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Jones MW, Penning BW, Jamann TM, Glaubitz JC, Romay C, Buckler ES, Redinbaugh MG. Diverse Chromosomal Locations of Quantitative Trait Loci for Tolerance to Maize chlorotic mottle virus in Five Maize Populations. PHYTOPATHOLOGY 2018; 108:748-758. [PMID: 29287150 DOI: 10.1094/phyto-09-17-0321-r] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
The recent rapid emergence of maize lethal necrosis (MLN), caused by coinfection of maize with Maize chlorotic mottle virus (MCMV) and a second virus usually from the family Potyviridae, is causing extensive losses for farmers in East Africa, Southeast Asia, and South America. Although the genetic basis of resistance to potyviruses is well understood in maize, little was known about resistance to MCMV. The responses of five maize inbred lines (KS23-5, KS23-6, N211, DR, and Oh1VI) to inoculation with MCMV, Sugarcane mosaic virus, and MLN were characterized. All five lines developed fewer symptoms than susceptible controls after inoculation with MCMV; however, the virus was detected in systemic leaf tissue from each of the lines similarly to susceptible controls, indicating that the lines were tolerant of MCMV rather than resistant to it. Except for KS23-5, the inbred lines also developed fewer symptoms after inoculation with MLN than susceptible controls. To identify genetic loci associated with MCMV tolerance, large F2 or recombinant inbred populations were evaluated for their phenotypic responses to MCMV, and the most resistant and susceptible plants were genotyped by sequencing. One to four quantitative trait loci (QTL) were identified in each tolerant population using recombination frequency and positional mapping strategies. In contrast to previous studies of virus resistance in maize, the chromosomal positions and genetic character of the QTL were unique to each population. The results suggest that different, genotype-specific mechanisms are associated with MCMV tolerance in maize. These results will allow for the development of markers for marker-assisted selection of MCMV- and MLN-tolerant maize hybrids for disease control.
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Affiliation(s)
- Mark W Jones
- First, second, and seventh authors: United States Department of Agriculture-Agricultural Research Service (USDA-ARS) Corn, Soybean and Wheat Quality Research Unit, Wooster, OH 44691; third author: Department of Crop Sciences, University of Illinois, Urbana 61801; fourth and fifth authors: Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853; sixth author: USDA-ARS Plant, Soil and Nutrition Research and Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853; and seventh author: Department of Plant Pathology, Ohio State University, Wooster 44691
| | - Bryan W Penning
- First, second, and seventh authors: United States Department of Agriculture-Agricultural Research Service (USDA-ARS) Corn, Soybean and Wheat Quality Research Unit, Wooster, OH 44691; third author: Department of Crop Sciences, University of Illinois, Urbana 61801; fourth and fifth authors: Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853; sixth author: USDA-ARS Plant, Soil and Nutrition Research and Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853; and seventh author: Department of Plant Pathology, Ohio State University, Wooster 44691
| | - Tiffany M Jamann
- First, second, and seventh authors: United States Department of Agriculture-Agricultural Research Service (USDA-ARS) Corn, Soybean and Wheat Quality Research Unit, Wooster, OH 44691; third author: Department of Crop Sciences, University of Illinois, Urbana 61801; fourth and fifth authors: Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853; sixth author: USDA-ARS Plant, Soil and Nutrition Research and Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853; and seventh author: Department of Plant Pathology, Ohio State University, Wooster 44691
| | - Jeff C Glaubitz
- First, second, and seventh authors: United States Department of Agriculture-Agricultural Research Service (USDA-ARS) Corn, Soybean and Wheat Quality Research Unit, Wooster, OH 44691; third author: Department of Crop Sciences, University of Illinois, Urbana 61801; fourth and fifth authors: Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853; sixth author: USDA-ARS Plant, Soil and Nutrition Research and Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853; and seventh author: Department of Plant Pathology, Ohio State University, Wooster 44691
| | - Cinta Romay
