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Introduction to Plant Breeding

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Plant Breeding in the Omics Era

Abstract

Plant breeding provides the seeds of new high-yielding cultivars, which often include other desired traits that increase farming profitability and sustainability. Genetics made plant breeding a science-based approach for crop improvement that continues evolving due to increasing knowledge. Conventional crossbreeding methods are now used along with tools ensuing from advances in omics and genetic engineering. Genome sequences are available for many plant species, and DNA markers are being used as aids in plant breeding. Advanced inbred lines, hybrids, and other breeding materials should be included in multi-environment testing for a thorough appraisal of their performance across locations and over years. An appropriate phenotypic assessment assists the development of new cultivars.

Plant breeding is human directed selection in genetically variable populations of plants.

William F. Tracy, Univ. of Wisconsin-Madison

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References

  • Arterburn MK, Jones SS, Kidwell KK (2009) Plant breeding and genetics. In encyclopedia of life support systems. Soils, plant growth and crop production, vol 1. EOLSS Publishers, Oxford. http://www.eolss.net/sample-chapters/c10/e1-05a-08-00.pdf

    Google Scholar 

  • Arvidsson S, Pérez-Rodríguez P, Mueller-Roeber B (2011) A growth phenotyping pipeline for Arabidopsis thaliana integrating image analysis and rosette area modeling for robust quantification of genotype effects. New Phytol 191:895–907

    Article  PubMed  Google Scholar 

  • Baenziger SP, Al-Otyak SM (2007) Plant breeding in the 21st century. Afr Crop Sci Conf Proc 8:1–3

    Google Scholar 

  • Basford KE, Federer WT, DeLacy IH (2004) Mixed model formulations for multi-environment trials. Agron J 96:143–147

    Article  Google Scholar 

  • Brummer CE, Barber WT, Collier SM, Cox TS, Johnson R, Murray SC, Olsen RT, Pratt RC, Thro AM (2011) Front Ecol Environ 9:561–568

    Article  Google Scholar 

  • Burgueño J, Crossa J, J, Cornelius PL, McLaren G, Trethowan R, Krishnamachari A (2007) Modeling additive × environment and additive × additive × environment using genetic covariances of relatives of wheat genotypes. Crop Sci 47:311–320

    Google Scholar 

  • Burney JA, Davis SJ, Lobell DB (2010) Greenhouse gas mitigation by agricultural intensification. Proc Natl Acad Sci U S A 107:12052–12057

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Cabrera-Bosquet L, Crossa J, von Zitzewitz J, Serret MD, Araus JL (2012) High-throughput phenotyping and genomic selection: the frontiers of crop breeding converge. J Integr Plant Biol 54:312–320

    Article  PubMed  Google Scholar 

  • Cobb NJ, DeClerck G, Greenberg A, Clark R, McCouch S (2013) Next-generation phenotyping: requirements and strategies for enhancing our understanding of genotype–phenotype relationships and its relevance to crop improvement. Theor Appl Genet 126:867–887

    Article  PubMed Central  PubMed  Google Scholar 

  • Cowling (2013) Sustainable plant breeding. Plant Breed 132:1–9

    Article  Google Scholar 

  • Crossa J, Franco J (2004) Statistical methods for classifying genotypes. Euphytica 137:19–37

    Article  CAS  Google Scholar 

  • Crossa J, Burgueño J, Cornelius PL, McLaren G, Trethowan R, Krishnamachari A (2006) Modeling genotype × environment interaction using additive genetic covariances of relatives for predicting breeding values of wheat genotypes. Crop Sci 46:1722–1733

    Article  Google Scholar 

  • Crossa J, Burgueño J, Dreisigacker S, Vargas M, Herrera S, Lillemo M, Singh RP, Trethowan R, Franco J, Warburton M, Reynolds M, Crouch JH, Ortiz R (2007) Association analysis of historical bread wheat germplasm using additive genetic covariance of relatives and population structure. Genetics 177:1889–1913

