title: Conditional QTL mapping for plant height with respect to the length of the spike and internode in two mapping populations of wheat.
abstract: Plant height (PH) in wheat is a complex trait; its components include spike length (SL) and internode lengths. To precisely analyze the factors affecting PH, two F(8:9) recombinant inbred line (RIL) populations comprising 485 and 229 lines were generated. Crosses were performed between Weimai 8 and Jimai 20 (WJ) and between Weimai 8 and Yannong 19 (WY). Possible genetic relationships between PH and PH components (PHC) were evaluated at the quantitative trait locus (QTL) level. PH and PHC (including SL and internode lengths from the first to the fourth counted from the top, abbreviated as FIITL, SITL, TITL, and FOITL, respectively) were measured in four environments. Individual and the pooled values from four trials were used in the present analysis. A QTL for PH was mapped using data on PH and on PH conditioned by PHC using IciMapping V2.2. All 21 chromosomes in wheat were shown to harbor factors affecting PH in two populations, by both conditional and unconditional QTL mapping methods. At least 11 pairwise congruent QTL were identified in the two populations. In total, ten unconditional QTL and five conditional QTL that could be detected in the conditional analysis only have been verified in no less than three trials in WJ and WY. In addition, three QTL on the short arms of chromosomes 4B, 4D, and 7B were mapped to positions similar to those of the semi-dwarfing genes Rht-B1, Rht-D1 and Rht13, respectively. Conditional QTL mapping analysis in WJ and WY proved that, at the QTL level, SL contributed the least to PH, followed by FIITL; TITL had the strongest influence on PH, followed by SITL and FOITL. The results above indicated that the conditional QTL mapping method can be used to evaluate possible genetic relationships between PH and PHC, and it can efficiently and precisely reveal counteracting QTL, which will enhance the understanding of the genetic basis of PH in wheat. The combination of two related populations with a large/moderate population size made the results authentic and accurate.
authors.affiliation: State Key Laboratory of Crop Biology, Shandong Key Laboratory of Crop Biology, Taian Subcenter of National Wheat Improvement Center, College of Agronomy, Shandong Agricultural University, Taian, China. sdaucf@126.com
authors.forename: Fa
authors.initials: F
authors.lastname: Cui
authors.forename: Jun
authors.initials: J
authors.lastname: Li
authors.forename: Anming
authors.initials: A
authors.lastname: Ding
authors.forename: Chunhua
authors.initials: C
authors.lastname: Zhao
authors.forename: Lin
authors.initials: L
authors.lastname: Wang
authors.forename: Xiuqin
authors.initials: X
authors.lastname: Wang
authors.forename: Sishen
authors.initials: S
authors.lastname: Li
authors.forename: Yinguang
authors.initials: Y
authors.lastname: Bao
authors.forename: Xingfeng
authors.initials: X
authors.lastname: Li
authors.forename: Deshun
authors.initials: D
authors.lastname: Feng
authors.forename: Lingrang
authors.initials: L
authors.lastname: Kong
authors.forename: Honggang
authors.initials: H
authors.lastname: Wang
mesh_terms: D002874:Chromosome Mapping; D003433:Crosses, Genetic; D005819:Genetic Markers / Q000235:genetics; D005838:Genotype; D010641:Phenotype; D040641:Quantitative Trait Loci / Q000235:genetics*; D014908:Triticum / Q000033:anatomy & histology* / Q000235:genetics*
chemical_list: D005819:Genetic Markers