Molecular Breeding

, Volume 26, Issue 2, pp 339–356 | Cite as

Molecular marker-assisted breeding options for maize improvement in Asia

  • B. M. Prasanna
  • Kevin Pixley
  • Marilyn L. Warburton
  • Chuan-Xiao Xie
Article

Abstract

Maize is one of the most important food and feed crops in Asia, and is a source of income for several million farmers. Despite impressive progress made in the last few decades through conventional breeding in the “Asia-7” (China, India, Indonesia, Nepal, Philippines, Thailand, and Vietnam), average maize yields remain low and the demand is expected to increasingly exceed the production in the coming years. Molecular marker-assisted breeding is accelerating yield gains in USA and elsewhere, and offers tremendous potential for enhancing the productivity and value of Asian maize germplasm. We discuss the importance of such efforts in meeting the growing demand for maize in Asia, and provide examples of the recent use of molecular markers with respect to (i) DNA fingerprinting and genetic diversity analysis of maize germplasm (inbreds and landraces/OPVs), (ii) QTL analysis of important biotic and abiotic stresses, and (iii) marker-assisted selection (MAS) for maize improvement. We also highlight the constraints faced by research institutions wishing to adopt the available and emerging molecular technologies, and conclude that innovative models for resource-pooling and intellectual-property-respecting partnerships will be required for enhancing the level and scope of molecular marker-assisted breeding for maize improvement in Asia. Scientists must ensure that the tools of molecular marker-assisted breeding are focused on developing commercially viable cultivars, improved to ameliorate the most important constraints to maize production in Asia.

Keywords

Maize Breeding Markers Genetic diversity QTL Stress resistance Quality 

Notes

Acknowledgments

Our sincere thanks to the scientists from the public and private sector institutions in India, China, Thailand and Vietnam, for responding to the survey on maize molecular marker-assisted breeding and providing relevant information; their names are withheld to protect the confidentiality of their responses.

References

  1. Agrama HA, Moussa ME, Naser ME, Tarek MA, Ibrahim AH (1999) Mapping of QTL for downy mildew resistance in maize. Theor Appl Genet 99:519–523Google Scholar
  2. Babu R, Nair SK, Kumar A et al (2005) Two-generation marker-aided backcrossing for rapid conversion of normal maize lines to quality protein maize (QPM). Theor Appl Genet 111:888–897PubMedGoogle Scholar
  3. Babu R, Nair SK, Kumar A, Rao HS et al (2006) Mapping QTLs for popping ability in a popcorn × flint corn cross. Theor Appl Genet 112:1392–1399PubMedGoogle Scholar
  4. Bantte K, Prasanna BM (2003) Simple sequence repeat polymorphism in Quality Protein Maize (QPM) lines. Euphytica 129:337–344Google Scholar
  5. Beló A, Zheng P, Luck S et al (2008) Whole genome scan detects an allelic variant of fad2 associated with increased oleic acid levels in maize. Mol Genet Genom 279:1–10Google Scholar
  6. Bernardo R, Charcosset A (2006) Usefulness of gene information in marker-assisted recurrent selection: a simulation appraisal. Crop Sci 46:614–621Google Scholar
  7. Bernardo R, Yu J (2007) Prospects for genome-wide selection for quantitative traits in maize. Crop Sci 47:1082–1090Google Scholar
  8. Bouchez A, Gallais A (2000) Efficiency of the use of doubled-haploids in recurrent selection for combining ability. Crop Sci 40:23–29Google Scholar
