Skip to main content

Genomics-Based Breeding Technology

  • Chapter
  • First Online:
Genetics and Genomics of Rice

Abstract

The completed gnome sequences of rice subspecies, indica and japonica, as well as the characterization of a large number of important trait-related genes, laid a sound foundation for genomics-based breeding. Re-sequencing thousands of rice germplasm accessions by next-generation sequencing technologies provided breeders with enormous amount of sequences for genetic marker development. Additionally, high-throughput marker assays were recently made available to breeders, and subsequently large-scale genotyping became economically and timely feasible. All of these together speeded up the development and implementation of genomics-based breeding. In the foreseeable future, genomics-based breeding will potentially become a common practice in rice variety development. This chapter reviews the recent advances in high-throughput genetic marker development and assay technologies and also provides a few examples of strategies for practicing genomics-based breeding in rice.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Godfray HC, Beddington JR, Crute IR et al (2010) Food security: the challenge of feeding 9 billion people. Science 327(5967):812–818

    Article  PubMed  CAS  Google Scholar 

  2. Jiang Y, Cai Z, Xie W, Long T, Yu H, Zhang Q (2011) Rice functional genomics research: progress and implications for crop genetic improvement. Biotechnol Adv 30(5):1059–1070

    Article  PubMed  CAS  Google Scholar 

  3. Chen L, Ren J (2004) High-throughput DNA analysis by microchip electrophoresis. Comb Chem High Throughput Screen 7(1):29–43

    Article  PubMed  CAS  Google Scholar 

  4. Coburn JR, Temnykh SV, Paul EM, McCouch SR (2002) Design and application of microsatellite marker panels for semiautomated genotyping of rice (Oryza sativa L.). Crop Sci 42(6):2092

    Article  CAS  Google Scholar 

  5. Blair MW, Hedetale V, McCouch SR (2002) Fluorescent-labeled microsatellite panels useful for detecting allelic diversity in cultivated rice (Oryza sativa L.). Theor Appl Genet 105(2–3):449–457

    Article  PubMed  CAS  Google Scholar 

  6. Jain S, Jain RK, McCouch SR (2004) Genetic analysis of Indian aromatic and quality rice (Oryza sativa L.) germplasm using panels of fluorescently-labeled microsatellite markers. Theor Appl Genet 109(5):965–977

    Article  PubMed  CAS  Google Scholar 

  7. Garris AJ, Tai TH, Coburn J, Kresovich S, McCouch S (2005) Genetic structure and diversity in Oryza sativa L. Genetics 169(3):1631–1638

    Article  PubMed  CAS  Google Scholar 

  8. Pessoa-Filho M, Belo A, Alcochete AA, Rangel PH, Ferreira ME (2007) A set of multiplex panels of microsatellite markers for rapid molecular characterization of rice accessions. BMC Plant Biol 7:23

    Article  PubMed  CAS  Google Scholar 

  9. Jaccoud D, Peng K, Feinstein D, Kilian A (2001) Diversity arrays: a solid state technology for sequence information independent genotyping. Nucleic Acids Res 29(4):E25

    Article  PubMed  CAS  Google Scholar 

  10. Xie Y, McNally K, Li CY, Leung H, Zhu YY (2006) A high-throughput henomic tool: diversity array technology complementary for rice genotyping. J Integr Plant Biol 48(9):1069–1076

    Article  CAS  Google Scholar 

  11. Miller MR, Atwood TS, Eames BF et al (2007) RAD marker microarrays enable rapid mapping of zebrafish mutations. Genome Biol 8(6):R105

    Article  PubMed  CAS  Google Scholar 

  12. Miller MR, Dunham JP, Amores A, Cresko WA, Johnson EA (2007) Rapid and cost-effective polymorphism identification and genotyping using restriction site associated DNA (RAD) markers. Genome Res 17(2):240–248

    Article  PubMed  CAS  Google Scholar 

  13. Gupta PK, Rustgi S, Mir RR (2008) Array-based high-throughput DNA markers for crop improvement. Heredity 101(1):5–18

    Article  PubMed  CAS  Google Scholar 

  14. Zhu T, Salmeron J (2007) High-definition genome profiling for genetic marker discovery. Trends Plant Sci 12(5):196–202

    Article  PubMed  CAS  Google Scholar 

  15. Winzeler EA, Richards DR, Conway AR et al (1998) Direct allelic variation scanning of the yeast genome. Science 281(5380):1194–1197

