Genomic prediction for rust resistance in diverse wheat landraces

Theoretical and Applied Genetics

Volumn 127, Issue 8, 2014, Pages 1795-1803

  Daetwyler, Hans D ^a   Bansal, Urmil K ^b   Bariana, Harbans S ^b   Hayden, Matthew J ^a   Hayes, Ben J ^a  

^a LA TROBE UNIVERSITY   (Australia)

^b UNIVERSITY OF SYDNEY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

GENES; PLANTS (BOTANY); POLYMERASE CHAIN REACTION; REGRESSION ANALYSIS;

BAYESIAN ANALYSIS; BAYESIAN REGRESSION METHOD; BEST LINEAR UNBIASED PREDICTIONS; GENETIC RELATEDNESS; GENOMIC PREDICTIONS; PREDICTION ACCURACY; RUST RESISTANCE GENES; SELECTION DECISIONS;

FORECASTING;

TRITICUM AESTIVUM;

GENETIC MARKER;

BASIDIOMYCETES; BREEDING; DISEASE RESISTANCE; ECOTYPE; GENETIC MARKER; GENETICS; GENOMICS; GENOTYPE; GENOTYPE ENVIRONMENT INTERACTION; IMMUNOLOGY; INHERITANCE; MICROBIOLOGY; PHYLOGENY; PHYSIOLOGY; PLANT DISEASE; PLANT GENOME; PRINCIPAL COMPONENT ANALYSIS; PROCEDURES; QUANTITATIVE TRAIT; REGRESSION ANALYSIS; REPRODUCIBILITY; WHEAT;

BASIDIOMYCOTA; BREEDING; DISEASE RESISTANCE; ECOTYPE; GENE-ENVIRONMENT INTERACTION; GENETIC MARKERS; GENOME, PLANT; GENOMICS; GENOTYPE; INHERITANCE PATTERNS; PHYLOGENY; PLANT DISEASES; PRINCIPAL COMPONENT ANALYSIS; QUANTITATIVE TRAIT, HERITABLE; REGRESSION ANALYSIS; REPRODUCIBILITY OF RESULTS; TRITICUM;

EID: 84925884189     PISSN: 00405752     EISSN: 14322242     Source Type: Journal    
DOI: 10.1007/s00122-014-2341-8     Document Type: Article

References (35)

