Polyploidization has provided much genetic variation for plant adaptive evolution, but the mechanisms by which the molecular evolution of polyploid genomes establishes genetic architecture underlying species differentiation are unclear. Brassica is an ideal model to increase knowledge of polyploid evolution. Here we describe a draft genome sequence of Brassica oleracea, comparing it with that of its sister species B. rapa to reveal numerous chromosome rearrangements and asymmetrical gene loss in duplicated genomic blocks, asymmetrical amplification of transposable elements, differential gene co-retention for specific pathways and variation in gene expression, including alternative splicing, among a large number of paralogous and orthologous genes. Genes related to the production of anticancer phytochemicals and morphological variations illustrate consequences of genome duplication and gene divergence, imparting biochemical and morphological variation to B. oleracea. This study provides insights into Brassica genome evolution and will underpin research into the many important crops in this genus.

Brassica napus (2n = 4x = 38, AACC) is an important allopolyploid crop derived from interspecific crosses between Brassica rapa (2n = 2x = 20, AA) and Brassica oleracea (2n = 2x = 18, CC). However, no truly wild B. napus populations are known; its origin and improvement processes remain unclear. Here, we resequence 588 B. napus accessions. We uncover that the A subgenome may evolve from the ancestor of European turnip and the C subgenome may evolve from the common ancestor of kohlrabi, cauliflower, broccoli, and Chinese kale. Additionally, winter oilseed may be the original form of B. napus. Subgenome-specific selection of defense-response genes has contributed to environmental adaptation after formation of the species, whereas asymmetrical subgenomic selection has led to ecotype change. By integrating genome-wide association studies, selection signals, and transcriptome analyses, we identify genes associated with improved stress tolerance, oil content, seed quality, and ecotype improvement. They are candidates for further functional characterization and genetic improvement of B. napus.

R2R3-MYB proteins (2R-MYBs) are one of the main transcription factor families in higher plants. Since the evolutionary history of this gene family across the eukaryotic kingdom remains unknown, we performed a comparative analysis of 2R-MYBs from 50 major eukaryotic lineages, with particular emphasis on land plants. A total of 1548 candidates were identified among diverse taxonomic groups, which allowed for an updated classification of 73 highly conserved subfamilies, including many newly identified subfamilies. Our results revealed that the protein architectures, intron patterns and sequence characteristics were remarkably conserved in each subfamily. At least four subfamilies were derived from early land plants, 10 evolved from spermatophytes and 19 from angiosperms, demonstrating the diversity and preferential expansion of this gene family in land plants. Moreover, we determined that their remarkable expansion was mainly attributed to whole genome and segmental duplication, where duplicates were preferentially retained within certain subfamilies that shared three homologous intron patterns (a, b and c) even though up to 12 types of patterns existed. Through our integrated distributions, sequence characteristics and phylogenetic tree analyses, we confirm that 2R-MYBs are old and postulate that 3R-MYBs may be evolutionarily derived from 2R-MYBs via intragenic domain duplication.

Crop production is the primary goal of agricultural activities, which is always taken into consideration. However, global agricultural systems are coming under increasing pressure from the rising food demand of the rapidly growing world population and changing climate. To address these issues, improving high-yield and climate-resilient related-traits in crop breeding is an effective strategy. In recent years, advances in omics techniques, including genomics, transcriptomics, proteomics, and metabolomics, paved the way for accelerating plant/crop breeding to cope with the changing climate and enhance food production. Optimized omics and phenotypic plasticity platform integration, exploited by evolving machine learning algorithms will aid in the development of biological interpretations for complex crop traits. The precise and progressive assembly of desire alleles using precise genome editing approaches and enhanced breeding strategies would enable future crops to excel in combating the changing climates. Furthermore, plant breeding and genetic engineering ensures an exclusive approach to developing nutrient sufficient and climate-resilient crops, the productivity of which can sustainably and adequately meet the world’s food, nutrition, and energy needs. This review provides an overview of how the integration of omics approaches could be exploited to select crop varieties with desired traits.

Real-time quantitative polymerase chain reaction (qPCR) is one of the most important methods for analyzing the expression patterns of target genes. However, successful qPCR experiments rely heavily on the use of high-quality primers. Various qPCR primer databases have been developed to address this issue, but these databases target only a few important organisms. Here, we developed the qPrimerDB database, founded on an automatic gene-specific qPCR primer design and thermodynamics-based validation workflow. The qPrimerDB database is the most comprehensive qPCR primer database available to date, with a web front-end providing gene-specific and pre-computed primer pairs across 147 important organisms, including human, mouse, zebrafish, yeast, thale cress, rice and maize. In this database, we provide 3331426 of the best primer pairs for each gene, based on primer pair coverage, as well as 47760359 alternative gene-specific primer pairs, which can be conveniently batch downloaded. The specificity and efficiency was validated for qPCR primer pairs for 66 randomly selected genes, in six different organisms, through qPCR assays and gel electrophoresis. The qPrimerDB database represents a valuable, timesaving resource for gene expression analysis. This resource, which will be routinely updated, is publically accessible at http://biodb.swu.edu.cn/qprimerdb.