Genetic mapping and genomic prediction of sclerotinia stem rot resistance to rapeseed/canola (Brassica napus L.) at seedling stage

Using genotype imputation to integrate Canola populations for genome-wide association and genomic prediction of blackleg resistance

BACKGROUND

Integrating germplasm populations genotyped by different genotyping platforms via genotype imputation is a way to utilize accumulated genetic resources. In this study, we used 278 canola samples genotyped via whole-genome sequencing (WGS) at 10× coverage to evaluate the imputation accuracy of three imputation approaches. The optimal imputation methods were used to impute and integrate two Canola genotype datasets: a diverse canola collection genotyped by genotyping-by-sequencing via transcriptome (GBS-t) and a double haploid (DH) line collection genotyped with low-coverage WGS (skim-WGS). The genomic predictive ability (GP) and detection power of marker‒trait association (GWAS) of the combined population for blackleg resistance were evaluated.

RESULTS

The empirical imputation accuracy (r2) measured as the squared correlation between observed and imputed genotypes was moderate for Minimac3 when imputing from the GBS-t density to the WGS. The accuracy dramatically improved from 0.64 to 0.82 by removing SNPs with poor Minimac3-reported Rsq (Rsq < 0.2) quality statistics. The r2 for GLIMPSE was higher than that for Beagle when imputing from different low-coverage to full-coverage WGS. We imputed and integrated the diverse canola collection and the DH lines, and the combined population showed similar or slightly greater predictive ability (PA) for blackleg resistance traits than did each of the single populations with ~ 921 K SNPs. Higher marker-trait association (MTA) detection powers were indicated with the combined population; however, similar numbers of MTAs were discovered when each single population was combined in a meta-GWAS.

CONCLUSION

It is feasible to impute and integrate germplasms from different sequencing platforms for downstream analyses. However, genetic heterogeneity across populations could add complexity to the analysis. Increasing the sample size by combining datasets showed slightly greater predictive ability and greater detection power in GWASs in the present study.

Hybrid Prediction in Horticulture Crop Breeding: Progress and Challenges

In the context of rapidly increasing population and diversified market demands, the steady improvement of yield and quality in horticultural crops has become an urgent challenge that modern breeding efforts must tackle. Heterosis, a pivotal theoretical foundation for plant breeding, facilitates the creation of superior hybrids through crossbreeding and selection among a variety of parents. However, the vast number of potential hybrids presents a significant challenge for breeders in efficiently predicting and selecting the most promising candidates. The development and refinement of effective hybrid prediction methods have long been central to research in this field. This article systematically reviews the advancements in hybrid prediction for horticultural crops, including the roles of marker-assisted breeding and genomic prediction in phenotypic forecasting. It also underscores the limitations of some predictors, like genetic distance, which do not consistently offer reliable hybrid predictions. Looking ahead, it explores the integration of phenomics with genomic prediction technologies as a means to elevate prediction accuracy within actual breeding programs.

Natural variation in BnaA07.MKK9 confers resistance to Sclerotinia stem rot in oilseed rape

Sclerotinia stem rot (SSR), caused by the necrotrophic fungus Sclerotinia sclerotiorum, is one of the most devastating diseases for several major oil-producing crops. Despite its impact, the genetic basis of SSR resistance in plants remains poorly understood. Here, through a genome-wide association study, we identify a key gene, BnaA07. MKK9, that encodes a mitogen-activated protein kinase kinase that confers SSR resistance in oilseed rape. Our functional analyses reveal that BnaA07.MKK9 interacts with BnaC03.MPK3 and BnaC03.MPK6 and phosphorylates them at the TEY activation motif, triggering a signaling cascade that initiates biosynthesis of ethylene, camalexin, and indole glucosinolates, and promotes accumulation of H2O2 and the hypersensitive response, ultimately conferring resistance. Furthermore, variations in the coding sequence of BnaA07.MKK9 alter its kinase activity and improve SSR resistance by ~30% in cultivars carrying the advantageous haplotype. These findings enhance our understanding of SSR resistance and may help engineer novel diversity for future breeding of oilseed rape.