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Darwin C (1859) On the origin of species by means of natural selection, or the preservation of favoured races in the struggle for life. John Murray, London

    Book  Google Scholar 

  • Darwin C, Wallace AR (1858) On the tendency of species to form varieties, and on the perpetuation of varieties and species by natural means of selection. J Proc Linn Soc Lond Zool 3:46–50

    Google Scholar 

  • Des Marais DL, Hernandez KM, Juenger TE (2013) Genotype-by-environment interaction and plasticity: exploring genomic responses of plants to the abiotic environment. Annu Rev Ecol Evol Syst 44:5–29

    Article  Google Scholar 

  • Dwivedi SL, Sahrawat KL, Upadhyaya HD, Ortiz R (2013) Food, nutrition and agrobiodiversity under global climate change. Adv Agron 120:1–128

    Article  CAS  Google Scholar 

  • van Elsen A, Ayerdi Gotor A, de Vicente C, Traon D, Gennatas J, Amat L, Negri V, Chable V (2013) Plant breeding for an EU bio-based economy. JRC scientific and policy reports, joint research centre, institute for prospective technological Studies. European Commission, Publications Office of the European Union, Luxembourg

    Google Scholar 

  • Evenson RE, Gollin D (2003) Assessing the impact of the green revolution, 1960 to 2000. Science 300:758–761

    Article  CAS  PubMed  Google Scholar 

  • Fischer RA, Edmeades GO (2010) Breeding and cereal yield progress. Crop Sci 50:85–98

    Article  Google Scholar 

  • Fisher RA (1918) The correlation between relatives on the supposition of Mendelian inheritance. Trans R Soc Edinb 52:399–433

    Article  Google Scholar 

  • Fisher RA (1925a) Statistical methods for research workers. Oliver & Boyd, Edinburgh

    Google Scholar 

  • Fisher RA (1925b) Theory of statistical estimation. Proc Camb Phil Soc 22:705–722

    Article  Google Scholar 

  • Fisher RA (1935) The design of experiments. Oliver & Boyd, Edinburgh

    Google Scholar 

  • Furbank RT, Tester M (2011) Phenomics technologies to relieve the phenotyping bottleneck. Trends Plant Sci 16:635–644

    Article  CAS  PubMed  Google Scholar 

  • Gauch HG Jr (2006) Winning the accuracy game. Am Sci 94:135–143

    Article  Google Scholar 

  • Grishkevich V, Yanai I (2013) The genomic determinants of genotype × environment interactions in gene expression. Trends Genet 29:479–487

    Article  CAS  PubMed  Google Scholar 

  • Haldane JBS (1932) The causes of evolution. Longmans, Green, London

    Google Scholar 

  • Hallauer AR (1980) Relation of quantitative genetics to applied maize breeding. Rev Bras Genet 3:207–233

    Google Scholar 

  • Hamblin MT, Buckler ES, Jannick J-L (2011) Population genetics of genomics-based crop improvement methods. Trends Genet 27:98–106

    Article  CAS  PubMed  Google Scholar 

  • Hardy GH (1908) Mendelian proportions in a mixed population. Science 28:49–50

    Article  CAS  PubMed  Google Scholar 

  • Hill WG (2010) Understanding and using quantitative trait variation. Phil Trans R Soc B 365:73–85

    Article  PubMed Central  PubMed  Google Scholar 

  • Hill WG (2012) Quantitative genetics in the genomics era. Curr Genom 13:196–206

    Article  CAS  Google Scholar 

  • Jannink J-L (2005) Selective phenotyping to accurately map quantitative trait loci. Crop Sci 45:901–908

    Article  CAS  Google Scholar 

  • Jauhar PP (2006) Modern biotechnology as an integral supplement to conventional plant breeding: the prospects and challenges. Crop Sci 46:1841–1859

