FIGURE 3 Comparison of the percentage of correctly assigned samples (A, D), false negatives (B, D) and false positives (C, E) using lake–specific GB-RFLPs (A–C) and species-specific GB-RFLPs. On the left side of the plots are always estimates based on bootstrapping data using allele frequencies from a previously generated genomic dataset are on the left, data from GB-RFLP analyses on the right. Color-code in D–E indicates the populations of Crater Lake Apoyo (red), Xiloá (blue) and the great lake species A. citrinellus and A. labiatus(grey).
Most markers showed similar accuracy as in the bootstrapping dataset that was based on allele frequencies in the respective lakes with 1/18 markers performing much worse (>20% fewer correctly assigned samples; Fig. S3R) in the RT-RFLP assay than in the bootstrapping dataset (Fig. 3A–C). We also tested whether a combination of two markers would improve accuracy. For two populations, Great Lake Nicaragua (69% instead of 62.5%) and Crater Lake Masaya (100% instead of 94%), we found a marginal improvement of correct assignments (Table S4).
TABLE 1 Tested RFLP markers, their location in the reference genome, used restriction enzyme, quality of the marker, and correctly assigned individuals (in %). Quality was assessed based on a combination of the predicted and tested number of correctly assigned specimens (++++: >99%, +++: >95%, ++: >90%, +: >80%, –: <80%). Ingroup means “within test population”, outgroup “not within test population”. For lake markers (above line) the outgroup contains all samples, for species markers (below line) only sympatric species within the same respective crater lake.