  9. Chander S, Guo YQ, Yang XH et al (2008) Using molecular markers to identify two major loci controlling carotenoid contents in maize grain. Theor Appl Genet 116:223–233PubMedGoogle Scholar
  10. Chang MT, Coe EH Jr (2009) Doubled haploids. In: Kriz AL, Larkins BA (eds) Molecular genetic approaches to maize improvement. Biotechnology in agriculture and forestry, vol 63. Springer, BerlinGoogle Scholar
  11. Chen S, Song T (2003) Identification of haploids with high oil xenia effect in maize. Acta Agronomica Sinica 29:587–590Google Scholar
  12. Ching A, Caldwell KS, Jung M et al (2002) SNP frequency, haplotype structure and linkage disequilibrium in elite maize inbred lines. BMC Genet 3:19PubMedGoogle Scholar
  13. Choukan R, Hossainzadeh A, Ghannadha MR et al (2006) Use of SSR data to determine relationships and potential heterotic groupings within medium to late maturing Iranian maize inbred lines. Field Crops Res 95:212–222Google Scholar
  14. Coe E, Cone K, McMullen M, Chen SS, Davis G et al (2002) Access to the maize genome: an integrated physical and genetic map. Plant Physiol 128:9–12PubMedGoogle Scholar
  15. Cone KC, McMullen MD, Bi IV et al (2002) Genetic, physical, and informatics resources for maize. On the road to an integrated map. Plant Physiol 130:1598–1605PubMedGoogle Scholar
  16. Cuong BM, Hao PX, Regalado E et al. (2007a) Genetic diversity of maize inbred lines revealed by SSR markers and their relationship with performance of F1 hybrids. In: Pixley K, Zhang SH (eds) Proceedings of 9th Asian regional maize workshop. China Agricultural Science and Technology Press, Beijing, pp 53–57Google Scholar
  17. Cuong BM, Kha LQ, Tam NTM et al. (2007b) Genetic diversity of maize doubled haploid line nurseries in Vietnam and their potential for utilization in hybrid breeding. In: Pixley K, Zhang SH (eds) Proceedings of 9th Asian regional maize workshop. China Agricultural Science and Technology Press, Beijing, pp 67–71Google Scholar
  18. 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 49:1201–1210Google Scholar
  19. Ding J-Q, Wang X-M, Chander S, Li J-S (2008) Identification of QTL for maize resistance to common smut by using recombinant inbred lines developed from the Chinese hybrid Yuyu22. J Appl Genet 49:147–154PubMedGoogle Scholar
  20. Dixon J, Nalley L, Hellin J (2008) Asian maize trade and value chains. In: Gulati A, Dixon J (eds) Maize in Asia: changing markets and incentives. Academic Foundation, New DelhiGoogle Scholar
  21. Dubreuil P, Warburton ML, Chastanet M, Hoisington D, Charcosset A (2006) More on the introduction of temperate maize into Europe: large-scale bulk SSR genotyping and new historical elements. Maydica 51:281–291Google Scholar
  22. Eathington SR, Crosbie TM, Edwards M, Reiter RS, Bull JK (2007) Molecular markers in a commercial breeding program. Crop Sci 47:S154–S163Google Scholar
  23. Edgerton MD (2009) Increasing crop productivity to meet global needs for feed, food, and fuel. Plant Physiol 149:7–13PubMedGoogle Scholar
  24. Enoki H, Sato H, Koinuma K (2002) SSR analysis of genetic diversity among maize inbred lines adapted to cold regions of Japan. Theor Appl Genet 104:1270–1277PubMedGoogle Scholar
  25. Falcon WP (2008) The Asian maize economy in 2025. In: Gulati A, Dixon J (eds) Maize in Asia: changing markets and incentives. Academic Foundation, New DelhiGoogle Scholar
  26. Fan JB, Gunderson KL, Bibikova M et al (2006) Illumina universal bead arrays. Methods Enzymol 410:57–73PubMedGoogle Scholar
