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Molecular Breeding

, 36:115 | Cite as

Development of single nucleotide polymorphism markers in the large and complex rubber tree genome using next-generation sequence data

  • Livia Moura de Souza
  • Guilherme Toledo-Silva
  • Claudio Benicio Cardoso-Silva
  • Carla Cristina da Silva
  • Isabela Aparecida de Araujo Andreotti
  • Andre Ricardo Oliveira Conson
  • Camila Campos Mantello
  • Vincent Le Guen
  • Anete Pereira de SouzaEmail author
Article

Abstract

The development of single nucleotide polymorphism (SNP) markers provides the opportunity to improve many areas of plant breeding and population genetics. Unfortunately, for species such as the rubber tree (Hevea brasiliensis), the use of next-generation sequencing for genomic SNP discovery is very difficult because of the large genome size and the abundance of repeated sequences. Access to a set of validated SNP markers is a significant advantage for rubber researchers who wish to apply SNPs in scientific research. Here, we performed genomic sequencing of H. brasiliensis and generated 10,993,648 short reads, which were assembled into 10,071 contigs (N50 = 3078) by a de novo assembly strategy. A total of 2446 contigs presented no hits in the current H. brasiliensis genome assembly and may therefore be considered novel genomic sequences of rubber tree. A total of 143 putative polymorphic positions were selected, gene annotations were available for 58.7 % of the markers, and all of the sequences could be anchored to the released H. brasiliensis genome. These SNPs were validated in eight genotypes of H. brasiliensis and 15 F1 plants from a mapping population, resulting in 30 (20.9 %) positions correctly classified. The analysis revealed key candidate genes responsible for defence mechanisms and provided markers for further genetic improvement of Hevea in breeding programmes.

Keywords

Single nucleotide polymorphism Next-generation sequencing Molecular marker Hevea brasiliensis 

Notes

Acknowledgments

The authors gratefully acknowledge the Fundação de Amparo a Pesquisa do Estado de São Paulo, the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES, Computational Biology Program and Agropolis Program) and the Conselho Nacional de Desenvolvimento Científico e Tecnológico for financial support and scholarships and a research fellowship.

Authors’ contributions

LMS performed the molecular genetic studies, helped to perform the biocomputational analysis and drafted the manuscript. GTS, CBCS and CCS performed a biocomputational analysis and drafted the manuscript. GTS, ARC, CCM and IAAA assisted in the molecular genetics studies. VLG participated in the evaluations of the molecular data and helped to draft the manuscript. APS conceived the study, participated in its design and coordination and helped to draft the manuscript. All of the authors read and approved the final manuscript.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

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Supplementary material 1 (BZ2 2292 kb)
11032_2016_534_MOESM2_ESM.xlsx (282 kb)
Supplementary material 2 (XLSX 282 kb)

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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Livia Moura de Souza
    • 1
  • Guilherme Toledo-Silva
    • 1
    • 2
  • Claudio Benicio Cardoso-Silva
    • 1
  • Carla Cristina da Silva
    • 1
  • Isabela Aparecida de Araujo Andreotti
    • 1
  • Andre Ricardo Oliveira Conson
    • 1
  • Camila Campos Mantello
    • 1
  • Vincent Le Guen
    • 3
  • Anete Pereira de Souza
    • 1
    • 4
    Email author
  1. 1.Molecular Biology and Genetic Engineering Center (CBMEG)University of Campinas (UNICAMP)CampinasBrazil
  2. 2.Department of BiochemistryFederal University of Santa CatarinaFlorianópolisBrazil
  3. 3.UMR AGAPCentre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD)MontpellierFrance
  4. 4.Department of Plant Biology, Biology InstituteUniversity of Campinas (UNICAMP)CampinasBrazil

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