Comparative assessment of genotyping-by-sequencing and whole-exome
sequencing for estimating genetic diversity and geographic structure in
natural jaguar populations
Abstract
Biologists currently have an assortment of high-throughput sequencing
techniques allowing the study of population dynamics in increasing
detail. The utility of genetic estimates depends on their ability to
recover meaningful approximations while filtering out noise produced by
artifacts. We empirically compared the congruence of two reduced
representation approaches (genotyping-by-sequencing, GBS, and
whole-exome sequencing, WES) in estimating genetic diversity and
population structure using SNP markers typed in small samples of five
jaguar (Panthera onca) demes. Given their intrinsic properties as a
targeted capture, WES allowed for a more straightforward reconstruction
of loci compared to GBS, which in turn facilitated the identification of
true polymorphisms across individuals. In contrast, GBS data showed a
recurrent miscalling of heterozygous sites. We therefore used
WES-derived metrics as a benchmark against which GBS-derived indicators
were compared, varying the values of parameters for locus assembly,
genotype calling and SNP filtering in the latter technique. Changes in
parameterization induced measurable differences in summary statistics,
both between approaches and among distinct batches of GBS data. The
application of post-processing genotype filters based on mean depth of
reads had major effects on the consistency between approaches. Overall,
we observed that the direct empirical comparison of GBS and WES for
estimating population genetic attributes from the same set of
individuals provided an interesting opportunity to assess the
consistency of these approaches, revealing relevant aspects that should
be considered in such analyses. Our results highlight the importance of
thorough data filtering in genomic approaches to obtain robust genetic
diversity and differentiation estimates.