Schubert, Anne Christa: Quantitative trait loci analysis in spring wheat comparing two advanced backcross populations derived from an exotic wheat accession. - Bonn, 2010. - Dissertation, Rheinische Friedrich-Wilhelms-Universität Bonn.
Online-Ausgabe in bonndoc: https://nbn-resolving.org/urn:nbn:de:hbz:5N-20935
@phdthesis{handle:20.500.11811/4200,
urn: https://nbn-resolving.org/urn:nbn:de:hbz:5N-20935,
author = {{Anne Christa Schubert}},
title = {Quantitative trait loci analysis in spring wheat comparing two advanced backcross populations derived from an exotic wheat accession},
school = {Rheinische Friedrich-Wilhelms-Universität Bonn},
year = 2010,
month = jul,

note = {The objective of the present study was to identify and localise favourable, exotic QTL alleles for the improvement of 16 quantitative agronomic traits, quality parameters and disease resistances in elite wheat cultivars. Therefore, two advanced backcross populations, T84 and D84, in generation BC2F4 were derived from crosses of two German spring wheat cultivars (Triso and Devon) and one synthetic hexaploid wheat accession (Syn-84). The revealing populations, counting 223 (T84) and 176 (D84) BC2F4 lines, were phenotyped in field plots at four different locations in Germany under two different nitrogen supplies (high and low) in seasons 2004 and 2005. In addition, the populations were genotyped with 94 (T84) and 106 (D84) SSR markers, respectively. Phenotype and genotype data were merged to different QTL mapping methods with a significance threshold of P = 0.01 including marker as fixed effect, the environment, line nested in marker genotype, marker×environment and marker×nitrogen interaction effects as random effects. Multi-environmental QTL detections were considered in three-way (high N-level) and four-way (high and low N-levels) models determined through ANOVA and REML methods in SAS programme (SAS Institute 2003). In high N-level, 105 (T84) and 78 (D84) QTLs were detected as marker main effects and marker×environment interaction effects using ANOVA method. Through REML method 10 (T84) and 4 (D84) QTLs as marker main effects were identified. In high and low N-levels, 11 (T84) and 13 (D84) N-responsive QTLs and each 48 (T84 and D84) QTLs as marker main effects were ascertained using ANOVA method. Five (T84) and 4 (D84) QTLs as marker main effects were detected using REML method.
A comparison between QTL mapping methods revealed that REML methods validated QTLs with highest F-value computed by ANOVA methods. Moreover, no significant interaction effects were permitted using REML methods. It might be postulated that non validated QTLs, which have been detected only by the ANOVA analysis, were either false positive or small QTLs that were not robust enough through the stringent REML methods. The stringent REML methods computed with three-way and four-way models revealed six (T84) and one (D84) QTLs associated with exotic alleles improving traits of interest in regard to breeding efforts.
Exotic alleles reduced, for example, sensitivity to powdery mildew by 34.7% at QTL QPm.T84-7D, on chromosome arm 7DL in population T84. So far, this locus associated with resistance to powdery mildew was not published in QTL studies. QPm.T84-7D may be associated with a new resistance to powdery mildew conducted by Aegilops tauschii. The second population D84 validated the new QTL QPm.T84-7D where identical exotic alleles reduced sensitivity to powdery mildew by 27.5% (P = 0.037). In population T84, BC2F4 lines were selected, which carried favourable exotic QTL alleles in least one introgression. For days until heading, plant height and thousand grain weight eight, one and four BC2F4 lines were selected, which significantly improved the trait performance compared to the recurrent parent. The results of the current study prove that exotic alleles derived from synthetic hexaploid wheat can improve quantitative traits, as agronomic traits and disease resistances, in elite wheat varieties across multi-environments and two different genetic backgrounds.},

url = {https://hdl.handle.net/20.500.11811/4200}
}

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