2014
DOI: 10.1534/genetics.114.169367
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Linkage Disequilibrium with Linkage Analysis of Multiline Crosses Reveals Different Multiallelic QTL for Hybrid Performance in the Flint and Dent Heterotic Groups of Maize

Abstract: Multiparental designs combined with dense genotyping of parents have been proposed as a way to increase the diversity and resolution of quantitative trait loci (QTL) mapping studies, using methods combining linkage disequilibrium information with linkage analysis (LDLA). Two new nested association mapping designs adapted to European conditions were derived from the complementary dent and flint heterotic groups of maize (Zea mays L.). Ten biparental dent families (N = 841) and 11 biparental flint families (N = … Show more

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Cited by 85 publications
(147 citation statements)
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“…To map QTL in the NAM population (NAM2214), we used a JL model (Buckler et al 2009; Tian et al 2011) and a multi-locus linear regression model (MLLM) (Giraud et al 2014) adapted from Segura et al (2012). The model can be denoted as:y=Fα+140%truecMcβc+e,where y is the vector ( N  × 1) of adjusted phenotypic means for N RILs; F is a ( N  ×  P ) matrix of 0 and 1 that linked each RIL to the family it belonged, P being the number of families, α is the vector ( P  × 1) of family means; M c is the vector of genotypes of cofactor c that entered the model and β c its effect; and e is the vector of residual effects.…”
Section: Methodsmentioning
confidence: 99%
“…To map QTL in the NAM population (NAM2214), we used a JL model (Buckler et al 2009; Tian et al 2011) and a multi-locus linear regression model (MLLM) (Giraud et al 2014) adapted from Segura et al (2012). The model can be denoted as:y=Fα+140%truecMcβc+e,where y is the vector ( N  × 1) of adjusted phenotypic means for N RILs; F is a ( N  ×  P ) matrix of 0 and 1 that linked each RIL to the family it belonged, P being the number of families, α is the vector ( P  × 1) of family means; M c is the vector of genotypes of cofactor c that entered the model and β c its effect; and e is the vector of residual effects.…”
Section: Methodsmentioning
confidence: 99%
“…2013 or Giraud et al. 2014). These studies restricted the model to a single type of QTL effect, keeping the same type of incidence matrix across all loci.…”
Section: Methodsmentioning
confidence: 99%
“…The protection against false positives was ensured by backward elimination of candidate QTLs from a multilocus ME mixed model. Physical positions of significant SNPs were projected on the consensus genetic map for Dent genetic material (Giraud et al, 2014). Candidate SNPs distant less than 0.1 cМ were considered as belonging to a common QTL, described via the most significant SNP in the QTL and the interval between all SNPs belonging to the QTL.…”
Section: Gwas Analysismentioning
confidence: 99%