Precision Phenotyping Reveals Novel Loci for Quantitative Resistance to Septoria Tritici Blotch

Accurate, high-throughput phenotyping for quantitative traits is a limiting factor for progress in plant breeding. We developed an automated image analysis to measure quantitative resistance to septoria tritici blotch (STB), a globally important wheat disease, enabling identification of small chromosome intervals containing plausible candidate genes for STB resistance. 335 winter wheat cultivars were included in a replicated field experiment that experienced natural epidemic development by a highly diverse but fungicide-resistant pathogen population. More than 5.4 million automatically generated phenotypes were associated with 13,648 SNP markers to perform the GWAS. We identified 26 chromosome intervals explaining 1.9-10.6% of the variance associated with four independent resistance traits. Sixteen of the intervals overlapped with known STB resistance intervals, suggesting that our phenotyping approach can identify simultaneously (i.e., in a single experiment) many previously defined STB resistance intervals. Seventeen of the intervals were less than 5 Mbp in size and encoded only 173 genes, including many genes associated with disease resistance. Five intervals contained four or fewer genes, providing high priority targets for functional validation. Ten chromosome intervals were not previously associated with STB resistance, perhaps representing resistance to pathogen strains that had not been tested in earlier experiments. The SNP markers associated with these chromosome intervals can be used to recombine different forms of quantitative STB resistance that are likely to be more durable than pyramids of major resistance genes. Our experiment illustrates how high-throughput automated phenotyping can accelerate breeding for quantitative disease resistance.

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Precision phenotyping reveals novel loci for quantitative resistance to septoria tritici blotch in European winter wheat

10.1101/502260 ◽

2018 ◽

Cited By ~ 1

Author(s):

Steven Yates ◽

Alexey Mikaberidze ◽

Simon Krattinger ◽

Michael Abrouk ◽

Andreas Hund ◽

...

Keyword(s):

Disease Resistance ◽

Winter Wheat ◽

High Throughput ◽

Quantitative Resistance ◽

Small Chromosome ◽

Snp Markers ◽

Automated Image Analysis ◽

Septoria Tritici Blotch ◽

Septoria Tritici ◽

Limiting Factor

Accurate, high-throughput phenotyping for quantitative traits is the limiting factor for progress in plant breeding. We developed automated image analysis to measure quantitative resistance to septoria tritici blotch (STB), a globally important wheat disease, enabling identification of small chromosome intervals containing plausible candidate genes for STB resistance. 335 winter wheat cultivars were included in a replicated field experiment that experienced natural epidemic development by a highly diverse but fungicide-resistant pathogen population. More than 5.4 million automatically generated phenotypes were associated with 13,648 SNP markers to perform a GWAS. We identified 26 chromosome intervals explaining 1.9-10.6% of the variance associated with four resistance traits. Seventeen of the intervals were less than 5 Mbp in size and encoded only 173 genes, including many genes associated with disease resistance. Five intervals contained four or fewer genes, providing high priority targets for functional validation. Ten chromosome intervals were not previously associated with STB resistance. Our experiment illustrates how high-throughput automated phenotyping can accelerate breeding for quantitative disease resistance. The SNP markers associated with these chromosome intervals can be used to recombine different forms of quantitative STB resistance that are likely to be more durable than pyramids of major resistance genes.

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Measuring Quantitative Virulence in the Wheat Pathogen Zymoseptoria tritici Using High-Throughput Automated Image Analysis

Phytopathology ◽

10.1094/phyto-11-13-0328-r ◽

2014 ◽

Vol 104 (9) ◽

pp. 985-992 ◽

Cited By ~ 57

Author(s):

Ethan L. Stewart ◽

Bruce A. McDonald

Keyword(s):

