Yield of rapeseed is determined by three components: silique number, seed number per silique and thousand seed weight. Seed number per silique and thousand seed weight are influenced by silique length, seed density, silique breadth, silique thickness and silique volume. Some QTLs for silique traits have been reported in B. napus, however, no studies have focused on the six agronomic traits (seed number per silique, silique length, silique breadth, silique thickness, seed density and silique volume) simultaneously, and the genetic determinism of such complex traits have not been fully elucidated. In this study, the six silique traits were evaluated using 348 lines of a doubled haploid population, the KN population. The results showed that 2, 4, 1, 1 and 2 QTLs explaining > 10 % of phenotypic variation were obtained for silique length, silique breadth, silique thickness, seed number per silique and silique volume, respectively. Notably, three major effect QTLs (cqSB-C6-1, cqSB-C6-2 and cqSV-C6-3) were identified in at least three environments, and 17 unique QTLs controlling at least two traits were obtained. A high-density consensus map containing 1225 markers was constructed for QTL comparison by combining the KN map with other five published maps. The comparative results revealed that 14, 13 and 11 QTLs for silique breadth, silique thickness and silique volume might be the potential new QTLs because few QTLs for these traits were reported in B. napus. In addition, potential new QTLs for silique length (11), seed number per silique (6) and seed density (5) were also identified. Twenty-five candidate genes underlying 27 QTLs for silique related traits were obtained. This study constructed QTL analysis in B. napus, and obtained 60 consensus QTLs for six silique related traits. The potential new QTLs will enhance our understanding of the genetic control of silique traits, and the stable QTLs provided the targets for improving seed yield in future. These findings provided comprehensive insights into the genetic network affecting silique traits at QTL level in B. napus.

Rapeseed is the third largest oil seed crop in the world. The seeds of this plant store lipids in oil bodies, and oleosin is the most important structural protein in oil bodies. However, the function of oleosin in oil crops has received little attention. In the present study, 48 oleosin sequences from the Brassica napus genome were identified and divided into four lineages (T, U, SH, SL). Synteny analysis revealed that most of the oleosin genes were conserved, and all of these genes experienced purifying selection during evolution. Three and four important oleosin genes from Arabidopsis and B. napus, respectively, were cloned and analyzed for function in Arabidopsis. Overexpression of these oleosin genes in Arabidopsis increased the seed oil content slightly, except for BnaOLE3. Further analysis revealed that the average oil body size of the transgenic seeds was slightly larger than that of the wild type (WT), except for BnaOLE1. The fatty acid profiles showed that the linoleic acid content (13.3% at most) increased and the peanut acid content (11% at most) decreased in the transgenic lines. In addition, the seed size and thousand-seed weight (TSW) also increased in the transgenic lines, which could lead to increased total lipid production. We identified oleosin genes in the B. napus genome, and overexpression of oleosin in Arabidopsis seeds increased the seed weight and linoleic acid content (13.3% at most).

Rapeseed (Brassica napus, B. napus) is an important oil seed crop in the world. Previous studies showed that seed germination vigor might be correlated with seed oil content in B. napus, but the regulation mechanism for seed germination has not yet been explained clearly. Dissecting the regulation mechanism of seed germination and germination vigor is necessary. Here, proteomic and genomic approaches were used to analyze the germination process in B. napus seeds with different oil content. The identification of 165 differentially expressed proteins (DEPs) in the germinating seeds of B. napus with high and low oil content was accomplished by two-dimensional fluorescence difference in gel electrophoresis (2D-DIGE). The comparative proteomic results revealed that seeds with high oil content had higher metabolic activity, especially for sulfur amino acid metabolism. Thirty-one unique genes were shown to be significantly changed during germination between the seeds with high and low oil content, and thirteen of these genes were located within the confidence interval of germination-related quantitative trait locus (QTLs), which might play an important role in regulating seed germination vigor. The present results are of importance for the understanding of the regulation mechanism for seed germination vigor in B. napus.

Deciphering the genetic architecture of a species is a good way to understand its evolutionary history, but also to tailor its profile for breeding elite cultivars with desirable traits. Aligning QTLs from diverse population in one map and utilizing it for comparison, but also as a basis for multiple analyses assure a stronger evidence to understand the genetic system related to a given phenotype. In this study, 439 genes involved in fatty acid (FA) and triacylglycerol (TAG) biosyntheses were identified in Brassica napus. B. napus genome showed mixed gene loss and insertion compared to B. rapa and B. oleracea, and C genome had more inserted genes. Identified QTLs for oil (OC-QTLs) and fatty acids (FA-QTLs) from nine reported populations were projected on the physical map of the reference genome “Darmor-bzh” to generate a map. Thus, 335 FA-QTLs and OC-QTLs could be highlighted and 82 QTLs were overlapping. Chromosome C3 contained 22 overlapping QTLs with all trait studied except for C18:3. In total, 218 candidate genes which were potentially involved in FA and TAG were identified in 162 QTLs confidence intervals and some of them might affect many traits. Also, 76 among these candidate genes were found inside 57 overlapping QTLs, and candidate genes for oil content were in majority (61/76 genes). Then, sixteen genes were found in overlapping QTLs involving three populations, and the remaining 60 genes were found in overlapping QTLs of two populations. Interaction network and pathway analysis of these candidate genes indicated ten genes that might have strong influence over the other genes that control fatty acids and oil formation. The present results provided new information for genetic basis of FA and TAG formation in B. napus. A map including QTLs from numerous populations was built, which could serve as reference to study the genome profile of B. napus, and new potential genes emerged which might affect seed oil. New useful tracks were showed for the selection of population or/and selection of interesting genes for breeding improvement purpose.

Background: Cytoplasmic male sterility (CMS) is very important in hybrid breeding. The restorer-of-fertility (Rf) nuclear genes rescue the sterile phenotype. Most of the Rf genes encode pentatricopeptide repeat (PPR) proteins. Results: We investigated the restorer-of-fertility-like (RFL) gene family in Brassica napus. A total of 53 BnRFL genes were identified. While most of the BnRFL genes were distributed on 10 of the 19 chromosomes, gene clusters were identified on chromosomes A9 and C8. The number of PPR motifs in the BnRFL proteins varied from 2 to 19, and the majority of BnRFL proteins harbored more than 10 PPR motifs. An interaction network analysis was performed to predict the interacting partners of RFL proteins. Tissue-specific expression and RNA-seq analyses between the restorer line KC01 and the sterile line Shaan2A indicated that BnRFL1, BnRFL5, BnRFL6, BnRFL8, BnRFL11, BnRFL13 and BnRFL42 located in gene clusters on chromosomes A9 and C8 were highly expressed in KC01. Conclusions: In the present study, identification and gene expression analysis of RFL gene family in the CMS system were conducted, and seven BnRFL genes were identified as candidates for the restorer genes in Shaan2A CMS. Taken together, this method might provide new insight into the study of Rf genes in other CMS systems.