Genetic and molecular analysis of stem rot (Sclerotinia sclerotiorum) resistance in Brassica napus (canola type).

Identifying the molecular and genetic basis of resistance to Sclerotinia stem rot (Sclerotinia sclerotiorum) is critical for developing long-term and cost-effective management of this disease in rapeseed/canola (Brassica napus). Current cultural or chemical management options provide, at best, only partial and/or sporadic control. Towards this, a B. napus breeding population (Mystic x Rainbow), including the parents, F1, F2, BC1P1 and BC1P2, was utilized in a field study to determine the inheritance pattern of Sclerotinia stem rot resistance (based on stem lesion length, SLL). Broad sense heritability was 0.58 for SLL and 0.44 for days to flowering (DTF). There was a significant negative correlation between SLL and stem diameter (SD) (r = -0.39) and between SLL and DTF (r = -0.28), suggesting co-selection of SD and DTF traits, along with SLL, should assist in improving overall resistance. Non-additive genetic variance was evident for SLL, DTF, and SD. In a genome wide association study (GWAS), a significant quantitative trait locus (QTL) was identified for SLL. Several putative candidate marker trait associations (MTA) were located within this QTL region. Overall, this study has provided valuable new understanding of inheritance of resistance to S. sclerotiorum, and has identified QTL, MTAs and transgressive segregants with high-level resistances. Together, these will foster more rapid selection for multiple traits associated with Sclerotinia stem rot resistance, by enabling breeders to make critical choices towards selecting/developing cultivars with enhanced resistance to this devastating pathogen.

Identification of candidate genes for LepR1 resistance against Leptosphaeria maculans in Brassica napus.

Utilising resistance (R) genes, such as LepR1, against Leptosphaeria maculans, the causal agent of blackleg in canola (Brassica napus), could help manage the disease in the field and increase crop yield. Here we present a genome wide association study (GWAS) in B. napus to identify LepR1 candidate genes. Disease phenotyping of 104 B. napus genotypes revealed 30 resistant and 74 susceptible lines. Whole genome re-sequencing of these cultivars yielded over 3 million high quality single nucleotide polymorphisms (SNPs). GWAS in mixed linear model (MLM) revealed a total of 2,166 significant SNPs associated with LepR1 resistance. Of these SNPs, 2108 (97%) were found on chromosome A02 of B. napus cv. Darmor bzh v9 with a delineated LepR1_mlm1 QTL at 15.11-26.08 Mb. In LepR1_mlm1, there are 30 resistance gene analogs (RGAs) (13 nucleotide-binding site-leucine rich repeats (NLRs), 12 receptor-like kinases (RLKs), and 5 transmembrane-coiled-coil (TM-CCs)). Sequence analysis of alleles in resistant and susceptible lines was undertaken to identify candidate genes. This research provides insights into blackleg resistance in B. napus and assists identification of the functional LepR1 blackleg resistance gene.

Innovative Advances in Plant Genotyping.

Over the past decade, advances in plant genotyping have been critical in enabling the identification of genetic diversity, in understanding evolution, and in dissecting important traits in both crops and native plants. The widespread popularity of single-nucleotide polymorphisms (SNPs) has prompted significant improvements to SNP-based genotyping, including SNP arrays, genotyping by sequencing, and whole-genome resequencing. More recent approaches, including genotyping structural variants, utilizing pangenomes to capture species-wide genetic diversity and exploiting machine learning to analyze genotypic data sets, are pushing the boundaries of what plant genotyping can offer. In this chapter, we highlight these innovations and discuss how they will accelerate and advance future genotyping efforts.

Predicting Cloned Disease Resistance Gene Homologs (CDRHs) in Radish, Underutilised Oilseeds, and Wild Brassicaceae Species.

Brassicaceae crops, including Brassica, Camelina and Raphanus species, are among the most economically important crops globally; however, their production is affected by several diseases. To predict cloned disease resistance (R) gene homologs (CDRHs), we used the protein sequences of 49 cloned R genes against fungal and bacterial diseases in Brassicaceae species. In this study, using 20 Brassicaceae genomes (17 wild and 3 domesticated species), 3172 resistance gene analogs (RGAs) (2062 nucleotide binding-site leucine-rich repeats (NLRs), 497 receptor-like protein kinases (RLKs) and 613 receptor-like proteins (RLPs)) were identified. CDRH clusters were also observed in Arabis alpina, Camelina sativa and Cardamine hirsuta with assigned chromosomes, consisting of 62 homogeneous (38 NLR, 17 RLK and 7 RLP clusters) and 10 heterogeneous RGA clusters. This study highlights the prevalence of CDRHs in the wild relatives of the Brassicaceae family, which may lay the foundation for rapid identification of functional genes and genomics-assisted breeding to develop improved disease-resistant Brassicaceae crop cultivars.