1. Bariana HS, Brown GN, Bansal UK, Miah H, Standen GE, Lu M (2007) Breeding triple rust resistant wheat cultivars for Australia using conventional and marker-assisted selection technologies. Aust J Agric Res 58: 576-587
2. Bernardo R (2010) Genomewide selection with minimal crossing in self-pollinated crops. Crop Sci 50: 624-627
3. Cavanagh CR, Chao S, Wang S, Huang BE, Stephen S, Kiani S, Forrest K, Saintenac C, Brown-Guedira GL, Akhunova A, See D, Bai G, Pumphrey M, Tomar L, Wong D, Kong S, Reynolds M, da Silva ML, Bockelman H, Talbert L, Anderson JA, Dreisigacker S, Baenziger S, Carter A, Korzun V, Morrell PL, Dubcovsky J, Morell MK, Sorrells ME, Hayden MJ, Akhunov E (2013) Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landraces and cultivars. Proc Natl Acad Sci 110 (20): 8057-8062
4. Clark SA, Hickey JM, Daetwyler HD, Van der Werf JHJ (2012) The importance of information on relatives for the prediction of genomic breeding values and implications for the makeup of reference populations in livestock breeding schemes. Genet Sel Evol 44: 4
5. Crossa J, Gdl Campos, Perez P, Gianola D, Burgueno J, Araus JL, Makumbi D, Singh RP, Dreisigacker S, Yan J, Arief V, Banziger M, Braun H-J (2010) Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers. Genetics 186: 713-724
6. Daetwyler HD (2009) Genome-wide evaluation of populations. Wageningen University, Wageningen
7. Daetwyler HD, Villanueva B, Woolliams JA (2008) Accuracy of predicting the genetic risk of disease using a genome-wide approach. Plos One 3: e3395
8. Daetwyler HD, Pong-Wong R, Villanueva B, Woolliams JA (2010) The impact of genetic architecture on genome-wide evaluation methods. Genetics 185: 1021-1031
9. Daetwyler HD, Kemper KE, van der Werf JHJ, Hayes BJ (2012) Components of the accuracy of genomic prediction in a multibreed sheep population. J Anim Sci 90: 3375-3384
10. Erbe M, Hayes BJ, Matukumalli LK, Goswami S, Bowman PJ, Reich CM, Mason BA, Goddard ME (2012) Improving accuracy of genomic predictions within and between dairy cattle breeds with imputed high-density single nucleotide polymorphism panels. J Dairy Sci 95: 4114-4129
11. Erbe M, Gredler B, Seefried FR, Bapst B, Simianer H (2013) A function accounting for training set size and marker density to model the average accuracy of genomic prediction. Plos One 8: e81046
12. Fisher RA (1915) Frequency distribution of the values of the correlation coefficient in samples from an indefinitely large population. Biometrika 10: 507-521
13. Gilmour AR, Gogel B, Cullis BR, Thompson R (2009) ASReml user guide release 3.0. VSN International Ltd, Hemel Hempstead
14. Goddard ME (2009) Genomic selection: prediction of accuracy and maximisation of long term response. Genetica 136: 245-252
15. Habier D, Fernando RL, Dekkers JCM (2007) The impact of genetic relationship information on genome-assisted breeding values. Genetics 177: 2389-2397
16. Habier D, Tetens J, Seefried F-R, Lichtner P, Thaller G (2010) The impact of genetic relationship information on genomic breeding values in German Holstein cattle. Genet Sel Evol 42: 5
17. Hao C, Wang L, Ge H, Dong Y, Zhang X (2011) Genetic diversity and linkage disequilibrium in Chinese Bread Wheat (Triticum aestivum L.) revealed by SSR markers. Plos One 6: e17279
18. Hayes BJ, Visscher PM, Goddard ME (2009) Increased accuracy of artificial selection by using the realized relationship matrix. Genet Res 91: 47-60
19. Heffner EL, Sorrels ME, Jannink J-L (2009) Genomic selection for crop improvement. Crop Sci 49: 1-12
20. Heffner EL, Lorenz AJ, Jannink J-L, Sorrells ME (2010) Plant breeding with genomic selection: gain per unit time and cost. Crop Sci 50: 1681-1690
21. Heffner EL, Jannink J-L, Iwata H, Souza E, Sorrells ME (2011a) Genomic selection accuracy for grain quality traits in biparental wheat populations. Crop Sci 51: 2597-2606
22. Heffner EL, Jannink J-L, Sorrells ME (2011b) Genomic selection accuracy using multifamily prediction models in a wheat breeding program. Plant Gen 4: 65-75
23. Henderson CR (1984) Applications of linear model in animal breeding. University of Guelph, Guelph
24. Heslot N, Akdemir D, Sorrells M, Jannink J-L (2014) Integrating environmental covariates and crop modeling into the genomic selection framework to predict genotype by environment interactions. Theor Appl Genet 127: 463-480
25. Lagudah ES, McFadden H, Singh RP, Huerta-Espino J, Bariana HS, Spielmeyer W (2006) Molecular genetic characterization of the Lr34/Yr18 slow rusting resistance gene region in wheat. Theor Appl Genet 114: 21-30
26. Mago R, Brown-Guedira G, Dreisigacker S, Breen J, Jin Y, Singh R, Appels R, Lagudah ES, Ellis J, Spielmeyer W (2011) An accurate DNA marker assay for stem rust resistance gene Sr2 in wheat. Theor Appl Genet 122: 735-744
27. McIntosh RA, Park RF, Wellings CR (1995) Wheat rusts: an atlas of resistance genes. CSIRO Publications, East Melbourne
28. McIntosh RA, Dubcovsky J, Rogers J, Morris C, Appels R, Xia X (2010) Catalogue of gene symbols for wheat: 2010 supplement. Annu Wheat Newsl 56: 273-282
29. Meuwissen THE, Hayes BJ, Goddard ME (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157 (4): 1819-1829
30. Murray G, Brennan J (2009) The current and potential cost from diseases of wheat in Australia. In: Council GRD (ed), Barton, pp 1-70
31. Pszczola M, Strabel T, Mulder HA, Calus MPL (2012) Reliability of direct genomic values for animals with different relationships within and to the reference population. J Dairy Sci 95: 389-400
32. R Core Development Team (2010) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna
33. Rutkoski JE, Poland J, Jannink JL, Sorrells ME (2013) Imputation of unordered markers and the impact on genomic selection accuracy. G3: Genes Genomes Genet 3 (3): 427-439
34. Stekhoven DJ (2013) Nonparametric Missing Value Imputation using Random Forest. R package v1. 4 edn
35. Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt DR, Madden PA, Heath AC, Martin NG, Montgomery GW, Goddard ME, Visscher PM (2010) Common SNPs explain a large proportion of the heritability for human height. Nat Genet 42: 565-569