Theoretical and Applied Genetics

, Volume 127, Issue 3, pp 621–631 | Cite as

Fine genetic characterization of elite maize germplasm using high-throughput SNP genotyping

  • Xun Wu
  • Yongxiang Li
  • Yunsu Shi
  • Yanchun Song
  • Tianyu Wang
  • Yubi Huang
  • Yu Li
Original Paper


To investigate the genetic structure of Chinese maize germplasm, the MaizeSNP50 BeadChip with 56,110 single nucleotide polymorphisms (SNPs) was used to genotype a collection of 367 inbred lines widely used in maize breeding of China. A total of 41,819 informative SNPs with minor allele number of more than 0.05 were used to estimate the genetic diversity, relatedness, and linkage disequilibrium (LD) decay. Totally 1,015 SNPs evenly distributed in the genome were selected randomly to evaluate the population structure of these accessions. Results showed that two main groups could be determined i.e., the introduced germplasm and the local germplasm. Further, five subgroups corresponding to different heterotic groups, that is, Reid Yellow Dent (Reid), Lancaster Sure Crop (Lancaster), P group (P), Tang Sipingtou (TSPT), and Tem-tropic I group (Tem-tropic I), were determined. The genetic diversity of within subgroups was highest in the Tem-Tropic I and lowest in the P. Most lines in this panel showed limited relatedness with each other. Comparisons of gene diversity showed that there existed some conservative genetic regions in specific subgroups across the ten chromosomes, i.e., seven in the Lancaster, seven in the Reid, six in the TSPT, five in the P, and two in the Tem-Tropical I. In addition, the results also revealed that there existed fifteen conservative regions transmitted from Huangzaosi, an important foundation parent, to its descendants. These are important for further studies since the outcomes may provide clues to understand why Huangzaosi could become a foundation parent in Chinese maize breeding. For the panel of 367 elite lines, average LD distance was 391 kb and varied among different chromosomes as well as in different genomic regions of one chromosome. This analysis uncovered a high natural genetic diversity in the elite maize inbred set, suggesting that the panel can be used in association study, esp. for temperate regions.


Inbred Line Association Mapping Polymorphism Information Content Maize Inbred Line Heterotic Group 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was partly supported by the Ministry of Science and Technology of China (2011CB100100, 2011DFA30450), National Natural Science Foundation (U1138304), CAAS (Innovation Program) and the Ministry of Agriculture of China (2011-G15, Baozhong Project). We are grateful to Dr. Alain Charcosset for language correcting and suggestions on data analyses. We also thank anonymous reviewers for suggestions to improve the quality of this manuscript.

Supplementary material

122_2013_2246_MOESM1_ESM.docx (33 kb)
Supplementary material 1 (DOCX 33 kb)
122_2013_2246_MOESM2_ESM.docx (268 kb)
Supplementary material 2 (DOCX 268 kb)
122_2013_2246_MOESM3_ESM.docx (73 kb)
Supplementary material 3 (DOCX 73 kb)


