Genetic diversity and population structure of synthetic hexaploid-derived wheat (Triticum aestivum L.) accessions
A comprehensive understanding of the population structure and genetic diversity of potential germplasm is necessary for making breeding decisions and to fully interpret marker-trait associations. The purpose of this study was to examine the genetic diversity and population structure of a panel of 194 synthetic hexaploid-derived wheat (SHW; Triticum aestivum L.) accessions using 6904 polymorphic single nucleotide polymorphism (SNP) markers. Ancestry-based dissimilarity indices and marker-based genetic distances were positively correlated (r = 0.67). The variation in the primary synthetic parent in the pedigrees accounted for 4.52%, while the degree of the synthetic contribution accounted for only 1.06% of variation in the genetic distance. In addition, variation in the Aegilops tauschii Coss. (syn. Aegilops squarrosa auct. non L.) accession and T. turgidum accession used in the initial cross accounted for 3.48% and 2.75% of the variation in genetic distance, respectively. Using a model-based population structure approach, seven sub-populations were identified in the panel. Results of the model-based population structure analysis was for the most part in agreement with the distance-based clustering using unweighted pair group method with arithmetic mean (UPGMA) of the genetic distance or ancestry data and the principle component analysis of relatedness. We conclude that using a model-based approach provides a more statistically robust estimation of population structure. Results of this study, while highlighting the potential contribution of introgressed genome in the panel, provide the foundation for employing this panel in genome-wide association studies.
KeywordsSynthetic hexaploid derived wheat Genetic diversity Population structure Triticum and Aegilops tauschii
Technical assistance of Yasmina Bekkaoui for performing SNP array hybridization, bioinformatics support of Dr. Matthew Hayden at La Trobe University in Melbourne, Australia in SNP genotype calling, and the financial support of the project by the National Scientific and Engineering Council of Canada are duly acknowledged.
EG and AN design the experiment, TP provided the germplasm and pedigree data, MK and EG conducted the lab work, SK genotyped the population with SNP markers, EG analyzed the data and prepared the manuscript, EG, MK, SK, TP, and AN reviewed and edited the manuscript prior to submission.
Compliance with ethical standards
Conflict of interest
All authors declare that there is no conflict of interest.
- Bordes J, Ravel C, Jaubertie JP, Duperrier B, Gardet O, Heumez E, Pissavy AL, Charmet G, Le Gouis J, Balfourier F (2013) Genomic regions associated with the nitrogen limitation response revealed in a global wheat core collection. Theor Appl Genet 126:805–822. https://doi.org/10.1007/s00122-012-2019-z CrossRefGoogle Scholar
- Crossa J, Campos G, Perez P, Gianola D, Burgueno J, Araus JL, Makumbi D, Singh RP, Dreisigacker S, Yan J, Arief V, Banziger M, Braun H-J (2010) Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers. Genetics 186:713–724. https://doi.org/10.1534/genetics.110.118521 CrossRefGoogle Scholar
- Falconer DS, Mackay TFC (1996) Introduction to quantitative genetics, 4th edn. Addison Wesley Longman, HarlowGoogle Scholar
- Lage J, Warburton ML, Crossa J, Skovmand B, Andersen SB (2003) Assessment of genetic diversity in synthetic hexaploid wheats and their Triticum dicoccum and Aegilops tauschii parents using AFLPs and agronomic traits. Euphytica 134:305–317. https://doi.org/10.1023/B:EUPH.0000004953.85283.f4 CrossRefGoogle Scholar
- Marcussen T, Sandve SR, Heier L, Spannagl M, Pfeifer M, Jakobsen KS, Wulff BBH, Steuernagel B, Mayer KFX, Olsen O-A, Rogers J, el Dole J, Pozniak C, Eversole K, Feuillet C, Gill B, Friebe B, Lukaszewski AJ, Sourdille P et al (2014) Ancient hybridizations among the ancestral genomes of bread wheat. Science 345:1250092. https://doi.org/10.1126/science.1250092 CrossRefGoogle Scholar
- McFadden ES (1944) The artificial synthesis of Triticum spelta. Rec Genet Soc Am 13:26–27Google Scholar
- Nei M (1977) F-statistics and analysis of gene diversity in subdivided populations. Ann Hum Genet 41:225–233. https://doi.org/10.1111/j.1469-1809.1977.tb01918.x CrossRefGoogle Scholar
- Qadir A, Ilyas M, Akhtar W, Aziz E, Rasheed A, Mahmood T (2015) Study of genetic diversity in synthetic hexaploid wheats using random amplified polymorphic DNA. J Anim Plant Sci 25:1660–1666Google Scholar
- R core Team (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
- Sharma I, Tyagi BS, Singh G, Venkatesh K, Gupta OP (2015) Enhancing wheat production—a global perspective. Indian J Agric Sci 85:3–13Google Scholar
- Sukumaran S, Dreisigacker S, Lopes M, Chavez P, Reynolds MP (2015) Genome-wide association study for grain yield and related traits in an elite spring wheat population grown in temperate irrigated environments. Theor Appl Genet 128:353–363. https://doi.org/10.1007/s00122-014-2435-3 CrossRefGoogle Scholar
- Wang S, Wong D, Forrest K, Allen A, Chao S, Huang BE, Maccaferri M, Salvi S, Milner SG, Cattivelli L, Mastrangelo AM, Whan A, Stephen S, Barker G, Wieseke R, Plieske J, Lillemo M, Mather D, Appels R et al (2014) Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array. Plant Biotechnol J 12:787–796. https://doi.org/10.1111/pbi.12183 CrossRefGoogle Scholar
- Warburton ML, Crossa J, Franco J, Kazi M, Trethowan R, Rajaram S, Pfeiffer W, Zhang P, Dreisigacker S, Van Ginkel M (2006) Bringing wild relatives back into the family: recovering genetic diversity in CIMMYT improved wheat germplasm. Euphytica 149:289–301. https://doi.org/10.1007/s10681-005-9077-0 CrossRefGoogle Scholar
- Yu J, Pressoir G, Briggs WH, Vroh Bi I, Yamasaki M, Doebley JF, McMullen MD, Gaut BS, Nielsen DM, Holland JB, Kresovich S, Buckler ES (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 38:203–208. https://doi.org/10.1038/ng1702 CrossRefGoogle Scholar
- Yu M, Chen G, Zhang L, Liu Y, Liu D, Wang J, Pu Z, Zhang L, Lan X, Wei Y, Liu C, Zheng Y (2014) QTL mapping for important agronomic traits in synthetic hexaploid wheat derived from Aegiliops tauschii ssp. tauschii. J Integr Agric 13:1835–1844. https://doi.org/10.1016/S2095-3119(13)60655-3 CrossRefGoogle Scholar
- Zhang P, Dreisigacker S, Melchinger AE, Reif JC, Mujeeb Kazi A, Van Ginkel M, Hoisington D, Warburton ML (2005) Quantifying novel sequence variation and selective advantage in synthetic hexaploid wheats and their backcross-derived lines using SSR markers. Mol Breed 15:1–10. https://doi.org/10.1007/s11032-004-1167-5 CrossRefGoogle Scholar