Brassica napus (canola/oilseed rape/rapeseed) is an economically important crop, mostly found in temperate and sub-tropical regions, that is cultivated widely for its edible oil. Major diseases of Brassica crops such as Blackleg, Clubroot, Sclerotinia Stem Rot, Downy Mildew, Alternaria Leaf Spot and White Rust have caused significant yield and economic losses in rapeseed-producing countries worldwide, exacerbated by global climate change, and, if not remedied effectively, will threaten global food security. To gain further insights into the host–pathogen interactions in relation to Brassica diseases, it is critical that we review current knowledge in this area and discuss how omics technologies can offer promising results and help to push boundaries in our understanding of the resistance mechanisms. Omics technologies, such as genomics, proteomics, transcriptomics and metabolomics approaches, allow us to understand the host and pathogen, as well as the interaction between the two species at a deeper level. With these integrated data in multi-omics and systems biology, we are able to breed high-quality disease-resistant Brassica crops in a more holistic, targeted and accurate way.

During crop domestication and breeding, wild plant species have been shaped into modern high-yield crops and adapted to the main agro-ecological regions. However, climate change will impact crop productivity in these regions, and agriculture needs to adapt to support future food production. On a global scale, crop wild relatives grow in more diverse environments than crop species, and so may host genes that could support the adaptation of crops to new and variable environments. Through identification of individuals with increased climate resilience we may gain a greater understanding of the genomic basis for this resilience and transfer this to crops. Pangenome analysis can help to identify the genes underlying stress responses in individuals harbouring untapped genomic diversity in crop wild relatives. The information gained from the analysis of these pangenomes can then be applied towards breeding climate resilience into existing crops or to re-domesticating crops, combining environmental adaptation traits with crop productivity.

Among the Brassica oilseeds, canola (Brassica napus) is the most economically significant globally. However, its production can be limited by blackleg disease, caused by the fungal pathogen Lepstosphaeria maculans. The deployment of resistance genes has been implemented as one of the key strategies to manage the disease. Genetic resistance against blackleg comes in two forms: qualitative resistance, controlled by a single, major resistance gene (R gene), and quantitative resistance (QR), controlled by numerous, small effect loci. R-gene-mediated blackleg resistance has been extensively studied, wherein several genomic regions harbouring R genes against L. maculans have been identified and three of these genes were cloned. These studies advance our understanding of the mechanism of R gene and pathogen avirulence (Avr) gene interaction. Notably, these studies revealed a more complex interaction than originally thought. Advances in genomics help unravel these complexities, providing insights into the genes and genetic factors towards improving blackleg resistance. Here, we aim to discuss the existing R-gene-mediated resistance, make a summary of candidate R genes against the disease, and emphasise the role of players involved in the pathogenicity and resistance. The comprehensive result will allow breeders to improve resistance to L. maculans, thereby increasing yield.

Key message: Quantitative resistance (QR) loci discovered through genetic and genomic analyses are abundant in theBrassica napusgenome, providing an opportunity for their utilization in enhancing blackleg resistance. Quantitative resistance (QR) has long been utilized to manage blackleg inBrassica napus(canola, oilseed rape), even before major resistance genes (R-genes) were extensively explored in breeding programmes. In contrast to R-gene-mediated qualitative resistance, QR reduces blackleg symptoms rather than completely eliminating the disease. As a polygenic trait, QR is controlled by numerous genes with modest effects, which exerts less pressure on the pathogen to evolve; hence, its effectiveness is more durable compared to R-gene-mediated resistance. Furthermore, combining QR with major R-genes has been shown to enhance resistance against diseases in important crops, including oilseed rape. For these reasons, there has been a renewed interest among breeders in utilizing QR in crop improvement. However, the mechanisms governing QR are largely unknown, limiting its deployment. Advances in genomics are facilitating the dissection of the genetic and molecular underpinnings of QR, resulting in the discovery of several loci and genes that can be potentially deployed to enhance blackleg resistance. Here, we summarize the efforts undertaken to identify blackleg QR loci in oilseed rape using linkage and association analysis. We update the knowledge on the possible mechanisms governing QR and the advances in searching for the underlying genes. Lastly, we lay out strategies to accelerate the genetic improvement of blackleg QR in oilseed rape using improved phenotyping approaches and genomic prediction tools.

In Asia, a significant area under rice is affected by salinity. Salt stress can affect growth of crops as well as weeds. A study was conducted in a greenhouse to determine the effect of salinity (electrical conductivity [EC] of 1, 6, 12, 18, and 24 dS m⁻¹) on growth of barnyardgrass, horse purslane, junglerice, and rice. Growth variables were analyzed using regression analysis. The tested levels of EC influenced leaf production of barnyardgrass and junglerice but not that of horse purslane. As compared with the control treatment (EC of 1 dS m⁻¹), shoot biomass of barnyardgrass decreased by only 24% at 12 dS m⁻¹, whereas rice biomass declined by 59% at this level of EC. At EC of 24 dS m⁻¹, barnyardgrass still produced 4% of the biomass of the control treatment, whereas rice did not survive at this level of EC. Junglerice shoot biomass decreased by 73% at 18 dS m⁻¹EC compared with the control treatment, whereas rice shoot biomass declined by more than 86% at 18 dS m⁻¹EC. An EC of 10 dS m⁻¹was required to inhibit 50% shoot biomass of rice, whereas the EC to inhibit 50% shoot biomass of barnyardgrass and junglerice was 15 and 13 dS m⁻¹, respectively. Shoot biomass of horse purslane was not influenced by the tested levels of EC. At the highest EC (24 dS m⁻¹), at which rice did not survive, horse purslane shoot biomass was similar to that of the control treatment. In all weed species, data for root biomass showed trends similar to those of shoot biomass. The results of this study suggest that weeds were more tolerant to salt than rice, and horse purslane was the most tolerant species among the weeds.