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Crop Breeding for Sustainable Agriculture , Genomics Interventions in

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Encyclopedia of Sustainability Science and Technology

Definition of the Subject

There has been significant improvement in production and productivity of important cereal crops globally as a consequence of the “Green Revolution ” and other initiatives [1]. However, today the stage has reached that the available traditional methods of crop improvement are not sufficient to provide enough and staple food grains to the constantly growing world population [2]. This situation is projected to be worse by the year 2050, especially in context of climate change [3]. In other words, the conventional plant breeding practices may not be able to achieve the sustainability in today’s agriculture.

It is under such circumstances that advances in plant genomics research are opening up a new era in plant breeding , where the linkage of genes to specific traits will lead to more efficient and predictable breeding programs in future. Several initiatives have been started towards use of genomics technologies in...

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Abbreviations

Association mapping:

Association mapping is a high-resolution method for mapping quantitative trait loci (QTLs) or gene(s) for traits of interest based on linkage disequilibrium (LD) and holds great promise for the dissection of complex genetic traits.

Back cross (BC):

Back cross is a cross of the F1 with either of the parental genotype and the resultant progeny is called BC1. The progeny of the cross between BC1 and the recurrent parent is called as BC2.

Gene pyramiding:

Gene pyramiding is a process of accumulating the favorable genes/alleles from different genotypes into an elite/commercial cultivar. Gene pyramiding is often performed through marker-assisted selection (MAS).

Genome-wide selection or genomic selection (GS):

Genome-wide selection or genomic selection is a concept for accelerating genetic gain especially for complex traits in elite genotypes by utilizing genomic information and estimating their breeding values in breeding strategies. GS is becoming very popular over marker-assisted selection that was focused on few individual genes or few QTLs to improve genotypes, especially when recent advances in genomic technologies have drastically reduced the cost on marker genotyping.

Genomics-assisted breeding (GAB):

Genomics-assisted breeding is a holistic approach, where genomics technologies including molecular markers, trasncriptomics, metabolomics, proteomics, bioinformatics, and phenomics are integrated with conventional breeding strategies for breeding crop plants resistant/tolerant to biotic and abiotic stresses or improved for quality and yield.

Haplotype:

Haplotype is a set of alleles of closely linked loci on a chromosome that tend to be inherited together.

Linkage disequilibrium (LD):

Linkage disequilibrium is a nonrandom association of alleles at different loci, describing the condition with non-equal (increased or reduced) frequency of the haplotypes in a population at random combination of alleles at different loci. LD is not the same as linkage, although tight linkage may generate high levels of LD between alleles.

Marker-assisted selection (MAS):

Marker-assisted selection is a process of indirect selection for improving the traits of interest by employing morphological, biochemical, or DNA-based markers. DNA-based markers/molecular markers, in the recent past, were proven to be the markers of choice for MAS.

Narrow genetic base:

Narrow genetic base does frequently exists in modern crop cultivars or breeding lines due to the continuous use of small number of elite genotypes in breeding programs. In fact, it is a serious obstacle to sustain and improve crop productivity due to rapid vulnerability of genetically uniform cultivars to emerging biotic and abiotic stresses.

Next-generation sequencing (NGS) technologies:

Next-generation sequencing (NGS) technologies include various novel sequencing technologies for example 454/FLX (Roche Inc.), ABI SOLiD (Applied Biosystems), Solexa (Illumina Inc.), etc., that have surpassed traditional Sanger sequencing in through-put and in cost-effectiveness for generating large-scale sequence data.

Polygenes:

Polygenes are a group of non-allelic genes, each having a small quantitative effect, that together produce a wide range of phenotypic variation.

Quantitative trait loci (QTLs):

Quantitative trait loci are the loci or regions in the genome that contribute towards conferring tolerance to abiotic stresses (e.g., drought, salinity) or resistance to biotic stresses (e.g., fungal, bacterial, viral diseases) or improving agronomic traits (e.g., yield, quality) which are generally controlled by polygenes and greatly depend on gene × environmental (G × E) interactions.

Sustainable agriculture:

Sustainable agriculture refers to efficient agricultural production while maintaining the environment, farm profitability, and prosperity of farming communities.

