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Theoretical and Applied Genetics

, Volume 126, Issue 3, pp 567–581 | Cite as

Phenotypic diversity and association mapping for fruit quality traits in cultivated tomato and related species

  • Jiaxin Xu
  • Nicolas Ranc
  • Stéphane Muños
  • Sophie Rolland
  • Jean-Paul Bouchet
  • Nelly Desplat
  • Marie-Christine Le Paslier
  • Yan Liang
  • Dominique Brunel
  • Mathilde CausseEmail author
Original Paper

Abstract

Association mapping has been proposed as an efficient approach to assist in the identification of the molecular basis of agronomical traits in plants. For this purpose, we analyzed the phenotypic and genetic diversity of a large collection of tomato accessions including 44 heirloom and vintage cultivars (Solanum lycopersicum), 127 S. lycopersicum var. cerasiforme (cherry tomato) and 17 Solanum pimpinellifolium accessions. The accessions were genotyped using a SNPlex™ assay of 192 SNPs, among which 121 were informative for subsequent analysis. Linkage disequilibrium (LD) of pairwise loci and population structure were analyzed, and the association analysis between SNP genotypes and ten fruit quality traits was performed using a mixed linear model. High level of LD was found in the collection at the whole genome level. It was lower when considering only the 127 S. lycopersicum var. cerasiforme accessions. Genetic structure analysis showed that the population was structured into two main groups, corresponding to cultivated and wild types and many intermediates. The number of associations detected per trait varied, according to the way the structure was taken into account, with 0–41 associations detected per trait in the whole collection and a maximum of four associations in the S. lycopersicum var. cerasiforme accessions. A total of 40 associations (30 %) were co-localized with previously identified quantitative trait loci. This study thus showed the potential and limits of using association mapping in tomato populations.

Keywords

Linkage Disequilibrium Simple Sequence Repeat Marker Association Mapping Titratable Acidity Fruit Weight 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The research was financed by INRA AIP Bioresources project. Jiaxin Xu was supported by China Scholarship Council. We thank Hélène Burck for characterizing and maintaining the INRA tomato Genetic Resources collection. We are grateful to Yolande Carretero, Esther Pelpoir and Laure David for their help with growing and phenotyping cherry tomato accessions.

Supplementary material

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jiaxin Xu
    • 1
    • 2
  • Nicolas Ranc
    • 2
    • 4
  • Stéphane Muños
    • 2
    • 5
  • Sophie Rolland
    • 2
    • 6
  • Jean-Paul Bouchet
    • 2
  • Nelly Desplat
    • 2
  • Marie-Christine Le Paslier
    • 3
  • Yan Liang
    • 1
  • Dominique Brunel
    • 3
  • Mathilde Causse
    • 2
    Email author
  1. 1.College of HorticultureNorthwest A&F UniversityYang LingPeople’s Republic of China
  2. 2.Unité de Génétique et Amélioration des Fruits et LégumesINRA, UR1052AvignonFrance
  3. 3.Unité Etude du Polymorphisme des Génomes Végétaux, CEA-Institut de Génomique-CNGINRA, UR1279EvryFrance
  4. 4.Syngenta Seeds SASSaint-SauveurFrance
  5. 5.Laboratoire des Interactions Plantes Micro-organismes (LIPM)CNRS-INRA, UMR 2594/441Castanet-Tolosan CedexFrance
  6. 6.Amélioration des Plantes et Biotechnologies VégétalesINRA-AgroCampus Ouest-Université Rennes1, UMR118Le Rheu CedexFrance

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