    Article  CAS  Google Scholar 

  • Jin C, Lan H, Attie AD, Churchill GA, Bulutuglo D, Yandell BS (2004) Selective phenotyping for increased efficiency in genetic mapping studies. Genetics 168:2285–2293

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Joosen RVL, Arends D, Li W, Willems LAJ, Keurentjes JJB, Ligterink W, Jansen RC, Hilhorst HWM (2013) Identifying genotype-by-environment interactions in the metabolism of germinating Arabidopsis seeds using generalized genetical genomics. Plant Physiol 162:553–566. doi:10.1104/pp.113.216176

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Keurentjes JJB, Koornneef M, Vreugdenhil D (2008) Quantitative genetics in the age of omics. Curr Op Plant Biol 11:123–128

    Article  CAS  Google Scholar 

  • Knight J (2003) A dying breed. Nature 421:568–570

    Article  CAS  PubMed  Google Scholar 

  • Lamkey KR, Lee M (1993) Quantitative genetics, molecular markers, and plant improvement. In: Imrie BC, Hacker JB (eds) Focused plant improvement: towards responsible and sustainable agriculture. Proceeding 10th Australian Plant Breeding Conference, Gold Coast, 18–23 April 1993. Organising committee. Australian Convention and Travel Service, Canberra, Australlia, pp 104–115

    Google Scholar 

  • Malosetti M, Voltas J, Romagosa I, Ullrich SE, van Eeuwijk FA (2004) Mixed models including environmental covariables for studying QTL by environment interaction. Euphytica 137:139–145

    Article  CAS  Google Scholar 

  • Malosetti M, Ribaut J-M, van Eeuwijk FA (2013) The statistical analysis of multi-environment data: modeling genotype-by-environment interaction and its genetic basis. Front Physiol doi:10.3389/fphys.2013.00044

    Google Scholar 

  • Mendel JG (1866) Versuche über pflanzenhybriden. Verhandlungen des naturforschenden Vereines in Brünn, Bd. IV für das Jahr, 1865 Abhandlungen: 3–47

    Google Scholar 

  • Mifflin B (2000) Crop improvement in the 21st century. J Exp Bot 51:1–8

    Article  Google Scholar 

  • Mohammadi SA, Prassana BM (2003) Analysis of genetic diversity in crop plants—salient statistical tools and considerations. Crop Sci 43:1235–1248

    Article  Google Scholar 

  • Montes JM, Melchinger AE, Reif JC (2007) Novel throughput phenotyping platforms in plant genetic studies. Trends Plant Sci 12:433–436

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  Google Scholar 

  • Ortiz R (2002) Germplasm enhancement to sustain genetic gains in crop improvement. In: Engels JMM, Ramanatha Rao V, Brown AHD, Jackson M (eds) Managing plant genetic diversity. International Plant Genetic Resources Institute, Rome, Italy—CAB International, Wallingford, pp 275–290

    Google Scholar 

  • Piepho HP, Möhring J, Melchinger AE, Büchse A (2008) BLUP for phenotypic selection in plant breeding and variety testing. Euphytica 161:209–228

    Article  Google Scholar 

  • Posthuma D, Beem LM, de Geus EJC, van Baal GCM, von Hjelmborg JB, Iachine I, Boomsma DI (2003) Theory and practice in quantitative genetics. Twin Res 6:361–376

    Article  PubMed  Google Scholar 

  • Ramalho MAP, Carvalho BL, Rodrigues Nunes JA (2013) Perspectives for the use of quantitative genetics in breeding of autogamous plants. ISRN Genet 2013:718127. http://dx.doi.org/10.5402/2013/718127

    Google Scholar 

  • Reif JC, Melchinger AE, Frisch M (2005) Genetical and mathematical properties of similarity and dissimilarity coefficients applied in plant breeding and seed bank management. Crop Sci 45:1–7

