Unraveling the complex trait of crop yield with quantitative trait loci mapping in Brassica napus

Abstract

Yield is the most important and complex trait for the genetic improvement of crops. Although much research into the genetic basis of yield and yield-associated traits has been reported, in each such experiment the genetic architecture and determinants of yield have remained ambiguous. One of the most intractable problems is the interaction between genes and the environment. We identified 85 quantitative trait loci (QTL) for seed yield along with 785 QTL for eight yield-associated traits, from 10 natural environments and two related populations of rapeseed. A trait-by-trait meta-analysis revealed 401 consensus QTL, of which 82.5% were clustered and integrated into 111 pleiotropic unique QTL by meta-analysis, 47 of which were relevant for seed yield. The complexity of the genetic architecture of yield was demonstrated, illustrating the pleiotropy, synthesis, variability, and plasticity of yield QTL. The idea of estimating indicator QTL for yield QTL and identifying potential candidate genes for yield provides an advance in methodology for complex traits.

Figure 1.—

Demonstration of the process and result of two rounds of QTL meta-analysis for QTL mapped on 30- to 60-cM segments of A2 linkage group. (A) Thirteen identified QTL for seed yield detected from five experiments were integrated into four consensus QTL (which are shown with gray bars on the left) with shorter confidence intervals after the first round of meta-analysis. (B) The four consensus QTL for seed yield along with other consensus QTL for the four traits, flowering time, maturity time, plant height, and seed number discriminated with different color, were integrated into four unique QTL with further reduced confidence intervals after the second round of meta-analysis.

Figure 2.—

Expression response of 401 consensus QTL in natural environments. (A, top) Number of consensus QTL appeared in 1 to 10 (all) microenvironments. (A, bottom) Number of consensus QTL appeared in winter, semi-winter, or both macroenvironments. Most consensus QTL appeared in only one or two microenvironments, while a few were detected repeatedly in more than five. (B) Detailed view of QTL for seed yield detected in a 34.6-cM region of the C7 linkage group. All three consensus QTL were strongly expressed in the E7 microenvironment, two of which were weakly expressed in the S4 and S7 microenvironments, respectively.

Figure 3.—

Distribution of 401 consensus QTL for seed yield and eight yield-associated traits on 19 linkage groups. The abscissa represents the 19 linkage groups that were divided into 10-cM bins and the ordinate represents the number of QTL. The long dotted line in the middle shows the expected QTL number in each bin at the hypothesis of even distribution. The black triangles on the bottom axis indicate the first bin of each linkage group.

Figure 4.—

Dissection of the overlapping QTL cluster for seed yield and yield-associated traits in a 7.2-cM region on linkage group A2. Identified QTL are indicated as LOD curves. Confidence intervals (CI) for each identified QTL are shown as horizontal lines under the curves with the same color and style as the QTL. The CIs for consensus QTL, estimated after the first round of meta-analysis, are shown in the same way in which the CI for indicator QTL is shown as a line with arrowheads. After the second round of meta-analysis, the CI for the unique QTL of seed yield was 1.2 cM, having been reduced from an average of 4.3 cM for identified QTL and 2 cM for consensus QTL. Pseudochromosome fragments of Arabidopsis (fragment B in chromosome 1 and fragment E in chromosome 5), aligned by in silico comparative mapping, are shown in the lower part of the figure. The candidate genes, VIN3 and ZTL, underlying the unique QTL, estimated from the indicator QTL for flowering time, are shown at the bottom.