Vegetable height is an important botanical feature closely related to yield.

Vegetable height is an important botanical feature closely related to yield. eight environments (year??site??water regime combinations). Strong correlations between final herb height and numbers of large-effect alleles indicated that this alleles contributed additively to herb height. The additive effects showed that pyramiding elite alleles for target traits has significant potential for wheat breeding. Electronic supplementary material The online version of this article (doi:10.1007/s11032-013-9873-5) contains supplementary material, which is available to authorized users. genes with major effects have been described (McIntosh et al. 2008; Peng et al. 2011), Il17a but only (formerly (are widely used in wheat breeding programs; varieties with one or more of these genes accounted for >70?% of current commercial wheat cultivars worldwide (Ellis et al. 2007; Hedden 2003). The wide use of dwarfing sources based on a limited number of key parents leads to relatively narrow genetic diversity, which reduces adaptation to various environmental conditions (Evenson and Gollin 2003; Reif et al. 2005; Roussel et al. 2004). Therefore, it is essential to determine the genetic basis of herb height and exploit elite alleles, i.e. the alleles with favorable effects for breeding high-yielding varieties. The rapid development of molecular markers has provided a basis for detailed genetic analyses of complex traits, such as seed height, that involves several genes, and particularly for understanding interactions with environmental factors. Quantitative trait loci (QTL) associated with herb height were Vinorelbine (Navelbine) detected on almost all 21 chromosomes by linkage analysis and association mapping (Cadalen et al. 1998; Cui et al. 2011; Huang et al. 2006; Keller et al. 1999; Klahr et al. 2007; McCartney et al. 2005; Wang et al. 2010; Wu et al. 2010; Zhang et al. 2011). However, most of these studies measured only the final herb height, Vinorelbine (Navelbine) and did not annotate the quantitative variation on a time scale. Zhu proposed statistical methods for analyzing conditional genetic effects (Zhu 1995). By analyzing developmental behavior within the period (was duplicated five occasions. The admixture model of STRUCTURE allowed for a population mixture and correlated allele frequencies. The most appropriate value was evaluated by lnvalue, the Q-matrix of five repeats was integrated by using the CLUMPP software (Jakobsson and Rosenberg 2007). Association mapping For marker-trait association, a structured association approach was implemented by a general linear model (GLM) in TASSEL 2.1 (Bradbury et al. 2007). In order to correct for spurious associations, the Q-matrix was used in the model. The threshold (value) for significant association between markers and characteristics was 0.001. The phenotypic variance explained (PVE) for each significantly associated locus was evaluated by (from 2 to 9) is usually visualized in Supplementary Fig. S1a and the inflection point appeared at value occurred at and and were detected four occasions, i.e. was detected in PH3, was significantly associated with PH2, PH3 and S4, and the genetic distance between Vinorelbine (Navelbine) them was only 0.7?cM in Ta-SSR-2004 (Somers et al. 2004). Table?1 Phenotypic variation explained by SSR loci significantly (detected in the first period (PH1) was responsible for 14.06?% of the variation in herb height. Two loci on chromosomes 1B and 4B were significantly associated with PH2, with PVEs of 23.55 and 15.55?%, respectively. Seven loci identified in PH3 were distributed on chromosomes 1B, 2D, 4B, 4D, 5A and 7B. Of them, showed the biggest effect, detailing 28.34?% from the phenotypic variant. On the flowering stage, and had been.