4.5 Article

Advanced-backcross QTL analysis in spring barley: IV. Localization of QTL x nitrogen interaction effects for yield-related traits

期刊

EUPHYTICA
卷 177, 期 2, 页码 223-239

出版社

SPRINGER
DOI: 10.1007/s10681-010-0252-6

关键词

AB-QTL analysis; Hordeum vulgare ssp spontaneum; Yield-related traits; Nitrogen x N interaction; 4-Factorial mixed model ANOVA

资金

  1. German Plant Genome Research Initiative (GABI), Federal Ministry of Education and Research (BMBF) [0312278A]

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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 x environment interaction effects and QTL x N treatment interaction effects in the spring barley BC2DH population S42. The yield-related traits studied were number of ears per m(2), 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 x environment interaction, alone or in combination, accounted for 24 of the newly uncovered QTLs, whereas QTL x 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 m(2) 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.

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