Sustainable development:

Sustainable development is defined as balancing the fulfillment of human needs with the protection of the environment so that these needs can be met not only at the present time, but also in the future.

Bibliography

Primary literature

  1. Briggs SP (1998) Plant genomics: more than food for thought. Proc Natl Acad Sci USA 95:1986–1988

    Article  CAS  Google Scholar 

  2. Barrett CB (2010) Measuring food insecurity. Science 327:825–828

    Article  CAS  Google Scholar 

  3. Godfray HCJ, Beddington JR, Crute IR, Haddad L, Lawrence D, Muir JF, Pretty J, Robinson S, Thomas SM, Toulmin C (2010) Food security: the challenge of feeding 9 billion people. Science 327:812–818

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  6. Varshney RK, Graner A, Sorrells ME (2005) Genomics-assisted breeding for crop improvement. Trends Plant Sci 10:621–630

    Article  CAS  Google Scholar 

  7. Gupta PK, Varshney RK (2000) The development and use of microsatellite markers for genetics and plant breeding with emphasis on bread wheat. Euphytica 113:163–185

    Article  CAS  Google Scholar 

  8. Varshney RK, Langridge P, Graner A (2007) Application of genomics to molecular breeding of wheat and barley. Adv Genet 58:121–155

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  10. Varshney RK (2009) Gene-based marker systems in plants: high throughput approaches for discovery and genotyping. In: Jain SM, Brar DS (eds) Molecular techniques in crop improvement, vol II. Springer, The Netherlands, pp 119–140

    Google Scholar 

  11. Varshney RK, Hoisington DA, Tyagi AK (2006) Advances in cereal genomics and applications in crop breeding. Trends Biotechnol 24:490–499

    Article  CAS  Google Scholar 

  12. Paterson AH, Bowers JE, Bruggmann R, Dubchak I, Grimwood J, Gundlach H, Haberer G, Hellsten U, Mitros T, Al P et al (2009) The Sorghum bicolor genome and the diversification of grasses. Nature 457:551–556

    Article  CAS  Google Scholar 

  13. Varshney RK, Close TJ, Singh NK, Hoisington DA, Cook DR (2009) Orphan legume crops enter the genomics era! Curr Opin Plant Biol 12:202–210

    Article  Google Scholar 

  14. Varshney RK, Thudi M, May GD, Jackson SA (2010) Legume genomics and breeding. Plant Breed Rev 33:257–304

    Article  Google Scholar 

  15. Varshney RK, Dubey A (2009) Novel genomic tools and modern genetic and breeding approaches for crop improvement. J Plant Biochem Biotechnol 18:127–138

    Article  CAS  Google Scholar 

  16. Phillips RL (2010) Mobilizing science to break yield barriers. Crop Sci 50:S99–S108

    Article  Google Scholar 

  17. Gupta PK, Kumar J, Mir RR, Kumar A (2009) Marker-assisted selection as a component of conventional plant breeding. Plant Breed Rev 33:145–217

    Google Scholar 

  18. Kole C (2007) Genome mapping and molecular breeding in plants, a series of seven volumes: cereals and millets; oilseeds; pulses, sugar and tuber crops; fruits and nuts; vegetables; technical crops; and forest trees. Springer, Berlin/Heidelberg

    Google Scholar 

  19. Flint-Garcia SA, Thornsberry JM, Buckler ES IV (2003) Structure of linkage disequilibrium in plants. Ann Rev Plant Biol 54:357–374

    Article  CAS  Google Scholar 

  20. Gupta PK, Rustgi S, Kulwal PL (2005) Linkage disequilibrium and association studies in higher plants: present status and future prospects. Plant Mol Biol 57:461–485

    Article  CAS  Google Scholar 

  21. Buckler ES IV, Ersoz E, Yu J (2007) Applications of linkage disequilibrium and association mapping in crop plants. In: Varshney RK, Tuberosa R (eds) Genomics assisted crop improvement, vol I, Genomics approaches and platforms. Springer, Dordrecht, pp 97–119

    Google Scholar 

  22. Rafalski JA (2010) Association genetics in crop improvement. Curr Opin Plant Biol 13:174–180

    Google Scholar 

  23. Collard BCY, Mackill DJ (2008) Marker-assisted selection: an approach for precision plant breeding in the twenty-first century. Phil Trans R Soc B 363:557–572