    Article  PubMed  CAS  Google Scholar 

  16. Borevitz J (2006) Genotyping and mapping with high-density oligonucleotide arrays. Methods Mol Biol 323:137–145

    PubMed  CAS  Google Scholar 

  17. Borevitz JO, Hazen SP, Michael TP et al (2007) Genome-wide patterns of single-feature polymorphism in Arabidopsis thaliana. Proc Natl Acad Sci U S A 104(29):12057–12062

    Article  PubMed  CAS  Google Scholar 

  18. Borevitz JO, Liang D, Plouffe D et al (2003) Large-scale identification of single-feature polymorphisms in complex genomes. Genome Res 13(3):513–523

    Article  PubMed  CAS  Google Scholar 

  19. Hazen SP, Borevitz JO, Harmon FG et al (2005) Rapid array mapping of circadian clock and developmental mutations in Arabidopsis. Plant Physiol 138(2):990–997

    Article  PubMed  CAS  Google Scholar 

  20. Singer T, Fan Y, Chang HS, Zhu T, Hazen SP, Briggs SP (2006) A high-resolution map of Arabidopsis recombinant inbred lines by whole-genome exon array hybridization. PLoS Genet 2(9):e144

    Article  PubMed  CAS  Google Scholar 

  21. West MAL, Leeuwen H, Kozik A et al (2006) High-density haplotyping with microarray-based expression and single feature polymorphism markers in Arabidopsis. Genome Res 16(6):787–795

    Article  PubMed  CAS  Google Scholar 

  22. Kumar R, Qiu J, Joshi T, Valliyodan B, Xu D, Nguyen HT (2007) Single feature polymorphism discovery in rice. PLoS One 2(3):e284

    Article  PubMed  CAS  Google Scholar 

  23. Wang J, Yu H, Xie W et al (2010) A global analysis of QTLs for expression variations in rice shoots at the early seedling stage. Plant J 63:1063–1074

    Article  PubMed  CAS  Google Scholar 

  24. Xie W, Chen Y, Zhou G et al (2009) Single feature polymorphisms between two rice cultivars detected using a median polish method. Theor Appl Genet 119(1):151–164

    Article  PubMed  CAS  Google Scholar 

  25. Cui XP, Xu J, Asghar R et al (2005) Detecting single-feature polymorphisms using oligonucleotide arrays and robustified projection pursuit. Bioinformatics 21(20):3852–3858

    Article  PubMed  CAS  Google Scholar 

  26. Potokina E, Druka A, Luo Z, Wise R, Waugh R, Kearsey M (2008) Gene expression quantitative trait locus analysis of 16 000 barley genes reveals a complex pattern of genome-wide transcriptional regulation. Plant J 53(1):90–101

    Article  PubMed  CAS  Google Scholar 

  27. Banks TWJ, Somers MC, Daryl J (2009) Single-feature polymorphism mapping in bread wheat. Plant Genome 2(2):167

    Article  CAS  Google Scholar 

  28. Coram TE, Settles ML, Wang M, Chen X (2008) Surveying expression level polymorphism and single-feature polymorphism in near-isogenic wheat lines differing for the Yr5 stripe rust resistance locus. Theor Appl Genet 117(3):401–411

    Article  PubMed  CAS  Google Scholar 

  29. Sim SC, Robbins MD, Chilcott C, Zhu T, Francis DM (2009) Oligonucleotide array discovery of polymorphisms in cultivated tomato (Solanum lycopersicum L.) reveals patterns of SNP variation associated with breeding. BMC Genomics 10:466

    Article  PubMed  CAS  Google Scholar 

  30. Brookes AJ (1999) The essence of SNPs. Gene 234(2):177–186

    Article  PubMed  CAS  Google Scholar 

  31. Gupta PK, Roy JK, Prasad M (2001) Single nucleotide polymorphisms: a new paradigm for molecular marker technology and DNA polymorphism detection with emphasis on their use in plants. Curr Sci 80(4):524–535

    CAS  Google Scholar 

  32. Rafalski A (2002) Applications of single nucleotide polymorphisms in crop genetics. Curr Opin Plant Biol 5(2):94–100

    Article  PubMed  CAS  Google Scholar 

  33. Batley J, Barker G, O’Sullivan H, Edwards KJ, Edwards D (2003) Mining for single nucleotide polymorphisms and insertions/deletions in maize expressed sequence tag data. Plant Physiol 132(1):84–91

    Article  PubMed  CAS  Google Scholar 

  34. Clark RM, Schweikert G, Toomajian C et al (2007) Common sequence polymorphisms shaping genetic diversity in Arabidopsis thaliana. Science 317(5836):338–342

