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Characterization of a global germplasm collection and its potential utilization for analysis of complex quantitative traits in maize

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Abstract

Association mapping is a powerful approach for exploring the molecular basis of phenotypic variations in plants. A maize (Zea mays L.) association mapping panel including 527 inbred lines with tropical, subtropical and temperate backgrounds, representing the global maize diversity, was genotyped using 1,536 single nucleotide polymorphisms (SNPs). In total, 926 SNPs with minor allele frequencies of ≥0.1 were used to estimate the pattern of genetic diversity and relatedness among individuals. The analysis revealed broad phenotypic diversity and complex genetic relatedness in the maize panel. Two different Bayesian approaches identified three specific subpopulations, which were then reconfirmed by principal component analysis (PCA) and tree-based analyses. Marker–trait associations were performed to assess the suitability of different models for false-positive correction by population structure (Q matrix/PCA) and familial kinship (K matrix) alone or in combination in this panel. The K, Q + K and PCA + K models could reduce the false positives, and the Q + K model performed slightly better for flowering time, ear height and ear diameter. Our findings suggest that this maize panel is suitable for association mapping in order to understand the relationship between genotypic and phenotypic variations for agriculturally complex quantitative traits using optimal statistical methods.

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References

  • Andersen JR, Lübberstedt T (2003) Functional markers in plants. Trends Plant Sci 8:554–560

    Article  PubMed  CAS  Google Scholar 

  • Andersen JR, Zein I, Wenzel G, Krützfeldt B, Eder J, Ouzunova M, Lübberstedt T (2007) High levels of linkage disequilibrium and associations with forage quality at a Phenylalanine Ammonia-Lyase locus in European maize (Zea mays L.) inbreds. Theor Appl Genet 114:307–319

    Article  PubMed  CAS  Google Scholar 

  • Belo A, Zheng P, Luck S, Shen B, Meyer DJ, Li B, Tingey S, Rafalski A (2008) Whole genome scan detects an allelic variant of fad2 associated with increased oleic acid levels in maize. Mol Genet Genomics 279:1–10

    Article  PubMed  CAS  Google Scholar 

  • Buckler ES, Stevens NM (2005) Maize Origins, Domestication, and selection. In: Motley TJ, Zerega N, Cross H (eds) Darwin’s Harvest. Columbia University Press, New York, pp 67–90

    Google Scholar 

  • Buckler ES, Holland JB, Bradbury PJ, Acharya CB, Brown PJ, Browne C, Ersoz E, Flint-Garcia S, Garcia A, Glaubitz JC, Goodman MM, Harjes C, Guill K, Kroon DE, Larsson S, Lepak NK, Li HH, Mitchell SE, Pressoir G, Peiffer JA, Rosas MO, Rocheford TR, Romay MC, Romero S, Salvo S, Villeda HS, da Silva HS, Sun Q, Tian F, Upadyayula N, Ware D, Yates H, Yu JM, Zhang ZW, Kresovich S, McMullen MD (2009) The genetic architecture of maize flowering time. Science 325:714–718

    Article  PubMed  CAS  Google Scholar 

  • Camus-Kulandaivelu L, Veyrieras JB, Madur D, Combes V, Fourmann M, Barraud S, Dubreuil P, Gouesnard B, Manicacci D, Charcosset A (2006) Maize adaptation to temperate climate: relationship between population structure and polymorphism in the Dwarf8 gene. Genetics 172:2449–2463

    Article  PubMed  CAS  Google Scholar 

  • Devlin B, Roeder K (1999) Genomic control for association studies. Biometrics 55:997–1004

    Article  PubMed  CAS  Google Scholar 

  • Dhliwayo T, Pixley K, Menkir A, Warburton M (2009) Combining ability, genetic distances, and heterosis among elite CIMMYT and IITA tropical maize inbred lines. Crop Sci 49:1201–1210

    Article  Google Scholar 

  • Ducrocq S, Giauffret C, Madur D, Combes V, Dumas F, Jouanne S, Coubriche D, Jamin P, Moreau L, Charcosset A (2009) Fine mapping and haplotype structure analysis of a major flowering time quantitative trait locus on maize chromosome 10. Genetics 183:1555–1563

    Article  PubMed  CAS  Google Scholar 

  • Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620

    Article  PubMed  CAS  Google Scholar 

  • Excoffier L, Smouse PE, Quattro JM (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131:479–491