    Article  CAS  Google Scholar 

  24. Varshney RK, Hoisington DA, Nayak SN, Graner A (2009) Molecular plant breeding: methodology and achievements. In: Somers D, Langridge P, Gustafson PJ (eds) Methods in molecular biology: plant genomics. Humana, Totowa, pp 283–304

    Google Scholar 

  25. Farre G, Ramessar K, Twyman RM, Capell T, Christou P (2010) The humanitarian impact of plant biotechnology: recent breakthroughs vs bottlenecks for adoption. Curr Opin Plant Biol 13:219–225

    Article  Google Scholar 

  26. Ribaut J-M, de Vicente MC, Delannay X (2010) Molecular breeding in developing countries. Curr Opin Plant Biol 13:213–218

    Article  Google Scholar 

  27. Langridge P (2003) Molecular breeding of wheat and barley In: Tuberosa R, Phillips RL, Gale M (eds) Proceedings of the international congress “In the wake of the double helix: from the green revolution to the gene revolution,” Bologna, Italy, 27–31 May 2003, pp 279–286

    Google Scholar 

  28. Kuchel H, Fox R, Reinheimer J, Mosionek L, Willey N, Bariana H, Jefferies S (2007) The successful application of a marker-assisted wheat breeding strategy. Mol Breed 20:295–308

    Article  Google Scholar 

  29. Cakir M, McLean R, Wilson R, Barclay I, Moore C, Loughman R, Haley S, Kidwell K, Anderson J, Sorrells M, Manes Y, Hayden M, Feuille C, William M (2007) Genome level targeted breeding in wheat. In: Plant and Animal Genomes conference XV, San Diego, 13–17 Jan 2007 (http://www.intl-pag.org/15/abstracts/PAG15_W40_265.html)

  30. Neeraja CN, Maghirang-Rodriguez R, Pamplona A, Heuer S, Collard BCY, Septiningsih EM, Vergara G, Sanchez D, Xu K, Ismail AM, Mackill DJ (2007) A marker-assisted backcross approach for developing submergence-tolerant rice cultivars. Theor Appl Genet 115:767–776

    Article  CAS  Google Scholar 

  31. Xu K, Xu X, Fukao T, Canlas P, Maghirang-Rodriguez R, Heuer S, Ismail AM et al (2006) Sub1A is an ethylene-response-factor-like gene that confers submergence tolerance to rice. Nature 442:705–708

    Article  CAS  Google Scholar 

  32. Tanksley SD, Nelson JC (1996) Advanced backcross QTL analysis: a method for simultaneous discovery and transfer of valuable QTL from unadapted germplasm into elite breeding lines. Theor Appl Genet 92:191–203

    Article  Google Scholar 

  33. Hardin B (2000) Rice breeding gets marker assists. Agricultural Research Magazine 48:12, USDA-ARS, USA (www.ars.usda.gov/is/AR/archive/dec00/rice1200.pdf)

  34. Natarajkumar P, Sujatha K, Laha GS, Viraktamath BC, Reddy CS, Mishra B, Balachandran SM, Ram T, Srinivasarao K, Hari Y, Sundaram RM (2010) Identification of a dominant bacterial blight resistance gene from Oryza nivara and its molecular mapping. Rice Genetics Newsletters 25:54–56

    Google Scholar 

  35. Cao L, Zhuang J, Zhan X, Zeng K, Cheng S, Cao LY, Zhuang JY, Zhan D, Zheng KL, Cheng SH (2003) Hybrid rice resistance to bacterial blight developed by marker assisted selection. Chin J Rice Sci 17:184–186

    CAS  Google Scholar 

  36. Septiningsih EM, Pamplona AM, Sanchez DL, Neeraja CN, Vergara GV, Heuer S, Ismail AM, Mackill DJ (2009) Development of submergence-tolerant rice cultivars: the Sub1 locus and beyond. Ann Bot 103:151–160

    Article  CAS  Google Scholar 

  37. Singh S, Mackill DJ, Ismail AM (2009) Responses of SUB1 rice introgression lines to submergence in the field: Yield and grain quality. Field Crops Res 113:12–23

