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Marker-Assisted Breeding for Disease Resistance in Crop Plants

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Biotechnologies of Crop Improvement, Volume 3

Abstract

Breeding disease-resistant crop varieties is a cornerstone of disease management. Marker-assisted selection (MAS) incorporates a plethora of plant genomic resources into the process of breeding disease-resistant crops. Although there are species-specific and disease-specific considerations, much of the procedures and theory behind MAS are conserved. Using molecular markers is most likely to increase the efficiency of the breeding process in cases where disease resistance is controlled by one or few genes, and those genes have a large effect on the resistance phenotype. In cases where disease resistance is controlled by many genes of small effect, genomic selection (GS) may be more efficient than MAS or phenotypic selection. GS is an emerging technology, and many of the statistical principles and procedures are still being developed. This chapter should begin to inform breeders as to the potential and the details to consider if using a marker-assisted breeding tool in their plant breeding program.

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References

  • Baird NA, Etter PD, Atwood TS et al (2008) Rapid SNP discovery and genetic mapping using sequenced RAD markers. PLoS One 3:e3376. https://doi.org/10.1371/journal.pone.0003376

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Bhat JA, Ali S, Salgotra RK et al (2016) Genomic selection in the era of next generation sequencing for complex traits in plant breeding. Front Genet 7:221

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  Google Scholar 

  • Concibido VC, Diers BW, Arelli PR (2004) A decade of QTL mapping for cyst nematode resistance in soybean. Crop Sci 44:1121–1131

    Article  CAS  Google Scholar 

  • Cook DE, Lee TG, Guo X et al (2012) Copy number variation of multiple genes at Rhg1 mediates nematode resistance in soybean. Science 338:1206–1209. https://doi.org/10.1126/science.1228746

    Article  PubMed  CAS  Google Scholar 

  • Davey JW, Hohenlohe PA, Etter PD et al (2011) Genome-wide genetic marker discovery and genotyping using next-generation sequencing. Nat Rev Genet 12:499–510. https://doi.org/10.1038/nrg3012

    Article  PubMed  CAS  Google Scholar 

  • de los Campos G, Vazquez A, Fernando R et al (2013a) Prediction of complex human traits using the genomic best linear unbiased predictor. PLoS Genet 9:e1003608

    Article  CAS  PubMed Central  Google Scholar 

  • de Los Campos G, Hickey JM, Pong-Wong R (2013b) Whole-genome regression and prediction methods applied to plant and animal breeding. Genetics 193:327–345

    Article  PubMed  Google Scholar 

  • DePristo MA, Banks E, Poplin R et al (2011) A frame-work for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet 43:491–498

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Fan JB, Chee MS, Gunderson KL (2006) Highly parallel genomic assays. Nat Rev Genet 7:632–644

    Article  CAS  PubMed  Google Scholar 

  • Frisch M, Bohn M, Melchinger AE (1999) Comparison of selection strategies for marker-assisted backcrossing of a gene. Crop Sci 39:1295–1301

    Article  Google Scholar 

  • Gianola D, van Kaam JB (2008) Reproducing kernel Hilbert spaces regression methods for genomic assisted prediction of quantitative traits. Genetics 178:2289–2303

    Article  PubMed  PubMed Central  Google Scholar 

  • Grant D, Nelson RT, Cannon SB et al (2010) SoyBase, the USDA-ARS soybean genetics and genomics database. Nucl Acids Res 38:D843–D846. https://doi.org/10.1093/nar/gkp798

    Article  PubMed  CAS  Google Scholar 

  • Habier D, Fernando RL, Kizilkaya K et al (2011) Extension of the Bayesian alphabet for genomic selection. BMC Bioinform 12:186

    Article  Google Scholar 

  • Heffner EL, Jannink JL, Sorrells ME (2011a) Genomic selection accuracy using multifamily prediction models in a wheat breeding program. Plant Genet 4:65–75

    Article  Google Scholar 

  • Heffner EL, Jannink JL, Iwata H et al (2011b) Genomic selection accuracy for grain quality traits in biparental wheat populations. Crop Sci 51:2597–2606