    PubMed  CAS  Google Scholar 

  • Excoffier L, Laval G, Schneider S (2005) Arlequin ver. 3.0: an integrated software package for population genetics data analysis. Evol Bioinform Online 1:47–50

    CAS  Google Scholar 

  • Falush D, Stephens M, Pritchard JK (2003) Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164:1567–1587

    PubMed  CAS  Google Scholar 

  • Fan JB, Gunderson KL, Bibikova M, Yeakley JM, Chen J, Garcia EW, Lebruska LL, Laurent M, Shen R, Barker D (2006) Illumina universal bead arrays. Meth Enzymol 410:57–73

    Article  PubMed  CAS  Google Scholar 

  • Flint-Garcia SA, Thuillet AC, Yu JM, Pressoir G, Romero SM, Mitchell SE, Doebley J, Kresovich S, Goodman MM, Buckler ES (2005) Maize association population: a high-resolution platform for quantitative trait locus dissection. Plant J 44:1054–1064

    Article  PubMed  CAS  Google Scholar 

  • Gao H, Williamson S, Bustamante CD (2007) A Markov Chain Monte Carlo approach for joint inference of population structure and inbreeding rates from multilocus genotype data. Genetics 176:1635–1651

    Article  PubMed  Google Scholar 

  • Gore MA, Chia JM, Elshire R, Sun Q, Ersoz E, Hurwitz BL, Peiffer JA, McMullen MD, Grills GS, Ross-Ibarra J, Ware DH, Buckler ES (2009) A first-generation haplotype map of maize. Science 326:1115–1117

    Article  PubMed  CAS  Google Scholar 

  • Gupta PK, Rustgi S, Mir RR (2008) Array-based high-throughput DNA markers for crop improvement. Heredity 101:5–18

    Article  PubMed  CAS  Google Scholar 

  • 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 12:e1367

    Article  Google Scholar 

  • Hardy OJ, Vekemans X (2002) Spagedi: a versatile computer program to analyse spatial genetic structure at the individual or population levels. Mol Ecol Notes 2:618–620

    Article  Google Scholar 

  • Harjes CE, Rocheford TR, Bai L, Brutnell TP, Kandianis CB, Sowinski SG, Stapleton AE, Vallabhaneni R, Williams M, Wurtzel ET, Yan JB, Buckler ES (2008) Natural genetic variation in lycopene epsilon cyclase tapped for maize biofortification. Science 319:330–333

    Article  PubMed  CAS  Google Scholar 

  • Inghelandt DV, Melchinger AE, Lebreton CL, Stich B (2010) Population structure and genetic diversity in a commercial maize breeding program assessed with SSR and SNP markers. Theor Appl Genet 120:1289–1299

    Article  PubMed  Google Scholar 

  • 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 21:1801–1806

    Article  Google Scholar 

  • Kang HM, Zaitlen NA, Wade CM, Kirby A, Heckerman D, Daly MJ, Eskin E (2008) Efficient control of population structure in model organism association mapping. Genetics 178:1709–1723

    Article  PubMed  Google Scholar 

  • Laurie CC, Chasalow SD, LeDeaux JR, McCarroll R, Bush D, Hauge B, Lai CQ, Clark D, Rocheford TR, Dudley JW (2004) The genetic architecture of response to long-term artificial selection for oil concentration in the maize kernel. Genetics 168:2141–2155

    Article  PubMed  Google Scholar 

  • Li Q, Li L, Yang XH, Warburton ML, Bai GH, Dai JR, Li JS, Yan JB (2010a) Relationship, evolutionary fate and function of two maize orthologous genes of rice GW2 associated with kernel size and weight. BMC Plant Biol 10:143

    Article  PubMed  Google Scholar 

  • Li Q, Yang XH, Bai GH, Warburton ML, Mahuku G, Gore M, Dai JR, Li JS, Yan JB (2010b) Characterization of a putative GS3 ortholog involved in maize kernel development. Theor Appl Genet 120:753–763

    Article  PubMed  CAS  Google Scholar 

  • Liu KJ, Muse SV (2005) PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics 21:2128–2129

    Article  PubMed  CAS  Google Scholar 

  • Liu KJ, Goodman M, Muse S, Smith JS, Buckler ES, Doebley J (2003) Genetic structure and diversity among maize inbred lines as inferred from DNA microsatellites. Genetics 165:2117–2128