Image Analysis ◽

High Throughput ◽

Digital Image ◽

Digital Image Analysis ◽

Continuous Distribution ◽

Automated Image Analysis ◽

Host Specialization ◽

Septoria Tritici Blotch ◽

Septoria Tritici ◽

Zymoseptoria Tritici

Zymoseptoria tritici, causal agent of Septoria tritici blotch on wheat, produces pycnidia in chlorotic and necrotic lesions on infected leaves. A high-throughput phenotyping method was developed based on automated digital image analysis that accurately measures the percentage of leaf area covered by lesions (PLACL) as well as pycnidia size and number. A seedling inoculation assay was conducted using 361 Z. tritici isolates originating from a controlled cross and two different winter wheat cultivars. Pycnidia size and density were found to be quantitative traits that showed a continuous distribution in the progeny. There was a weak correlation between pycnidia density and size (r = −0.27) and between pycnidia density and PLACL (r = 0.37). There were significant differences in PLACL and pycnidia density on resistant and susceptible cultivars. In all, >20% of the offspring exhibited significantly different pycnidia density on the two cultivars, consistent with host specialization. Automated image analysis provided greater accuracy and precision compared with traditional visual estimates of virulence. These results show that digital image analysis provides a powerful tool for measuring differences in quantitative virulence among strains of Z. tritici.

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Resistance of the Wheat Cultivar ‘Renan’ to Septoria Leaf Blotch Explained by a Combination of Strain Specific and Strain Non-Specific QTL Mapped on an Ultra-Dense Genetic Map

Genes ◽

10.3390/genes13010100 ◽

2021 ◽

Vol 13 (1) ◽

pp. 100

Author(s):

Camilla Langlands-Perry ◽

Murielle Cuenin ◽

Christophe Bergez ◽

Safa Ben Krima ◽

Sandrine Gélisse ◽

...

Keyword(s):

Genetic Map ◽

Quantitative Resistance ◽

Kinase Domain ◽

Snp Markers ◽

Septoria Tritici Blotch ◽

Septoria Tritici ◽

Zymoseptoria Tritici ◽

Major Resistance Genes ◽

Pathogen Populations ◽

Leucine Rich Repeats

Quantitative resistance is considered more durable than qualitative resistance as it does not involve major resistance genes that can be easily overcome by pathogen populations, but rather a combination of genes with a lower individual effect. This durability means that quantitative resistance could be an interesting tool for breeding crops that would not systematically require phytosanitary products. Quantitative resistance has yet to reveal all of its intricacies. Here, we delve into the case of the wheat/Septoria tritici blotch (STB) pathosystem. Using a population resulting from a cross between French cultivar Renan, generally resistant to STB, and Chinese Spring, a cultivar susceptible to the disease, we built an ultra-dense genetic map that carries 148,820 single nucleotide polymorphism (SNP) markers. Phenotyping the interaction was done with two different Zymoseptoria tritici strains with contrasted pathogenicities on Renan. A linkage analysis led to the detection of three quantitative trait loci (QTL) related to resistance in Renan. These QTL, on chromosomes 7B, 1D, and 5D, present with an interesting diversity as that on 7B was detected with both fungal strains, while those on 1D and 5D were strain-specific. The resistance on 7B was located in the region of Stb8 and the resistance on 1D colocalized with Stb19. However, the resistance on 5D was new, so further designated Stb20q. Several wall-associated kinases (WAK), nucleotide-binding and leucine-rich repeats (NB-LRR) type, and kinase domain carrying genes were present in the QTL regions, and some of them were expressed during the infection. These results advocate for a role of Stb genes in quantitative resistance and for resistance in the wheat/STB pathosystem being as a whole quantitative and polygenic.

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Ranking Quantitative Resistance to Septoria tritici Blotch in Elite Wheat Cultivars Using Automated Image Analysis

Phytopathology ◽

10.1094/phyto-04-17-0163-r ◽

2018 ◽

Vol 108 (5) ◽

pp. 568-581 ◽

Cited By ~ 32

Author(s):

Petteri Karisto ◽

Andreas Hund ◽

Kang Yu ◽

Jonas Anderegg ◽

Achim Walter ◽

...

