Molecular mapping of qualitative genes for resistance to
1. Introduction
Blackleg disease caused by the heterothallic ascomycete fungus
Among the bacterial, fungal, viral and phytoplasmic-like diseases, blackleg is the most important global disease of
2. Symptoms
Blackleg disease causes two distinct symptoms; leaf lesions and stem canker. Outbreak of the fungus is characterised by dirty-whitish spots on leaves with small dark fruiting bodies (pycnidia). Black lesions are generally also seen on the leaves and deep brown lesions with a dark margin can be seen on the base of stem [11]. In severe epidemic conditions fungus girdles the stem at the crown, leading to lodging of the plant and possible severance of the stem. Typical lesions of blackleg can also occur on pods. Pod infection may leads to premature pod shatter and seed infection.
3. Biology of the pathogen and epidemiology of the L. maculans
The pathogen can infect several crucifers, including cruciferous weeds. Up to 28 crucifer species have been reported as hosts [14]. During infection, the pathogen grows systemically down towards the tap root of the plant, producing severe disease symptoms at the adult plant stage characterised by stem cankers.
In Australia and most parts of Europe,
4. Management of the L. maculans
Various practices such as crop rotation, stubble management, time of sowing, seed dressing and foliar application of fungicide, and deployment of genetic resistance have been employed to control this disease and subsequently reduce yield losses [9, 29]. Deployment of host resistance has been used as the most cost-effective and environmentally sound measure for disease control in various crops including in rapeseed. This strategy has been extensively used to manage blackleg disease especially in Australia, Canada, France, and Germany.
5. Evaluation of germplasm for L. maculans resistance
An efficient and reliable method for phenotyping resistance to
Resistance of
Doubled haploid (DH) populations were screened for resistance to
Assessment of adult plants for resistance to
Assessment of blackleg resistance under field conditions is usually performed by exposing the plants to a mixed population of
6. Natural genetic variation for resistance to L. maculans
The introgression of blackleg resistance (
It has been reported that all B genome Brassica species;
Genetic resources for adult plant resistance are very limited and most of them are derived from the French cultivar Jet Neuf [62]. Efforts are currently being made to identify both qualitative and quantitative resistance in the Australian Brassica Germplasm Improvement Programs.
7. Inheritance of resistance to L. maculans
Genetic inheritance studies revealed that resistance to
7.1. Qualitative resistance
Monogenic inheritance was reported in several spring and winter cultivars of
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Maxol/S006 (140 DH) |
Cotyledon inoculation | RAPD | Bulked segregant analysis | A7 | T04.680 (14cM) | 74 |
Quinta/Score (110 F2) |
Cotyledon inoculation | RAPD | Bulked segregant analysis | A7 | C02.1375/O15.1360 (19cM) | 57, 74 | ||
Maxol/Westar-10 (96 DH) |
Cotyledon inoculation and stem canker | SSR, DArT | Whole genome mapping | A7 | Xna12a-02a/Xra2-a05b | 82 | ||
Columbus/Westar-10 | Cotyledon inoculation and stem canker | SSR | A7 chromosome specific mapping | A7 | Xol12-e03a/Xna12-a02a | 82 | ||
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Glacier/Score (110 F2) | Cotyledon inoculation | RAPD | Bulked segregant analysis | A7 | M08.1200, M08.600, P02.700 |
57, 74 |
Glacier/Yudal (BC189) | Cotyledon inoculation | RAPD | Bulked segregant analysis | A7 | M08.1200, M08.600, P02.700 | 74 | ||
Darmor/Samourai (133 DH) | Cotyledon, Field | RAPD | Bulked segregant analysis | A7 | M08.1200 (10cM), | 74 | ||
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Maxol/S006 (140DH) | Cotyledon inoculation | RAPD | Bulked segregant analysis | A7 | Q12.750 (7cM) | 74 |
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Quinta/Score (110F2) | Cotyledon inoculation | RAPD | Bulked segregant analysis | A7 | C02.1375 (3.6 cM)/ O15.1360 (`33 cM) |
74 |
Skipton/Ag-Spectrum | Cotyledon and Stem canker | SSR | Whole genome mapping | BRMS075 (`0.7 cM) | 32 | |||
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Recombinant lines ( |
Cotyledon and field test | RAPD/ RFLP |
Bulked segregant analysis | B8 | OPG02.800, OPT01 | 47 |
