, 214:21 | Cite as

Genetic variation and association mapping of aphid (Macrosiphoniella sanbourni) resistance in chrysanthemum (Chrysanthemum morifolium Ramat.)

  • Xiao Fu
  • Jiangshuo Su
  • Kaili Yu
  • Yifan Cai
  • Fei Zhang
  • Sumei Chen
  • Weimin Fang
  • Chen Fadi
  • Zhiyong Guan


Aphid, Macrosiphoniella sanbourni, is a major insect pest that adversely affects ornamental quality and production of chrysanthemum, thus it is critical to develop new cultivars resistant to aphid. However, the genetic mechanism governing aphid resistance is thus far not thoroughly investigated in chrysanthemum. This study aimed to characterize the genetic variation of the aphid resistance in a global collection of 80 chrysanthemum entries, during summer and autumn under greenhouse condition, and to identify the molecular markers for aphid resistance by association mapping. The performances of aphid resistance, quantified by the average damage index of aphid, was significantly correlated (r = 0.93, P < 0.01) between two seasons. The coefficients phenotypic and genetic variation was calculated around 26–27%; and a high magnitude (0.93) of broad-sense heritability, together with a moderate relative genetic advance (~ 68%), was estimated for aphid resistance. By using the MLM model that integrates population structure and kinship matrix as covariates association mapping identified 11 markers related to aphid resistance, with the individually explained phenotypic variation ranging from ~ 11 to ~ 57%. Of the three markers predicted in both seasons, SSR184-1 and E1M5-1were identified as favorable alleles for aphid resistance. Seven cultivars harboring the two favorable alleles were identified as potential donor parents for future improvement of resistance against aphid. These findings add further understanding of the genetic determination of aphid resistance, and the identified favorable alleles and donor parents open a possibility to produce chrysanthemums with enhanced aphid resistance in future.


Aphid resistance Association mapping Chrysanthemum Favorable allele Genetic variation 



This work was financially supported by the National Natural Science Foundation of China (Grant Nos. 31471900 and 31672192). Germplasm Resources Protection (crop) project of Ministry of Agriculture (Grant No. 1120162130135252031).

Supplementary material

10681_2017_2085_MOESM1_ESM.tif (24.9 mb)
Supplementary material 1 (TIFF 25521 kb). Fig. S1 Planting design of the aphid-induced rows and the investigated accessions
10681_2017_2085_MOESM2_ESM.tif (287 kb)
Supplementary material 2 (TIFF 287 kb). Fig. S2 The structure of the AM set of 80 chrysanthemums based on an admixture model with K = 2. Pop 1 and Pop 2 represent the two sub-populations defined by a Q threshold of 0.8
10681_2017_2085_MOESM3_ESM.tif (654 kb)
Supplementary material 3 (TIFF 653 kb). Fig. S3 The distribution of pair-wise kinship coefficients in the AM set of 80 chrysanthemums
10681_2017_2085_MOESM4_ESM.tif (2.2 mb)
Supplementary material 4 (TIFF 2219 kb). Fig. S4 Quantile–quantile (Q–Q) probability plot for I* value obtained from the application of MLM model taking population structure and kinship matrix into account. Each dot represents a marker
10681_2017_2085_MOESM5_ESM.tif (49.8 mb)
Supplementary material 5 (TIFF 51017 kb). Fig. S5 Non-choice test on the aphid resistance of each five resistant and susceptive chrysanthemum cultivars using artificial inoculation method. A, a sample of ten wingless adult aphids (second instar nymphs) placed in a plastic clip cage on the underside of the full leaf; B, different aphid densities of susceptive and resistant genotypes at 7d after inoculation; C, the average aphid damage index (I*) of each five resistant and susceptive chrysanthemum genotypes between the non-choice (artificial inoculation) and choice (simulated field evaluation) tests
10681_2017_2085_MOESM6_ESM.xlsx (16 kb)
Supplementary material 6 (XLSX 15 kb)
10681_2017_2085_MOESM7_ESM.xlsx (11 kb)
Supplementary material 7 (XLSX 10 kb)


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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2017

Authors and Affiliations

  • Xiao Fu
    • 1
  • Jiangshuo Su
    • 1
  • Kaili Yu
    • 1
  • Yifan Cai
    • 1
  • Fei Zhang
    • 1
  • Sumei Chen
    • 1
  • Weimin Fang
    • 1
  • Chen Fadi
    • 1
  • Zhiyong Guan
    • 1
  1. 1.College of HorticultureNanjing Agricultural UniversityNanjingPeople’s Republic of China

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