Combined linkage and linkage disequilibrium QTL mapping in multiple families of maize (Zea mays L.) line crosses highlights complementarities between models based on parental haplotype and single locus polymorphism

Advancements in genotyping are rapidly decreasing marker costs and increasing marker density. This opens new possibilities for mapping quantitative trait loci (QTL), in particular by combining linkage disequilibrium information and linkage analysis (LDLA). In this study, we compared different approa...

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Bibliographic Details
Published in:	Theoretical and applied genetics Vol. 126; no. 11; pp. 2717 - 2736
Main Authors:	Bardol, N, Ventelon, M, Mangin, B, Jasson, S, Loywick, V, Couton, F, Derue, C, Blanchard, P, Charcosset, A, Moreau, Laurence
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer-Verlag 01-11-2013 Springer Berlin Heidelberg Springer Springer Nature B.V Springer Verlag
Subjects:	Accuracy Agriculture Alleles Biochemistry Biomedical and Life Sciences Biotechnology Chromosome Mapping Cluster Analysis Computer Science Corn Crosses, Genetic crossing data collection Genetic aspects Genetic Loci - genetics Genetic polymorphisms Genome, Plant - genetics genotyping Haplotypes Haplotypes - genetics Inheritance Patterns - genetics Life Sciences linkage disequilibrium Linkage Disequilibrium - genetics loci Mathematics Models, Genetic Original Paper Physiological aspects Plant Biochemistry Plant Breeding/Biotechnology Plant Genetics and Genomics Polymorphism Polymorphism, Genetic Quantitative genetics Quantitative trait loci Quantitative Trait Loci - genetics Simulation single nucleotide polymorphism Statistical power Vegetal Biology Zea mays Zea mays - genetics France Quantitative Trait Locus Detection Parental Allele Quantitative Trait Locus Quantitative Trait Locus Mapping Quantitative Trait Locus Allele IDENTITY DIALLEL CROSS QUANTITATIVE TRAIT LOCI POPULATION MARKERS POWER GENETIC ARCHITECTURE ALLELIC NUMBER COMPLEX TRAITS GENOME-WIDE ASSOCIATION
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Summary:	Advancements in genotyping are rapidly decreasing marker costs and increasing marker density. This opens new possibilities for mapping quantitative trait loci (QTL), in particular by combining linkage disequilibrium information and linkage analysis (LDLA). In this study, we compared different approaches to detect QTL for four traits of agronomical importance in two large multi-parental datasets of maize (Zea mays L.) of 895 and 928 testcross progenies composed of 7 and 21 biparental families, respectively, and genotyped with 491 markers. We compared to traditional linkage-based methods two LDLA models relying on the dense genotyping of parental lines with 17,728 SNP: one based on a clustering approach of parental line segments into ancestral alleles and one based on single marker information. The two LDLA models generally identified more QTL (60 and 52 QTL in total) than classical linkage models (49 and 44 QTL in total). However, they performed inconsistently over datasets and traits suggesting that a compromise must be found between the reduction of allele number for increasing statistical power and the adequacy of the model to potentially complex allelic variation. For some QTL, the model exclusively based on linkage analysis, which assumed that each parental line carried a different QTL allele, was able to capture remaining variation not explained by LDLA models. These complementarities between models clearly suggest that the different QTL mapping approaches must be considered to capture the different levels of allelic variation at QTL involved in complex traits.
Bibliography:	http://dx.doi.org/10.1007/s00122-013-2167-9 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	0040-5752 1432-2242
DOI:	10.1007/s00122-013-2167-9