A Random Model Approach to QTL Mapping in Multi-parent Advanced Generation

27 28 Most standard quantitative trait locus (QTL) mapping procedures apply to populations derived 29 from the cross of two parents. QTL detected from such bi-parental populations are rarely 30 relevant to breeding programs due to the narrow genetic basis; only two alleles are involved per 31 locus. To improve the generality and applicability of mapping results, QTL should be detected 32 using populations initiated from multiple parents, such as the multi-parent advanced generation 33 inter-cross (MAGIC) populations. The greatest challenges of QTL mapping in MAGIC 34 populations come from multiple founder alleles and control of the genetic background 35 information. We developed a random model methodology by treating the founder effects of each 36 locus as random effects following a normal distribution with a locus specific variance. We also 37 fit a polygenic effect to the model to control the genetic background. To improve the statistical 38 power for a scanned marker, we release the marker effect absorbed by the polygene back to the 39 model. In contrast to the fixed model approach, we estimate and test the variance of each locus 40 and scan the entire genome one locus at a time using the likelihood ratio test statistics. 41 Simulation studies showed that the new method can increase statistical power and reduce Type I 42 error compared with composite interval mapping (CIM) and multi-parent whole-genome average 43 interval mapping (MPWGAIM). We demonstrated the method using a public Arabidopsis 44 thaliana MAGIC population and a mouse MAGIC population. 45