  27. Flint-Garcia SA, Thuillet AC, Yu JM et al (2005) Maize association population: a high-resolution platform for quantitative trait locus dissection. Plant J 44:1054–1064PubMedGoogle Scholar
  28. Forster BP, Thomas WTB (2005) Doubled haploids in genetics and plant breeding. Plant Breed Rev 25:57–88Google Scholar
  29. Fraley RT (2009) Molecular genetic approaches to maize improvement–an introduction. In: Kriz AL, Larkins BA (eds) Molecular genetic approaches to maize improvement. Biotechnology in agriculture and forestry, vol 63. Springer, BerlinGoogle Scholar
  30. Fu Y, Wen T-J, Ronin YI, Chen HD et al (2006) Genetic dissection of intermated Recombinant Inbred Lines using a new genetic map of maize. Genetics 174:1671–1683PubMedGoogle Scholar
  31. Gao S, Martinez C, Skinner DJ et al (2008) Development of a seed DNA-based genotyping system for marker-assisted selection in maize. Mol Breed 22:477–494Google Scholar
  32. Garg A, Prasanna BM, Sharma RC et al. (2009) Genetic analysis and mapping of QTLs for resistance to banded leaf and sheath blight (Rhizoctonia solani f.sp. sasakii) in maize. In: Proceedings of 10th Asian regional maize workshop (October 20–23, 2008, Makassar, Indonesia). CIMMYT, Mexico DF (in press)Google Scholar
  33. George MLC, Prasanna BM, Rathore RS et al (2003) Identification of QTLs conferring resistance to downy mildews of maize in Asia. Theor Appl Genet 107:544–551PubMedGoogle Scholar
  34. George ML, Regalado E, Warburton M, Vasal S, Hoisington D (2004a) Genetic diversity of maize inbred lines in relation to downy mildew. Euphytica 135:145–155Google Scholar
  35. George MLC, Regalado E, Li W et al (2004b) Molecular characterization of Asian maize inbred lines by multiple laboratories. Theor Appl Genet 109:80–91PubMedGoogle Scholar
  36. Gerpacio RV, Pingali PL (2007) Tropical and subtropical maize in Asia: production systems, constraints, and research priorities. CIMMYT, Mexico DFGoogle Scholar
  37. Gulati A, Dixon J (eds) (2008) Maize in Asia: changing markets and incentives. Academic Foundation, New DelhiGoogle Scholar
  38. Gupta PK, Rustgi S, Mir RR (2008) Array-based high-throughput DNA markers for crop improvement. Heredity 101:5–18PubMedGoogle Scholar
  39. Gupta HS, Agrawal PK, Mahajan V et al (2009) Quality protein maize for nutritional security: rapid development of short duration hybrids through molecular marker assisted breeding. Curr Sci 96:230–237Google Scholar
  40. 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:e1367PubMedGoogle Scholar
  41. Hao Z, Li X, Xie C et al (2008) Two consensus quantitative trait loci clusters controlling anthesis-silking interval, ear setting and grain yield might be related with drought tolerance in maize. Ann Appl Biol 153:73–83Google Scholar
  42. Harjes CE, Rocheford TR, Bai L et al (2008) Natural genetic variation in Lycopene epsilon cyclase tapped for maize biofortification. Science 319:330–333PubMedGoogle Scholar
  43. Heckenberger M, Bohn M, Ziegle JS et al (2002) Variation of DNA fingerprints among accessions within maize inbred lines and implications for identification of essentially derived varieties. I. Genetic and technical sources of variation in SSR data. Mol Breed 10:181–191Google Scholar
  44. Heckenberger M, van der Voort RJ, Melchinger AE, Peleman J, Bohn M (2003) Variation of DNA fingerprints among accessions within maize inbred lines and implications for identification of essentially derived varieties. II. Genetic and technical sources of variation in AFLP data and comparison to SSR data. Mol Breed 12:97–106Google Scholar
