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Frequency distributions of the panicle blast severity in the three tested generations in different fields (Figure 3A, B, and C) suggested that multiple loci are involved in panicle blast resistance of Miyazakimochi.
The MLMM algorithm assumes that multiple loci are associated with resistance, and is a stepwise EMMAX, which re-computes genetic and error variance each step (Segura et al. 2012).
However, traits that are controlled by allelic series or multiple loci are not Mendelian characters, and are not subject to Mendelian ratios.
In the combined approach, sequences from multiple loci are concatenated, and the resulting data set is analyzed using phylogenetic methods.
Multiple loci are also required in some methods for estimating the effective population size of ancestral populations [15], [16].
Multiple loci are involved in the evolution of photoperiodic response in W. smithii as evidenced from both line-cross analysis [12], [47] [49] and QTL mapping [29].
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Furthermore, inferences based on single genes could lead to erroneous conclusions and population genetic outcomes, thus usage of multiple loci is suggested.
In order to examine genealogical concordance, multiple loci were examined.
We expect that for different regions of the genome the error rates will differ, and extending these methods to multiple loci is an important direction for future work.
If multiple loci were available, these were concatenated.
Reads that aligned to multiple loci were discarded.
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