Discriminating styles (DS), pollen-mediated pseudo-self compatibility (PMPSC), and general pseudo-self compatibility (PSC) phenomena were investigated by re-analyzing data from Petunia hybrida where known S genotypes were used. This demonstrated how female coefficient of crossability (FCC)/male coefficient of crossability (MCC) scatter diagrams and regression analyses aid in identifying and quantifying PSC within an self incompatible (SI) population. One of the female testers was identified by statistics to be SI, not DS, in contrast to what was reported in the original report, where all the plants were assumed to have operating DS. In addition, none of the females expressed PMPSC. Based on regression analysis and chi-square tests, a threshold between 27% and 31% PSC was estimated to be necessary for expression of DS. The presence of DS was also required to test for the existence of PMPSC as reported previously. The upper left-hand quadrant of the FCC/MCC scatter diagram which contains all the deviants from the theoretical SI model, is the location expression of DS has been identified. Placement for PMPSC deviants is not possible, due to the interrelationship with DS. Percent PSC did not directly equate with the different types of PSC phenomena but was useful for identifying and ranking DS in female parents. The compatible tester used in this experiment did not always produce the highest outcross seed set with the females as expected. Therefore, due to the confounding effects of the different types of PSC, it is important to choose the compatible testers with care. Regression analyses of FCC/MCC values indicated that S2.2 and S1.2 male testers did not behave in a similar fashion to S1.1 testers. It is hypothesized that this disparity could be the result of the expression of a general PSC gene, different from the DS or PMPSC genes, which is linked to the S2 allele. Since these general PSC effects associated with the S2 allele are minor in comparison to DS and PMPSC, it was necessary to distinguish the difference using statistical analysis.
- Discriminating styles (DS)
- S alleles
- pseudo-self compatibility (PMPSC)