    Article  PubMed  CAS  Google Scholar 

  35. Huang X, Wei X, Sang T et al (2010) Genome-wide association studies of 14 agronomic traits in rice landraces. Nat Genet 42(11):961–967

    Article  PubMed  CAS  Google Scholar 

  36. Vignal A, Milan D, SanCristobal M, Eggen A (2002) A review on SNP and other types of molecular markers and their use in animal genetics. Genet Sel Evol 34(3):275–306

    Article  PubMed  CAS  Google Scholar 

  37. Newton CR, Graham A, Heptinstall LE et al (1989) Analysis of any point mutation in DNA. The amplification refractory mutation system (ARMS). Nucleic Acids Res 17(7):2503–2516

    Article  PubMed  CAS  Google Scholar 

  38. Neff MM, Turk E, Kalishman M (2002) Web-based primer design for single nucleotide polymorphism analysis. Trends Genet 18(12):613–615

    Article  PubMed  CAS  Google Scholar 

  39. Tung CW, Zhao K, Wright MH et al (2010) Development of a research platform for dissecting phenotype–genotype associations in rice (Oryza spp.). Rice 3(4):205–217

    Google Scholar 

  40. McCouch SR, Zhao K, Wright M et al (2010) Development of genome-wide SNP assays for rice. Breed Sci 60(5):524–535

    Article  Google Scholar 

  41. Deulvot C, Charrel H, Marty A et al (2010) Highly-multiplexed SNP genotyping for genetic mapping and germplasm diversity studies in pea. BMC Genomics 11(1):468

    Article  PubMed  CAS  Google Scholar 

  42. Kwon SJ, Truco MJ, Hu J (2011) LSGermOPA, a custom OPA of 384 EST-derived SNPs for high-throughput lettuce (Lactuca sativa L.) germplasm fingerprinting. Mol Breed 29(4):887–901

    Google Scholar 

  43. Zhao K, Wright M, Kimball J et al (2010) Genomic diversity and introgression in O. sativa reveal the impact of domestication and breeding on the rice genome. PLoS One 5(5):e10780

    Article  PubMed  CAS  Google Scholar 

  44. Yamamoto T, Nagasaki H, Yonemaru J et al (2010) Fine definition of the pedigree haplotypes of closely related rice cultivars by means of genome-wide discovery of single-nucleotide polymorphisms. BMC Genomics 11:267

    Article  PubMed  CAS  Google Scholar 

  45. Zhou F, Xie W, Yu H, Li J, Zhang Q, Inventors (2012) A rice whole genome-wide SNP array and its application. China Patent 201210055775.X, 5 Mar 2012

    Google Scholar 

  46. Bell PA, Chaturvedi S, Gelfand CA et al (2002) SNPstream UHT: ultra-high throughput SNP genotyping for pharmacogenomics and drug discovery. Biotechniques suppl 70–72, 74, 76–77

    Google Scholar 

  47. Denomme GA, Van Oene M (2005) High-throughput multiplex single-nucleotide polymorphism analysis for red cell and platelet antigen genotypes. Transfusion 45(5):660–666

    Article  PubMed  CAS  Google Scholar 

  48. Montpetit A, Phillips MS, Mongrain I, Lemieux R, St-Louis M (2006) High-throughput molecular profiling of blood donors for minor red blood cell and platelet antigens. Transfusion 46(5):841–848

    Article  PubMed  CAS  Google Scholar 

  49. Meirmans PG, Lamothe M, Perinet P, Isabel N (2007) Species-specific single nucleotide polymorphism markers for detecting hybridization and introgression in poplar. Can J Bot 85(11):1082–1091

    Article  CAS  Google Scholar 

  50. De la Vega FM, Lazaruk KD, Rhodes MD, Wenz MH (2005) Assessment of two flexible and compatible SNP genotyping platforms: TaqMan SNP genotyping assays and the SNPlex genotyping system. Mutat Res 573(1–2):111–135

    PubMed  Google Scholar 

  51. Pomeroy R, Duncan G, Sunar-Reeder B et al (2009) A low-cost, high-throughput, automated single nucleotide polymorphism assay for forensic human DNA applications. Anal Biochem 395(1):61–67

    Article  PubMed  CAS  Google Scholar 

  52. Paux E, Sourdille P, Mackay I, Feuillet C (2011) Sequence-based marker development in wheat: advances and applications to breeding. Biotechnol Adv 30(5):1071–1088

