Black spot disease (BSD), induced by Alternaria alternata, constitutes a significant menace to chrysanthemum. Identifying resistant germplasm resources underscores its critical importance in chrysanthemum breeding. To elucidate the genetic basis and candidate genes underpinning chrysanthemum BSD resistance, we conducted a multi-locus genome-wide association study (GWAS) using a panel of 152 accessions and 351555 single nucleotide polymorphisms (SNPs) via the 3VmrMLM method. We observed extensive phenotypic variation for the disease severity index (DSI) of BSD, with coefficients of variation ranging from 70.79% to 85.00%, and the broad-sense heritability was calculated at 74.36%. GWAS result detected seventy-one quantitative trait nucleotides (QTNs) and seven QTN-by-environment interactions (QEIs), accounting for 1.53%—7.06% and 0.68%—3.16% of the phenotypic variation, respectively. Eighteen stable QTNs were identified in more than two methods, from which eight highly favorable SNP alleles were extracted for BSD resistance. Furthermore, we observed a significant dosage-pyramiding effect (P < 0.001) among the favorable alleles. Among the genes surrounding the QTNs and QEIs, 12 were homologous to known disease-resistance genes in Arabidopsis, and 14 candidate genes were mined by combining the functional annotation and transcriptomics data, respectively. Our results help better understand the genetic architecture of BSD resistance, and the identified significant SNPs and candidate genes pave the way for future molecular breeding of chrysanthemums with enhanced BSD resistance.

Nitrogen (N) is a limiting factor that determines the yield and quality of chrysanthemum. Genetic variation in N use efficiency (NUE) has been reported among chrysanthemum genotypes. We performed a transcriptome analysis of two chrysanthemum genotypes, ‘Nannonglihuang’ (LH, N-efficient genotype) and ‘Nannongxuefeng’ (XF, N-inefficient genotype), under low N (0.4 mmol L^–1 N) and normal N (8 mmol L^–1 N) treatments for 15 d and an N recovery treatment for 12 h (low N treatment for 15 d and then normal N treatment for 12 h) to understand the genetic factors impacting NUE in chrysanthemum. The two genotypes exhibited contrasting responses to the different N treatments. The N-efficient genotype LH had significant superiority in agronomic traits, N accumulation and glutamine synthase activity under both normal N and low N treatments. Low N treatment promoted root growth in LH, but inhibited root growth in XF. Transcriptome analysis revealed that the low N treatment increased the expression of some N metabolism genes, genes related to auxin and abscisic acid signal transduction in the roots of both genotypes, as well as genes related to gibberellin signal transduction in roots of LH. The N recovery treatment just increased the expression of genes related to cytokinin signal transduction in roots of LH. The expression levels of the NRT2.1, AMT1.1, and Gln1 genes related to gibberellin and cytokinin signal transduction were higher in roots of LH than in XF under different N treatments, suggesting that the genes related to N metabolism and hormone (auxin, abscisic acid, gibberellin, and cytokinin) signal transduction in roots of LH are more sensitive to different N treatments than those of XF. Co-expression network analysis (WGCNA) also identified hub genes like bZIP43, bHLH93, NPF6.3, IBR10, MYB62, PP2C, PP2C06 and NLP7, which may be the key regulators of N-mediated responses in chrysanthemum and play crucial roles in enhancing NUE and resistance to low N stress in the N-efficient chrysanthemum genotype. These results revealed the key factors involved in regulating NUE in chrysanthemum at the genetic level, which provides new insights into the complex mechanism of efficient nitrogen utilization in chrysanthemum, and can be useful for the improvement and breeding of high NUE chrysanthemum genotypes.