- First, second, and seventh authors: United States Department of Agriculture-Agricultural Research Service (USDA-ARS) Corn, Soybean and Wheat Quality Research Unit, Wooster, OH 44691; third author: Department of Crop Sciences, University of Illinois, Urbana 61801; fourth and fifth authors: Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853; sixth author: USDA-ARS Plant, Soil and Nutrition Research and Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853; and seventh author: Department of Plant Pathology, Ohio State University, Wooster 44691
| | - Edward S Buckler
- First, second, and seventh authors: United States Department of Agriculture-Agricultural Research Service (USDA-ARS) Corn, Soybean and Wheat Quality Research Unit, Wooster, OH 44691; third author: Department of Crop Sciences, University of Illinois, Urbana 61801; fourth and fifth authors: Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853; sixth author: USDA-ARS Plant, Soil and Nutrition Research and Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853; and seventh author: Department of Plant Pathology, Ohio State University, Wooster 44691
| | - Margaret G Redinbaugh
- First, second, and seventh authors: United States Department of Agriculture-Agricultural Research Service (USDA-ARS) Corn, Soybean and Wheat Quality Research Unit, Wooster, OH 44691; third author: Department of Crop Sciences, University of Illinois, Urbana 61801; fourth and fifth authors: Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853; sixth author: USDA-ARS Plant, Soil and Nutrition Research and Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853; and seventh author: Department of Plant Pathology, Ohio State University, Wooster 44691
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Sun X, Mumm RH. Method to represent the distribution of QTL additive and dominance effects associated with quantitative traits in computer simulation. BMC Bioinformatics 2016; 17:73. [PMID: 26852240 PMCID: PMC4744427 DOI: 10.1186/s12859-016-0906-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2015] [Accepted: 01/22/2016] [Indexed: 11/25/2022] Open
Abstract
Background Computer simulation is a resource which can be employed to identify optimal breeding strategies to effectively and efficiently achieve specific goals in developing improved cultivars. In some instances, it is crucial to assess in silico the options as well as the impact of various crossing schemes and breeding approaches on performance for traits of interest such as grain yield. For this, a means by which gene effects can be represented in the genome model is critical. Results To address this need, we devised a method to represent the genomic distribution of additive and dominance gene effects associated with quantitative traits. The method, based on meta-analysis of previously-estimated QTL effects following Bennewitz and Meuwissen (J Anim Breed Genet 127:171–9, 2010), utilizes a modified Dirichlet process Gaussian mixture model (DPGMM) to fit the number of mixture components and estimate parameters (i.e. mean and variance) of the genomic distribution. The method was demonstrated using several maize QTL data sets to provide estimates of additive and dominance effects for grain yield and other quantitative traits for application in maize genome simulations. Conclusions The DPGMM method offers an alternative to the over-simplified infinitesimal model in computer simulation as a means to better represent the genetic architecture of quantitative traits, which likely involve some large effects in addition to many small effects. Furthermore, it confers an advantage over other methods in that the number of mixture model components need not be known a priori. In addition, the method is robust with use of large-scale, multi-allelic data sets or with meta-analyses of smaller QTL data sets which may be derived from bi-parental populations in precisely estimating distribution parameters. Thus, the method has high utility in representing the genetic architecture of quantitative traits in computer simulation. Electronic supplementary material The online version of this article (doi:10.1186/s12859-016-0906-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Xiaochun Sun
- Department of Crop Sciences and the Illinois Plant Breeding Center, University of Illinois at Urbana-Champaign, 1102 S. Goodwin Ave., Urbana, IL, 61801, USA. .,Present address: Dow AgroSciences, Indianapolis, IN, USA.
| | - Rita H Mumm
- Department of Crop Sciences and the Illinois Plant Breeding Center, University of Illinois at Urbana-Champaign, 1102 S. Goodwin Ave., Urbana, IL, 61801, USA. .,GeneMax Services, Urbana, IL, 61802, USA.