    Article  PubMed  CAS  Google Scholar 

  53. Martinez-Cruz B, Ziegle J, Sanz P et al (2011) Multiplex single-nucleotide polymorphism typing of the human Y chromosome using TaqMan probes. Investig Genet 2:13

    Article  PubMed  Google Scholar 

  54. Jiang Y, Shen H, Liu X et al (2011) Genetic variants at 1p11.2 and breast cancer risk: a two-stage study in Chinese women. PLoS One 6(6):e21563

    Article  PubMed  CAS  Google Scholar 

  55. Hopp K, Weber K, Bellissimo D, Johnson ST, Pietz B (2010) High-throughput red blood cell antigen genotyping using a nanofluidic real-time polymerase chain reaction platform. Transfusion 50(1):40–46

    Article  PubMed  CAS  Google Scholar 

  56. Zhao K, Tung CW, Eizenga GC et al (2011) Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa. Nat Commun 2:467

    Article  PubMed  CAS  Google Scholar 

  57. Ganal MW, Durstewitz G, Polley A et al (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):e28334

    Article  PubMed  CAS  Google Scholar 

  58. Mitsui J, Fukuda Y, Azuma K et al (2010) Multiplexed resequencing analysis to identify rare variants in pooled DNA with barcode indexing using next-generation sequencer. J Hum Genet 55(7):448–455

    Article  PubMed  CAS  Google Scholar 

  59. Craig DW, Pearson JV, Szelinger S et al (2008) Identification of genetic variants using bar-coded multiplexed sequencing. Nat Methods 5(10):887–893

    Article  PubMed  CAS  Google Scholar 

  60. Cronn R, Liston A, Parks M, Gernandt DS, Shen R, Mockler T (2008) Multiplex sequencing of plant chloroplast genomes using Solexa sequencing-by-synthesis technology. Nucleic Acids Res 36(19):e122

    Article  PubMed  CAS  Google Scholar 

  61. Huang X, Feng Q, Qian Q et al (2009) High-throughput genotyping by whole-genome resequencing. Genome Res 19(6):1068–1076

    Article  PubMed  CAS  Google Scholar 

  62. Huang X, Zhao Y, Wei X et al (2011) Genome-wide association study of flowering time and grain yield traits in a worldwide collection of rice germplasm. Nat Genet 44(1):32–39

    Article  PubMed  CAS  Google Scholar 

  63. Ku CS, Loy EY, Salim A, Pawitan Y, Chia KS (2010) The discovery of human genetic variations and their use as disease markers: past, present and future. J Hum Genet 55(7):403–415

    Article  PubMed  Google Scholar 

  64. Hattori Y, Nagai K, Furukawa S et al (2009) The ethylene response factors SNORKEL1 and SNORKEL2 allow rice to adapt to deep water. Nature 460(7258):1026–1030

    Article  PubMed  CAS  Google Scholar 

  65. Ammiraju JSS, Luo M, Goicoechea JL et al (2006) The Oryza bacterial artificial chromosome library resource: construction and analysis of 12 deep-coverage large-insert BAC libraries that represent the 10 genome types of the genus Oryza. Genome Res 16(1):140–147

    Article  PubMed  Google Scholar 

  66. Ammiraju JSS, Song X, Luo M et al (2010) The Oryza BAC resource: a genus-wide and genome scale tool for exploring rice genome evolution and leveraging useful genetic diversity from wild relatives. Breed Sci 60(5):536–543

    Article  Google Scholar 

  67. Wing R, Kim HR, Goicoechea J et al (2007) The Oryza Map Alignment Project (OMAP): a new resource for comparative genome studies within Oryza [computer program]. Springer, New York

    Google Scholar 

  68. Edwards D, Batley J (2010) Plant genome sequencing: applications for crop improvement. Plant Biotechnol J 8(1):2–9

    Article  PubMed  CAS  Google Scholar 

  69. Imelfort M, Duran C, Batley J, Edwards D (2009) Discovering genetic polymorphisms in next-generation sequencing data. Plant Biotechnol J 7(4):312–317

    Article  PubMed  CAS  Google Scholar 

  70. Pop M, Salzberg SL (2008) Bioinformatics challenges of new sequencing technology. Trends Genet 24(3):142–149

    Article  PubMed  CAS  Google Scholar 

  71. Laitinen RAE, Schneeberger K, Jelly NS, Ossowski S, Weigel D (2010) Identification of a spontaneous frame shift mutation in a nonreference Arabidopsis accession using whole genome sequencing. Plant Physiol 153(2):652–654

