Eagle: multi-locus association mapping on a genome-wide scale made routine

WGNAM: whole-genome nested association mapping

A powerful QTL analysis method for nested association mapping populations is presented. Based on a one-stage multi-locus model, it provides accurate predictions of founder specific QTL effects. Nested association mapping (NAM) populations have been created to enable the identification of quantitative trait loci (QTL) in different genetic backgrounds. A whole-genome nested association mapping (WGNAM) method is presented to perform QTL analysis in NAM populations. The WGNAM method is an adaptation of the multi-parent whole genome average interval mapping approach where the crossing design is incorporated through the probability of inheriting founder alleles for every marker across the genome. Based on a linear mixed model, this method provides a one-stage analysis of raw phenotypic data, molecular markers, and crossing design. It simultaneously scans the whole-genome through an iterative process leading to a model with all the identified QTL while keeping the false positive rate low. The WGNAM approach was assessed through a simulation study, confirming to be a powerful and accurate method for QTL analysis for a NAM population. This novel method can also accommodate a multi-reference NAM (MR-NAM) population where donor parents are crossed with multiple reference parents to increase genetic diversity. Therefore, a demonstration is presented using a MR-NAM population for wheat (Triticum aestivum L.) to perform a QTL analysis for plant height. The strength and size of the putative QTL were summarized enhancing the understanding of the QTL effects depending on the parental origin. Compared to other methods, the proposed methodology based on a one-stage analysis provides greater power to detect QTL and increased accuracy in the estimation of their effects. The WGNAM method establishes the basis for accurate QTL mapping studies for NAM and MR-NAM populations.

Eagle for better genome-wide association mapping

Eagle is an R package for multi-locus association mapping on a genome-wide scale. It is unlike other multi-locus packages in that it is easy to use for R users and non-users alike. It has two modes of use, command line and graphical user interface. Eagle is fully documented and has its own supporting website, http://eagle.r-forge.r-project.org/index.html. Eagle is a significant improvement over the method-of-choice, single-locus association mapping. It has greater power to detect SNP-trait associations. It is based on model selection, linear mixed models, and a clever idea on how random effects can be used to identify SNP-trait associations. Through an example with real mouse data, we demonstrate Eagle's ability to bring clarity and increased insight to single-locus findings. Initially, we see Eagle complementing single-locus analyses. However, over time, we hope the community will make, increasingly, multi-locus association mapping their method-of-choice for the analysis of genome-wide association study data.