Use of genomic selection in breeding rice (Oryza sativa L.) for resistance to rice blast (Magnaporthe oryzae)
Rice blast (RB), caused by the fungal pathogen Magnaporthe oryzae , is a major disease in rice ( Oryzae sativa L.) with resistance controlled by major and minor genes. Genomic selection (GS) is a breeding technology applicable for selecting traits controlled by many genes. Our objective was to asses...
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Published in | Molecular breeding Vol. 39; no. 8; pp. 1 - 16 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
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Springer Netherlands
01.08.2019
Springer Nature B.V |
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Abstract | Rice blast (RB), caused by the fungal pathogen
Magnaporthe oryzae
, is a major disease in rice (
Oryzae sativa
L.) with resistance controlled by major and minor genes. Genomic selection (GS) is a breeding technology applicable for selecting traits controlled by many genes. Our objective was to assess the utility of GS in improving RB resistance. A population of 161 accessions from Africa and another population of 162 accessions from the USA were evaluated for resistance to six and eight RB isolates, respectively. Each rice population was genotyped with single nucleotide polymorphism (SNP) markers. The accuracy of GS was determined using seven models: genomic best linear unbiased prediction (gBLUP), gBLUP with some markers as fixed effects (fgBLUP), gBLUP model with population structure as a covariate (sgBLUP), multitrait gBLUP (mgBLUP), Bayesian (BayesA and BayesC) models, and a multiple linear regression model using significant markers (MLR). Each set of population had accessions with good resistance to multiple isolates. Using cross-validation, the accuracy of gBLUP ranged from 0.15 to 0.72; the gBLUP, sgBLUP, mgBLUP, and Bayesian methods had similar accuracy, while fgBLUP gave the greatest accuracy. Without cross-validation, gBLUP, sgBLUP, fgBLUP, and Bayesian methods were similar and were superior to mgBLUP and MLR. In general, a GS model built on data from one isolate was able to predict the phenotypes generated from other isolates, suggesting common genes controlling resistance across isolates. Our results demonstrate that GS may be a very useful method to improve RB resistance. The fgBLUP model could be used to effectively select for both durable and resistance traits conferred by major genes. |
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AbstractList | Rice blast (RB), caused by the fungal pathogen Magnaporthe oryzae, is a major disease in rice (Oryzae sativa L.) with resistance controlled by major and minor genes. Genomic selection (GS) is a breeding technology applicable for selecting traits controlled by many genes. Our objective was to assess the utility of GS in improving RB resistance. A population of 161 accessions from Africa and another population of 162 accessions from the USA were evaluated for resistance to six and eight RB isolates, respectively. Each rice population was genotyped with single nucleotide polymorphism (SNP) markers. The accuracy of GS was determined using seven models: genomic best linear unbiased prediction (gBLUP), gBLUP with some markers as fixed effects (fgBLUP), gBLUP model with population structure as a covariate (sgBLUP), multitrait gBLUP (mgBLUP), Bayesian (BayesA and BayesC) models, and a multiple linear regression model using significant markers (MLR). Each set of population had accessions with good resistance to multiple isolates. Using cross-validation, the accuracy of gBLUP ranged from 0.15 to 0.72; the gBLUP, sgBLUP, mgBLUP, and Bayesian methods had similar accuracy, while fgBLUP gave the greatest accuracy. Without cross-validation, gBLUP, sgBLUP, fgBLUP, and Bayesian methods were similar and were superior to mgBLUP and MLR. In general, a GS model built on data from one isolate was able to predict the phenotypes generated from other isolates, suggesting common genes controlling resistance across isolates. Our results demonstrate that GS may be a very useful method to improve RB resistance. The fgBLUP model could be used to effectively select for both durable and resistance traits conferred by major genes. Rice blast (RB), caused