  45. Heckenberger M, Bohn M, Frisch M, Maurer HP, Melchinger AE (2005) Identification of essentially derived varieties with molecular markers: an approach based on statistical test theory and computer simulations. Theor Appl Genet 111:598–608PubMedGoogle Scholar
  46. Johnson L (2001) Marker assisted sweet corn breeding: a model for specialty crops. In: Proceedings of 56th Annu Corn Sorghum Ind Res Conf, Chicago, IL (5–7 Dec 2001). Am Seed Trade Assoc, Washington, pp 25–30Google Scholar
  47. Johnson R (2004) Marker-assisted selection. Plant Breed Rev 24:293–309Google Scholar
  48. Jones E, Sullivan H, Bhattramakki D, Smith J (2007) A comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize Zea mays L. Theor Appl Genet 115:361–371PubMedGoogle Scholar
  49. Jones E, Chu W, Ayele M et al (2009) Development of single nucleotide polymorphism (SNP) markers for use in commercial maize (Zea mays L.) germplasm. Mol Breed. doi: 10.1007/s11032-009-9281-z Google Scholar
  50. Khanduri A, Tiwari A, Prasanna BM et al. (2009) Conversion of elite maize lines in India into QPM versions using an integrated phenotypic and molecular marker-assisted selection strategy. In: Proceedings of 10th Asian regional maize workshop (October 20–23, 2008, Makassar, Indonesia). CIMMYT, Mexico DF (in press)Google Scholar
  51. Lee M, Sharopova N, Beavis WD et al (2002) Expanding the genetic map of maize with the intermated B73 × Mo17 (IBM) population. Plant Mol Biol 48:453–461PubMedGoogle Scholar
  52. Li Y, Du J, Wang T, Shi Y, Song Y, Jia J (2002) Genetic diversity and relationships among Chinese maize inbred lines revealed by SSR markers. Maydica 47:93–101Google Scholar
  53. Li Y-L, Dong Y-B, Niu S-Z (2006) QTL analysis of popping fold and the consistency of QTLs under two environments in popcorn. Acta Genetica Sinica 33:724–732PubMedGoogle Scholar
  54. Li X, Li M, Xie C, Zhang SH (2007) Application of SSR markers in maize varietal identification and protection. In: Pixley K, Zhang SH (eds) Proceedings of 9th Asian regional maize workshop. China Agricultural Science and Technology Press, Beijing, pp 45–48Google Scholar
  55. Li XH, Wang ZH, Gao SH et al (2008) Analysis of QTL for resistance to head smut (Sporisorium reiliana) in maize. Field Crops Res 106:148–155Google Scholar
  56. Liu K, Goodman MM, Muse S et al (2003) Genetic structure and diversity among maize inbred lines as inferred from DNA microsatellites. Genetics 165:2117–2128PubMedGoogle Scholar
  57. Liu X, He D, Zhang H et al (2006) QTL mapping for resistance to MDMV2B in maize. J Agric Univ Hebei 29:56–59Google Scholar
  58. Liu X, Li M, Li X, Zhang SH (2007) Genetic diversity of Chinese maize OPVs determined by SSR analysis of bulk samples. In: Pixley K, Zhang SH (eds) Proceedings of 9th Asian regional maize workshop. China Agricultural Science and Technology Press, Beijing, pp 31–35Google Scholar
  59. Liu X, Xie C, Zhao Q et al (2008a) Establishment of fluorescent SSR technique on detecting allelic frequency in maize (Zea mays L.) populations with bulk sampling strategy in China. Scientia Agricultura Sinica 41:3991–3998Google Scholar
  60. Liu ZH, Xie HL, Tian GW et al (2008b) QTL mapping of nutrient components in maize kernels under low nitrogen conditions. Plant Breed 127:279–285Google Scholar
  61. Lu GH, Tang JH, Yan J-B et al (2006) Quantitative trait loci mapping of maize yield and its components under different water treatments at flowering time. J Integr Plant Biol 48:1233–1243Google Scholar