    Article  Google Scholar 

  • Heffner EL, Jannink JL, Sorrells ME (2011c) Genomic selection accuracy using multifamily prediction models in a wheat breeding program. Plant Genome 4:65–75

    Article  Google Scholar 

  • Heslot N, Yang HP, Sorrells ME et al (2012) Genomic selection in plant breeding: a comparison of models. Crop Sci 52:146–160

    Article  Google Scholar 

  • Heslot N, Rutkoski J, Poland J et al (2013) Impact of marker ascertainment bias on genomic selection accuracy and estimates of genetic diversity. PLoS One 8(9):e74612. https://doi.org/10.1371/journal.pone.0074612

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Holliday JA, Wang T, Aitken S (2012) Predicting adaptive phenotypes from multilocus genotypes in Sitka spruce (Picea sitchensis) using random forest. G3 2:1085–1093

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Huang X, Feng Q, Qian Q et al (2009) High-throughput genotyping by whole-genome resequencing. Genome Res 19:1068–1076. https://doi.org/10.1101/gr.089516.108

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  • Jarquín D, Kocak K, Posadas L et al (2014) Genotyping by sequencing for genomic prediction in a soybean breeding population. BMC Genomics 15(1):740

    Google Scholar 

  • Kisha TJ, Sneller CH, Diers BW (1997) Relationship between genetic distance among parents and genetic variance in populations of soybean. Crop Sci 37(4):1317–1325

    Article  Google Scholar 

  • Li Z, Sillanpää MJ (2012) Overview of LASSO-related penalized regression methods for quantitative trait mapping and genomic selection. Theor Appl Genet 125:419–435

    Article  CAS  PubMed  Google Scholar 

  • Li YH, Zhou G, Ma J et al (2014) De novo assembly of soybean wild relatives for pan-genome analysis of diversity and agronomic traits. Nat Biotechnol 32(10):1045–1052

    Article  CAS  PubMed  Google Scholar 

  • Liu S, Kandoth PK, Warren SD et al (2012) A soybean cyst nematode resistance gene points to a new mechanism of plant resistance to pathogens. Nature 492:256–260

    PubMed  CAS  Google Scholar 

  • Marulanda JJ, Melchinger AE, Würschum T (2015) Genomic selection in biparental populations: assessment of parameters for optimum estimation set design. Plant Breed 134:623–630

    Article  CAS  Google Scholar 

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

    PubMed  PubMed Central  CAS  Google Scholar 

  • Morris GP, Ramu P, Deshpande SP et al (2013) Population genomic and genome-wide association studies of agroclimatic traits in sorghum. Proc Natl Acad Sci U S A 110(2):453–458

    Article  PubMed  Google Scholar 

  • Mudge J, Cregan PB, Kenworthy JP et al (1997) Two microsatellite markers that flank the major soybean cyst nematode resistance locus. Crop Sci 37:1611–1615

    Article  CAS  Google Scholar 

  • Nakaya A, Isobe SN (2012) Will genomic selection be a practical method for plant breeding? Ann Bot 110:1303–1316

    Article  PubMed  PubMed Central  Google Scholar 

  • Ornella L, Singh S, Perez P et al (2012) Genomic prediction of genetic values for resistance to wheat rusts. Plant Genome 5:136–148

    Article  CAS  Google Scholar 

  • Peterson BK, Weber JN, Kay EN et al (2012) Double digest RADseq: an inexpensive method for de novo SNP discovery and genotyping in model and non-model species. PLoS One 7:e37135

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Poland JA, Rife TW (2012) Genotyping-by-sequencing for plant breeding and genetics. Plant Genome 5:92–102. https://doi.org/10.3835/plantgenome2012.05.0005

    Article  CAS  Google Scholar 

  • Riggs RD, Schmitt DP (1987) Nematodes. In: Wilcox JR (ed) Soybeans: improvement, production, and uses, Agron mongr, 2nd edn. ASA, CSSA, SSSA, Madison, pp 757–778

