Data from: Detection of individual ploidy levels with genotyping-by-sequencing (GBS) analysis

Ploidy levels sometimes vary among individuals or populations,
particularly in plants. When such variation exists, accurate determination
of cytotype can inform studies of ecology or trait variation and is
required for population genetic analyses. Here we propose and evaluate a
statistical approach for distinguishing low-level ploidy variants (e.g.,
diploids, triploids and tetraploids) based on genotyping-by-sequencing
data. The method infers cytotypes based on observed heterozygosity and the
ratio of DNA sequences containing different alleles at thousands of
heterozygous SNPs (i.e., allelic ratios). Whereas the method does not
require prior information on ploidy, a reference set of samples with known
ploidy can be included in the analysis if it is available. We explore the
power and limitations of this method using simulated data sets and GBS
data from natural populations of aspen (Populus tremuloides) known to
include both diploid and triploid individuals. The proposed method was
able to reliably discriminate among diploids, triploids and tetraploids in
simulated data sets, and this was true for different levels of genetic
diversity, inbreeding and population structure. Power and accuracy were
minimally affected by low coverage (i.e., 2X), but did sometimes suffer
when simulated mixtures of diploids, autotetraploids and allotetraploids
were analyzed. Cytotype assignments based on the proposed method closely
matched those from previous microsatellite and flow cytometry data when
applied to GBS data from aspen. An R package (gbs2ploidy) implementing the
proposed method is available from CRAN.