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Theoretical and Applied Genetics

, Volume 132, Issue 8, pp 2237–2252 | Cite as

A novel high-density grapevine (Vitis vinifera L.) integrated linkage map using GBS in a half-diallel population

  • Javier Tello
  • Catherine Roux
  • Hajar Chouiki
  • Valérie Laucou
  • Gautier Sarah
  • Audrey Weber
  • Sylvain Santoni
  • Timothée Flutre
  • Thierry Pons
  • Patrice This
  • Jean-Pierre Péros
  • Agnès DoligezEmail author
Original Article

Abstract

Key message

A half-diallel population involving five elite grapevine cultivars was generated and genotyped by GBS, and highly-informative segregation data was used to construct a high-density genetic map for Vitis vinifera L.

Abstract

Grapevine is one of the most relevant fruit crops in the world. Deeper genetic knowledge could assist modern grapevine breeding programs to develop new wine grape varieties able to face climate change effects. To assist in the rapid identification of markers for crop yield components, grape quality traits and adaptation potential, we generated a large Vitis vinifera L. population (N = 624) by crossing five red wine cultivars in a half-diallel scheme, which was subsequently sequenced by an efficient GBS procedure. A high number of fully informative genetic variants was detected using a novel mapping approach capable of reconstructing local haplotypes from adjacent biallelic SNPs, which were subsequently used to construct the densest consensus genetic map available for the cultivated grapevine to date. This 1378.3-cM map integrates 10 bi-parental consensus maps and orders 4437 markers in 3353 unique positions on 19 chromosomes. Markers are well distributed all along the grapevine reference genome, covering up to 98.8% of its genomic sequence. Additionally, a good agreement was observed between genetic and physical orders, adding confidence in the quality of this map. Collectively, our results pave the way for future genetic studies (such as fine QTL mapping) aimed to understand the complex relationship between genotypic and phenotypic variation in the cultivated grapevine. In addition, the method used (which efficiently delivers a high number of fully informative markers) could be of interest to other outbred organisms, notably perennial fruit crops.

Notes

Author contribution statement

PT, JPP and AD conceived the idea of the study and contributed to funding acquisition; CR, TP and AD obtained and/or assisted in the maintenance of the plant material used in this work; CR and AW carried out the genotyping of the plant material; SS defined GBS protocols; HC and GS defined bioinformatics pipelines for GBS data analysis; JT, CR and VL performed bioinformatics analysis of GBS data; JT, TF and AD defined scripts for genetic mapping; JT analysed data and wrote the manuscript with the inputs from all authors, who approved the final version of the manuscript; AD coordinated this work.

Acknowledgements

JT was supported by the Agreenskills + Fellowship Programme, which has received funding from the EU's Seventh Framework Programme under grant agreement No. FP7-609398. This work was partially supported by the Géno-Vigne® Technological Unit, the Agropolis Fondation (under the ARCAD project No 0900–001), and by the CIRAD - UMR AGAP HPC Data Center of the South Green Bioinformatics platform (https://www.southgreen.fr/). Authors acknowledge Thierry Lacombe for his help with the French Network of Grapevine Repositories Database, and the staff of the INRA Vassal grapevine collection for their help with the crosses and the maintenance of the plantlets before being transferred to the Domaine du Chapitre Experimental Vineyard.

Compliance with ethical standards

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Ethical standards

The authors declare that the experiments comply with the current laws of the country in which they were carried out.

Availability of data and materials

Information on the plant material used in this work can be retrieved from the French Network of Grapevine Repositories Database (https://bioweb.supagro.inra.fr/collections_vigne). The raw sequence data have been deposited in the National Center for Biotechnology Information (NCBI) database (https://www.ncbi.nlm.nih.gov/bioproject/508587). Datasets are available in the Portail Data INRA public repository (https://doi.org/10.15454/99SLGP). All other relevant information is specified in the manuscript or included as Additional Files.

Supplementary material

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.UMR AGAPUniversity of Montpellier-CIRAD-INRA-Montpellier SupAgroMontpellierFrance
  2. 2.UMT Geno-Vigne®IFV-INRA-Montpellier SupAgroMontpellierFrance

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