    Google Scholar 

  • Roy KW (1997) Fusarium solani on soybean roots: nomenclature of causal agent of sudden death syndrome and identity and relevance of F. solani form B. Plant Dis 81:259–266

    Article  PubMed  Google Scholar 

  • Schmutz J, Cannon SB, Schlueter J et al (2010) Genome sequence of the palaeopolyploid soybean. Nature 463:178–183

    Article  CAS  PubMed  Google Scholar 

  • Shi Z, Liu S, Noe J et al (2015) SNP identification and marker assay development for high-throughput selection of soybean cyst nematode resistance. BMC Genomics 16:314

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Song Q, Hyten DL, Jia G et al (2013) Development and evaluation of SoySNP50K, a high-density genotyping array for soybean. PLoS ONE 8(1):e54985

    Google Scholar 

  • Wang Z, Gerstein M, Snyder M (2009) RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet 10:57–63

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Wang X, Yang Z, Xu C (2015) A comparison of genomic selection methods for breeding value prediction. Science Bulletin 60(10):925–935

    Google Scholar 

  • Wen Z, Boyse JF, Song Q et al (2015) Genomic consequences of selection and genome-wide association mapping in soybean. BMC Genomics 16:671

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Xu Y, Crouch JH (2008) Marker-assisted selection in plant breeding: from publications to practice. Crop Sci 48:391–407. https://doi.org/10.2135/cropsci2007.04.0191

    Article  Google Scholar 

  • Xu X, Zeng L, al TY (2013) Pinpointing genes underlying the quantitative trait loci for root-knotnematode resistance in palaeopolyploid soybean by whole genome resequencing. Proc Natl Acad Sci 110:13469–13474

    Article  PubMed  PubMed Central  Google Scholar 

  • Yan J, Shah T, Warburton ML et al (2009) Genetic characterization and linkage disequilibrium estimation of a global maize collection using SNP markers. PLoS One 4(12):8451. https://doi.org/10.1371/journal.pone.0008451.

    Article  Google Scholar 

  • Zhang Z, Hao J, Yuan J et al (2014) Phytophthora root rot resistance in soybean E00003. Crop Sci 54(2):492–499

    Article  Google Scholar 

  • Zhang J, Song Q, Cregan PB et al (2016) Genome wide association study, genomic prediction and marker assisted selection for seed weight in soybean (Glycine max). Theor Appl Genet 129:117–130

    Article  CAS  PubMed  Google Scholar 

  • Zhang S, Zhang Z, Bales C et al (2017a) Mapping novel aphid resistance QTL from wild soybean, Glycine soja 85-32. Theor Appl Genet 130(9):1941–1952. https://doi.org/10.1007/s00122-017-2935-z

    Article  PubMed  CAS  Google Scholar 

  • Zhang S, Zhang Z, Wen Z et al (2017b) Fine mapping of the aphid resistance genes Rag6 and Rag3c from Glycine soja 85-32. Theor Appl Genet. https://doi.org/10.1007/s00122-017-2979-0

  • Zhao Y, Mette M, Gowda M et al (2014) Bridging the gap between marker-assisted and genomic selection of heading time and plant height in hybrid wheat. Heredity 112:638–645. https://doi.org/10.1038/hdy.2014.1

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Zhong S, Dekkers JCM, Fernando RL et al (2009) Factors affecting accuracy from genomic selection in populations derived from multiple inbred lines: a barley case study. Genetics 182:355–364

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zou H, Hastie T (2005) Regularization and variable selection via the elastic net. J R Stat Soc Ser B 67:301–320

    Article  Google Scholar 

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Correspondence to Paul Joseph Collins .

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Collins, P.J., Wen, Z., Zhang, S. (2018). Marker-Assisted Breeding for Disease Resistance in Crop Plants. In: Gosal, S., Wani, S. (eds) Biotechnologies of Crop Improvement, Volume 3. Springer, Cham. https://doi.org/10.1007/978-3-319-94746-4_3

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