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Abstract
Diseases caused by viruses are found throughout the maize-growing regions of the world and can cause significant losses for producers. In this review, virus diseases of maize and the pathogens that cause them are discussed. Factors leading to the spread of disease and measures for disease control are reviewed, as is our current knowledge of the genetics of virus resistance in this important crop.
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Affiliation(s)
- Margaret G Redinbaugh
- USDA, Agricultural Research Service, Corn, Soybean and Wheat Quality Research Unit and Department of Plant Pathology, Ohio State University-OARDC, Wooster, Ohio, USA.
| | - José L Zambrano
- Instituto Nacional Autónomo de Investigaciones Agropecuarias (INIAP), Programa Nacional del Maíz, Quito, Ecuador
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Zambrano JL, Jones MW, Brenner E, Francis DM, Tomas A, Redinbaugh MG. Genetic analysis of resistance to six virus diseases in a multiple virus-resistant maize inbred line. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2014; 127:867-80. [PMID: 24500307 DOI: 10.1007/s00122-014-2263-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2013] [Accepted: 01/03/2014] [Indexed: 05/11/2023]
Abstract
Novel and previously known resistance loci for six phylogenetically diverse viruses were tightly clustered on chromosomes 2, 3, 6 and 10 in the multiply virus-resistant maize inbred line, Oh1VI. Virus diseases in maize can cause severe yield reductions that threaten crop production and food supplies in some regions of the world. Genetic resistance to different viruses has been characterized in maize populations in diverse environments using different screening techniques, and resistance loci have been mapped to all maize chromosomes. The maize inbred line, Oh1VI, is resistant to at least ten viruses, including viruses in five different families. To determine the genes and inheritance mechanisms responsible for the multiple virus resistance in this line, F1 hybrids, F2 progeny and a recombinant inbred line (RIL) population derived from a cross of Oh1VI and the virus-susceptible inbred line Oh28 were evaluated. Progeny were screened for their responses to Maize dwarf mosaic virus, Sugarcane mosaic virus, Wheat streak mosaic virus, Maize chlorotic dwarf virus, Maize fine streak virus, and Maize mosaic virus. Depending on the virus, dominant, recessive, or additive gene effects were responsible for the resistance observed in F1 plants. One to three gene models explained the observed segregation of resistance in the F2 generation for all six viruses. Composite interval mapping in the RIL population identified 17 resistance QTLs associated with the six viruses. Of these, 15 were clustered in specific regions of chr. 2, 3, 6, and 10. It is unknown whether these QTL clusters contain single or multiple virus resistance genes, but the coupling phase linkage of genes conferring resistance to multiple virus diseases in this population could facilitate breeding efforts to develop multi-virus resistant crops.
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Affiliation(s)
- Jose Luis Zambrano
- Department of Horticulture and Crop Science, The Ohio State University-Ohio Agriculture Research and Development Center (OSU-OARDC), Wooster, OH, 44691, USA
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Lebeau A, Gouy M, Daunay MC, Wicker E, Chiroleu F, Prior P, Frary A, Dintinger J. Genetic mapping of a major dominant gene for resistance to Ralstonia solanacearum in eggplant. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2013; 126:143-58. [PMID: 22930132 DOI: 10.1007/s00122-012-1969-5] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2012] [Accepted: 08/16/2012] [Indexed: 05/24/2023]
Abstract
Resistance of eggplant against Ralstonia solanacearum phylotype I strains was assessed in a F(6) population of recombinant inbred lines (RILs) derived from a intra-specific cross between S. melongena MM738 (susceptible) and AG91-25 (resistant). Resistance traits were determined as disease score, percentage of wilted plants, and stem-based bacterial colonization index, as assessed in greenhouse experiments conducted in Réunion Island, France. The AG91-25 resistance was highly efficient toward strains CMR134, PSS366 and GMI1000, but only partial toward the highly virulent strain PSS4. The partial resistance found against PSS4 was overcome under high inoculation pressure, with heritability estimates from 0.28 to 0.53, depending on the traits and season. A genetic map was built with 119 AFLP, SSR and SRAP markers positioned on 18 linkage groups (LG), for a total length of 884 cM, and used for quantitative trait loci (QTL) analysis. A major dominant gene, named ERs1, controlled the resistance to strains CMR134, PSS366, and GMI1000. Against strain PSS4, this gene was not detected, but a significant QTL involved in delay of disease progress was detected on another LG. The possible use of the major resistance gene ERs1 in marker-assisted selection and the prospects offered for academic studies of a possible gene for gene system controlling resistance to bacterial wilt in solanaceous plants are discussed.
