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首页> 外文期刊>Euphytica >Advanced-backcross QTL analysis in spring barley: IV. Localization of QTL × nitrogen interaction effects for yield-related traits
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Advanced-backcross QTL analysis in spring barley: IV. Localization of QTL × nitrogen interaction effects for yield-related traits

机译:春季大麦的先进回交QTL分析:IV。产量相关性状的QTL×氮互作效应定位

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The advanced backcross quantitative trait locus (AB-QTL) analysis has proven its usefulness to identify and localize favourable alleles from exotic germplasm and to transfer those alleles into elite varieties. In a balanced design with up to six environments and two nitrogen fertilization (N treatment) levels, a 4-factorial mixed model analysis of variance (ANOVA) was used to identify QTL main effects, QTL × environment interaction effects and QTL × N treatment interaction effects in the spring barley BC2DH population S42. The yield-related traits studied were number of ears per m2, days until heading, plant height, thousand grain weight (TGW) and grain yield. In total, 82 QTLs were detected for all traits. This finding was compared to a previous QTL study of the same population S42, where the current field data was reduced to one half through restriction of the analysis to the standard N treatment level (von Korff et al., Theor Appl Genet 112: 1221–1231, 2006). These authors located 54 QTLs for the same traits by applying a 3-factorial mixed model similar to the current model but excluding the factor N treatment. We found that QTL × environment interaction, alone or in combination, accounted for 24 of the newly uncovered QTLs, whereas QTL × N treatment interaction was of lesser importance with six new cases in total. A valuable QTL interacting with N treatment has been identified on chromosome 7H where lines carrying the wild barley allele were superior in number of ears per m2 in either N treatment. We conclude that in population S42 the extension of the phenotype data set and the inclusion of N treatment into the mixed model increased the power of QTL detection by providing an additional replication rather than by revealing specific N treatment QTLs.
机译:先进的回交定量性状基因座(AB-QTL)分析已证明其可用于鉴定和定位来自外来种质的有利等位基因并将这些等位基因转移到优良品种中。在具有多达六个环境和两个氮肥(N处理)水平的平衡设计中,使用4因子混合方差分析(ANOVA)来识别QTL主效应,QTL×环境相互作用效应和QTL×N处理相互作用对大麦BC 2 DH群体S42的影响研究的产量相关性状为每m 2 的穗数,抽穗前的天数,株高,千粒重(TGW)和籽粒产量。总共检测到所有性状的82个QTL。将该结果与先前对相同种群S42进行的QTL研究进行了比较,在该研究中,通过将分析限制在标准N处理水平下,当前现场数据减少了一半(von Korff等人,Theor Appl Genet 112:1221– 1231,2006)。这些作者通过应用与当前模型相似的三因子混合模型,找到了54个具有相同性状的QTL,但不包括因子N处理。我们发现,QTL×环境相互作用(单独或组合)占新发现的QTL的24个,而QTL×N治疗相互作用在六个新病例中的重要性较低。已经在7H染色体上鉴定了与N处理相互作用的有价值的QTL,其中在任一N处理中,携带野生大麦等位基因的品系每m 2 的穗数均更高。我们得出结论,在种群S42中,通过提供额外的复制而不是通过揭示特定的N处理QTL,扩展了表型数据集并将N处理纳入混合模型提高了QTL检测的能力。

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