Identification of quantitative trait loci under drought conditions in tropical maize. 2. Yield components and marker-assisted selection strategies

Abstract

In most maize-growing areas yield reductions due to drought have been observed. Drought at flowering time is, in some cases, the most damaging. In the experiment reported here, trials with F families, derived from a segregating F population, were conducted in the field under well-watered conditions (WW) and two other water-stress regimes affecting flowering (intermediate stress, IS, and severe stress, SS). Several yield components were measured on equal numbers of plants per family: grain yield (GY), ear number (ENO), kernel number (KNO), and 100-kernel weight (HKWT). Correlation analysis of these traits showed that they were not independent of each other. Drought resulted in a 60% decrease of GY under SS conditions. By comparing yield under WW and SS conditions, the families that performed best under WW conditions were found to be proportionately more affected by stress, and the yield reductions due to SS conditions were inversely proportional to the performance under drought. Moreover, no positive correlation was observed between a drought-tolerance index (DTI) and yield under WW conditions. The correlation between GY under WW and SS conditions was 0.31. Therefore, in this experiment, selection for yield improvement under WW conditions only, would not be very effective for yield improvement under drought. Quantitative trait loci (QTLs) were identified for GY, ENO and KNO using composite interval mapping (CIM). No major QTLs, expressing more then 13% of the phenotypic variance, were detected for any of these traits, and there were inconsistencies in their genomic positions across water regimes. The use of CIM allowed the evaluation of QTL-by-environment interactions (Q;E) and could thus identify ''stable'' QTLs Communicated by G. E. Hart

Mapping Density Response in Maize: A Direct Approach for Testing Genotype and Treatment Interactions

“…Introgression effects for grain yield per plant were positively correlated to the effects on kernel number per plant ( Table 4), results that agree with previous reports that kernel number is the principal yield component in maize and that its correlation with grain yield is not affected by stress (Ribaut et al 1996(Ribaut et al , 1997Chapman and Edmeades 1999;Frova et al 1999). There was no statistically significant phenotypic correlation between ASI and yield components.…”

“…Plants susceptible to drought stress tend to delay silking and have longer ASIs. Anthesis date, on the other hand, is less affected in the presence of several different stresses (Ribaut et al 1996(Ribaut et al , 1997. Plant heights modify the ability of a genotype to avoid shading by neighboring individuals.…”

“…Therefore, ASI was not likely to be responsible for how the genotypes differed for responses to density measured in terms of yield and its component traits. Previous research has consistently reported that the phenotypic correlation between ASI and yield increases under intermediate to severe drought conditions (Bolanos and Edmeades 1996;Ribaut et al 1997;Betran et al 2003). However, the relationship between ASI and grain yield per plant may be specific to drought stress.…”

Microsatellite-assisted backcross selection in maize

“…Differences in laboratory strategies such as different DNA markers are rarely taken into account in theoretical papers (Ribault et al, 2002) and the practical implications of the use of different marker technologies should be considered to achieve selection. Newer and simpler DNA marker systems have been developed and even the technological constraints of early restriction fragment length polymorphism (RFLP) methods seemed to have been overcome (Ribaut et al, 1997), with high-density DNA marker maps having been constructed for almost every important crop species (OBrien, 1993). According to Young (1999), more than 400 articles containing the key words 'marker-assisted breeding' or 'marker-assisted selection' can be found in the 1995 to 1999 Current Contents, yet few if any, actually describe the use of marker-assisted technology leading to the release of varieties and few give experimental results validating the efficiency of markerassisted methodologies in different crop species (Ragot et al, 1994;Stuber, 1994;Salina et al, 2003;Lecomte et al, 2004).…”

QTL mapping to anthracnose leaf blight resistance in tropical maize

“…Tropical maize populations have broad genetic basis compared with those of temperate climate zones. Besides, tropical areas are more likely to undergo environmental stress than temperate areas (Ribaut et al 1997). Thus, QTL mapping in tropical genotypes enabled identifying new genomic regions and resistance alleles, which are possibly not yet known to the scientific community.…”