Detection of QTLs with additive effects and additive-by-environment interaction effects on panicle number in rice (Oryza sativa L.) with single-segment substitution lines
A novel population consisting of 35 single-segment substitution lines (SSSLs) originating from crosses between the recipient parent, Hua-jing-xian 74 (HJX74), and 17 donor parents was evaluated in six cropping season environments to reveal the genetic basis of genetic main effect (G) and genotype-by...
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Veröffentlicht in: | Theoretical and applied genetics 2008-05, Vol.116 (7), p.923-931 |
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Zusammenfassung: | A novel population consisting of 35 single-segment substitution lines (SSSLs) originating from crosses between the recipient parent, Hua-jing-xian 74 (HJX74), and 17 donor parents was evaluated in six cropping season environments to reveal the genetic basis of genetic main effect (G) and genotype-by-environment interaction effect (GE) for panicle number (PN) in rice. Subsets of lines were grown in up to six environments. An indirect analysis method was applied, in which the total genetic effect was first partitioned into G and GE by using the mixed linear-model approach, and then QTL (quantitative trait locus) analyses on these effects were conducted separately. At least 18 QTLs for PN in rice were detected and identified on 9 of 12 rice chromosomes. A single QTL effect (a + ae) ranging from -1.5 to 1.2 was divided into two components, additive effect (a) and additive x environment interaction effect (ae). A total number of 9 and 16 QTLs were identified with a ranging from -0.4 to 0.6 and ae ranging from -1.0 to 0.6, respectively, the former being stable but the latter unstable across environments. Three types of QTLs were suggested according to their effects expressed. Two QTLs (Pn-1b and Pn-6d) expressed stably across environments due to the association with only a, nine QTLs (Pn-1a, Pn-3c, Pn-3d, Pn-4, Pn-6a, Pn-6b, Pn-8, Pn-9 and Pn-12) with only ae were unstable, and the remaining seven of QTLs were identified with both a and ae, which also were unstable across environments. This is the first report on the detection of QE (QTL-by-environment interaction effect) of QTLs with SSSLs. Our results illustrate the efficiency of characterizing QTLs and analyzing action of QTLs through SSSLs, and further demonstrate that QE is an important property of many QTLs. Information provided in this paper could be used in the application of marker-assisted selection to manipulate PN in rice. |
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ISSN: | 0040-5752 1432-2242 |
DOI: | 10.1007/s00122-008-0724-4 |