    Article  PubMed  CAS  Google Scholar 

  72. Schneeberger K, Ossowski S, Lanz C et al (2009) SHOREmap: simultaneous mapping and mutation identification by deep sequencing. Nat Methods 6(8):550–551

    Article  PubMed  CAS  Google Scholar 

  73. Abe A, Kosugi S, Yoshida K et al (2012) Genome sequencing reveals agronomically important loci in rice using MutMap. Nat Biotechnol 30(2):174–178

    Article  PubMed  CAS  Google Scholar 

  74. Xie W, Feng Q, Yu H et al (2010) Parent-independent genotyping for constructing an ultrahigh-density linkage map based on population sequencing. Proc Natl Acad Sci U S A 107:10578–10583

    Article  PubMed  CAS  Google Scholar 

  75. Yu H, Xie W, Wang J et al (2011) Gains in QTL detection using an ultra-high density SNP map based on population sequencing relative to traditional RFLP/SSR markers. PLoS One 6:e17595

    Article  PubMed  CAS  Google Scholar 

  76. Van Tassell CP, Smith TP, Matukumalli LK et al (2008) SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries. Nat Methods 5(3):247–252

    Article  PubMed  CAS  Google Scholar 

  77. Baird NA, Etter PD, Atwood TS et al (2008) Rapid SNP discovery and genetic mapping using sequenced RAD markers. PLoS One 3(10):e3376

    Article  PubMed  CAS  Google Scholar 

  78. Trebbi D, Maccaferri M, de Heer P et al (2011) High-throughput SNP discovery and genotyping in durum wheat (Triticum durum Desf.). Theor Appl Genet 123(4):555–569

    Article  PubMed  Google Scholar 

  79. Gore MA, Chia JM, Elshire RJ et al (2009) A first-generation haplotype map of maize. Science 326(5956):1115–1117

    Article  PubMed  CAS  Google Scholar 

  80. Hyten DL, Cannon SB, Song Q et al (2010) High-throughput SNP discovery through deep resequencing of a reduced representation library to anchor and orient scaffolds in the soybean whole genome sequence. BMC Genomics 11(1):38

    Article  PubMed  CAS  Google Scholar 

  81. Seeb JE, Carvalho G, Hauser L, Naish K, Roberts S, Seeb LW (2011) Single-nucleotide polymorphism (SNP) discovery and applications of SNP genotyping in nonmodel organisms. Mol Ecol Resour 11(suppl 1):1–8

    Article  PubMed  Google Scholar 

  82. Davey JL, Blaxter MW (2010) RADSeq: next-generation population genetics. Brief Funct Genomics 9(5–6):416–423

    PubMed  CAS  Google Scholar 

  83. Emrich SJ, Barbazuk WB, Li L, Schnable PS (2007) Gene discovery and annotation using LCM-454 transcriptome sequencing. Genome Res 17(1):69–73

    Article  PubMed  CAS  Google Scholar 

  84. Severin AJ, Peiffer GA, Xu WW et al (2010) An integrative approach to genomic introgression mapping. Plant Physiol 154(1):3–12

    Article  PubMed  CAS  Google Scholar 

  85. Trick M, Long Y, Meng J, Bancroft I (2009) Single nucleotide polymorphism (SNP) discovery in the polyploid Brassica napus using Solexa transcriptome sequencing. Plant Biotechnol J 7(4):334–346

    Article  PubMed  CAS  Google Scholar 

  86. Ebana K, Yonemaru J, Fukuoka S et al (2010) Genetic structure revealed by a whole-genome single-nucleotide polymorphism survey of diverse accessions of cultivated Asian rice (Oryza sativa L.). Breed Sci 60(4):390–397

    Article  Google Scholar 

  87. Masouleh AK, Waters DLE, Reinke RF, Henry RJ (2009) A high-throughput assay for rapid and simultaneous analysis of perfect markers for important quality and agronomic traits in rice using multiplexed MALDI-TOF mass spectrometry. Plant Biotechnol J 7(4):355–363

    Article  PubMed  CAS  Google Scholar 

  88. Bai SL, Zhong X, Ma L et al (2007) A simple and reliable assay for detecting specific nucleotide sequences in plants using optical thin-film biosensor chips. Plant J 49(2):354–366

    Article  PubMed  CAS  Google Scholar 

  89. Wittwer CT, Reed GH, Gundry CN, Vandersteen JG, Pryor RJ (2003) High-resolution genotyping by amplicon melting analysis using LCGreen. Clin Chem 49(6):853