    PubMed  CAS  Google Scholar 

  • Long AD, Langley CH (1999) The power of association studies to detect the contribution of candidate genetic loci to variation in complex traits. Genome Res 9:720–731

    PubMed  CAS  Google Scholar 

  • Lu YL, Yan JB, Guimarǎes GT, Taba S, Hao ZF, Gao SB, Chen SJ, Li JS, Zhang SH, Vivek BS, Magorokosho C, Mugo S, Makumbi D, Parentoni SN, Shah T, Rong TZ, Crouch JH, Xu YB (2009) Molecular characterization of global maize breeding germplasm based on genome-wide single nucleotide polymorphisms. Theor Appl Genet 120:93–115

    Article  PubMed  CAS  Google Scholar 

  • Mackay TFC, Stone EA, Ayroles JF (2009) The genetics of quantitative traits: challenges and prospects. Nat Rev Genet 10:565–577

    Article  PubMed  CAS  Google Scholar 

  • McMullen MD, Kresovich S, Villeda HS, Bradbury P, Li HH, Sun Q, Flint-Garcia S, Thornsberry J, Acharya C, Bottoms C, Brown P, Browne C, Eller M, Guill K, Harjes C, Kroon D, Lepak N, Mitchell SE, Peterson B, Pressoir G, Romero S, Rosas MO, Salvo S, Yates H, Hanson M, Jones E, Smith S, Glaubitz JC, Goodman M, Ware D, Holland JB, Buckler ES (2009) Genetic properties of the maize nested association mapping population. Science 325:737–740

    Article  PubMed  CAS  Google Scholar 

  • Murray MG, Thompson WF (1980) Rapid isolation of high molecular weight plant DNA. Nucleic Acids Res 8:4321–4325

    Article  PubMed  CAS  Google Scholar 

  • Myles S, Peiffer J, Brown PJ, Ersoz ES, Zhang ZW, Costich DE, Buckler ED (2009) Association mapping: critical considerations shift from genotyping to experimental design. Plant Cell 21:2194–2202

    Article  PubMed  CAS  Google Scholar 

  • Nei M (1972) Genetic distance between populations. Am Nat 106:283–292

    Article  Google Scholar 

  • Ng SB, Turner EH, Robertson PD, Flygare SD, Bigham AW, Lee C, Shaffer T, Wong M, Bhattacharjee A, Eichler EE, Bamshad M, Nickerson DA, Shendure J (2009) Targeted capture and massively parallel sequencing of 12 human exomes. Nature 461:272–276

    Article  PubMed  CAS  Google Scholar 

  • Patterson N, Price AL, Reich D (2006) Population structure and eigenanalysis. PLoS Genet 2:e190

    Article  PubMed  Google Scholar 

  • Poole RW (1974) An introduction to quantitative ecology. McGraw-Hill, NY, USA, p 532

    Google Scholar 

  • Pressoir G, Brown PJ, Zhu WY, Upadyayula N, Rocheford T, Buckler ES, Kresovich S (2009) Natural variation in maize architecture is mediated by allelic differences at the PINOID co-ortholog barren inflorescence2. Plant J 58:618–628

    Article  PubMed  CAS  Google Scholar 

  • Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet 38:904–909

    Article  PubMed  CAS  Google Scholar 

  • Pritchard JK, Stephens M, Donnelly P (2000a) Inference of population structure using multilocus genotype data. Genetics 155:945–959

    PubMed  CAS  Google Scholar 

  • Pritchard JK, Stephens M, Rosenberg NA, Donnelly P (2000b) Association mapping in structured populations. Am J Hum Genet 67:170–181

    Article  PubMed  CAS  Google Scholar 

  • Purcell S, Cherny SS, Sham PC (2003) Genetic power calculator: design of linkage and association genetic mapping studies of complex traits. Bioinformatics 19:149–150

    Article  PubMed  CAS  Google Scholar 

  • Rohlf FJ (2000) NTSYS-pc. Numerical taxonomy and multivariate analysis system, Version 2.1. Exeter Software, New York

    Google Scholar 

  • Rosenberg NA (2004) DISTRUCT: a program for the graphical display of population structure. Mol Ecol Notes 4:137–138

    Article  Google Scholar 

  • Salvi S, Sponza G, Morgante M, Tomes D, Niu XM§, Fengler KA, Meeley R, Ananiev EV, Svitashev S, Bruggemann E, Li BL, Hainey CF, Radovic S, Zaina G, Rafalski JA, Tingey SV, Miao GH, Phillips RL, Tuberosa R (2007) Conserved non-coding genomic sequences associated with a flowering-time quantitative trait locus in maize. Proc Natl Acad Sci USA 104:11376–11381