  62. Ma XQ, Tang JH, Teng WT et al (2007) Epistatic interaction is an important genetic basis of grain yield and its components in maize. Mol Breed 20:41–51Google Scholar
  63. Manenti G, Galvan A, Pettinichchio A et al (2009) Mouse genome-wide association mapping needs linkage analysis to avoid false-positive loci. PLos Genet 5:e10003331Google Scholar
  64. Melchinger AE (1999) Genetic diversity and heterosis. In: Coors JG, Pandey S (eds) The genetics and exploitation of heterosis. ASA, CSSA, and SSSA, Madison, pp 99–118Google Scholar
  65. Mohammadi SA, Prasanna BM (2003) Analysis of genetic diversity in crop plants–salient statistical tools and considerations. Crop Sci 43:1235–1248Google Scholar
  66. Mohammadi SA, Prasanna BM, Sudan C, Singh NN (2002) A microsatellite marker based study of chromosomal regions and gene effects on yield and yield components in maize. Cell Mol Biol Letters 7:599–606Google Scholar
  67. Mohammadi SA, Prasanna BM, Sudan C, Singh NN (2008) SSR heterogenic patterns of maize parental lines and prediction of heterotic performance. Biotechnol Biotech Eq 22:541–547Google Scholar
  68. Montes JM, Melchinger AE, Reif JC (2007) Novel throughput phenotyping platforms in plant genetic studies. Trends Plant Sci 12:433–436PubMedGoogle Scholar
  69. Morris M, Dreher K, Ribaut J-M, Khairallah M (2003) Money matters (II): costs of maize inbred line conversion schemes at CIMMYT using conventional and marker-assisted selection. Mol Breed 11:235–247Google Scholar
  70. Myles S, Peiffer J, Brown PJ et al (2009) Association mapping: critical considerations shift from genotyping to experimental design. Plant Cell 21:2194–2202PubMedGoogle Scholar
  71. Nair SK, Prasanna BM, Garg A et al (2005) Identification and validation of QTLs conferring resistance to sorghum downy mildew (Peronosclerospora sorghi) and Rajasthan downy mildew (P. heteropogoni) in maize. Theor Appl Genet 110:1384–1392PubMedGoogle Scholar
  72. Pabendon MB, Mejaya MJ, Suherman O, Dahlan M, Subandi (2007) Application of SSR markers to fingerprint maize hybrids and their parental lines. In: Pixley K, Zhang SH (eds) Proceedings of 9th Asian regional maize workshop. China Agricultural Science and Technology Press, Beijing, pp 86–88Google Scholar
  73. Phillips RL (2009) Mobilizing science to break yield barriers. Background paper to the CGIAR 2009 science forum workshop “Beyond the yield curve: exerting the power of genetics, genomics and synthetic biology.” http://www.scienceforum2009.nl/Portals/11/BGWS4.pdf
  74. Phumichai C, Doungchan W, Puddhanon P et al (2008) SSR-based and grain yield-based diversity of hybrid maize in Thailand. Field Crops Res 108:157–162Google Scholar
  75. Pingali PL, Pandey S (2001) Meeting world maize needs: technological opportunities and priorities for the public sector. In: Pingali PL (ed) CIMMYT 1999/2000 world maize facts and trends. CIMMYT, Mexico DF, pp 1–24Google Scholar
  76. Powell W, Morgante M, Andre C et al (1996) The comparison of RFLP, RAPD, AFLP and SSR (microsatellite) markers for germplasm analysis. Mol Breed 2:225–238Google Scholar
  77. Prasanna BM (2009) Molecular markers for maize improvement in Asia. In: Proceedings of 10th Asian regional maize workshop (October 20–23, 2008, Makassar, Indonesia). CIMMYT, Mexico DF (in press)Google Scholar
  78. Prasanna BM, Hoisington D (2003) Molecular breeding for maize improvement: an overview. Indian J Biotech 2:85–98Google Scholar
  79. Prasanna BM, Sharma L (2005) The landraces of maize (Zea mays L.): diversity and utility. Indian J Plant Genet Resour 18:155–168Google Scholar
