Most agronomical traits exhibit quantitative variation, which is controlled by multiple genes and are environmentally dependent. To study the genetic variation of flowering time in Brassica napus, a DH population and its derived reconstructed F 2 population were planted in 11 field environments. The flowering time varied greatly with environments; 60% of the phenotypic variation was attributed to genetic effects. Five to 18 QTL at a statistically significant level (SL-QTL) were detected in each environment and, on average, two new SL-QTL were discovered with each added environment. Another type of QTL, microreal QTL (MR-QTL), was detected repeatedly from at least 2 of the 11 environments; resulting in a total of 36 SL-QTL and 6 MR-QTL. Sixty-three interacting pairs of loci were found; 50% of them were involved in QTL. Hundreds of floral transition genes in Arabidopsis were aligned with the linkage map of B. napus by in silico mapping; 28% of them aligned with QTL regions and 9% were consistent with interacting loci. One locus, BnFLC10, in N10 and a QTL cluster in N16 were specific to spring-and winter-cropped environments respectively. The number of QTL, interacting loci, and aligned functional genes revealed a complex genetic network controlling flowering time in B. napus.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.