Genetic architecture and genomic prediction of plant height-related traits in chrysanthemum

Plant height (PH) is a crucial trait determining plant architecture in chrysanthemum. To better understand the genetic basis of PH, we investigated the variations of PH, internode number (IN), internode length (IL), and stem diameter (SD) in a panel of 200 cut chrysanthemum accessions. Based on 330 710 high-quality SNPs generated by genotyping by sequencing, a total of 42 associations were identified via a genome-wide association study (GWAS), and 16 genomic regions covering 2.57 Mb of the whole genome were detected through selective sweep analysis. In addition, two SNPs, Chr1_339370594 and Chr18_230810045, respectively associated with PH and SD, overlapped with the selective sweep regions from FST and π ratios. Moreover, candidate genes involved in hormones, growth, transcriptional regulation, and metabolic processes were highlighted based on the annotation of homologous genes in Arabidopsis and transcriptomes in chrysanthemum. Finally, genomic selection for four PH-related traits was performed using a ridge regression best linear unbiased predictor model (rrBLUP) and six marker sets. The marker set constituting the top 1000 most significant SNPs identified via GWAS showed higher predictabilities for the four PH-related traits, ranging from 0.94 to 0.97. These findings improve our knowledge of the genetic basis of PH and provide valuable markers that could be applied in chrysanthemum genomic selection breeding programs.

Overview and Management of the Most Common Eukaryotic Diseases of Flax (Linum usitatissimum)

Flax is an important crop cultivated for its seeds and fibers. It is widely grown in temperate regions, with an increase in cultivation areas for seed production (linseed) in the past 50 years and for fiber production (fiber flax) in the last decade. Among fiber-producing crops, fiber flax is the most valuable species. Linseed is the highest omega-3 oleaginous crop, and its consumption provides several benefits for animal and human health. However, flax production is impacted by various abiotic and biotic factors that affect yield and quality. Among biotic factors, eukaryotic diseases pose a significant threat to both seed production and fiber quality, which highlights the economic importance of controlling these diseases. This review focuses on the major eukaryotic diseases that affect flax in the field, describing the pathogens, their transmission modes and the associated plant symptoms. Moreover, this article aims to identify the challenges in disease management and provide future perspectives to overcome these biotic stresses in flax cultivation. By emphasizing the key diseases and their management, this review can aid in promoting sustainable and profitable flax production.

Biobased, Macro-, and Nanoscale Fungicide Delivery Approaches for Plant Fungi Control

In this report, two polymeric matrix systems at macro and nanoscales were prepared for efficacious fungicide delivery. The macroscale delivery systems used millimeter-scale, spherical beads composed of cellulose nanocrystals and poly(lactic acid). The nanoscale delivery system involved micelle-type nanoparticles, composed of methoxylated sucrose soyate polyols. Sclerotinia sclerotiorum (Lib.), a destructive fungus affecting high-value industrial crops, was used as a model pathogen against which the efficacy of these polymeric formulations was demonstrated. Commercial fungicides are applied on plants frequently to overcome the transmission of fungal infection. However, fungicides alone do not persist on the plants for a prolonged period due to environmental factors such as rain and airflow. There is a need to apply fungicides multiple times. As such, standard application practices generate a significant environmental footprint due to fungicide accumulation in soil and runoff in surface water. Thus, approaches are needed that can either increase the efficacy of commercially active fungicides or prolong their residence time on plants for sustained antifungal coverage. Using azoxystrobin (AZ) as a model fungicide and canola as a model crop host, we hypothesized that the AZ-loaded macroscale beads, when placed in contact with plants, will act as a depot to release the fungicide at a controlled rate to protect plants against fungal infection. The nanoparticle-based fungicide delivery approach, on the other hand, can be realized via spray or foliar applications. The release rate of AZ from macro- and nanoscale systems was evaluated and analyzed using different kinetic models to understand the mechanism of AZ delivery. We observed that, for macroscopic beads, porosity, tortuosity, and surface roughness governed the efficiency of AZ delivery, and for nanoparticles, contact angle and surface adhesion energy were directing the efficacy of the encapsulated fungicide. The technology reported here can also be translated to a wide variety of industrial crops for fungal protection. The strength of this study is the possibility of using completely plant-derived, biodegradable/compostable additive materials for controlled agrochemical delivery formulations, which will contribute to reducing the frequency of fungicide applications and the potential accumulation of formulation components in soil and water.