  1. Bernardo R (1990) Methods used in developing maize inbreds. Maydica 35:1–16Google Scholar
  2. Bradbury PJ, Zhang Z, Kroon DE, Casstevens TM, Ramdoss Y, Buckler ES (2007) TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23:2633–2635PubMedCrossRefGoogle Scholar
  3. Charcosset A, Essioux L (1994) The effect of population structure on the relationship between heterosis and heterozygosity at marker loci. Theor Appl Genet 89:336–343PubMedGoogle Scholar
  4. Civardi L, Xia YJ, Edwards KJ, Schnable PS, Nikolau BJ (1994) The relationship between genetic and physical distances in the cloned al-sh2 interval of the Zea mays L. genome. Proc Natl Acad Sci USA 91:8268–8272PubMedCrossRefGoogle Scholar
  5. Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software structure: a simulation study. Mol Ecol 14:2611–2620PubMedCrossRefGoogle Scholar
  6. Galecki AT, Wolfinger RD, Linares OA, Smith MJ, Halter JB (2004) Ordinary differential equation PK/PD models using the SAS macro NLINMIX. J Biopharm Stat 14:483–503PubMedCrossRefGoogle Scholar
  7. Ganal MW, Durstewitz G, Polley A, Be’rard A, Buckler ES, Charcosset A, Clarke JD, Graner E, Hansen M, Joets J, Paslier ML, McMullen M, Montalent P, Rose M, Schön CC, Sun Q, Walter H, Martin O, Falque M (2011) A large Maize (Zea mays L.) SNP genotyping array: development and germplasm genotyping, and genetic mapping to compare with the B73 reference genome. PLoS ONE 6(12):e28334PubMedCentralPubMedCrossRefGoogle Scholar
  8. Hamblin MT, Warburton ML, Buckler ES (2007) Empirical comparison of simple sequence repeats and single nucleotide polymorphisms in assessment of maize diversity and relatedness. PLoS ONE 2:e1367PubMedCentralPubMedCrossRefGoogle Scholar
  9. Heerwaarden J, Hufford MB, Ross-Ibarra J (2012) Historical genomics of North American maize. Proc Natl Acad Sci USA 109:12420–12425PubMedCrossRefGoogle Scholar
  10. Hill WG, Weir BS (1994) Maximum-likelihood estimation of gene location by linkage disequilibrium. Am J Hum Genet 54(4):705–714PubMedCentralPubMedGoogle Scholar
  11. Hubisz MJ, Falush D, Stephens M, Pritchard JK (2009) Inferring weak population structure with the assistance of sample group information. Mol Ecol Resour 9:1322–1332PubMedCentralPubMedCrossRefGoogle Scholar
  12. Inghelandt D, Melchinger AE, Lebreton C, Stich B (2010) Population structure and genetic diversity in a commercial maize breeding program assessed with SSR and SNP markers. Theor Appl Genet 120:1289–1299PubMedCentralPubMedCrossRefGoogle Scholar
  13. Inghelandt D, Reif JC, Dhillon BS, Flament P, Melchinger AE (2011) Extent and genome-wide distribution of linkage disequilibrium in commercial maize germplasm. Theor Appl Genet 123:11–20PubMedCrossRefGoogle Scholar
  14. Jakobsson M, Rosenberg NA (2007) CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23:1801–1806PubMedCrossRefGoogle Scholar
  15. Jung M, Ching A, Bhattramakki D, Dolan M, Tingey S, Morgante M, Rafalski A (2004) Linkage disequilibrium and sequence diversity in a 500-kbp region around the adh1 locus in elite maize germplasm. Theor Appl Genet 109:681–689PubMedCrossRefGoogle Scholar
  16. Lai J, Li R, Xu X, Jin W, Xu M, Zhao H, Xiang Z, Song W, Ying K, Zhang M, Jiao Y, Ni P, Zhang J, Li D, Guo X, Ye K, Jian M, Wang B, Zheng H, Liang H, Zhang X, Wang S, Chen S, Li J, Fu Y, Springer Nathan M, Yang H, Wang J, Dai J, Schnable Patrick S, Wang J (2010) Genome-wide patterns of genetic variation among elite maize inbred lines. Nat Genet 42:1027–1030PubMedCrossRefGoogle Scholar
  17. Li S (1997) The development and application of maize inbred line “Huangzaosi”. Beijing Agric Sci 15:19–21 (in Chinese)Google Scholar
  18. Li Y, Wang T (2010) Germplasm base of maize breeding in China and formation of foundation parents. J Maize Sci 18:1–8 (in Chinese)Google Scholar
  19. Li Y, Shi Y, Cao Y, Wang T (2005) Establishment of a core collection for maize germplasm preserved in Chinese National Genebank using geographic distribution and characterization data. Genet Resour Crop Evol 51:845–852CrossRefGoogle Scholar
  20. Liu K, Muse SV (2005) PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics 21:2128–2129PubMedCrossRefGoogle Scholar
  21. Liu Z, Wu X, Liu H, Li Y, Li Q, Wang F, Shi Y, Song Y, Song W, Zhao J, Lai J, Li Y, Wang T (2012) Genetic diversity and population structure of important Chinese maize inbred lines revealed by 40 core simple sequence repeats (SSRs). Scientia Agricultura Sinica 45:2107–2138 (in Chinese)Google Scholar
