Comparative mapping of quantitative trait loci involved in heterosis for seedling and yield traits in oilseed rape (Brassica napus L.)

Abstract

Little is known about the genetic control of heterosis in the complex polyploid crop species oilseed rape (Brassica napus L.). In this study, two large doubled-haploid (DH) mapping populations and two corresponding sets of backcrossed test hybrids (THs) were analysed in controlled greenhouse experiments and extensive field trials for seedling biomass and yield performance traits, respectively. Genetic maps from the two populations, aligned with the help of common simple sequence repeat markers, were used to localise and compare quantitative trait loci (QTL) related to the expression of heterosis for seedling developmental traits, plant height at flowering, thousand seed mass, seeds per silique, siliques per unit area and seed yield. QTL were mapped using data from the respective DH populations, their corresponding TH populations and from mid-parent heterosis (MPH) data, allowing additive and dominance effects along with digenic epistatic interactions to be estimated. A number of genome regions containing numerous heterosis-related QTL involved in different traits and at different developmental stages were identified at corresponding map positions in the two populations. The co-localisation of per se QTL from the DH population datasets with heterosis-related QTL from the MPH data could indicate regulatory loci that may also contribute to fixed heterosis in the highly duplicated B. napus genome. Given the key role of epistatic interactions in the expression of heterosis in oilseed rape, these QTL hotspots might harbour genes involved in regulation of heterosis (including fixed heterosis) for different traits throughout the plant life cycle, including a significant overall influence on heterosis for seed yield.

Fig. 1

Comparative map positions of main effect QTL for seedling and seed yield-related traits in DH and backcrossed TH populations derived from the crosses ‘Express 617’ × ‘V8’ (ExV8) and ‘Express 617’ × ‘R53’ (ExR53) along with MPH data from ExV8 and ExR53, respectively. QTL for silique traits were calculated previously by Radoev et al. (2008). To facilitate comparisons with previous publications the chromosome nomenclature follows the N01-N19 nomenclature for B. napus, with the A and C genome nomenclature suggested by the Multinational Brassica Genome Project (see www.brassica.info) given in brackets. White (DH data), grey (TH data) and black (MPH data) bars show the 1-logarithm of odds (LOD) intervals for each QTL. The prefix to each QTL name indicates the dataset from which the QTL was calculated, whereas the traits are abbreviated as follows: y yield, TSM thousand seed mass, ph plant height at flowering, slpa siliques per unit area, spsl seeds per silique, 06 2006 field trials, 07 2007 field trials, lfw leaf fresh weight, sfw shoot fresh weight, hcl hypocotyl length, la leaf area

Fig. 1

Comparative map positions of main effect QTL for seedling and seed yield-related traits in DH and backcrossed TH populations derived from the crosses ‘Express 617’ × ‘V8’ (ExV8) and ‘Express 617’ × ‘R53’ (ExR53) along with MPH data from ExV8 and ExR53, respectively. QTL for silique traits were calculated previously by Radoev et al. (2008). To facilitate comparisons with previous publications the chromosome nomenclature follows the N01-N19 nomenclature for B. napus, with the A and C genome nomenclature suggested by the Multinational Brassica Genome Project (see www.brassica.info) given in brackets. White (DH data), grey (TH data) and black (MPH data) bars show the 1-logarithm of odds (LOD) intervals for each QTL. The prefix to each QTL name indicates the dataset from which the QTL was calculated, whereas the traits are abbreviated as follows: y yield, TSM thousand seed mass, ph plant height at flowering, slpa siliques per unit area, spsl seeds per silique, 06 2006 field trials, 07 2007 field trials, lfw leaf fresh weight, sfw shoot fresh weight, hcl hypocotyl length, la leaf area