    Article  PubMed  CAS  Google Scholar 

  • Schnable PS, Ware D, Fulton RS, Stein JC, Wei FS, Pasternak S, Liang CZ, Zhang JW, Fulton L, Graves TA, Minx P, Reily AD, Courtney L, Kruchowski SS, Tomlinson C, Strong C, Delehaunty K, Fronick C, Courtney B, Rock SM, Belter E, Du FY, Kim K, Abbott RM, Cotton M, Levy A, Marchetto P, Ochoa K, Jackson SM, Gillam B et al (2009) The B73 maize genome: complexity, diversity, and dynamics. Science 326:1112–1115

    Article  PubMed  CAS  Google Scholar 

  • Spencer CCA, Su Z, Donnelly P, Marchini J (2009) Designing genome-wide association studies: sample size, power, imputation, and the choice of genotyping chip. PLoS Genetics 5:e1000477

    Article  PubMed  Google Scholar 

  • Stich B, Möhring J, Piepho HP, Heckenberger M, Buckler ES, Melchinger AE (2008) Comparison of mixed-model approaches for association mapping. Genetics 178:1745–1754

    Article  PubMed  Google Scholar 

  • Szalma SJ, Buckler ES, Snook ME, McMullen MD (2005) Association analysis of candidate genes for maysin and chlorogenic acid accumulation in maize silks. Theor Appl Genet 110:1324–1333

    Article  PubMed  CAS  Google Scholar 

  • Tester M, Langridge P (2010) Breeding technologies to increase crop production in a changing world. Science 327:818–822

    Article  PubMed  CAS  Google Scholar 

  • Thornsberry JM, GoodmanM M, Doebley J, Kresovich S, Nielsen D, Buckler ES (2001) Dwarf8 polymorphisms associated with variation in flowering time. Nat Genet 28:286–289

    Article  PubMed  CAS  Google Scholar 

  • Varshney RK, Nayak SN, May GD, Jackson SA (2009) Next-generation sequencing technologies and their implications for crop genetics and breeding. Trends Biotechnol 27:522–530

    Article  PubMed  CAS  Google Scholar 

  • Vielle-Calzada JP, de la Vega OM, Hernández-Guzmán G, Ibarra-Laclette E, Alvarez-Mejía C, Vega-Arreguín JC, Jiménez-Moraila B, Fernández-Cortés A, Corona-Armenta G, Herrera-Estrella L, Herrera-Estrella A (2009) The palomero genome suggests metal effects on domestication. Science 326:1078

    Article  PubMed  CAS  Google Scholar 

  • Vigouroux Y, Glaubitz JC, Matsuoka Y, Goodman MM, Sánchez GJ, Doebley J (2008) Population structure and genetic diversity of new world maize races assessed by dna microsatellites. Am J Bot 95:1240–1253

    Article  PubMed  Google Scholar 

  • Visscher PM (2008) Sizing up human height variation. Nat Genet 40:489–490

    Article  PubMed  CAS  Google Scholar 

  • Wang RH, Yu YT, Zhao JR, Shi YS, Song YC, Wang TY, Li Y (2008) Population structure and linkage disequilibrium of a mini core set of maize inbred lines in China. Theor Appl Genet 117:1141–1153

    Article  PubMed  CAS  Google Scholar 

  • Wilson LM, Wllitt SR, lbáñes AM, Rocheford TR, Goodman MM, Buckler ES (2004) Dissection of maize kernel composition and starch production by candidate associations. Plant Cell 16:2719–2733

    Article  PubMed  CAS  Google Scholar 

  • Xie CX, Warburton M, Li MS, Li XH, Xiao MJ, Hao ZF, Zhao Q, Zhang SH (2008) An analysis of population structure and linkage disequilibrium using multilocus data in 187 maize inbred lines. Mol Breed 21:407–418

    Article  Google Scholar 

  • Yan JB, 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:e8451

    Article  PubMed  Google Scholar 

  • Yan JB, Kandianis CB, Harjes CE, Bai L, Kim EH, Yang XH, Skinner D, Fu ZY, Mitchell S, Li Q, Fernandez MGS, Zaharieva M, Babu R, Fu Y, Palacios N, Li JS, DellaPenna D, Brutnell BucklerES, Warburton ML, Rocheford T (2010a) Rare genetic variation at Zea mays crtRB1 increases β-carotene in maize grain. Nat Genet 42:322–327