  80. Prasanna BM, Vasal SK, Kassahun B, Singh NN (2001) Quality protein maize. Curr Sci 81:1308–1319Google Scholar
  81. Prasanna BM, Beiki AH, Sekhar JC, Srinivas A, Ribaut J-M (2009a) Mapping QTLs for component traits influencing drought stress tolerance of maize in India. J Plant Biochem Biotech 18:151–160Google Scholar
  82. Prasanna BM, Hettiarachchi K, Mahatman K et al. (2009b) Molecular marker-assisted pyramiding of genes conferring resistance to Turcicum leaf blight and Polysora rust in maize inbred lines in India. In: Proceedings of 10th Asian regional maize workshop (October 20–23, 2008, Makassar, Indonesia). CIMMYT, Mexico DF (in press)Google Scholar
  83. Pray C (2006) The Asian Maize Biotechnology Network (AMBIONET): a model for strengthening national agricultural research systems. CIMMYT, Mexico DFGoogle Scholar
  84. Pushpavalli SNCVL, Sudan C, Mohammadi SA, Nair SK, Prasanna BM et al (2002) Analysis of simple sequence repeat (SSR) polymorphism in Indian maize inbred lines. J Genet Breed 56:229–236Google Scholar
  85. Qiu F, Zheng Y, Zhang Z, Xu S (2007) Mapping of QTL associated with waterlogging tolerance during the seedling stage in maize. Ann Bot 99:1067–1081PubMedGoogle Scholar
  86. Ragot M, Lee M (2007) Marker-assisted selection in maize: current status, potential, limitations and perspectives from the private and public sectors In: Marker-assisted selection—current status and future perspectives in crops, livestock, forestry and fish. FAO, Rome, pp 117–150Google Scholar
  87. Reif JC, Xia XC, Melchinger AE et al (2004) Genetic diversity determined within and among CIMMYT maize populations of tropical, subtropical, and temperate germplasm by SSR markers. Crop Sci 44:326–334CrossRefGoogle Scholar
  88. Ribaut J-M, Ragot M (2006) Marker-assisted selection to improve drought adaptation in maize: the backcross approach, perspectives, limitations and opportunities. J Exp Bot 58:351–360PubMedGoogle Scholar
  89. Sabry A, Jeffers D, Vasal SK, Frederiksen R, Magill C (2006) A region of maize chromosome 2 affects response to downy mildew pathogens. Theor Appl Genet 113:321–330PubMedGoogle Scholar
  90. Sales EK, Magulama EE, Butardo NG et al (2004) Diversity analysis of maize inbred lines using SSR markers. Phil J Crop Sci 29:66–71Google Scholar
  91. Schnable PS, Ware D, Fulton RS et al (2009) The B73 genome: complexity, diversity, and dynamics. Science 326:1112–1115PubMedGoogle Scholar
  92. Sharma L, Prasanna BM, Singh NK et al. (2009) ‘Sikkim Primitives’ reveal significant phenotypic and molecular distinctness from other maize landraces in India. In: Proceedings of 10th Asian regional maize workshop (October 20–23, 2008, Makassar, Indonesia). CIMMYT, Mexico DF (in press)Google Scholar
  93. Singh P, Rao HS, Dubey L, Naik P, Prasanna BM (2009) Graphical genotyping of genomic resources (QTL-NILs and RILs) and transcriptome profiling of maize genotypes in response to sorghum downy mildew (Peronosclerospora sorghi) in India. In: Proceedings of 10th Asian regional maize workshop (October 20–23, 2008, Makassar, Indonesia). CIMMYT, Mexico DF (in press)Google Scholar
  94. Smith JSC, Hussain T, Jones ES et al (2008) Use of doubled haploids in maize breeding: implications for intellectual property protection and genetic diversity in hybrid crops. Mol Breed 22:51–59Google Scholar
  95. Song X-F, Song T-M, Dai J-R, Rocheford T, Li J-S (2004) QTL mapping of kernel oil concentration with high-oil maize by SSR markers. Maydica 49:41–48Google Scholar
