Novel gene loci associated with susceptibility or cryptic quantitative resistance to Pyrenopeziza brassicae in Brassica napus

Abstract

Key message Quantitative disease resistance (QDR) controls the association of the light leaf spot pathogen with Brassica napus; four QDR loci that were in linkage disequilibrium and eight gene expression markers were identified. Abstract Quantitative disease resistance (QDR) can provide durable control of pathogens in crops in contrast to resistance (R) gene-mediated resistance which can break down due to pathogen evolution. QDR is therefore a desirable trait in crop improvement, but little is known about the causative genes, and so it is difficult to incorporate into breeding programmes. Light leaf spot, caused by Pyrenopeziza brassicae, is an important disease of oilseed rape (canola, Brassica napus). To identify new QDR gene loci, we used a high-throughput screening pathosystem with P. brassicae on 195 lines of B. napus combined with an association transcriptomics platform. We show that all resistance against P. brassicae was associated with QDR and not R gene-mediated. We used genome-wide association analysis with an improved B. napus population structure to reveal four gene loci significantly (P = 0.0001) associated with QDR in regions showing linkage disequilibrium. On chromosome A09, enhanced resistance was associated with heterozygosity for a cytochrome P450 gene co-localising with a previously described locus for seed glucosinolate content. In addition, eight significant gene expression markers with a false discovery rate of 0.001 were associated with QDR against P. brassicae. For seven of these, expression was positively correlated with resistance, whereas for one, a HXXXD-type acyl-transferase, negative correlation indicated a potential susceptibility gene. The study identifies novel QDR loci for susceptibility and resistance, including novel cryptic QDR genes associated with heterozygosity, that will inform future crop improvement.

Pathogen lifestyle determines host genetic signature of quantitative disease resistance loci in oilseed rape (Brassica napus)

“…The P. brassicae methods and phenotype dataset used were the same as in our previous publication (Fell et al, 2022). Disease severity was scored on a scale of 1 to 6-with a score of 1 for no sporulation and 6 for the most sporulation-and was calculated for the 129 genotypes.…”

“…Genome-Wide Association (GWA) and GEM mapping were done using the R-based GWA and GEM Automation (GAGA) pipeline (Nichols, 2022), which utilizes GAPIT Version 3 (Lipka et al, 2012;Wang and Zhang, 2021). GAGA was run using our recently updated population structure (Fell et al, 2022) and B. napus Pantranscriptome version 11 (Havlickova et al, 2018). For GWA analyses, generalized linear model (GLM), Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) (Huang et al, 2019), and Fixed and random model Circulating Probability Unification (FarmCPU) (Liu et al, 2016) models were compared using QQ plots to select the best-fitting model.…”

Pathogen lifestyle determines host genetic signature of quantitative disease resistance loci in oilseed rape (Brassica napus)

“…The R-based GAGA pipeline is available at https://github.com/bsnichols/GAGA. Our population structure is available in Fell et al (2022) [37]. Supplemental les are also available at https://zenodo.org/record/8321694.…”

“…Disease susceptibility signi cantly impacts B. napus yields so enhanced resistance is a major breeding objective. Employing associative transcriptomics (AT) (Harper et al 2012, Havlickova et al 2018, we previously identi ed single nucleotide polymorphism (SNP) and gene expression marker (GEM) candidate loci linked to B. napus QDR against Pyrenopeziza brassicae (Fell et al 2022). The GEM analysis utilizes transcriptomic data representing a baseline pre-infection expression level-a foundation for investigating constitutive QDR.…”

Recognition of Necrosis and Ethylene-inducing like peptides confers disease resistance inBrassica napusand is modulated byBSK1in Arabidopsis

“…Although this complexity presents challenges for polyploid species, the bioinformatics resources for gene identification are well advanced for B. napus including the availability of two reference genomes, ZS11 (Song et al, 2020) and Darmor-bzh (Chalhoub et al, 2014). Genome-wide association studies (GWAS) and associative transcriptomics (AT) involve associating single nucleotide polymorphisms (SNPs) in genomes or transcriptomes respectively with polymorphic traits in genetically diverse accessions and have been used to identify candidate resistance gene loci for S. sclerotiorum (Sclerotinia stem rot), Plasmodiophora brassicae (clubroot) and Pyrenopeziza brassicae (light leaf spot) in B. napus (Dakouri et al, 2021;Fell, Muthayil Ali, et al, 2022;Roy et al, 2021).…”