    Article  Google Scholar 

  38. Narayanan NN, Baisakh N, Vera Cruz CM, Gnanamanickam SS, Datta K, Datta SK (2002) Molecular breeding for the development of blast and bacterial blight resistance in rice cv. IR50. Crop Sci 42:2072–2079

    Article  CAS  Google Scholar 

  39. Toennissen GH, Toole JCO, DeVries J (2003) Advances in plant biotechnology and its adoption in developing countries. Curr Opin Plant Biol 6:191–198

    Article  Google Scholar 

  40. He Y, Li X, Zhang J, Jiang G, LiuS, Chen S, TuJ, Xu C, Zhang Q (2004) Gene pyramiding to improve hybrid rice by molecular-marker techniques. In: New directions for a diverse planet: proceedings 4th international crop science congress, Brisbane, Australia (http://www.cropscience.org.au/icsc2004/)

  41. Gopalakrishnan S, Sharma RK, Anand Rajkumar K, Joseph M, Singh VP, Singh AK, Bhat KV, Singh NK, Mohapatra T (2008) Integrating marker assisted background analysis with foreground selection for identification of superior bacterial blight resistant recombinants in Basmati rice. Plant Breed 127:131–139

    Article  CAS  Google Scholar 

  42. Basavaraj SH, Singh VK, Singh A, Singh A, Singh A, Anand D, Yadav S, Ellur RK, Singh D, Gopalakrishnan S, Nagarajan M, Mohapatra T, Prabhu KV, Singh AK (2010) Marker-assisted improvement of bacterial blight resistance in parental lines of Pusa RH10, a superfine grain aromatic rice hybrid. Mol Breed 26:293–305

    Google Scholar 

  43. Singh S, Sidhu S, Huang N, Vikal Y, Li Z, Brar DS, Dhaliwal HS, Khush GS (2001) Pyramiding three bacterial blight resistance genes (xa5, xa13 and Xa21) using marker assisted selection into indica rice cultivar PR106. Theor Appl Genet 102:1011–1015

    Article  CAS  Google Scholar 

  44. Sundaram RM, Vishnupriya MR, Laha GS, Rani NS, Rao PS, Balachandran SM, Reddy GA, Sarma NP, Sonti RV (2009) Introduction of bacterial blight resistance into Triguna a high yielding, mid-early duration rice variety. Biotechnol J 4:400–407

    Article  CAS  Google Scholar 

  45. Joseph M, Gopalakrishnan S, Sharma RK, Singh VP, Singh AK, Singh NK, Mohapatra T (2004) Combining bacterial blight resistance and Basmati quality characteristics by phenotypic and molecular-marker assisted selection in rice. Mol Breed 13:377–387

    Article  CAS  Google Scholar 

  46. Cheng S-H, Zhuang J-Y, Cao L-Y, Chen S-G, Peng Y-C, Fan Y-Y, Zhan XD, Zheng KL (2004) Molecular breeding for super rice. Chinese J Rice Sci 18:377–383

    CAS  Google Scholar 

  47. Kumar J, Mir RR, Kumar N, Kumar A, Mohan A, Prabhu KV, Balyan HS, Gupta PK (2009) Marker assisted selection for pre-harvest sprouting tolerance and leaf rust resistance in bread wheat. Plant Breed doi:10.1111/j.1439-0523.2009.01758.x

    Google Scholar 

  48. Bainotti C, Fraschina J, Salines JH, Nisi JE, Dubcovsky J, Lewis SM, Bullrich L, Vanzetti L, Cuniberti M, Campos P, Formica MB, Masiero B, Alberione E, Helguera M (2009) Registration of ‘BIOINTA2004’ wheat. J Plant Registr 3:165–169

    Article  Google Scholar 

  49. DePauw RM, Townley-Smith TF, Humphreys G, Knox RE, Clarke FR, Clarke JM (2005) Lillian hard red spring wheat. Can J Plant Sci 85:397–401

    Article  Google Scholar 

  50. Elias EM (2005) Fusarium resistant tetraploid wheat. United States Patent Application 20050273875

    Google Scholar 

  51. DePauw RM, Knox RE, Thomas JB, Smith M, Clarke JM, Clarke FR, McCaig TN, Fernandez MR (2009) Goodeve hard red spring wheat. Can J Plant Sci 89:937–944

