- Kernel hardness (KHA) is a major factor determining break flour yield (BFY) and end-use quality of common wheat (Triticum aestivum L.). Within the soft wheat class, genotypes with consistently softer grains than common soft wheat are considered to be 'extra-soft'. In addition, 'extra-soft' wheats have greater BFY than common soft wheat lines. In order to better understand this interrelationship, a set of 164 F₆-recombinant inbred lines (RILs) developed from a soft × 'extra-soft' wheat cross was evaluated for KHA, BFY, and other related traits in six field environments. The estimates of broad-sense heritability for KHA and BFY ranged from 0.84 to 0.96 and 0.56 to 0.76, respectively. Significant environmental effects and genotype by environment interactions were detected for all traits evaluated.
A comprehensive genetic linkage map was created with 650 molecular markers based on this mapping population. Three chromosome translocations, 1BL.1RS, 2NˇS-2AS.2AL and 5B:7B, were identified during linkage analysis. A total of 47 quantitative trait loci (QTL) were identified for nine traits including KHA, BFY, bran yield (BRN), unground middling yield (MID), plant height (PHT), days to heading (HDD), thousand-kernel weight (TKW), grain protein content (GPC), and test weight (TWT). The number of QTL per trait ranged from three for MID to nine for GPC. The phenotypic variance explained by individual QTL ranged from 5.8 to 47.6%. Among five QTL identified for KHA, the two most important QTL were located on chromosomes 4DS (Xbarc1118-Rht-D1 interval) and 4BS (Xwmc617-Rht-B1 interval), indicating that the 'extra-soft' characteristic was not controlled by the 5DS Hardness (Ha) locus which encodes the two puroindoline genes pinA and pinB. The co-location of QTL for KHA, BFY, BRN, and MID on 4DS suggested that genetic factors affecting KHA may have a pleiotropic effect on BFY. Two co-located QTL for TWT, TKW and PHT were detected on 4DS and 4BS, and a QTL for HDD was detected on 4DS, indicating that these QTL may represent the consequence of the semi-dwarfing green-revolution genes Rht-D1 and Rht-B1 located on 4DS and 4BS, respectively. Additional analysis suggested that the QTL for KHA on 4DS and 4BS are the effects of genes linked to Rht-D1 and Rht-B1, rather than pleiotropic effects of these genes. Some coincident QTL for the traits that were evaluated represent the interrelationships of phenotypic traits, where both KHA and BFY were associated with HDD and TWT based on path coefficient analysis.
Association mapping can be an effective means for identifying, validating, and fine mapping genes and QTL in crop plants. To test this approach, a set of 94 diverse elite wheat lines was phenotyped for five important traits and genotyped with 487 molecular markers. In this study, the marker-trait association analysis showed that the gene pinB (Ha locus) was significantly associated with KHA as it is known to define the difference between soft and hard wheat classes. Additionally, the significant associations of marker XwPt-7187 with KHA, XwPt-1250 and XwPt-4628 with TWT, and Xgwm512 with PHT mark the first report of such associations in these genomic regions.
This study, aiming at the genetic dissection of wheat kernel extra-softness and related traits, enhanced our understanding of both genetic control of and environmental effects on these important traits. Path coefficient analysis showed the promise of an alternative phenotypic selection approach that is more cost effective than direct measurement of kernel quality. Three chromosome translocations were discovered and their approximate chromosome break points were located. Numerous QTL were identified for these important traits. The major QTL can serve as a start point for fine mapping that eventually lead to the cloning of the QTL through map-based or candidate gene approach. Association mapping, as an alternate approach and complementary tool to QTL mapping, was demonstrated feasible in wheat for identification of marker-trait associations and cross validation of QTL or genes identified from bi-parent mapping populations.