Mining of Cloned Disease Resistance Gene Homologs (CDRHs) in Brassica Species and Arabidopsis thaliana.

Various diseases severely affect Brassica crops, leading to significant global yield losses and a reduction in crop quality. In this study, we used the complete protein sequences of 49 cloned resistance genes (R genes) that confer resistance to fungal and bacterial diseases known to impact species in the Brassicaceae family. Homology searches were carried out across Brassica napus, B. rapa, B. oleracea, B. nigra, B. juncea, B. carinata and Arabidopsis thaliana genomes. In total, 660 cloned disease R gene homologs (CDRHs) were identified across the seven species, including 431 resistance gene analogs (RGAs) (248 nucleotide binding site-leucine rich repeats (NLRs), 150 receptor-like protein kinases (RLKs) and 33 receptor-like proteins (RLPs)) and 229 non-RGAs. Based on the position and distribution of specific homologs in each of the species, we observed a total of 87 CDRH clusters composed of 36 NLR, 16 RLK and 3 RLP homogeneous clusters and 32 heterogeneous clusters. The CDRHs detected consistently across the seven species are candidates that can be investigated for broad-spectrum resistance, potentially providing resistance to multiple pathogens. The R genes identified in this study provide a novel resource for the future functional analysis and gene cloning of Brassicaceae R genes towards crop improvement.

Advancing designer crops for climate resilience through an integrated genomics approach.

Climate change and exponential population growth are exposing an immediate need for developing future crops that are highly resilient and adaptable to changing environments to maintain global food security in the next decade. Rigorous selection from long domestication history has rendered cultivated crops genetically disadvantaged, raising concerns in their ability to adapt to these new challenges and limiting their usefulness in breeding programmes. As a result, future crop improvement efforts must rely on integrating various genomic strategies ranging from high-throughput sequencing to machine learning, in order to exploit germplasm diversity and overcome bottlenecks created by domestication, expansive multi-dimensional phenotypes, arduous breeding processes, complex traits and big data.

In silico integration of disease resistance QTL, genes and markers with the Brassica juncea physical map.

Brassica juncea (AABB), Indian mustard, is a source of disease resistance genes for a wide range of pathogens. The availability of reference genome sequences for B. juncea has made it possible to characterise the genomic structure and distribution of these disease resistance genes. Potentially functional disease resistance genes can be identified by co-localization with genetically mapped disease resistance quantitative trait loci (QTL). Here we identify and characterise disease resistance gene analogs (RGAs), including nucleotide-binding site-leucine-rich repeat (NLR), receptor-like kinase (RLK) and receptor-like protein (RLP) classes, and investigate their association with disease resistance QTL intervals. The molecular genetic marker sequences for four white rust (Albugo candida) disease resistance QTL, six blackleg (Leptosphaeria maculans) disease resistance QTL and BjCHI1, a gene cloned from B. juncea for hypocotyl rot disease, were extracted from previously published studies and used to compare with candidate RGAs. Our results highlight the complications for the identification of functional resistance genes, including the duplicated appearance of genetic markers for several resistance loci, including Ac2(t), AcB1-A4.1, AcB1-A5.1, Rlm6 and PhR2 in both the A and B genomes, due to the presence of homoeologous regions. Furthermore, the white rust loci, Ac2(t) and AcB1-A4.1, mapped to the same position on chromosome A04 and may be different alleles of the same gene. Despite these challenges, a total of nine candidate genomic regions hosting 14 RLPs, 28 NLRs and 115 RLKs were identified. This study facilitates the mapping and cloning of functional resistance genes for applications in crop improvement programs. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-022-01309-5.

Recent Findings Unravel Genes and Genetic Factors Underlying Leptosphaeria maculans Resistance in Brassica napus and Its Relatives.

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.