    Article  Google Scholar 

  52. Graybosch RA, Peterson CJ, Baenziger PS, Baltensperger DD, Nelson LA, Jin Y, Kolmer J, Seabourn B, French R, Hein G, Martin TJ, Beecher B, Schwarzacher T, Heslop-Harrison P (2009) Registration of ‘Mace’ hard red winter wheat. J Plant Registr 3:51–56

    Article  Google Scholar 

  53. Randhawa HS, Mutti JS, Kidwell K, Morris CF, Chen X, Gill KS (2009) Rapid and targeted introgression of genes into popular wheat cultivars using marker-assisted background selection. PLoS ONE 4:e5752

    Article  CAS  Google Scholar 

  54. Helguera M, Khan IA, Kolmer J, Lijavetzky D, Zhong-Qi L, Dubcovsky J (2003) PCR assays for the Lr37-Yr17-Sr38 cluster of rust resistance genes and their use to develop isogenic hard red spring wheat lines. Crop Sci 43:1839–1847

    Article  CAS  Google Scholar 

  55. Barloy D, Lemoine J, Abelard P, Tanguy AM, Rivoal R, Jahier J (2007) Marker-assisted pyramiding of two cereal cyst nematode resistance genes from Aegilops variabilis in wheat. Mol Breed 20:31–40

    Article  CAS  Google Scholar 

  56. Brevis JC, Dubcovsky J (2008) Effect of the Gpc-B1 region from Triticum turgidum ssp. dicoccoides on grain yield, thousand grain weight and protein yield. In: Appels R, Eastwood R, Lagudah E, Langridge P, Mackay M, McIntyre L, Sharp P (eds) Proceedings of 11th international wheat genet symposium, Brisbane, Australia, 24–29 Aug 2008. Sydney University Press, pp 1–3 (http://hdl.handle.net/2123/3179)

  57. Yu L-X, Abate Z, Anderson JA, Bansal UK, Bariana HS, Bhavani S, Dubcovsky J, Lagudah ES, Liu S, Sambasivam PK, Singh RP, Sorrells ME (2009) Developing and optimizing markers for stem rust resistance in wheat. The Borlaug Global Rust Initiative 2009 Technical Workshop, 17–20 March 2009, Ciudad Obregon, Mexico

    Google Scholar 

  58. Nocente F, Gazza L, Pasquini M (2007) Evaluation of leaf rust resistance genes Lr1, Lr9, Lr24, Lr47 and their introgression into common wheat cultivars by marker-assisted selection. Euphytica 155:329–336

    Article  CAS  Google Scholar 

  59. Tanksley SD, Grandillo S, Fulton TM, Zamir D, Eshed Y, Petiard V, Lopez J, Beck-Bunn T (1996) Advanced backcross QTL analysis in a cross between an elite processing line of tomato and its wild relative L. pimpinellifolium. Theor Appl Genet 92:213–224

    Article  CAS  Google Scholar 

  60. Xiao J, Li J, Grandillo S, Ahn S, Yuan L, Tanksley SD, McCouch SR (1998) Identification of trait-improving quantitative trait loci alleles from a wild rice relative, Oryza rufipogon. Genetics 150:899–909

    CAS  Google Scholar 

  61. Moncada P, Martínez CP, Borrero J, Chatel M, Gauch H Jr, Guimaraes E, Tohme J, McCouch SR (2001) Quantitative trait loci for yield and yield components in an Oryza sativa × O. rufipogon BC2F2 population evaluated in an upland environment. Theor Appl Genet 102:41–52

    Article  CAS  Google Scholar 

  62. Pillen K, Zacharias A, Léon J (2003) Advanced backcross QTL analysis in barley (Hordeum vulgare L.). Theor Appl Genet 107:340–352

    Article  CAS  Google Scholar 

  63. Huang XQ, Cöster H, Ganal MW, Röder MS (2003) Advanced backcross QTL analysis for the identification of quantitative trait loci alleles from wild relatives of wheat (Triticum aestivum L.). Theor Appl Genet 106:1379–1389

    CAS  Google Scholar 

  64. Edwards M, Johnson L (1994) RFLPs for rapid recurrent selection. In: Analysis of molecular marker data. Joint plant breeding symposia series, ASA, Madison, pp 33–40

