Abstract
Key messageThe identity-by-descent (IBD)-based mixed model approach introduced in this study can detect quantitative trait loci (QTLs) referring to the parental origin and simultaneously account for multilevel relatedness of individuals within and across families. This unified approach is proved to be a powerful approach for all kinds of multiparental population (MPP) designs.Multiparental populations (MPPs) have become popular for quantitative trait loci (QTL) detection. Tools for QTL mapping in MPPs are mostly developed for specific MPPs and do not generalize well to other MPPs. We present an IBD-based mixed model approach for QTL mapping in all kinds of MPP designs, e.g., diallel, Nested Association Mapping (NAM), and Multiparental Advanced Generation Intercross (MAGIC) designs. The first step is to compute identity-by-descent (IBD) probabilities using a general Hidden Markov model framework, called reconstructing ancestry blocks bit by bit (RABBIT). Next, functions of IBD information are used as design matrices, or genetic predictors, in a mixed model approach to estimate variance components for multiallelic genetic effects associated with parents. Family-specific residual genetic effects are added, and a polygenic effect is structured by kinship relations between individuals. Case studies of simulated diallel, NAM, and MAGIC designs proved that the advanced IBD-based multi-QTL mixed model approach incorporating both kinship relations and family-specific residual variances (IBD.MQMkin_F) is robust across a variety of MPP designs and allele segregation patterns in comparison to a widely used benchmark association mapping method, and in most cases, outperformed or behaved at least as well as other tools developed for specific MPP designs in terms of mapping power and resolution. Successful analyses of real data cases confirmed the wide applicability of our IBD-based mixed model methodology.
Highlights
multiparental population (MPP) designs have their unique advantages for quantitative trait loci (QTL) mapping over biparental populations and association panels
A diallel mating design of carrot was constructed to dissect the genetic architecture of shoot growth by estimating the general and specific combing abilities and non-additive effects (Turner et al 2018); a maize Nested Association Mapping (NAM) population was proved to be able to capture small effect QTLs when they were shared by families (Ogut et al 2015); Multiparental Advanced Generation Intercross (MAGIC) populations allow a large set of QTLs segregating with higher resolution and can increase the chance of detecting QTLs (Mackay et al 2014)
Another study compared the different designs of biparental, multiparental, and association panels in the context of the genome sequencing era to show their complementarity in genetic studies (Pascual et al 2016)
Summary
MPP designs have their unique advantages for QTL mapping over biparental populations and association panels. Crossing two parents in a biparental population can balance allele frequencies and increase the chance to detect rare QTLs, but the narrow genetic diversity from only two parents limits the number of detected QTLs (Liu and Zeng 2000; Pascual et al 2016). QTL mapping models can be classified into family-based (or linkage) and population-based (or linkage disequilibrium) approaches based on the specific design (Myles et al 2009; Würschum 2012; Xu et al 2017). The multi-QTL effect (MQE) model with a mixture of bi-allelic, ancestral, and parental QTL effects and cross-specific residual proposed by Garin et al (2017) provides an example of such an approach for the EU-NAM maize data collection. A good example of the latter is the inclusive composite interval mapping (ICIM) approach as described by Li et al (2007), Zhang et al (2019), and Shi et al (2019), with an application to an eight-way MAGIC design in cow pea
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