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.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-012-2003-7) contains supplementary material, which is available to authorized users.

Bridging the genotyping gap: using genotyping by sequencing (GBS) to add high-density SNP markers and new value to traditional bi-parental mapping and breeding populations

“…Yet, at the same time, traditional bi-parental mapping populations continue to play an important role in gene discovery, and both bi-parental and multi-parent breeding populations remain the foundation of many plant breeding programs (Almeida et al 2013;Famoso et al 2011;Rosyara et al 2009). While new "reference genomes" are being sequenced every day, many plant breeders and geneticists using traditional mapping and breeding populations continue to work with sparse molecular marker data, or in cases of extremely resource-limited programs (such as those often found in developing countries) no marker data at all, despite the abundance of public data on select lines (Rosyara et al 2009).…”

Stay-Green and Associated Vegetative Indices to Breed Maize Adapted to Heat and Combined Heat-Drought Stresses

“…Heat stress, however, was consistent throughout the season in both years, as reflected by both the mean daily maximum temperature (37.3 and 37.6 • C for 2014 and 2015, respectively) and the frequency of days with temperatures above the optimum (0.88 and 0.93 for 2014 and 2015, respectively). Compared to experiments carried out by CIMMYT using germplasm of similar genetic background under non-stressed conditions [14,34,35], grain yield was 53% and 82% lower for the experiments carried out in 2014 and 2015, respectively. These large yield reductions as a result of heat and combined heat and drought stress reflect the synergy of both stress factors when they occur together, as reported earlier [8].…”

“…Averaged across experiments, AUC SG was lower in 2015 relative to 2014 as a result of larger stress experienced during 2015, whereas the correlation of AUC SG with grain yield was similar in both years (r g = 0.56 and 0.50 for 2014 and 2015, respectively). Stability across years, correlations with grain yield, and high heritability (h 2 = 0.48-0.93), in addition to importance of stay-green shown in the past [34,35], make AUC SG a useful secondary trait for use in breeding programs in which target environments are characterized by frequent droughts after flowering and are exposed to heat stress. Although all trials in this study were exposed to stress around flowering and grain filling, it is expected that AUC SG is also a useful secondary trait under non-stressed conditions [14,19].…”

Quantitative trait locus analysis for kernel width using maize recombinant inbred lines

“…Maize kernel structure is a crucial trait that defines yield and appearance, but studies on the genetic mechanisms of kernel structure are few compared to those on other agronomic traits, such as yield (Huang et al, 2010;Peng et al, 2013;Xu et al, 2014), plant morphology Yu et al, 2014), disease resistance (Tao et al, 2013;Zambrano et al, 2014;Xu et al, 2014), and drought tolerance (Rahman et al, 2011;Almeida et al, 2013). However, a few studies have conducted QTL mapping for maize kernel width and investigated correlations with kernel structure.…”