title: QTL mapping in three tropical maize populations reveals a set of constitutive and adaptive genomic regions for drought tolerance.
abstract: Despite numerous published reports of quantitative trait loci (QTL) for drought-related traits, practical applications of such QTL in maize improvement are scarce. Identifying QTL of sizeable effects that express more or less uniformly in diverse genetic backgrounds across contrasting water regimes could significantly complement conventional breeding efforts to improve drought tolerance. We evaluated three tropical bi-parental populations under water-stress (WS) and well-watered (WW) regimes in Mexico, Kenya and Zimbabwe to identify genomic regions responsible for grain yield (GY) and anthesis-silking interval (ASI) across multiple environments and diverse genetic backgrounds. Across the three populations, on average, drought stress reduced GY by more than 50 % and increased ASI by 3.2 days. We identified a total of 83 and 62 QTL through individual environment analyses for GY and ASI, respectively. In each population, most QTL consistently showed up in each water regime. Across the three populations, the phenotypic variance explained by various individual QTL ranged from 2.6 to 17.8 % for GY and 1.7 to 17.8 % for ASI under WS environments and from 5 to 19.5 % for GY under WW environments. Meta-QTL (mQTL) analysis across the three populations and multiple environments identified seven genomic regions for GY and one for ASI, of which six mQTL on chr.1, 4, 5 and 10 for GY were constitutively expressed across WS and WW environments. One mQTL on chr.7 for GY and one on chr.3 for ASI were found to be 'adaptive' to WS conditions. High throughput assays were developed for SNPs that delimit the physical intervals of these mQTL. At most of the QTL, almost equal number of favorable alleles was donated by either of the parents within each cross, thereby demonstrating the potential of drought tolerant × drought tolerant crosses to identify QTL under contrasting water regimes.
authors.affiliation: Universidade Federal de Viçosa (UFV), CEP 36.570-000, Viçosa, Minas Gerais, Brazil.
authors.forename: Gustavo Dias
authors.initials: GD
authors.lastname: Almeida
authors.forename: Dan
authors.initials: D
authors.lastname: Makumbi
authors.forename: Cosmos
authors.initials: C
authors.lastname: Magorokosho
authors.forename: Sudha
authors.initials: S
authors.lastname: Nair
authors.forename: Aluízio
authors.initials: A
authors.lastname: Borém
authors.forename: Jean-Marcel
authors.initials: JM
authors.lastname: Ribaut
authors.forename: Marianne
authors.initials: M
authors.lastname: Bänziger
authors.forename: Boddupalli M
authors.initials: BM
authors.lastname: Prasanna
authors.forename: Jose
authors.initials: J
authors.lastname: Crossa
authors.forename: Raman
authors.initials: R
authors.lastname: Babu
mesh_terms: D000222:Adaptation, Physiological / Q000235:genetics*; D001947:Breeding; D002874:Chromosome Mapping; D055864:Droughts; D004777:Environment; D005819:Genetic Markers; D018745:Genome, Plant; D007630:Kenya; D008800:Mexico; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci; D013312:Stress, Physiological / Q000235:genetics; D014867:Water / Q000032:analysis; D003313:Zea mays / Q000235:genetics*; D015030:Zimbabwe
chemical_list: D005819:Genetic Markers; D014867:Water