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Affiliation(s)
- A Lebeau
- CIRAD, UMR Peuplements végétaux et Bioagresseurs en Milieu Tropical (PVBMT), 7 chemin de l'IRAT, 97410 Saint Pierre, La Réunion, France
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Luan J, Wang F, Li Y, Zhang B, Zhang J. Mapping quantitative trait loci conferring resistance to rice black-streaked virus in maize (Zea mays L.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2012; 125:781-791. [PMID: 22562145 DOI: 10.1007/s00122-012-1871-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2011] [Accepted: 04/10/2012] [Indexed: 05/31/2023]
Abstract
Maize rough dwarf disease (MRDD) is one of the most serious virus diseases of maize worldwide, and it causes great reduction of maize production. In China, the pathogen was shown to be rice black-streaked virus (RBSDV). Currently, MRDD has spread broadly and leads to significant loss in China. However, there has been little research devoted to this disease. Our aims were to identify the markers and loci underlying resistance to this virus disease. In this study, segregation populations were constructed from two maize elite lines '90110', which is highly resistant to MRDD and 'Ye478', which is highly susceptible to MRDD. The F(2) and BC(1) populations were used for bulk sergeant analysis (BSA) to identify resistance-related markers. One hundred and twenty F(7:9) RILs were used for quantitative trait loci (QTL) mapping through the experiment of multiple environments over 3 years. Natural occurrence and artificial inoculation were both used and combined to determine the phenotype of plants. Five QTL, qMRD2, qMRD6, qMRD7, qMRD8 and qMRD10 were measured in the experiments. The qMRD8 on chromosome 8 was proved to be one major QTL conferring resistance to RBSDV disease in almost all traits and environments, which explained 12.0-28.9 % of the phenotypic variance for disease severity in this present study.
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Affiliation(s)
- Junwen Luan
- School of Life Sciences, Shandong University, Jinan, China
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Ingvardsen CR, Xing Y, Frei UK, Lübberstedt T. Genetic and physical fine mapping of Scmv2, a potyvirus resistance gene in maize. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2010; 120:1621-34. [PMID: 20155410 DOI: 10.1007/s00122-010-1281-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2009] [Accepted: 01/24/2010] [Indexed: 05/08/2023]
Abstract
Sugarcane mosaic virus (SCMV) is an important virus pathogen both in European and Chinese maize production, causing serious losses in grain and forage yield in susceptible cultivars. Two major resistance loci confer resistance to SCMV, one located on chromosome 3 (Scmv2) and one on chromosome 6 (Scmv1). We developed a large isogenic mapping population segregating in the Scmv2, but not the Scmv1 region, to minimize genetic variation potentially affecting expression of SCMV resistance. We fine mapped Scmv2 to a region of 0.28 cM, covering a physical distance of 1.3426 Mb, and developed six new polymorphic SSR markers based on publicly available BAC sequences within this region. At present, we still have three recombinants left between Scmv2 and the nearest polymorphic marker on either side of the Scmv2 locus. The region showed synteny to a 1.6 Mb long sequence on chromosome 12 in rice. Analysis of the public B73 BAC library as well as the syntenic rice region did not reveal any similarity to known resistance genes. However, four new candidate genes with a possible involvement in movement of virus were detected.