Keyword(s):

Image Analysis ◽

Quantitative Resistance ◽

Major Gene ◽

Growing Season ◽

Automated Image Analysis ◽

Septoria Tritici Blotch ◽

Septoria Tritici ◽

Wheat Cultivars ◽

Zymoseptoria Tritici ◽

Breeding Programs

Quantitative resistance is likely to be more durable than major gene resistance for controlling Septoria tritici blotch (STB) on wheat. Earlier studies hypothesized that resistance affecting the degree of host damage, as measured by the percentage of leaf area covered by STB lesions, is distinct from resistance that affects pathogen reproduction, as measured by the density of pycnidia produced within lesions. We tested this hypothesis using a collection of 335 elite European winter wheat cultivars that was naturally infected by a diverse population of Zymoseptoria tritici in a replicated field experiment. We used automated image analysis of 21,420 scanned wheat leaves to obtain quantitative measures of conditional STB intensity that were precise, objective, and reproducible. These measures allowed us to explicitly separate resistance affecting host damage from resistance affecting pathogen reproduction, enabling us to confirm that these resistance traits are largely independent. The cultivar rankings based on host damage were different from the rankings based on pathogen reproduction, indicating that the two forms of resistance should be considered separately in breeding programs aiming to increase STB resistance. We hypothesize that these different forms of resistance are under separate genetic control, enabling them to be recombined to form new cultivars that are highly resistant to STB. We found a significant correlation between rankings based on automated image analysis and rankings based on traditional visual scoring, suggesting that image analysis can complement conventional measurements of STB resistance, based largely on host damage, while enabling a much more precise measure of pathogen reproduction. We showed that measures of pathogen reproduction early in the growing season were the best predictors of host damage late in the growing season, illustrating the importance of breeding for resistance that reduces pathogen reproduction in order to minimize yield losses caused by STB. These data can already be used by breeding programs to choose wheat cultivars that are broadly resistant to naturally diverse Z. tritici populations according to the different classes of resistance.

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An Improved Method for Measuring Quantitative Resistance to the Wheat Pathogen Zymoseptoria tritici Using High-Throughput Automated Image Analysis

Phytopathology ◽

10.1094/phyto-01-16-0018-r ◽

2016 ◽

Vol 106 (7) ◽

pp. 782-788 ◽

Cited By ~ 38

Author(s):

Ethan L. Stewart ◽

Christina H. Hagerty ◽

Alexey Mikaberidze ◽

Christopher C. Mundt ◽

Ziming Zhong ◽

...

Keyword(s):

Image Analysis ◽

Quantitative Resistance ◽

Recombinant Inbred Lines ◽

Continuous Distribution ◽

Field Resistance ◽

Automated Image Analysis ◽

Septoria Tritici Blotch ◽

Septoria Tritici ◽

Improved Method ◽

Zymoseptoria Tritici

Zymoseptoria tritici causes Septoria tritici blotch (STB) on wheat. An improved method of quantifying STB symptoms was developed based on automated analysis of diseased leaf images made using a flatbed scanner. Naturally infected leaves (n = 949) sampled from fungicide-treated field plots comprising 39 wheat cultivars grown in Switzerland and 9 recombinant inbred lines (RIL) grown in Oregon were included in these analyses. Measures of quantitative resistance were percent leaf area covered by lesions, pycnidia size and gray value, and pycnidia density per leaf and lesion. These measures were obtained automatically with a batch-processing macro utilizing the image-processing software ImageJ. All phenotypes in both locations showed a continuous distribution, as expected for a quantitative trait. The trait distributions at both sites were largely overlapping even though the field and host environments were quite different. Cultivars and RILs could be assigned to two or more statistically different groups for each measured phenotype. Traditional visual assessments of field resistance were highly correlated with quantitative resistance measures based on image analysis for the Oregon RILs. These results show that automated image analysis provides a promising tool for assessing quantitative resistance to Z. tritici under field conditions.

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Ranking quantitative resistance to Septoria tritici blotch in elite wheat cultivars using automated image analysis

10.1101/129353 ◽

2017 ◽

Cited By ~ 2

Author(s):

Petteri Karisto ◽

Andreas Hund ◽

Kang Yu ◽

Jonas Anderegg ◽

Achim Walter ◽

...