    Article  Google Scholar 

  • Saïdou A-A, Thuillet A-C, Couderc M, Mariac C, Vigouroux Y (2014) Association studies including genotype by environment interactions—prospects and limits. BMC Genet 15:3. http://www.biomedcentral.com/1471-2156/15/3

    Article  PubMed Central  PubMed  Google Scholar 

  • Sax K (1923) The association of size differences with seed-coat pattern and pigmentation in Phaseolus vulgaris. Genetics 8:552–560

    PubMed Central  CAS  PubMed  Google Scholar 

  • Stamp P, Visser R (2012) The twenty-first century, the century of plant breeding. Euphytica 186:585–591

    Article  Google Scholar 

  • Stevenson JR, Villoria N, Byerlee D, Kelley T, Maredia M (2013) Green revolution research saved an estimated 18 to 27 million hectares from being brought into agricultural production. Proc Natl Acad Sci U S A 110:8363–8368

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Tanksley SD, Medina-Filho H, Rick CM (1982) Use of naturally-occurring enzyme variation to detect and map genes controlling quantitative traits in an interspecific backcross of tomato. Heredity 49:11–25

    Article  Google Scholar 

  • Vargas M, Crossa J, van Eeuwijk FA, Ramirez ME, Sayre K (1999) Using partial least squares, factorial regression and AMMI models for interpreting genotype × environment interaction. Crop Sci 39:955–967

    Article  Google Scholar 

  • Vencovsky R, Crossa J (2003) Measurements of representativeness used in genetic resources conservation and plant breeding. Crop Sci 43:1912–1921

    Article  Google Scholar 

  • Wallace JG, Larsson SL, Buckler ES (2014) Entering the second century of maize quantitative genetics. Heredity 112:30–38

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Walsh B (2001) Quantitative genetics in the era of genomics. Theor Popul Biol 59:175–184

    Article  CAS  PubMed  Google Scholar 

  • Weinberg W (1908). Über den nachweis der vererbung beim menschen. Jahresh Ver vaterl Naturkunde Württ 64:368–382

    Google Scholar 

  • Weir BS (2007) Impact of dense genetic marker maps on plant population genetic studies. Euphytica 154:355–364

    Article  Google Scholar 

  • White JW, Andrade-Sanchez P, Gore MA, Bronson KF, Coffelt TA, Conley MM, Feldmann KA, French AN, Heun JT, Hunsaker DJ, Jenks MA, Kimball BA, Roth RL, Strand RJ, Kelly RT, Wall GW, Wang G (2012) Field-based phenomics for plant genetics research. Field Crops Res 133:101–112

    Article  Google Scholar 

  • Woeste KE, Blanche SB, Moldenhauer KA, Nelson CD (2010) Plant breeding and rural development in the United States. Crop Sci 50:1625–1632

    Article  Google Scholar 

  • Wright S (1921) Systems of mating. Parts I–V. Genetics 6:111–178

    PubMed Central  CAS  PubMed  Google Scholar 

  • Wright S (1931) Evolution in Mendelian populations. Genetics 16:97–159

    PubMed Central  CAS  PubMed  Google Scholar 

  • Yan W, Hunt LA, Sheng Q, Szlavnics Z (2000) Cultivar evaluation and mega-environment investigation based on GGE biplot. Crop Sci 40:596–605

    Article  Google Scholar 

  • Yan W, Pageau D, Fregeau-Reid J, Durand J (2011) Assessing the representativeness and repeatability of test locations for genotype evaluation. Crop Sci 51:1603–1610

    Article  Google Scholar 

  • Zhao F, Xu S (2012) Genotype by environment interaction of quantitative traits: a case study in barley. G3 2:779–788

    Article  PubMed Central  PubMed  Google Scholar 

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Correspondence to Rodomiro Ortiz Ríos .

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Ortiz Ríos, R. (2015). Introduction to Plant Breeding. In: Plant Breeding in the Omics Era. Springer, Cham. https://doi.org/10.1007/978-3-319-20532-8_1

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