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2311.1/Darmor (221 F2) |
Cotyledon | RAPD | Bulked segregant analysis | A7 | T12.650 (4cM) | 74, 85 |
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Darmor-bzh/Yudal (132 DH) |
Cotyledon | RAPD | Bulked segregant analysis | A7 | T12.650/C02.1375 | 74 |
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Addition lines (Darmor/Junius) |
Cotyledon test | Isozyme RAPD |
Whole genome mapping | B4 | OPA11.1200, OPC19.3300 | 83, 84 |
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6270/Springfield (DHP95) | Cotyledon inoculation and field resistance | RFLP | Whole genome analysis | A2 (N2) | pR4b, pO85h, pW180b, pN181a, pW207a | 31 |
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6279/3027 (DHP96) | Cotyledon inoculation and field resistance | RFLP | Whole genome analysis | A10 (N10) | pN21b, pR34b, pN53b | 31 |
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Surpass400/Westar (N-o-1)-BC |
Cotyledon inoculation | SSR | A1 and A10 chromosome specific mapping | sR12281a (2.2 cM) sN2428Rb (0.7 cM) |
69 | |
Topas (DH16516)/Surpass400 | Cotyledon inoculaton | SSR, SCAR | A10 chromosome specific mapping | A10 (N10) | Ind10-12 | 79 | ||
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16S/PAS12//16S (BC3S2) |
Cotyledon inoculation Disease nursery (field) |
SSR | A genome specific marker analysis | A6 | sN2189b (8.8cM) sR9571a (8.3 cM) |
77 |
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Surpass400/Westar (1513 F3BC2) | Cotyledon inoculation | SRAP, SNP | Selective genotyping | A10 (N10) | 80E24a (0.1 cM) | 70 |
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Surpass400/Westar (1513 F3BC2) | Cotyledon inoculation | SRAP, SNP | Selective genotyping | A10 (N10) | R278 (1.2 cM) | 70 |
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Cresor (resistant)/Westar (susceptible) | Field/artificial inoculation | RFLP | Whole genome analysis | Linkage group 6 (A7) | cDNA011/cDNA110 | 64 |
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Major (resistant)/Stellar (susceptible) | Cotyledon Stem inoculation |
RFLP | Whole genome analysis | A7 | TG5D9b/WG5A1A | 65 |
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Shiralee/90-3046 (153 DH lines) |
Cotyledon incoulation | RFLP, RAPD | Bulked segregant analysis | A7 | RAPD654 (~4.8cM) | 66 |
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Shiralee/PSA12 (BC1 lines) |
Cotyledon incoulation | RFLP, EST, SCAR | Bulked segregant analysis | A7 | est126M9a/est149M9d | 140 |
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DH12075/PSA12 (BC1 lines) |
Cotyledon incoulation | RFLP, EST, SCAR | Bulked segregant analysis | A7 | est126M9a/est149M9d | 140 |
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Maluka/90-3046 (34 DH lines) |
Cotyledon incoulation | RFLP, RAPD | Bulked segregant analysis | A7 | RAPD654 (~4.8cM) | 66 |
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Maluka/Westar | Cotyledon, Adult | RFLP, AFLP, RAPD | Bulked segregant analysis | A7 | 22-25 | 67 |
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RB87-62/Westar | Cotyledon, adult plant | RFLP, AFLP, RAPD | Bulked segregant analysis | A7 | 22-25 | 67 |
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Cresor/Westar | Cotyledon, adult plant | RFLP, AFLP, RAPD | Bulked segregant analysis | A7 | 22-25 | 67 |
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Skipton/Ag-Spectrum (DH) | Cotyledon incoulation | SSR | Whole genome analysis | A1 | Xpbcessrna16-Xbrms017b | 32 |
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Skipton/Ag-Spectrum (DH) | Cotyledon inoculation | SSR | Whole genome analysis | A10 | Xcb10079d-Xcb10079c | 32 |
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Westar/Dunkeld (F2) | Cotyledon inoculation | SRAP | Bulked segregant analysis | A7 | NA12A02-200/NA12A02-190, BG20SA12-480/BG20SA12-475/BN204 | 81 |
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150-2-1, 151-2-1, Aurea, Picra | Cotyledon inoculation | - | - | - | - | 71 |
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156-2-1 | Cotyledon inoculation | - | - | - | - | 71 |
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02-159-4-1 | Cotyledon inoculation | - | - | - | - | 72 |
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Surpass400 | Cotyledon inoculation | - | - | - | - | 73 |
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AC Vulcan/UM3132 (F2) |
