QTL Analysis For Grain Number And Related Traits In Wheat

Wheat is one of the most important crops in the world. Its yield improving is an important way to satisfy people's demand. Wheat grain yield is determined by three yield components, spikes per plant, grain number per spike and grain weight. Increasing the grain number per spike (GNS) is one of the approaches that have contributed to wheat yield improvement. Therefore, the study on discovering more grain number QTL from the wild wheat resources was important for future wheat breeding and related researches. The Chinese winter wheat cultivar 'Laizhou953' and a synthetic hexaploid wheat, Am3 (T. carthlicum accession PS5×Ae. tauschii accession Ae38), were used as the recurrent and donor parent in this study, respectively. After four generation of backcrossing and three generation of selfing, BC₅F₃ population was constructed. Introgression lines, secondary mapping populations from the introgression lines and 96 wheat varieties were used as materials for grain number per spike (GNS), spike length (SL) and spikelets (SPI) QTL detection. The results obtained were listed as below.1. 80 BC5F3 introgression lines were used for mapping of spike characteristics, which were generated from repeated backcrossing between Am3 and Laizhou953. One-way ANOVA analysis was used to detect QTLs for three spike characteristics. The presence of a QTL was judged to be likely when the significant effect was observed for a single marker/trait combination with P≤0.01. In total, 21,11 and 17 putative QTLs were detected for GNS, SL and SPI. 37 spike characteristics QTLs were detected in more than one season and one location. 7 QTLs for GNS, SL and SPI were all mapped in the same interval.2. A BC5F2 population consisting of 75 plants was constructed by selfing one of the BC5F1 plant, which had high grain number and generated from repeated backcrossing between Am3 and Laizhou953. Single marker analysis and composite interval mapping were used to detect QTL for three spike characteristics. 18, 8 and 19 loci were detected for GNS, SL and SPI using single marker analysis. Using composite interval mapping, 2, 2 and 4 putative QTL were detected for GNS, SL and SPI, and can explain 1-15%, 1-22% and 1-9% phenotypic variation. One GNS QTL and one SL QTL were detected in two seasons. Two GNS QTL and one SPI QTL were detected in two environments (2007). The QTL in 1A for GNS and SPI were mapped in the same interval. The QTL in 4A for SL and SPI were mapped in the same interval. The QTL for GNS, SL and SPI were mapped in the same interval in 7B.3. Xgwm113 was detected decrease SL and GNS on chromosome 4B by using introgression lines carrying Am3 segments in the background of Laizhou953. Using mark assistant selection an introgression line (IL1) was selected with segregation of marker Xgwm113-4B. A BC₅F_2:3 population consisting of 85 plants was constructed by the selfing of ILL 69 SSR markers located on chromosome 4B were selected to scan IL1 and 10 markers detected the Am3 fragment transferred to L953. Using composite interval mapping, there was GNS QTL Qgn.caas-4B around markers Xgwm113 on chromosome 4B were detected. The segregation values of grain number fitted Mendelian inheritance ratios of single gene. The Qgn.caas-4B can explain 35.61% of the observed phenotypic variation. To fine mapping Qgn.caas-4B, a large population containing 497 plants was constructed with the selfing of ILL Using substitution mapping, spike characteristics QTL was finally narrowed down to a 1.2cM region between Xgwm113-Xgwm857. 30 wild wheat varieties and 56 wheat cultivars were selected to examine the genetic diversity with marker Xgwm113 and Xgwm857. Evaluation of two markers polymorphisms indicated that cultivated wheat reduced 49.0% and 33.4% diversity than in wild wheat. The SSR loci Xgwm113 and Xgwm857 had high frequencies allele the same as Laizhou953 which was 73.2% and 58.9% in cultivars wheat. The test statistical lnRH were used to prove the region of the genome that were given significantly results for two populations and thus are likely to contain genes under selection. Two SSR were proved to be association with grain number in these varieties. All the results revealed that the region from Xgwm113 to Xgwm857 was might play an important role in the regulation of spike characteristics during the domestication of wheat grain number.4. 132 SSR markers were used to investigate the genetic diversity of 96 wheat cultivars which selected from 14 countries and locations. Based on SSR data, with clustering analysis, 96 materials were clustered 4 SGs. 90 wheat cultivars were selected from 2 SGs for association mapping. Totally 1181 alleles were revealed among 90 cultivars in 132 SSR and the average gene diversity was 0.65. 132 SSR were selected to prove if it was associated with three spike traits, which were collected from 3 environments (Beijingchangping well-watered condition, Luoyang drought stress condition, Luoyang well-watered condition). In which, 5 SSR loci with GNS, 31 were associated with SL, 12 with SPI. Xbarc158 (1A),Xbarc324 (3A) and Xbarc217 (4D) which associated with SL were detected in 2 environments (Beijingchangping well-watered condition and Luoyang well-watered condition); Xcfa2219 (1A) and Xgwm4 (4A) which associated with SPI were detected in 2 environments (Beijingchangping well-watered condition and Luoyang drought stress condition). Xbarc294 (3A),Xksu62 (4B) and Xbarc89 (5B) were associated with GNS and SL.Xcfa2219 (1A),Xgwm558 (2A),Xbarc334 (4D) and Xbarc177 (5D) were associated with SL and SPI.