Keyword(s):

Image Analysis ◽

Quantitative Resistance ◽

Major Gene ◽

Growing Season ◽

Automated Image Analysis ◽

Septoria Tritici Blotch ◽

Septoria Tritici ◽

Wheat Cultivars ◽

Zymoseptoria Tritici ◽

Breeding Programs

AbstractQuantitative resistance is likely to be more durable than major gene resistance for controlling Septoria tritici blotch (STB) on wheat. Earlier studies hypothesized that resistance affecting the degree of host damage, as measured by the percentage of leaf area covered by STB lesions, is distinct from resistance that affects pathogen reproduction, as measured by the density of pycnidia produced within lesions. We tested this hypothesis using a collection of 335 elite European winter wheat cultivars that was naturally infected by a diverse population of Zymoseptoria tritici in a replicated field experiment. We used automated image analysis (AIA) of 21420 scanned wheat leaves to obtain quantitative measures of conditional STB intensity that were precise, objective, and reproducible. These measures allowed us to explicitly separate resistance affecting host damage from resistance affecting pathogen reproduction, enabling us to confirm that these resistance traits are largely independent. The cultivar rankings based on host damage were different from the rankings based on pathogen reproduction, indicating that the two forms of resistance should be considered separately in breeding programs aiming to increase STB resistance. We hypothesize that these different forms of resistance are under separate genetic control, enabling them to be recombined to form new cultivars that are highly resistant to STB. We found a significant correlation between rankings based on automated image analysis and rankings based on traditional visual scoring, suggesting that image analysis can complement conventional measurements of STB resistance, based largely on host damage, while enabling a much more precise measure of pathogen reproduction. We showed that measures of pathogen reproduction early in the growing season were the best predictors of host damage late in the growing season, illustrating the importance of breeding for resistance that reduces pathogen reproduction in order to minimize yield losses caused by STB. These data can already be used by breeding programs to choose wheat cultivars that are broadly resistant to naturally diverse Z. tritici populations according to the different classes of resistance.

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Meta-Analysis Reveals Consensus Genomic Regions Associated with Multiple Disease Resistance in Wheat ( Triticum Aestivum L.)

10.21203/rs.3.rs-773587/v1 ◽

2021 ◽

Author(s):

Dinesh Kumar Saini ◽

Amneek Chahal ◽

Neeraj Pal ◽

Puja Srivast ◽

Pushpendra Kumar Gupta

Keyword(s):

Disease Resistance ◽

Physical Map ◽

Association Studies ◽

Meta Analysis ◽

Septoria Tritici Blotch ◽

Septoria Tritici ◽

Karnal Bunt ◽

Genome Wide Association Studies ◽

Head Blight ◽

Multiple Disease Resistance

Abstract In wheat, meta-QTLs (MQTLs), and candidate genes (CGs) were identified for multiple disease resistance (MDR). For this purpose, information was collected from 58 studies for mapping QTLs for resistance to one or more of the five diseases. As many as 493 QTLs were available from these studies, which were distributed in five diseases as follows: septoria tritici blotch (STB) 126 QTLs; septoria nodorum blotch (SNB), 103; fusarium head blight (FHB), 184; karnal bunt (KB), 66, and loose smut (LS), 14. Of these 493 QTLs, only 291 QTLs could be projected onto a consensus genetic map, giving 63 MQTLs. The CI of the MQTLs ranged from 0.04 to 15.31 cM with an average of 3.09 cM per MQTL. This is a ~ 4.39 fold reduction from the CI of initial QTLs, which ranged from 0 to 197.6 cM, with a mean of 13.57 cM. Of 63 MQTLs, 60 were anchored to the reference physical map of wheat (the physical interval of these MQTLs ranged from 0.30 to 726.01 Mb with an average of 74.09 Mb). Thirty-eight (38) of these MQTLs were verified using marker-trait associations (MTAs) derived from genome-wide association studies. As many as 874 CGs were also identified which were further investigated for differential expression using data from five transcriptome studies, resulting in 194 differentially expressed genes (DEGs). Among the DEGs, 85 genes had functions previously reported to be associated with disease resistance. These results should prove useful for fine mapping of MDR genes and marker-assisted breeding.