    Article  PubMed  CAS  Google Scholar 

  90. Borras E, Jurado I, Hernan I et al (2011) Clinical pharmacogenomic testing of KRAS, BRAF and EGFR mutations by high resolution melting analysis and ultra-deep pyrosequencing. BMC Cancer 11:406

    Article  PubMed  CAS  Google Scholar 

  91. Chen X, Kong F, Wang Q, Li C, Zhang J, Gilbert GL (2011) Rapid detection of isoniazid, rifampin, and ofloxacin resistance in Mycobacterium tuberculosis clinical isolates using high-resolution melting analysis. J Clin Microbiol 49(10):3450–3457

    Article  PubMed  CAS  Google Scholar 

  92. Dagar V, Chow CW, Ashley DM, Algar EM (2009) Rapid detection of SMARCB1 sequence variation using high resolution melting. BMC Cancer 9:437

    Article  PubMed  CAS  Google Scholar 

  93. Krypuy M, Newnham GM, Thomas DM, Conron M, Dobrovic A (2006) High resolution melting analysis for the rapid and sensitive detection of mutations in clinical samples: KRAS codon 12 and 13 mutations in non-small cell lung cancer. BMC Cancer 6:295

    Article  PubMed  CAS  Google Scholar 

  94. Reed GH, Wittwer CT (2004) Sensitivity and specificity of single-nucleotide polymorphism scanning by high-resolution melting analysis. Clin Chem 50(10):1748–1754

    Article  PubMed  CAS  Google Scholar 

  95. Hofinger BJ, Jing HC, Hammond-Kosack KE, Kanyuka K (2009) High-resolution melting analysis of cDNA-derived PCR amplicons for rapid and cost-effective identification of novel alleles in barley. Theor Appl Genet 119(5):851–865

    Article  PubMed  CAS  Google Scholar 

  96. Lehmensiek A, Sutherland MW, McNamara RB (2008) The use of high resolution melting (HRM) to map single nucleotide polymorphism markers linked to a covered smut resistance gene in barley. Theor Appl Genet 117(5):721–728

    Article  PubMed  CAS  Google Scholar 

  97. Dong C, Vincent K, Sharp P (2009) Simultaneous mutation detection of three homoeologous genes in wheat by high resolution melting analysis and mutation surveyor. BMC Plant Biol 9:143

    Article  PubMed  CAS  Google Scholar 

  98. Li YD, Chu ZZ, Liu XG, Jing HC, Liu YG, Hao DY (2010) A cost-effective high-resolution melting approach using the EvaGreen dye for DNA polymorphism detection and genotyping in plants. J Integr Plant Biol 52(12):1036–1042

    Article  PubMed  CAS  Google Scholar 

  99. Yu R, Shan X, Wang S et al (2011) A screening method for detecting simple sequence repeat (SSR) polymorphism of Zea mays using high-resolution melting-curve analysis. Afr J Biotechnol 10(73):16443–16447

    CAS  Google Scholar 

  100. Li J, Wang X, Dong R et al (2011) Evaluation of high-resolution melting for gene mapping in rice. Plant Mol Biol Rep 29(4):979–985

    Google Scholar 

  101. Croxford AE, Rogers T, Caligari PD, Wilkinson MJ (2008) High-resolution melt analysis to identify and map sequence-tagged site anchor points onto linkage maps: a white lupin (Lupinus albus) map as an exemplar. New Phytol 180(3):594–607

    Article  PubMed  CAS  Google Scholar 

  102. Golding BGB, Hee-Jin Jeong HJJ, Jo YDJYD, Soung-Woo Park SWP, Byoung-Cheorl Kang BCK (2010) Identification of Capsicum species using SNP markers based on high resolution melting analysis. Genome 53(12):1029–1040

    Article  CAS  Google Scholar 

  103. Wu SB, Wirthensohn MG, Hunt P, Gibson JP, Sedgley M (2008) High resolution melting analysis of almond SNPs derived from ESTs. Theor Appl Genet 118(1):1–14

    Article  PubMed  CAS  Google Scholar 

  104. Collard BCY, Jahufer MZZ, Brouwer JB, Pang ECK (2005) An introduction to markers, quantitative trait loci (QTL) mapping and marker-assisted selection for crop improvement: the basic concepts. Euphytica 142:169–196

    Article  CAS  Google Scholar 

  105. Steele KA, Edwards G, Zhu J, Witcombe JR (2004) Marker-evaluated selection in rice: shifts in allele frequency among bulks selected in contrasting agricultural environments identify genomic regions of importance to rice adaptation and breeding. Theor Appl Genet 109(6):1247–1260