Cotyledon test | RFLP, SSR | Whole genome mapping | J13 (B3) | PN199RV (22.1 cM), sBb31143F (8.7 CM) |
43 |
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AC Vulcan/UM3132 (F2) |
Cotyledon test | RFLP, SSR | Whole genome mapping | J18 (B8) | PN120cRI, sB1534 |
43 |
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B genome introgression lines | cotyledon | RAPD, RGA & SCAR | B genome-specific | not defined | B5-1520, C5-1000, RGALm | 80 |
Recently, two genes
7.2. Quantitative resistance
Quantitative inheritance for field resistance has been reported in segregating populations derived from
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Av-Sapphire/Westar10 |
Lake Bolac, Australia |
E34M15_S190/E35M53_S416 | A1 | 2.5-5.6 | 14-16 | Not known (-) | 86* |
E34M15_S218/E35M53_S350 | A2 | 1.3-3.8 | 4-26 | - | |||
Dahlen, Australia | CB10443_W258_S269 | C1 | 0.8-2.9 | 3-8 | - | ||
Lake Bolac | E36M47_W197/E34M62_W127 | LG1 | 1.0-3.6 | 4-10 | - | ||
Caiman3/Westar |
Lake Bolac |
BRMS056/E34M50_W140 | A1 | 2.9-3.5 | 20-22.7 | - | 86* |
Dahlan | E35M53_C455/E34M15_W271 | A10 | 1.4-3.0 | 5-34 | - | ||
Not shown | C5 | 4.4-5.6 | 19-23 | - | |||
Camberra4/Westar | Lake Bolac | E36M55_C306/E33M57_C306 | A5 | 0.5-2.6 | 1.5-33 | - | 86* |
Dahlen | Na12D10_w203 | A1/C1 | 2.9-5.1 | 17-18 | - | ||
Lake Bolac | E36M62_W414/01ju1fE07_cl_3b | A10 | 0.3-2.7 | 2-31 | - | ||
Not shown | C7-2 | 2.7-3.7 | 13-24 | - | |||
E33M59_W107/E33M53_C75 | LG2 | 2.1-2.8 | 14-28 | - | |||
Darmor/Samourai |
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A1 | 2.3 | 6.7 | Samourai | 88 |
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A2 | 2.3-3.02 | 8.1-14.6 | Darmor | |||
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A6 | 1.9-2.8 | 6.2-10.0 | Samourai | |||
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A10 | 2.7 | 11.0 | Samourai | |||
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C2 | 2.0-2.2 | 8.0-8.4 | Darmor | |||
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C4 | 2.4-3.2 | 6.7-12.2 | Darmor | |||
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C8 | 1.9 | - | Samourai | |||
Darmor/Yudal |
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A2 | 2.4-5.5 | 3.8-8.5 | Darmor | 87 Delourme et al, 2008; comm. pers.) |
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A4 | 3.3 | 4.8 | Darmor | |||
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A6 | 5-12.2 | 7.2-20 | Darmor | |||
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A7 | 4.5 | 6.9 | Darmor | |||
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A8 | 7.2 | 13.0 | Darmor | |||
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A9 | 3.3 | 4.8 | Darmor | |||
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C2 | 5.5-6.6 | 8.3-13.3 | Yudal | |||
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C4 | 4.7-9.5 | 6.7-15.2 | Darmor | |||
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C8 | 4.2 | 6.2 | Darmor | |||
Rainbow/Av-Sapphire | Lake Bolac | E33M57_R105 | A9-2 | 3.7 | 13 | - | |
Skipton/Ag-Spectrum |
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A2 | 7.0 | 11.5 | Ag-Spectrum | 32 |
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A9 | 2.9 | 5.0 | Skipton | |||
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A10b | 2.2 | 6.2 | Skipton | |||
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C1 | 4.2 | 11.5 | Ag-Spectrum | |||
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C2a | 6.8 | 16.6 | Skipton | |||
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C3 | 4.2 | 24.5 | Skipton | |||
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C6 | 6.1 | 14.5 | Ag-Spectrum | |||
ATR Beacon stubble, Wagga, Australia |
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A1a | 6.1 | 26.1 | Ag-Spectrum |
8. Gene-for gene interactions
Host resistance genes (
At least ten
9. Alien gene introgression for blackleg resistance
Deployment of
Crouch
Using transgenic technology,
10. Durability of resistance to L. maculans
Durable disease resistance can be achieved by utilisation of one or more single dominant
Previous research has shown that different qualitative gene sources for resistance vary in providing effective durable resistance over period of time. For example, Light
Single resistance genes do not always provide a durable resistance as has been shown in a field experiment using the