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Advances in breeding techniques for durable Septoria tritici blotch (STB) resistance in cereals

10.19103/as.2021.0092.12 ◽

2021 ◽

pp. 303-356

Author(s):

Harsh Raman ◽

Keyword(s):

Quantitative Resistance ◽

Durable Resistance ◽

Genetic Resistance ◽

Septoria Tritici Blotch ◽

Septoria Tritici ◽

Zymoseptoria Tritici ◽

Winter Cereal ◽

Cereal Breeding ◽

Qualitative Resistance ◽

Breeding Techniques

Septoria tritici blotch (STB), caused by the hemibiotrophic fungus Zymoseptoria tritici, is one of the most important foliar diseases of winter cereal crops. Recent advances are helping to understand the genetic basis and architecture of resistance to STB. To date, at least 22 genes for qualitative resistance and over 200 quantitative trait loci (QTL) for quantitative resistance have been identified in cereals. This knowledge is enabling cereal breeding programs to develop varieties with more durable resistance to STB. This chapter reviews recent research on genetic resistance loci and breeding strategies based on both conventional and biotechnology-based breeding approaches (molecular marker/genomic-assisted breeding, genetic transformation, and gene-editing) to achieve achieving durable resistance to STB infection and minimise grain yield losses.

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Contributions of disease resistance and escape to the control of septoria tritici blotch of wheat

Plant Pathology ◽

10.1111/j.1365-3059.2009.02118.x ◽

2009 ◽

Vol 58 (5) ◽

pp. 910-922 ◽

Cited By ~ 50

Author(s):

L. S. Arraiano ◽

N. Balaam ◽

P. M. Fenwick ◽

C. Chapman ◽

D. Feuerhelm ◽

...

Keyword(s):

Disease Resistance ◽

Septoria Tritici Blotch ◽

Septoria Tritici

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Mining synthetic hexaploids for multiple disease resistance to improve bread wheat

Australian Journal of Agricultural Research ◽

10.1071/ar07227 ◽

2008 ◽

Vol 59 (5) ◽

pp. 421 ◽

Cited By ~ 24

Author(s):

F. C. Ogbonnaya ◽

M. Imtiaz ◽

H. S. Bariana ◽

M. McLean ◽

M. M. Shankar ◽

...

Keyword(s):

Disease Resistance ◽

Leaf Rust ◽

Resistance Gene ◽

Bread Wheat ◽

Stripe Rust ◽

Stem Rust ◽

Wheat Yield ◽

Septoria Tritici Blotch ◽

Septoria Tritici ◽

Seedling Resistance

A collection of 253 synthetic hexaploid wheats (SHWs) produced from 192 Aegilops tauschii accessions and 39 elite durum varieties were studied to identify, characterise, and evaluate potentially untapped diversity of disease resistance in wheat. The diseases for which resistance was sought included cereal cyst nematode (CCN), root lesion nematode (RLN), Stagonospora nodorum blotch (SNB), Septoria tritici blotch (STB), and the 3 rusts, leaf rust, stem rust, and stripe rust, all important diseases of bread wheat worldwide, which can severely reduce wheat yield and quality. The SHWs exhibited a wide spectrum of resistance to the 8 pathogens. The frequency of disease-resistant SHWs ranged from 1% for one species of RLN (Pratylenchus neglectus), 3% and 10% for Septoria nodorum leaf and glume blotch, 10% for seedling resistance to yellow leaf spot, 16% for CCN, 21% for the second species of RLN (Pratylenchus thornei), 73% for Septoria tritici blotch, and 15%, 40%, and 24% for leaf rust, stem rust, and stripe rust, respectively. Five SHWs, Aus26860, Aus30258, Aus30294, Aus30301, and Aus30304, exhibited high levels of resistance to CCN, YLP, STB, LR, and SR, while 56 SHWs showed resistance to either 3 or 4 diseases. The genetics of resistance to CCN in some of the SHWs revealed that some of the accessions carry the same CCN gene(s) against pathotype Ha13, while others may carry different resistance gene(s). Additional studies were carried out to understand the relationship between the resistances identified in SHWs and the ones already present in common wheat, in particular the resistance genes Cre1 and Cre3 against CCN. The use of perfect markers associated with Cre1 and Cre3 suggested that some SHWs may carry a new CCN resistance gene(s), which could be deployed in breeding programs to increase the diversity of available resistance. The identification of SHWs with resistance to a range of diseases provides an opportunity to generate genetic knowledge and resistant germplasm to be used in future variety development.

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