    Article  PubMed  CAS  Google Scholar 

  • Yan JB, Warburton M, Crouch J (2010b) Association mapping for enhancing maize genetic improvement. Crop Sci (in press)

  • Yan JB, Yang XH, Hector S, Sánchez H, Li JS, Warburton M, Zhou Y, Crouch JH, Xu YB (2010c) High-throughput SNP genotyping with the GoldenGate assay in maize. Mol Breed 25:441–451

    Article  CAS  Google Scholar 

  • Yang XH, Yan JB, Shah T, Warburton ML, Li Q, Li L, Gao YF, Chai YC, Fu ZY, Zhou Y, Xu ST, Bai GH, Meng YJ, Zheng YP, Li JS (2010) Genetic analysis and characterization of a new maize association mapping panel for quantitative trait loci dissection. Theor Appl Genet 121:417–431

    Article  PubMed  Google Scholar 

  • Yu JM, Buckler ES (2006) Genetic association mapping and genome organization of maize. Curr Opin Biotechnol 17:1–6

    Article  Google Scholar 

  • Yu JM, Pressoir G, Briggs WH, Bi IV, Yamasaki M, Doebley JF, McMullen MD, Gaut BS, 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

    Article  PubMed  CAS  Google Scholar 

  • Yu JM, Zhang ZW, Zhu CS, Tabanao DA, Pressoir G, Tuinstra MR, Kresovich S, Todhunter RJ, Buckler ES (2009) Simulation appraisal of the adequacy of number of background markers for relationship estimation in association mapping. Plant Genome 2:63–77

    Article  CAS  Google Scholar 

  • Zhang ZW, Buckler ED, Casstevens TM, Bradbury PJ (2009) Software engineering the mixed model for genome-wide association studies on large samples. Brief Bioinform 10:664–675

    Article  PubMed  Google Scholar 

  • Zhao K, Aranzana MJ, Kim S, Lister C, Shindo C, Tang C, Toomajian C, Zheng H, Dean C, Marjoram P, Nordborg M (2007) An arabidopsis example of association mapping in structured samples. PLoS Genet 3:e4

    Article  PubMed  Google Scholar 

  • Zheng G, Freidlin B, Li ZH, Gastwirth JL (2005) Genomic control for association studies under various genetic models. Biometrics 61:186–192

    Article  PubMed  Google Scholar 

  • Zhu CS, Yu JM (2009) Nonmetric multidimensional scaling corrects for population structure in association mapping with different sample types. Genetics 182:875–888

    Article  PubMed  Google Scholar 

  • Zhu CS, Gore M, Buckler ES, Yu JM (2008) Status and prospects of association mapping in plants. Plant Genome 1:5–20

    Article  CAS  Google Scholar 

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Acknowledgments

We thank Drs. Pixley Kevin, Palacios Natalia and Taba Suketoshi from CIMMYT for providing partial materials used in this study. We gratefully acknowledge the editor Dr. Roberto Tuberosa and two anonymous reviewers for their valuable suggestions. This research was supported by the National Hi-Tech Research and Development Program of China (2006AA100103, 2006AA10Z183, 2006AA10A107), the NSFC-CIMMYT Project (30821140352), and the Genetically Modified Varieties Breeding Science and Technology Projects of China.

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  1. National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, 100193, Beijing, China

    Xiaohong Yang, Shutu Xu, Lin Li, Jiansheng Li & Jianbing Yan

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

    Shibin Gao

  3. National Key Laboratory of Crop Improvement, Huazhong Agricultural University, 430070, Wuhan, Hubei, China

    Zuxin Zhang

  4. International Maize and Wheat Improvement Center (CIMMYT), Apdo. Postal 6-641, 06600, Mexico, Edo Mex, Mexico

    Boddupalli M. Prasanna & Jianbing Yan

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  1. Xiaohong Yang
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Correspondence to Jianbing Yan.

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Xiaohong Yang and Shibin Gao contributed equally to this work.

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Yang, X., Gao, S., Xu, S. et al. Characterization of a global germplasm collection and its potential utilization for analysis of complex quantitative traits in maize. Mol Breeding 28, 511–526 (2011). https://doi.org/10.1007/s11032-010-9500-7

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