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Affiliation(s)
- Christina Roenn Ingvardsen
- Department of Genetics and Biotechnology, Faculty of Agricultural Sciences, University of Aarhus, Forsøgsvej 1, 4200, Slagelse, Denmark.
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Huang CW, Cheng YS, Rouvier R, Yang KT, Wu CP, Huang HL, Huang MC. Duck (Anas platyrhynchos) linkage mapping by AFLP fingerprinting. Genet Sel Evol 2009; 41:28. [PMID: 19291328 PMCID: PMC2666072 DOI: 10.1186/1297-9686-41-28] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2009] [Accepted: 03/17/2009] [Indexed: 11/10/2022] Open
Abstract
Amplified fragment length polymorphism (AFLP) with multicolored fluorescent molecular markers was used to analyze duck (Anas platyrhynchos) genomic DNA and to construct the first AFLP genetic linkage map. These markers were developed and genotyped in 766 F2 individuals from six families from a cross between two different selected duck lines, brown Tsaiya and Pekin. Two hundred and ninety-six polymorphic bands (64% of all bands) were detected using 18 pairs of fluorescent TaqI/EcoRI primer combinations. Each primer set produced a range of 7 to 29 fragments in the reactions, and generated on average 16.4 polymorphic bands. The AFLP linkage map included 260 co-dominant markers distributed in 32 linkage groups. Twenty-one co-dominant markers were not linked with any other marker. Each linkage group contained three to 63 molecular markers and their size ranged between 19.0 cM and 171.9 cM. This AFLP linkage map provides important information for establishing a duck chromosome map, for mapping quantitative trait loci (QTL mapping) and for breeding applications.
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Affiliation(s)
- Chang-Wen Huang
- Department of Animal Science, National Chung Hsing University, 250 Kuo-Kung Road, Taichung 402, Taiwan
- Institute of Cellular and Organism Biology, Academia Sinica, 128 Section 2, Academia Road, Nankang, Taipei 115, Taiwan
| | - Yu-Shin Cheng
- Livestock Research Institute, Council of Agriculture, Hsin-Hua, Tainan 712, Taiwan
| | - Roger Rouvier
- Institut National de la Recherche Agronomique, Station d'Amélioration Génétique des Animaux, Centre de Recherches de Toulouse, BP52627, F31326 Castanet-Tolosan Cedex, France
| | - Kuo-Tai Yang
- Department of Animal Science, National Chung Hsing University, 250 Kuo-Kung Road, Taichung 402, Taiwan
- Institute of Biomedical Sciences, Academia Sinica, 128 Section 2, Academia Road, Nankang, Taipei 115, Taiwan
| | - Chean-Ping Wu
- Department of Animal Science, National Chung Hsing University, 250 Kuo-Kung Road, Taichung 402, Taiwan
- Department of Animal Science, National Chiayi University, 300 Syuefu Road, Chiayi 600, Taiwan
| | - Hsiu-Lin Huang
- Department of Animal Science, National Chung Hsing University, 250 Kuo-Kung Road, Taichung 402, Taiwan
| | - Mu-Chiou Huang
- Department of Animal Science, National Chung Hsing University, 250 Kuo-Kung Road, Taichung 402, Taiwan
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Maule AJ, Caranta C, Boulton MI. Sources of natural resistance to plant viruses: status and prospects. MOLECULAR PLANT PATHOLOGY 2007; 8:223-31. [PMID: 20507494 DOI: 10.1111/j.1364-3703.2007.00386.x] [Citation(s) in RCA: 88] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
SUMMARY Globally, virus diseases are common in agricultural crops and have a major agronomic impact. They are countered through the deployment of genetic resistance against the virus, or through the use of a range of farming practices based upon the propagation of virus-free plant material and the exclusion of the virus vectors from the growing crop. We review here the current status of our knowledge of natural virus resistance genes, and consider the future prospects for the deployment of these genes against virus infection.
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Affiliation(s)
- Andrew J Maule
- John Innes Centre, Norwich Research Park, Colney, Norwich NR4 7UH, UK
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