by the fungal pathogen Magnaporthe oryzae , is a major disease in rice ( Oryzae sativa L.) with resistance controlled by major and minor genes. Genomic selection (GS) is a breeding technology applicable for selecting traits controlled by many genes. Our objective was to assess the utility of GS in improving RB resistance. A population of 161 accessions from Africa and another population of 162 accessions from the USA were evaluated for resistance to six and eight RB isolates, respectively. Each rice population was genotyped with single nucleotide polymorphism (SNP) markers. The accuracy of GS was determined using seven models: genomic best linear unbiased prediction (gBLUP), gBLUP with some markers as fixed effects (fgBLUP), gBLUP model with population structure as a covariate (sgBLUP), multitrait gBLUP (mgBLUP), Bayesian (BayesA and BayesC) models, and a multiple linear regression model using significant markers (MLR). Each set of population had accessions with good resistance to multiple isolates. Using cross-validation, the accuracy of gBLUP ranged from 0.15 to 0.72; the gBLUP, sgBLUP, mgBLUP, and Bayesian methods had similar accuracy, while fgBLUP gave the greatest accuracy. Without cross-validation, gBLUP, sgBLUP, fgBLUP, and Bayesian methods were similar and were superior to mgBLUP and MLR. In general, a GS model built on data from one isolate was able to predict the phenotypes generated from other isolates, suggesting common genes controlling resistance across isolates. Our results demonstrate that GS may be a very useful method to improve RB resistance. The fgBLUP model could be used to effectively select for both durable and resistance traits conferred by major genes. |
ArticleNumber | 114 |
Author | McHale, Leah K. Mgonja, Emmanuel M. Sneller, Clay H. Wang, Guo-Liang Huang, Mao Luzi-Kihupi, Ashura Balimponya, Elias G. |
Author_xml | – sequence: 1 givenname: Mao surname: Huang fullname: Huang, Mao organization: Department of Horticulture and Crop Science, The Ohio State University – sequence: 2 givenname: Elias G. surname: Balimponya fullname: Balimponya, Elias G. organization: Tanzania Official Seed Certification Institute – sequence: 3 givenname: Emmanuel M. surname: Mgonja fullname: Mgonja, Emmanuel M. organization: Department of Plant Pathology, The Ohio State University – sequence: 4 givenname: Leah K. surname: McHale fullname: McHale, Leah K. organization: Department of Horticulture and Crop Science, The Ohio State University – sequence: 5 givenname: Ashura surname: Luzi-Kihupi fullname: Luzi-Kihupi, Ashura organization: Department of Crop Science and Horticulture, Sokoine University of Agriculture – sequence: 6 givenname: Guo-Liang surname: Wang fullname: Wang, Guo-Liang organization: Department of Plant Pathology, The Ohio State University – sequence: 7 givenname: Clay H. surname: Sneller fullname: Sneller, Clay H. email: sneller.5@osu.edu organization: Department of Horticulture and Crop Science, The Ohio State University |
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Keywords | Genotype by sequencing Susceptible Accuracy Resistant Rice blast Genomic selection |
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Snippet | Rice blast (RB), caused by the fungal pathogen
Magnaporthe oryzae
, is a major disease in rice (
Oryzae sativa
L.) with resistance controlled by major and... Rice blast (RB), caused by the fungal pathogen Magnaporthe oryzae, is a major disease in rice (Oryzae sativa L.) with resistance controlled by major and minor... |
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SubjectTerms | Accuracy Bayesian analysis Biomedical and Life Sciences Biotechnology Disease control Genes Genomics Life Sciences Magnaporthe oryzae Markers Mathematical models Molecular biology Nucleotides Oryza sativa Phenotypes Plant biology Plant breeding Plant Genetics and Genomics Plant Pathology Plant Physiology Plant reproduction Plant Sciences Polymorphism Population Population structure Regression analysis Regression models Rice Rice blast Single-nucleotide polymorphism |
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Title | Use of genomic selection in breeding rice (Oryza sativa L.) for resistance to rice blast (Magnaporthe oryzae) |
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