Molecular Breeding

, 37:116 | Cite as

Constructing high-density genetic maps for polyploid sugarcane (Saccharum spp.) and identifying quantitative trait loci controlling brown rust resistance

  • Xiping Yang
  • Sushma Sood
  • Neil Glynn
  • Md. Sariful Islam
  • Jack Comstock
  • Jianping WangEmail author


Sugarcane (Saccharum spp.) is an important economic crop for producing edible sugar and bioethanol. Brown rust has long been a major disease impacting sugarcane production worldwide. Resistance resource and markers linked to resistance are valuable tools for disease resistance improvement. An F1 segregating population derived from a cross between two hybrid sugarcane clones, brown rust-susceptible CP95-1039 and brown rust-resistant CP88-1762, were genotyped using genotyping by sequencing approach and also phenotyped in a replicated field trial. Single nucleotide polymorphism (SNP) and presence/absence markers were called with seven different pipelines to maximize reliable marker identification. High-density maps were constructed for both parental clones with a total map length of 4224.4 cM, and a marker density of one marker per 1.7 cM for CP95-1039, and a total map length of 4373.2 cM, and one marker per 2.0 cM for CP88-1762. Among the seven SNP callers, Tassel and Genome Analysis ToolKit performed better than other callers in single-dose SNP detection and contribution to genetic maps. Two major quantitative trait loci (QTL) controlling brown rust resistance were identified, which can explain 21 and 30% of the phenotypic variation, respectively. The genetic maps generated here will improve our understanding of sugarcane’s complex genome structure and discovery of underlying sequence variations controlling agronomic traits. The putative QTL controlling brown rust resistance can effectively be utilized in sugarcane breeding programs to expedite the selection process of brown rust resistance after validation.


Brown rust Genotyping by sequencing Genetic map Polyploidy Quantitative trait locus Saccharum spp. 



We thank Erik A. Hanson of the Agronomy Department, University of Florida, for editing this manuscript. We gratefully thank Kay McCorkle at Sugarcane Field Station, USDA, ARS, for technical support in the greenhouse and field. This research is financially supported by the Florida Sugar Cane League.

Compliance with ethical standards

Data availability

The GBS sequences are available from the NCBI sequence read archive (SRA) database with an accession number of SRP102185.

Supplementary material

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Figure S1 (DOC 714 kb)
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Figure S2 (DOC 653 kb)
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ESM 1 (XLSX 15 kb)


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Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.Agronomy Department, Genetics InstituteUniversity of FloridaGainesvilleUSA
  2. 2.Sugarcane Field Station, USDA, ARSCanal PointUSA
  3. 3.Syngenta SeedsVero BeachUSA
  4. 4.Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems BiologyFujian Agriculture and Forestry UniversityFuzhouChina

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