    Article  PubMed  CAS  Google Scholar 

  106. Hospital F (2001) Size of donor chromosome segments around introgressed loci and reduction of linkage drag in marker-assisted backcross programs. Genetics 158(3):1363–1379

    PubMed  CAS  Google Scholar 

  107. Collard BC, Mackill DJ (2008) Marker-assisted selection: an approach for precision plant breeding in the twenty-first century. Philos Trans R Soc Lond B Biol Sci 363(1491):557–572

    Article  PubMed  CAS  Google Scholar 

  108. Singh S, Sidhu J, Huang N et al (2001) Pyramiding three bacterial blight resistance genes (xa5, xa13 and Xa21) using marker-assisted selection into indica rice cultivar PR106. Theor Appl Genet 102(6):1011–1015

    Article  CAS  Google Scholar 

  109. Zhang Q (2007) Strategies for developing Green Super Rice. Proc Natl Acad Sci U S A 104(42):16402–16409

    Article  PubMed  CAS  Google Scholar 

  110. Peleman JD, van der Voort JR (2003) Breeding by design. Trends Plant Sci 8(7):330–334

    Article  PubMed  CAS  Google Scholar 

  111. Wang JK, Li HH, Zhang XC et al (2011) Molecular design breeding in crops in China. Acta Agron Sin 37(2):191–201 (In Chinese with English abstract)

    Article  CAS  Google Scholar 

  112. Wang J, Wan X, Li H, Pfeiffer WH, Crouch J, Wan J (2007) Application of identified QTL-marker associations in rice quality improvement through a design-breeding approach. Theor Appl Genet 115(1):87–100

    Article  PubMed  Google Scholar 

  113. Wang J, Chapman SC, Bonnett DG, Rebetzke GJ, Crouch J (2007) Application of population genetic theory and simulation models to efficiently pyramid multiple genes via marker-assisted selection. Crop Sci 47(2):582–590

    Article  Google Scholar 

  114. Wei X, Liu L, Xu J et al (2010) Breeding strategies for optimum heading date using genotypic information in rice. Mol Breed 25(2):287–298

    Article  CAS  Google Scholar 

  115. Qu Z, Li L, Luo J et al (2012) QTL mapping of combining ability and heterosis of agronomic traits in rice backcross recombinant inbred lines and hybrid crosses. PLoS One 7(1):e28463

    Article  PubMed  CAS  Google Scholar 

  116. Riedelsheimer C, Czedik-Eysenberg A, Grieder C et al (2012) Genomic and metabolic prediction of complex heterotic traits in hybrid maize. Nat Genet 44(2):217–220

    Article  PubMed  CAS  Google Scholar 

  117. Chen S, Lin XH, Xu CG, Zhang Q (2000) Improvement of bacterial blight resistance of ‘Minghui 63’, an elite restorer line of hybrid rice, by molecular marker-assisted selection. Crop Sci 40(1):239–244

    Article  Google Scholar 

  118. Liu SP, Li X, Wang CY, Li XH, He YQ (2003) Improvement of resistance to rice blast in Zhenshan 97 by molecular marker-aided selection. Acta Bot Sin 45(11):1346–1350

    Google Scholar 

  119. Joseph M, Gopalakrishnan S, Sharma RK et al (2004) Combining bacterial blight resistance and Basmati quality characteristics by phenotypic and molecular marker-assisted selection in rice. Mol Breed 13(4):377–387

    Article  CAS  Google Scholar 

  120. Zhang Q, Li J, Xue Y, Han B, Deng XW (2008) Rice 2020: a call for an international coordinated effort in rice functional genomics. Mol Plant 1(5):715–719

    Article  PubMed  CAS  Google Scholar 

  121. Koide Y, Kawasaki A, Telebanco-Yanoria M et al (2010) Development of pyramided lines with two resistance genes, Pish and Pib, for blast disease (Magnaporthe oryzae B. Couch) in rice (Oryza sativa L.). Plant Breed 129(6):670–675

    Article  CAS  Google Scholar 

  122. Koide Y, Kobayashi N, Xu D, Fukuta Y (2009) Resistance genes and selection DNA markers for blast disease in rice (Oryza sativa L.). Jpn Agric Res Q 43:255–280

    Article  CAS  Google Scholar 

  123. Myint KKM, Fujita D, Matsumura M, Sonoda T, Yoshimura A, Yasui H (2011) Mapping and pyramiding of two major genes for resistance to the brown planthopper (Nilaparvata lugens [Stal]) in the rice cultivar ADR52. Theor Appl Genet 124(3):495–504

