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Theoretical and Applied Genetics

, Volume 125, Issue 8, pp 1589–1601 | Cite as

Genetic analysis of phytosterol content in sunflower seeds

  • Othmane MerahEmail author
  • Nicolas Langlade
  • Marion Alignan
  • Jane Roche
  • Nicolas Pouilly
  • Yannick Lippi
  • Felicity Vear
  • Muriel Cerny
  • Andrée Bouniols
  • Zephirin Mouloungui
  • Patrick Vincourt
Original Paper

Abstract

Interest in phytosterol contents due to their potential benefits for human health has been largely documented in several crop species. Studies were focused mainly on total sterol content and their concentration or distribution in seed. This study aimed at providing new insight into the genetic control of total and individual sterol contents in sunflower seed through QTL analyses in a RIL population characterized over 2 years showing contrasted rainfall during seed filling. Results indicated that 13 regions on 9 linkage groups were involved in different phytosterol traits. Most of the QTL mapped were stable across years in spite of contrasted growing conditions. Some of them explained up to 30 % of phenotypic variation. Two QTL, located on LG10, near b1, and on LG14, were found to co-localize with QTL for oil content, indicating that likely, a part of the genetic variation for sterol content is only the result of genetic variation for oil content. However, three other QTL, stable over the 2 years, were found on LG1, LG4 and LG7 each associated with a particular class of sterols, suggesting that some enzymes known to be involved in the sterol metabolic pathway may determine the specificity of sterol profiles in sunflower seeds. These results suggest that it may be possible to introduce these traits as criteria in breeding programmes for quality in sunflower. The molecular markers linked to genetic factors controlling phytosterol contents could help selection during breeding programs.

Keywords

Quantitative Trait Locus Recombinant Inbred Line Phytosterol Campesterol Recombinant Inbred Line Population 
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

We would like to thank the European Union for financially supporting this study (EFDR 7440 and 12688). Thanks are due to Elodie Gestas for her help in phytosterol analyses. The participation of Dr. O. Merah was supported by IUT A, Paul Sabatier University of Toulouse, France. This work also benefited from the support of the Genoplante 1999-2004 and OLEOSOL projects, funded respectively by the French Agence Nationale pour la Recherche (ANR) and the Midi-Pyrénées Region, French governmental support to competitive clusters, and the EDFR, for the establishment of the genetic map.

Supplementary material

122_2012_1937_MOESM1_ESM.xlsx (14 kb)
File 1: Excel file “map_fusion_public.xlsx” containing information on the genetic map (XLSX 14 kb)
122_2012_1937_MOESM2_ESM.xlsx (77 kb)
File 2: Excel file “sterol_pathway_CG_annotation.xlsx” containing gene sequence (FASTA format) and annotation for 7 candidate genes. Genotype XRQ (XLSX 77 kb)

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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Othmane Merah
    • 1
    • 2
    Email author
  • Nicolas Langlade
    • 3
    • 4
  • Marion Alignan
    • 1
    • 2
  • Jane Roche
    • 1
    • 2
  • Nicolas Pouilly
    • 3
    • 4
  • Yannick Lippi
    • 3
    • 4
  • Felicity Vear
    • 5
  • Muriel Cerny
    • 1
    • 2
  • Andrée Bouniols
    • 1
    • 2
  • Zephirin Mouloungui
    • 1
    • 2
  • Patrick Vincourt
    • 3
    • 4
  1. 1.Laboratoire de Chimie Agro-industrielle (LCA)INP-ENSIACET, Université de ToulouseToulouseFrance
  2. 2.INRA, UMR 1010 CAIToulouseFrance
  3. 3.Laboratoire des Interactions Plantes-Microorganismes (LIPM)INRA, UMR441Castanet-TolosanFrance
  4. 4.Laboratoire des Interactions Plantes-Microorganismes (LIPM)CNRS, UMR2594Castanet-TolosanFrance
  5. 5.INRA, UMR 1095 INRA-Université Blaise Pascal 234Clermont-FerrandFrance

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