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Durrant, Caroline (1)
Ehrenreich, Ian M. (1)
Kover, Paula X. (1)
Mauricio, Rodney (1)
Mott, Richard (1)
Purugganan, Michael D. (1)
Scarcelli, Nora (1)
Trakalo, Joseph (1)
Valdar, William (1)
Year of Publication
A Multiparent Advanced Generation Inter-Cross to Fine-Map Quantitative Traits in Arabidopsis thaliana
Kover, Paula X.
Ehrenreich, Ian M.
Purugganan, Michael D.
Identifying natural allelic variation that underlies quantitative trait variation remains a fundamental problem in genetics. Most studies have employed either simple synthetic populations with restricted allelic variation or performed association mapping on a sample of naturally occurring haplotypes. Both of these approaches have some limitations, therefore alternative resources for the genetic dissection of complex traits continue to be sought. Here we describe one such alternative, the Multiparent Advanced Generation Inter-Cross (MAGIC). This approach is expected to improve the precision with which QTL can be mapped, improving the outlook for QTL cloning. Here, we present the first panel of MAGIC lines developed: a set of 527 recombinant inbred lines (RILs) descended from a heterogeneous stock of 19 intermated accessions of the plant Arabidopsis thaliana. These lines and the 19 founders were genotyped with 1,260 single nucleotide polymorphisms and phenotyped for development-related traits. Analytical methods were developed to fine-map quantitative trait loci (QTL) in the MAGIC lines by reconstructing the genome of each line as a mosaic of the founders. We show by simulation that QTL explaining 10% of the phenotypic variance will be detected in most situations with an average mapping error of about 300 kb, and that if the number of lines were doubled the mapping error would be under 200 kb. We also show how the power to detect a QTL and the mapping accuracy vary, depending on QTL location. We demonstrate the utility of this new mapping population by mapping several known QTL with high precision and by finding novel QTL for germination data and bolting time. Our results provide strong support for similar ongoing efforts to produce MAGIC lines in other organisms.
Most traits of economic and evolutionary interest vary quantitatively and have multiple genes affecting their expression. Dissecting the genetic basis of such traits is crucial for the improvement of crops and management of diseases. Here, we develop a new resource to identify genes underlying such quantitative traits in Arabidopsis thaliana, a genetic model organism in plants. We show that using a large population of inbred lines derived from intercrossing 19 parents, we can localize the genes underlying quantitative traits better than with existing methods. Using these lines, we were able to replicate the identification of previously known genes that affect developmental traits in A. thaliana and identify some new ones. This paper also presents all the necessary biological and computational material necessary for the scientific community to use these lines in their own research. Our results suggest that the use of lines derived from a multiparent advanced generation inter-cross (MAGIC lines) should be very useful in other organisms.
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