11. Molecular dissection of qualitative and quantitative resistance loci
Molecular markers have been applied to identify loci associated with resistance to
Loci for resistance to
11.1. Qualitative resistance
The majority of genes for resistance to
A major gene named
Genomic regions of chromosome A10 harbours
The blackleg resistance gene
11.2. Quantitative resistance
The genetic basis of quantitative resistance has been investigated only in limited
In order to validate the stability of QTL for field resistance to
QTL for blackleg resistance were identified in four mapping populations derived from the crosses Caiman/Westar10, Camberra/Westar10, AVSapphire/Westar10 and Rainbow/AVSapphire [86]. Multiple QTLs were identified accounting for 13–33% of phenotypic variance. A recent study [32] identified seven significant QTL associated with blackleg resistance, scored on the basis of internal disease score, on chromosomes A2, A9, A10, C1, C2, C3 and C6 in a DH population derived from Skipton/Ag-Spectrum. The genotypic variation explained by the individual QTL ranged from 5% to 24.5%. Both parents contributed the alleles for blackleg resistance. This study showed poor correlation between canker lesion scores over the two years (2009, 2010). Some of the genomic regions for blackleg resistance may be the same as reported previously that have been identified using both classical QTL and association mapping approaches [31, 69, 87, 137, 144, 145]. The conservation of QTL between Australian and French studies is interesting and suggests the non-specificity of these QTL, irrespective of the environment, genetic background and G x E interactions [32]. However, it is possible that some of the original donor gene sources in French and Australian parental lines used for mapping resistance genes may be the same.
The majority of mapping populations used to map blackleg resistance genes in
12. Host R -gene cloning and candidate gene analysis
At least 20
In
In order to clone genes controlling blackleg resistance in
Recently an alternative approach for identifying candidate
13. Predictive breeding for resistance to L. maculans using molecular markers
Success of new disease resistance genes relies heavily on the successful transfer of target genomic regions from donor sources and the development of rigorous selection methods. Molecular markers have been used to improve the effectiveness and efficiency of selection strategies in predictive breeding in several agricultural crops. However, the development of molecular markers in
In most of the breeding programs, selection for blackleg is conducted once a year during the growing season, hampering selection efficiency. Several studies suggest a significant correlation between cotyledon test and canker lesion scores. Therefore, cotyledon tests can be used for selection for resistance to
The published literature suggests that little effort has been made to evaluate the allelic relationship among the known genes from different sources, to test stability of majority of QTL or qualitative genes identified over diverse growing environments, or to test their usefulness in achieving long term durable control of the disease. Table 1 also suggests that majority of markers are not very closely linked (<1cM) with resistance loci. Diagnostic or perfect markers for resistance genes are required for routine MAS and will assist allele enrichment strategies in breeding programs, although this is not always possible, even if the complete gene is cloned and characterised for its functionality [187]. The linkage between molecular markers and
14. Conclusions
It is now clear that major resistance genes will be overcome in time, as has been seen in many crop plants. Therefore, there is constant need to identify new sources of both qualitative and quantitative resistance loci and to properly utilise the resources available to us so that resistance can be deployed long term. Recent advances in molecular marker systems, such as the development of highly-parallel systems for genotyping and sequencing, have created new opportunities and strategies to select for qualitative and quantitative traits, including resistance to
Acknowledgments
Authors are thankful to Dr Regine Delourme, INRA, Le Rheu, Cedex France for providing critical comments and QTL information for quantitative resistance in the Darmor/Yudal population.
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