  96. Stuber CW, Edwards MD, Wendel JF (1987) Molecular marker facilitated investigations of quantitative trait loci in maize. II. Factors influencing yield and its component traits. Crop Sci 27:639–648CrossRefGoogle Scholar
  97. Tarter JA, Goodman MM, Holland JB (2004) Recovery of exotic alleles in semiexotic maize inbreds derived from crosses between Latin American accessions and a temperate line. Theor Appl Genet 109:609–617PubMedGoogle Scholar
  98. Tenaillon MI, Sawkins MC, Long AD et al (2001) Patterns of DNA sequence polymorphism along chromosome 1 of maize (Zea mays ssp. mays L.). Proc Natl Acad Sci USA 98:9161–9166PubMedGoogle Scholar
  99. Teng WT, Can JS, Chen YH et al (2004) Analysis of maize heterotic groups and patterns during past decade in China. Sci Agric Sin 37:1804–1811Google Scholar
  100. Thornsberry JM, Goodman MM, Doebley J et al (2001) Dwarf8 polymorphisms associate with variation in flowering time. Nat Genet 28:286–289PubMedGoogle Scholar
  101. Tie S, Xia J, Qiu F, Zheng Y (2006) Genome-wide analysis of maize cytoplasmic male sterility-S based on QTL mapping. Plant Mol Biol Reporter 24:71–80Google Scholar
  102. Tuberosa R, Salvi S, Giuliani S et al (2007) Genome-wide approaches to investigate and improve maize response to drought. Crop Sci 47:S120–S141Google Scholar
  103. Vroh Bi I, McMullen MD, Villeda HS et al (2006) Single nucleotide polymorphisms and insertion-deletions for genetic markers and anchoring the maize fingerprint contig physical map. Crop Sci 46:12–21Google Scholar
  104. Wada N, Feng C, Gulati A (2008) Introduction and overview. In: Gulati A, Dixon J (eds) Maize in Asia: changing markets and incentives. Academic Foundation, New DelhiGoogle Scholar
  105. Wang Y, Ji Y, Zhengfeng Z, Yonglian Z (2006) The comparative analysis based on maize integrated QTL map and meta-analysis of plant height QTLs. Chin Sci Bull 51:2219–2230Google Scholar
  106. Wang R, Yu Y, Zhao J et al (2008) Population structure and linkage disequilibrium of a mini core set of maize inbred lines in China. Theor Appl Genet 117:1141–1153PubMedGoogle Scholar
  107. Warburton ML, Xianchun X, Crossa J et al (2002) Genetic characterization of CIMMYT inbred maize lines and open pollinated populations using large scale fingerprinting methods. Crop Sci 42:1832–1840CrossRefGoogle Scholar
  108. Warburton M, Setimela P, Franco J et al. (2009) Cost-effective fingerprinting methodology to distinguish maize open pollinated varieties. Crop Sci (in press)Google Scholar
  109. Wisser RJ, Balint-Kurti PJ, Nelson RJ (2006) The genetic architecture of disease resistance in maize: a synthesis of published studies. Phytopathology 96:120–129PubMedGoogle Scholar
  110. Wu Y, Li X, Zhang Z et al (2008) Genomic DNA sequence, gene structure, conserved domains, and natural alleles of Gln1-3 gene in maize. Acta Agronomica Sinica 34:1114–1120Google Scholar
  111. Wu Y, Li X, Hao Z, Xie C (2009) Genomic DNA sequence, gene structure, conserved domains, and natural alleles of Gln1-4 gene in maize. Acta Agronomica Sinica 35:983–991Google Scholar
  112. Xiao YN, Li XH, George ML et al (2005) Quantitative trait loci analysis of drought tolerance and yield in maize in China. Plant Mol Biol Reporter 23:155–165Google Scholar
  113. Xie C, Zhang S, Li M et al (2007) Inferring genome ancestry and estimating molecular relatedness among 187 Chinese maize inbred lines. J Genet Genom 34:738–748Google Scholar
  114. Xie C, Warburton M, Li M et al (2008) An analysis of population structure and linkage disequilibrium using multilocus data in 187 maize inbred lines. Mol Breed 21:407–418Google Scholar