    Google Scholar 

  65. Bernardo R, Charcosset A (2006) Usefulness of gene information in marker-assisted recurrent selection: a simulation appraisal. Crop Sci 46:614–621

    Article  Google Scholar 

  66. Ragot M, Gay G, Muller J-P, Durovray J (2000) Efficient selection for the adaptation to the environment through QTL mapping and manipulation in maize. In: Ribaut J-M, Poland D (eds) Molecular approaches for the genetic improvement of cereals for stable production in water-limited environments. CIMMYT, México DF, pp 128–130

    Google Scholar 

  67. Ribaut J-M, Ragot M (2007) Marker-assisted selection to improve drought adaptation in maize: the backcross approach, perspectives, limitations, and alternative. J Exp Bot 58:351–360

    Article  CAS  Google Scholar 

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

    CAS  Google Scholar 

  69. Heffner EL, Sorrells ME, Jannink J-L (2009) Genomic selection for crop improvement. Crop Sci 49:1–12

    Article  CAS  Google Scholar 

  70. Wong CK, Bernardo R (2008) Genome-wide selection in oil palm: increasing selection gain per unit time and cost with small populations. Theor Appl Genet 116:815–824

    Article  CAS  Google Scholar 

  71. Gregory P (1989) Sustainability and CIP's research. CIP Circular 17,2: 8–11, CIP, Lima, Peru

    Google Scholar 

  72. Charlafti I (2003) Science and sustainability. EMBO Rep 4:454–456

    Article  CAS  Google Scholar 

Books and Reviews

  • Bradford KJ, Van Deynze A, Gutterson N, Parrott W, Strauss SH (2005) Regulating transgenic crops sensibly: lessons from plant breeding, biotechnology and genomics. Nat Biotech 23:439–444

    Article  CAS  Google Scholar 

  • Gupta PK, Varshney RK (2004) Cereal genomics. Kluwer, The Netherlands

    Google Scholar 

  • Hall D, Tegström C, Ingvarsson PK (2010) Using association mapping to dissect the genetic basis of complex traits in plants. Brief Funct Genom Pro 9:157–165

    Google Scholar 

  • Innes NL (2008) A plant breeding contribution to sustainable agriculture. Ann Appl Biol 126:1–18

    Article  Google Scholar 

  • Moose SP, Mumm RH (2008) Molecular plant breeding as the foundation for 21st century crop improvement. Plant Physiol 147:969–977

    Article  CAS  Google Scholar 

  • Persley GJ, Peacock J, van Montagu M (2002) Biotechnology and sustainable agriculture. ICSU series on science for sustainable development No. 6, ICSU

    Google Scholar 

  • Reganold JP, Papendick RI, Parr JF (1990) Sustainable agriculture. Sci Am 262:112–120

    Article  Google Scholar 

  • Ribaut J-M (2007) Drought adaptation in cereals. Food Products Press, Binghamton

    Google Scholar 

  • Salmeron J, Herrera-Estrella LR (2006) Plant biotechnology: fast-forward genomics for improved crop production. Curr Opin Plant Biol 9:177–179

    Article  Google Scholar 

  • Serageldin I (1999) Biotechnology and food security in the 21st century. Science 285:387–389

    Article  CAS  Google Scholar 

  • Varshney RK, Tuberosa R (2007) Genomics-assisted crop improvement, vol I, Genomics approaches and platforms. Springer, The Netherlands

    Book  Google Scholar 

  • Varshney RK, Tuberosa R (2007) Genomics-assisted crop improvement, vol II, Genomics Applications in Crops. Springer, The Netherlands

    Book  Google Scholar 

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Acknowledgments

We thank the Generation Challenge Program (www.generationcp.org), the Indian Council of Agriculture Research (ICAR) and the Department of Biotechnology (DBT) of Government of India for funding various research projects (RKV) on genomics applications in breeding.

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Kulwal, P.L., Thudi, M., Varshney, R.K. (2012). Crop Breeding for Sustainable Agriculture , Genomics Interventions in. In: Meyers, R.A. (eds) Encyclopedia of Sustainability Science and Technology. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0851-3_271

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