    Google Scholar 

  124. Wang C, Wen G, Lin X, Liu X, Zhang D (2009) Identification and fine mapping of the new bacterial blight resistance gene, Xa31 (t), in rice. Eur J Plant Pathol 123(2):235–240

    Article  CAS  Google Scholar 

  125. Jiang G, Xu C, Tu J, Li X, He Y, Zhang Q (2004) Pyramiding of insect- and disease-resistance genes into an elite indica, cytoplasm male sterile restorer line of rice, ‘Minghui 63’. Plant Breed 123(2):112–116

    Article  CAS  Google Scholar 

  126. Zhang J, Li X, Jiang G, Xu Y, He Y (2006) Pyramiding of Xa7 and Xa21 for the improvement of disease resistance to bacterial blight in hybrid rice. Plant Breed 125(6):600–605

    Article  CAS  Google Scholar 

  127. Hu J, Li X, Wu C et al (2012) Pyramiding and evaluation of the brown planthopper resistance genes Bph14 and Bph15 in hybrid rice. Mol Breed 29(1):61–69

    Article  CAS  Google Scholar 

  128. Liu SP, Li X, Wang ZY, Li XH, He YQ (2003) Gene pyramiding to increase the blast resistance in rice. Mol Plant Breed 1(1):22–26

    CAS  Google Scholar 

  129. Zhou P, Tan Y, He Y, Xu C, Zhang Q (2003) Simultaneous improvement for four quality traits of Zhenshan 97, an elite parent of hybrid rice, by molecular marker-assisted selection. Theor Appl Genet 106(2):326–331

    PubMed  CAS  Google Scholar 

  130. Hu J, Yang CJ, Zhang QL, Gao GJ, He YQ (2011) Resistance of pyramided rice hybrids to brown planthoppers. Chinese Bull Entomol 48(5):1341–1347 (In Chinese with English abstract)

    Google Scholar 

  131. Meuwissen THE, Hayes BJ, Goddard ME (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157(4):1819–1829

    PubMed  CAS  Google Scholar 

  132. Kolbehdari D, Schaeffer LR, Robinson JA (2007) Estimation of genome-wide haplotype effects in half-sib designs. J Anim Breed Genet 124(6):356–361

    Article  PubMed  CAS  Google Scholar 

  133. Hoerl AE, Kennard RW (2000) Ridge regression: biased estimation for nonorthogonal problems. Technometrics 42(1):80–86

    Article  Google Scholar 

  134. Bennewitz J, Solberg T, Meuwissen T (2009) Genomic breeding value estimation using nonparametric additive regression models. Genet Sel Evol 41(1):20

    Article  PubMed  Google Scholar 

  135. Long N, Gianola D, Rosa GJ, Weigel KA, Avendano S (2007) Machine learning classification procedure for selecting SNPs in genomic selection: application to early mortality in broilers. J Anim Breed Genet 124(6):377–389

    Article  PubMed  CAS  Google Scholar 

  136. Jannink JL, Lorenz AJ, Iwata H (2010) Genomic selection in plant breeding: from theory to practice. Brief Funct Genomics 9(2):166–177

    Article  PubMed  CAS  Google Scholar 

  137. Habier D, Fernando RL, Dekkers JC (2007) The impact of genetic relationship information on genome-assisted breeding values. Genetics 177(4):2389–2397

    PubMed  CAS  Google Scholar 

  138. Zhong S, Dekkers JC, Fernando RL, Jannink JL (2009) Factors affecting accuracy from genomic selection in populations derived from multiple inbred lines: a Barley case study. Genetics 182(1):355–364

    Article  PubMed  CAS  Google Scholar 

  139. Ober U, Ayroles JF, Stone EA et al (2012) Using whole-genome sequence data to predict quantitative trait phenotypes in Drosophila melanogaster. PLoS Genet 8(5):e1002685

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

We thank Dr. Shunyuan Xiao for helpful comments and discussion. This research is partially supported by China 863 research program (2012AA10A304). We apologize for not being able to cite some of the related publications because of the scope.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Fasong Zhou Ph.D. .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Science+Business Media New York

About this chapter

Cite this chapter

Zhou, F., He, H., Chen, H., Yu, H., Lorieux, M., He, Y. (2013). Genomics-Based Breeding Technology. In: Zhang, Q., Wing, R. (eds) Genetics and Genomics of Rice. Plant Genetics and Genomics: Crops and Models, vol 5. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7903-1_22

Download citation

Publish with us

Policies and ethics