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In addition, an extensive repertoire of genomic tools facilitate the cloning of quantitative trait loci (QTL) –. thaliana for many ecological and developmental traits –. Thus, new resources to dissect and exploit this variation are needed.Īrabidopsis thaliana is an ideal species in which to develop resources because it is a model for the study of plant genetics, and extensive natural variation segregates among accessions of A. Naturally occurring genetic variation is a valuable source of alleles for economically important traits, but much of the genetic basis of natural variation in these traits remains unresolved. Their phenotypic expression is determined by the combination of many genetic and environmental factors. Most plant traits of agronomic and economic interest, such as seed dormancy, flowering time, fruit production, disease resistance, etc., vary quantitatively and have complex genetic inheritance. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.įunding: This research was supported by a BBSRC grant (BB/D016029/1) to PXK and RM and by MRC fellowships to WV and CD. Received: MaAccepted: JPublished: July 10, 2009Ĭopyright: © 2009 Kover et al. PLoS Genet 5(7):Įditor: Rodney Mauricio, University of Georgia, United States of America
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(2009) A Multiparent Advanced Generation Inter-Cross to Fine-Map Quantitative Traits in Arabidopsis thaliana.
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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.Ĭitation: Kover PX, Valdar W, Trakalo J, Scarcelli N, Ehrenreich IM, Purugganan MD, et al. This paper also presents all the necessary biological and computational material necessary for the scientific community to use these lines in their own research. Using these lines, we were able to replicate the identification of previously known genes that affect developmental traits in A. 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. Here, we develop a new resource to identify genes underlying such quantitative traits in Arabidopsis thaliana, a genetic model organism in plants. Dissecting the genetic basis of such traits is crucial for the improvement of crops and management of diseases. Most traits of economic and evolutionary interest vary quantitatively and have multiple genes affecting their expression. Our results provide strong support for similar ongoing efforts to produce MAGIC lines in other organisms. 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. We also show how the power to detect a QTL and the mapping accuracy vary, depending on QTL location. 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. 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. These lines and the 19 founders were genotyped with 1,260 single nucleotide polymorphisms and phenotyped for development-related traits. 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. This approach is expected to improve the precision with which QTL can be mapped, improving the outlook for QTL cloning. Here we describe one such alternative, the Multiparent Advanced Generation Inter-Cross (MAGIC). Both of these approaches have some limitations, therefore alternative resources for the genetic dissection of complex traits continue to be sought. Most studies have employed either simple synthetic populations with restricted allelic variation or performed association mapping on a sample of naturally occurring haplotypes. Identifying natural allelic variation that underlies quantitative trait variation remains a fundamental problem in genetics.