Plant Breeding Institute

Genome wide association mapping in quinoa

Quinoa

Quinoa (Chenopodium quinoa) is a traditional Andean crop that was domesticated around 5000-7000 years ago. The production and consumptions of quinoa have rapidly expanded in recent years, due to its broad adaptability and nutritional value. Despite its long history of domestication, modern breeding and genetic improvement programs were started only a few decades ago. Now with the availability of the genome sequence, we can use genomics to improve quinoa and spread its production even far beyond from its origin.

Quinoa germplasm possesses great genetic diversity. Adaptation and cultivation of quinoa in Northern Europe can profit from its diversity. Understanding the genetics underlying agronomically important traits is essential for fast improvement of crops. Genome-Wide Association Studies (GWAS) based on single nucleotide polymorphisms, which rely on linkage disequilibrium and historical recombination in large diverse populations is an effective way of identifying candidates genes/loci that control agronomically important traits.

Objectives:

In this study, we aim to identify candidate genes for agronomically important traits by genome-wide association study in quinoa. We will phenotype a diversity panel of quinoa obtained from different geographical locations in field trials at the Kiel University (Northern Germany), as well as in Australia, China and the USA. All the accessions on the diversity panel have been already resequenced. Using the phenotypic and the sequencing data, we will be able to identify candidate genes for relevant traits for adaptation of quinoa to different climatic conditions. These candidate genes will facilitate marker-assisted selection in modern breeding programs by accelerating the breeding progress.

Results:

We are performing field trials with a diversity panel of 334 quinoa accessions. We re-sequenced the diversity panel in collaboration with the King Abdullah University of Science and Technology to identify nucleotide polymorphism among the diversity panel. Currently, we are performing GWAS study for agronomically important traits such as; flowering time, plant height, panicle length, branching, days to maturity, seed yield, seed saponin content, thousand-kernel weight,  grain size, plant stem color, axil color. We will identify major candidate genes for those agronomically important traits. We will analyze the haplotype variation in those candidate genes to study their effects on geographical distribution and adaption of quinoa.  Moreover, we will study the selective sweeps emerged during domestication and selection of quinoa.

Research team:

Prof. Dr. Christian Jung
Dr. Nazgol Emrani
M.Sc. Dilan Sarange
M.Sc. Nathaly Maldonado
B.Sc. Edward Assare
Monika Bruisch
Brigitte Neidhardt-Olf

Scientific Partner:

  • Prof. Dr. Mark Tester (King Abdullah University of Science and Technology, KAUST).
  • Prof. Dr. Karl Schmid (University of Hohenheim)
  • Jun.-Prof. Dr. Sandra M. Schmöckel (University of Hohenheim)
  • Dr. Kevin Murphy (Washington State University)

Publications:

Sarange D., N. Emrani and C. Jung. 2019. Flowering time regulation in quinoa and related species of Amaranthaceae family. XXVII. Plant and Animal Genome Conference. January 12-16, 2019, San Diego, USA

Sarange D., N. Emrani and C. Jung. 2018. Unravelling genetic mechanisms of flowering time control in Quinoa. III. International Symposium: Genetic Variation of Flowering Time Genes and Applications for Crop Improvement. March 14-16, 2018, Kiel,Germany.

Jarvis, D.E., Y.S. Ho, D.J. Lightfoot, S.M. Schmockel, B. Li, T.J. Borm, H. Ohyanagi, K. Mineta, C.T. Michell, N. Saber, N.M. Kharbatia, R.R. Rupper, A.R. Sharp, N. Dally, B.A. Boughton, Y.H. Woo, G. Gao, E.G. Schijlen, X. Guo, A.A. Momin, S. Negrao, S. Al-Babili, C. Gehring, U. Roessner, C. Jung, K. Murphy, S.T. Arold, T. Gojobori, C.G. Linden, E.N. van Loo, E.N. Jellen, P.J. Maughan, and M. Tester, 2017: The genome of Chenopodium quinoa. Nature 542, 307-312.

Financial Support:

Funding has been provided by the KAUST`s internal competitive research program under grant No. OSR-2016-CRG5-2966.


Last revision: 28.05.2019                 Responsible for this webpage: Dilan Sarange