  115. Xu Y, Crouch JH (2008) Marker-assisted selection in plant breeding: from publications to practice. Crop Sci 48:391–407Google Scholar
  116. Xu S-X, Liu J, Liu J-S (2005) The use of SSRs for predicting the hybrid yield and yield heterosis in 15 key inbred lines of Chinese maize. Hereditas 141:207–215Google Scholar
  117. Yan J, Yang X, Shah T et al (2009a) High-throughput SNP genotyping with the GoldenGate assay in maize. Mol Breed. doi: 10.1007/s11032-009-9343-2 PubMedGoogle Scholar
  118. Yan J, Kandianis CB, Harjes CE (2009b) Rare genetic variation at ZmCrtR-B1 Increases beta-carotene in maize grain. Nat Genet (accepted for publication)Google Scholar
  119. Yang X, Yan J, Shah T, Warburton M et al. (2009) Genetic analysis and characterization of a new maize association mapping panel for quantitative trait loci dissection. Theor Appl Genet (accepted for publication)Google Scholar
  120. Yu J, Pressoir G, Briggs WH et al (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 38:203–208PubMedGoogle Scholar
  121. Yu YT, Wang RH, Shi YS et al (2007) Genetic diversity and structure of the core collection for maize lines in China. Maydica 52:181–194Google Scholar
  122. Yu J, Holland JB, McMullen MD, Buckler ED (2008) Genetic design and statistical power of nested association mapping in maize. Genetics 178:539–551PubMedGoogle Scholar
  123. Yuan LX, Fu JH, Warburton M et al (2000) Comparison of genetic diversity among maize inbred lines based on RFLPs, SSRs, AFLPs and RAPDs. Acta Agronomica Sinica 27:725–733Google Scholar
  124. Yuan LX, Fu JH, Zhang SH et al (2001) Heterotic grouping of maize inbred lines using RFLP and SSR markers. Acta Agronomica Sinica 27:149–156Google Scholar
  125. Zhang SH, Li XH, Wang ZH et al (2003) QTL mapping for resistance to SCMV in Chinese maize germplasm. Maydica 48:307–312Google Scholar
  126. Zhang F, Wan X-Q, Pan G-T (2006) QTL mapping of Fusarium moniliforme ear rot resistance in maize. 1. Map construction with microsatellite and AFLP markers. J Appl Genet 47:9–15PubMedGoogle Scholar
  127. Zhang ZM, Zhao MJ, Ding HP et al (2007) Analysis of the epistatic and QTL x environments interaction effects of plant height in maize (Zea mays L.). Int J Plant Prod 2:153–162Google Scholar
  128. Zhang S, Liu Z, Li D et al (2008) Analysis of quantitative trait loci for grain quality of maize doubled haploid population. J Agric Univ Hebei 31:1–5Google Scholar
  129. Zhao M, Zhang Z, Zhang S et al (2006a) Quantitative trait loci for resistance to Banded Leaf and Sheath Blight in maize. Crop Sci 46:1039–1045Google Scholar
  130. Zhao W, Canaran P, Jurkuta R et al (2006b) Panzea: a database and resource for molecular and functional diversity in the maize genome. Nucl Acids Res 34:D725–D757Google Scholar
  131. Zhu C, Gore M, Buckler ES, Yu J (2008) Status and prospects of association mapping in plants. Plant Genome 1:5–20Google Scholar

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© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • B. M. Prasanna
    • 1
  • Kevin Pixley
    • 2
    • 3
  • Marilyn L. Warburton
    • 4
  • Chuan-Xiao Xie
    • 5
  1. 1.Division of GeneticsIndian Agricultural Research Institute (IARI)New DelhiIndia
  2. 2.International Maize and Wheat Improvement Center (CIMMYT)TexcocoMexico
  3. 3.University of WisconsinMadisonUSA
  4. 4.USDA-ARS CHPRRUMississippi StateUSA
  5. 5.Institute of Crop ScienceChinese Academy of Agricultural Sciences (CAAS)BeijingChina

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