github.com/drobledoruiz/conservation_genomics).
ABSTRACT
Since European colonization, Leadbeater's possum (Gymnobelideus leadbeateri) has declined across its range to the point where it is now only patchily distributed within the montane ash forests of the Central Highlands of Victoria. The loss of large hollow-bearing trees coupled with inadequate recruitment of mature ash forest has been predicted to result in a reduction in population size of up to 90% by 2020. Furthermore, bioclimatic analyses have suggested additional reductions in the species' distribution under a variety of climate change scenarios. Using a panel of 15 highly resolving microsatellite markers and mitochondrial control region sequence data, we infer past and present gene flow. Populations in the northern part of the core range were highly admixed, and showed no signs of either current or historical barriers to gene flow. A marginal, isolated and inbred population at Yellingbo was highly genetically differentiated, both in terms of current and historic genetic structure. Sequence data confirmed the conclusions from earlier genetic simulation studies that the Yellingbo population has been isolated from the rest of the species range since before European-induced changes to the montane landscape, and formed part of a larger genetic unit that is now otherwise extinct. Historic loss of maternal lineages in the Central Highlands of Victoria was detected despite signals of immigration, indicating population declines that most probably coincided with changes in climate at the end of the Pleistocene. Given ongoing habitat loss and the recent (February 2009) wildfire in the Central Highlands, we forecast (potentially extensive) demographic declines, in line with predicted range reductions under climate change scenarios.
