Combining quantitative trait Loci analysis and an ecophysiological model to analyze the genetic variability of the responses of maize leaf growth to temperature and water deficit

Abstract

Ecophysiological models predict quantitative traits of one genotype in any environment, whereas quantitative trait locus (QTL) models predict the contribution of alleles to quantitative traits under a limited number of environments. We have combined both approaches by dissecting into effects of QTLs the parameters of a model of maize (Zea mays) leaf elongation rate (LER; H. Ben Haj Salah, F. Tardieu [1997] Plant Physiol 114: 893-900). Response curves of LER to meristem temperature, water vapor pressure difference, and soil water status were established in 100 recombinant inbred lines (RILs) of maize in six experiments carried out in the field or in the greenhouse. All responses were linear and common to different experiments, consistent with the model. A QTL analysis was carried out on the slopes of these responses by composite interval mapping confirmed by bootstrap analysis. Most QTLs were specific of one response only. QTLs of abscisic acid concentration in the xylem sap colocalized with QTLs of response to soil water deficit and conferred a low response. Each parameter of the ecophysiological model was computed as the sum of QTL effects, allowing calculation of parameters for 11 new RILs and two parental lines. LERs were simulated and compared with measurements in a growth chamber experiment. The combined model accounted for 74% of the variability of LER, suggesting that it has a general value for any RIL under any environment.

Figure 1

Dissection of the responses of LER to temperature, evaporative demand, and soil water status in two typical RILs (white and black symbols). A, LER per unit clock time, plotted against meristem temperature. C, LER per unit thermal time, plotted against meristem temperature. The mean LER is an estimate of parameter a of Equation 1. D, LER per unit thermal time, plotted against meristem to air water vapor pressure difference (VPD) in well-watered plants. E, LER per unit thermal time during night periods, plotted against predawn leaf water potential. B, Graphical representations of parameters a, b, b₀, c and c₀ of Equation 1. A through D, experiments GC1 (▵), GC2 (○), FC1 (□), and FC2(▿). E, Experiments GS1 (□), GS2 (○), and mean values of LER in experiments GC1 and GC2 in the absence of evaporative demand and water deficit (◊).

Figure 2

Frequency distributions of parameters of the response curves in the 100 studied RILs. A, Intrinsic LER (parameter a). B, Slope of the relationship between LER and meristem to air vapor pressure difference (parameter b). C, x Intercept of the same relationships (parameter b₀). D, Slope of the relationship between LER and predawn leaf water potential (parameter c). C, x Intercept of the same relationships (parameter c₀). The values corresponding to parental lines (PLs) are also shown. Insets in A, B, and D, Frequency distributions of r² corresponding to each RIL.

Figure 3

Positions of the most relevant QTLs detected. a, Intrinsic elongation rate; b, slope of the response of elongation rate to meristem to air VPD; c, slope of the response of elongation rate to soil water potential; b₀ and c₀, x intercept of the same relationships (see Fig. 1B). QTLs of concentration of abscisic acid (ABA) in the xylem sap in plants grown at a predawn leaf water potential of −0.20 MPa. Only QTLs with highest F and high bootstrap values are presented, for better legibility (see Table II for other QTLs). QTLs that decrease the value of the trait in the PL F-2 are on the left side of the chromosomes and those that increase it are on the right.

Figure 4

Frequency distributions of the concentration of ABA in the xylem sap of the 100 RILs at a predawn leaf water potential of −0.20 MPa.

Figure 5

Test of the combined QTL and ecophysiological model of LER, either on the same RILs as in the QTL analysis (A and B) or on 13 lines that were not taken into account in the QTL analysis (C). A and B, Measured values plotted against predicted values using Equation 1. Parameters of Equation 1 were determined either by individual regression for each RIL as in Figure 1A or by using the QTL models of Table II (B). C, Measured values originating from growth chamber experiments (11 RILs and two PLs) or a greenhouse experiment with water deficit (two PLs). C, Each symbol represents an RIL or a PL.

Figure 6

Time courses of measured and modeled LERs during a climatic scenario in the growth chamber. Five RILs are presented, which were not taken into account in the detection of QTLs. Values corresponding to two RILs with similar predicted and measured values were averaged for better legibility. The modeled values were obtained from the ecophysiological model (Eq. 1) whose parameters were calculated as a sum of QTL effects with the genetic models (Table II). A, Change with time of meristem temperature (plain line) and VPD (dotted line). Numbers on the top of the panel represent periods, identified for better legibility in the text. Black bars on the bottom indicate the night periods. B, LER measured with linear variable displacement transducers (LVDTs), averaged on two or more plants of each RIL. Each line style represents a RIL. C, Modeled LER for the same RILs.

Figure 7

Example of output of the bootstrap analysis for a QTL located on chromosome 10. Each vertical bar indicates the proportion of cases in which a QTL was detected at the considered position in a series of 1,000 random samplings. Positions were 5 cM apart. In the case considered here, a QTL was found in 94% of cases in an interval of 20 cM encompassing the QTL. The trace of LOD values in the composite interval mapping on the 100 RILs is also shown.