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Molecular characterization of global maize breeding germplasm based on genome-wide single nucleotide polymorphisms

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Abstract

Characterization of genetic diversity is of great value to assist breeders in parental line selection and breeding system design. We screened 770 maize inbred lines with 1,034 single nucleotide polymorphism (SNP) markers and identified 449 high-quality markers with no germplasm-specific biasing effects. Pairwise comparisons across three distinct sets of germplasm, CIMMYT (394), China (282), and Brazil (94), showed that the elite lines from these diverse breeding pools have been developed with only limited utilization of genetic diversity existing in the center of origin. Temperate and tropical/subtropical germplasm clearly clustered into two separate groups. The temperate germplasm could be further divided into six groups consistent with known heterotic patterns. The greatest genetic divergence was observed between temperate and tropical/subtropical lines, followed by the divergence between yellow and white kernel lines, whereas the least divergence was observed between dent and flint lines. Long-term selection for hybrid performance has contributed to significant allele differentiation between heterotic groups at 20% of the SNP loci. There appeared to be substantial levels of genetic variation between different breeding pools as revealed by missing and unique alleles. Two SNPs developed from the same candidate gene were associated with the divergence between two opposite Chinese heterotic groups. Associated allele frequency change at two SNPs and their allele missing in Brazilian germplasm indicated a linkage disequilibrium block of 142 kb. These results confirm the power of SNP markers for diversity analysis and provide a feasible approach to unique allele discovery and use in maize breeding programs.

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Acknowledgments

We thank Drs. Marilyn Warburton and Rodomiro Ortiz for their critical review and suggestions which much improved the manuscript, Dr. Kevin Pixley for constructive discussion, and Eva Huerta Miranda, Carlos Martinez Flores, Martha Hernandez Rodríguez, Alberto Vergara Alva, Maria Asunción Moreno Ortega, and Jose Simon Pastrana Marias for lab and field assistance. The maize breeding program team from Embrapa (Drs. Paulo Evaristo O. Guimarães, Cleso A.P. Pacheco, and Lauro J.M. Guimarães) provided breeding materials and related information for the 94 Brazilian maize germplasm. This work at CIMMYT is funded by the Rockefeller Foundation, Bill and Melinda Gates Foundation, and European Community, and through other attributed or unrestricted funds provided by the members of the Consultative Group on International Agricultural Research (CGIAR) and national governments of USA, Japan, and UK. The Brazilian research was supported by Embrapa, FAPEMIG, The Generation Challenge Program and The McKnight Foundation—CCRP. Yanli Lu was supported by China Scholarship Council for her research at CIMMYT as a joint PhD student.

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Authors and Affiliations

  1. International Maize and Wheat Improvement Center (CIMMYT), Km 45, Carretera, Mexico-Veracruz, El Batan, Texcoco, Mexico

    Yanli Lu, Jianbing Yan, Suketoshi Taba, Zhuanfang Hao, Trushar Shah, Jonathan H. Crouch & Yunbi Xu

  2. Maize Research Institute, Sichuan Agricultural University, Ya’an, Sichuan, 625014, China

    Yanli Lu, Shibin Gao & Tingzhao Rong

  3. Embrapa Maize and Sorghum, CP 151, Sete Lagoas, MG, 35701-970, Brazil

    Claudia T. Guimarães & Sidney N. Parentoni

  4. Institute of Crop Science, Chinese Academy of Agricultural Sciences, National Key Facilities for Crop Genetic Resources and Improvement, 100081, Beijing, China

    Zhuanfang Hao & Shihuang Zhang

  5. National Maize Improvement Center of China, China Agricultural University, 100094, Beijing, China

    Shaojiang Chen & Jiansheng Li

  6. CIMMYT, 12.5 Km peg Mazowe Road, P.O. Box MP163, Mount Pleasant, Harare, Zimbabwe

    Bindiganavile S. Vivek & Cosmos Magorokosho

  7. CIMMYT, PO Box 1041, Village Market, 00621, Nairobi, Kenya

    Stephen Mugo & Dan Makumbi

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  1. Yanli Lu
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  2. Jianbing Yan
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Correspondence to Yunbi Xu.

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Communicated by T. Luebberstedt.

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Table S1

List of 770 maize inbred lines used in the study. Information provided in this supplemental table include ID, brief name, sample name, pedigree, origin, adaptation, kernel color, kernel texture, and the subsets that were used to compare allele frequencies in yellow versus white (Subset 1), dent versus flint (Subset 2) comparisons. (XLS 180 kb)

Table S2

Summary statistics for the 1034 informative SNP markers identified from the 1536 SNP chip. Information provided in this supplemental table include SNP order, SNP index, SNP name, SNP, chromosome, physical position, contig, minor allele frequency, heterozygosity, gene diversity, and polymorphic information content (PIC). Subset A represents 449 high-quality SNPs; Subsets B and C represent 499 and 279 SNP markers after excluding markers that showed allelic frequency difference larger than 10% and 5% between temperate and tropical/subtropical germplasm collections, respectively. (XLS 267 kb)

Table S3

Inbred lines with their proportional memberships in the model-based subgroups determined by STRUCTURE. Eight groups/clusters were identified. Information about membership of inbred lines corresponding to each cluster is provided. (XLS 178 kb)

Fig. S1

A successful score with obvious three clusters as shown by a single nucleotide polymorphism (SNP) marker, PZA00566.5. AA and BB indicate the homozygous clusters, AB indicates heterozygotes. A plot located outside of cluster was regarded as missing. (TIFF 1790 kb)

Fig. S2

Cluster dendrogram constructed for 770 maize inbred lines genotyped with 1034 SNP markers. Two major groups are identified as “China” and “CIMMYT and Brazil”. Six groups are identified within “China” by different colors as SPT, LRC, PA, PB, Lancaster, and BSSS. (TIFF 5065 kb)

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Lu, Y., Yan, J., Guimarães, C.T. et al. Molecular characterization of global maize breeding germplasm based on genome-wide single nucleotide polymorphisms. Theor Appl Genet 120, 93–115 (2009). https://doi.org/10.1007/s00122-009-1162-7

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