  22. Lu H, Bernardo R (2001) Molecular marker diversity among current and historical maize inbreds. Theor Appl Genet 103:613–617CrossRefGoogle Scholar
  23. Lu Y, Yan J, Guimaraes CT, Taba S, Hao Z, Gao S, Chen S, Li J, Zhang S, Vivek BS, Magorokosho C, Mugo S, Makumbi D, Parentoni SN, Shah T, Rong T, Crouch JH, Xu Y (2009) Molecular characterization of global maize breeding germplasm based on genome-wide single nucleotide polymorphisms. Theor Appl Genet 120:93–115PubMedCrossRefGoogle Scholar
  24. Lu Y, Shah T, Hao Z, Taba S, Zhang S, Gao S, Liu J, Cao M, Wang J, Prakash AB, Rong T, Xu Y (2011) Comparative SNP and haplotype analysis reveals a higher genetic diversity and rapider LD decay in tropical than temperate germplasm in maize. PLoS ONE 6:e24861PubMedCentralPubMedCrossRefGoogle Scholar
  25. Pressoir G, Berthaud J (2004) Population structure and strong divergent selection shape phenotypic diversification in maize landraces. Heredity 92:95–101PubMedCrossRefGoogle Scholar
  26. Remington DL, Thornsberry JM, Matsuoka Y, Wilson LM, Whitt SR, Doebley J, Kresovich S, Goodman MM, Buckler ES (2001) Structure of linkage disequilibrium and phenotypic associations in the maize genome. Proc Natl Acad Sci USA 98:11479–11484PubMedCrossRefGoogle Scholar
  27. Riedelsheimer C, Czedik-Eysenberg A, Grieder C, Lisec J, Technow F, Sulpice R, Altmann T, Stitt M, Willmitzer L, Melchinger AE (2012) Genomic and metabolic prediction of complex heterotic traits in hybrid maize. Nat Genet 44:217–220PubMedCrossRefGoogle Scholar
  28. Saghai-Maroof MA, Soliman KM, Jorgensen RA, Allard RW (1984) Ribosomal DNA spacer-length polymorphisms in barley: Mendelian inheritance, chromosomal location, and population dynamics. Proc Natl Acad Sci 81:8014–8018PubMedCrossRefGoogle Scholar
  29. Troyer AF (1990) A retrospective view of corn genetic resources. J Hered 81:17–24Google Scholar
  30. Troyer AF (1999) Background of US hybrid corn. Crop Sci 39:601–626CrossRefGoogle Scholar
  31. Wang Y, Wang Z, Wang Y (1997) Studies on the heterosis utilizing models of main maize germplasms in China. Scientia Agricutural Sinica 30:16–24 (in Chinese)Google Scholar
  32. Wang R, Yu Y, Zhao J, Shi Y, Song Y, Wang T, Li Y (2008) Population structure and linkage disequilibrium of a mini core set of maize inbred lines in China. Theor Appl Genet 117:1141–1153PubMedCrossRefGoogle Scholar
  33. Wang M, Yan J, Zhao J, Song W, Zhang X, Xiao Y, Zheng Y (2012) Genome-wide association study (GWAS) of resistance to head smut in maize. Plant Sci 196:125–131PubMedCrossRefGoogle Scholar
  34. Weng J, Xie C, Hao Z, Wang J, Liu C, Li M, Zhang D, Bai L, Zhang S, Li X (2011) Genome-wide association study Identifies candidate genes that affect plant height in Chinese elite maize (Zea mays L.) Inbred Lines. PLoS ONE 6:e29229PubMedCentralPubMedCrossRefGoogle Scholar
  35. Yan J, Shah T, Warburton ML, Buckler ES, McMullen MD, Crouch J (2009) Genetic characterization and linkage disequilibrium estimation of a global maize collection using SNP markers. PLoS ONE 4:e8451PubMedCentralPubMedCrossRefGoogle Scholar
  36. Yan J, Yang X, Shah T, Sánchez-Villeda H, Li J, Warburton M, Zhou Y, Crouch J, Xu Y (2010) High-throughput SNP genotyping with the GoldenGate assay in maize. Mol Breeding 25:441–451CrossRefGoogle Scholar
  37. Yang X, Gao S, Xu S, Zhang Z, Prasanna BM, Li L, Li J, Yan J (2010a) Characterization of a global germplasm collection and its potential utilization for analysis of complex quantitative traits in maize. Mol Breeding 28:511–526CrossRefGoogle Scholar
  38. Yang X, Yan J, Shah T, Warburton ML, Li Q, Li L, Gao Y, Chai Y, Fu Z, Zhou Y, Xu S, Bai G, Meng Y, Zheng Y, Li J (2010b) Genetic analysis and characterization of a new maize association mapping panel for quantitative trait loci dissection. Theor Appl Genet 121:417–431PubMedCrossRefGoogle Scholar
  39. Yu Y, Wang R, Zhao J, Shi Y, Song Y, Wang T, Li Y (2007) Genetic diversity and structure of the core collection for maize inbred lines in China. Maydica 52:181–194Google Scholar
  40. Zeng S (1990) The maize germplasm base of hybrid in China. Scientia Agricultura Sinica 23:1–9 (in Chinese)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Maize InstituteSichuan Agricultural UnversityYa’anChina
  2. 2.Institute of Crop ScienceChinese Academy of Agricultural SciencesBeijingChina
  3. 3.Nanchong Academy of Agricultural SciencesNanchongChina

Personalised recommendations