Traits related to flowering time are the most promising agronomic traits that directly impact the seed yield and oil quality of rapeseed (Brassica napus L.). Developing early flowering and maturity rapeseed varieties is an important breeding objective in B. napus. Many studies have reported on days to flowering, but few have reported on budding, bolting, and the interval between bolting and DTF. Therefore, elucidating the genetic architecture of QTLs and genes regulating flowering time, we presented an integrated investigation on SNP and haplotype-based genome-wide association study of 373 diverse B. napus germplasm, which were genotyped by the 60K SNP array and were phenotyped in the four environments. The results showed that a total of 15 and 37 QTLs were detected from SNP and haplotype-based GWAS, respectively. Among them, seven QTL clusters were identified by haplotype-based GWAS. Moreover, three and eight environmentally stable QTLs were detected by SNP-GWAS and haplotype-based GWAS, respectively. By integrating the above two approaches and by co-localizing the four traits, ten (10) genomic regions were under selection on chromosomes A03, A07, A08, A10, C06, C07, and C08. Interestingly, the genomic regions FT.A07.1, FT.A08, FT.C06, and FT.C07 were identified as novel. In these ten regions, a total of 197 genes controlling FT were detected, of which 14 highly expressed DEGs were orthologous to 13 Arabidopsis thaliana genes after integration with transcriptome results. In a nutshell, the above results uncovered the genetic architecture of important agronomic traits related to flowering time and provided a basis for multiple molecular marker-trait associations in B. napus.

Cultivated peanut (Arachis hypogaea L.) is an important economic and oilseed crop worldwide, providing high-quality edible oil and high protein content. Seed size/weight and oil content are two important determinants of yield and quality in peanut breeding. To identify key regulators controlling these two traits, two peanut cultivars with contrasting phenotypes were compared to each other, one having a larger seed size and higher oil content (Zhonghua16, ZH16 for short), while the second cultivar had smaller-sized seeds and lower oil content (Zhonghua6, ZH6). Whole transcriptome analyses were performed on these two cultivars at four stages of seed development. The results showed that ~40% of the expressed genes were stage-specific in each cultivar during seed development, especially at the early stage of development. In addition, we identified a total of 5356 differentially expressed genes (DEGs) between ZH16 and ZH6 across four development stages. Weighted gene co-expression network analysis (WGCNA) based on DEGs revealed multiple hub genes with potential roles in seed size/weight and/or oil content. These hub genes were mainly involved in transcription factors (TFs), phytohormones, the ubiquitin–proteasome pathway, and fatty acid synthesis. Overall, the candidate genes and co-expression networks detected in this study could be a valuable resource for genetic breeding to improve seed yield and quality traits in peanut.

Sclerotinia stem rot (SSR) caused by Sclerotinia sclerotiorum (S. sclerotiorum) is the main disease threat of oilseed rape (Brassica napus), resulting in huge economic losses every year. SSR resistance manifests as quantitative disease resistance (QDR), and no gene with complete SSR resistance has been cloned or reported so far. Transcriptome analysis has revealed a large number of defense-related genes and response processes. However, the similarities and differences in the defense responses of different tissues are rarely reported. In this study, we analyzed the similarities and differences of different tissues in response to S. sclerotiorum at 24 h post inoculation (hpi) by using the published transcriptome data for respective leaf and stem inoculation. At 24 hpi, large differences in gene expression exist in leaf and stem, and there are more differentially expressed genes and larger expression differences in leaf. The leaf is more sensitive to S. sclerotiorum and shows a stronger response than stem. Different defense responses appear in the leaf and stem, and the biosynthesis of lignin, callose, lectin, chitinase, PGIP, and PR protein is activated in leaf. In the stem, lipid metabolism-mediated defense responses are obviously enhanced. For the common defense responses in both leaf and stem, the chain reactions resulting from signal transduction and biological process take the primary responsibility. This research will be beneficial to exploit the potential of different tissues in plant defense and find higher resistance levels of genotypic variability in different environments. Our results are significant in the identification of resistance genes and analysis of defense mechanisms.