Chia-Lin Chung

Resistance loci affecting distinct stages of fungal pathogenesis: use of introgression lines for QTL mapping and characterization in the maize - Setosphaeria turcica pathosystem

BackgroundStudies on host-pathogen interactions in a range of pathosystems have revealed an array of mechanisms by which plants reduce the efficiency of pathogenesis. While R-gene mediated resistance confers highly effective defense responses against pathogen invasion, quantitative resistance is associated with intermediate levels of resistance that reduces disease progress. To test the hypothesis that specific loci affect distinct stages of fungal pathogenesis, a set of maize introgression lines was used for mapping and characterization of quantitative trait loci (QTL) conditioning resistance to Setosphaeria turcica, the causal agent of northern leaf blight (NLB). To better understand the nature of quantitative resistance, the identified QTL were further tested for three secondary hypotheses: (1) that disease QTL differ by host developmental stage; (2) that their performance changes across environments; and (3) that they condition broad-spectrum resistance.ResultsAmong a set of 82 introgression lines, seven lines were confirmed as more resistant or susceptible than B73. Two NLB QTL were validated in BC4F2 segregating populations and advanced introgression lines. These loci, designated qNLB1.02 and qNLB1.06, were investigated in detail by comparing the introgression lines with B73 for a series of macroscopic and microscopic disease components targeting different stages of NLB development. Repeated greenhouse and field trials revealed that qNLB1.06Tx303 (the Tx303 allele at bin 1.06) reduces the efficiency of fungal penetration, while qNLB1.02B73 (the B73 allele at bin 1.02) enhances the accumulation of callose and phenolics surrounding infection sites, reduces hyphal growth into the vascular bundle and impairs the subsequent necrotrophic colonization in the leaves. The QTL were equally effective in both juvenile and adult plants; qNLB1.06Tx303 showed greater effectiveness in the field than in the greenhouse. In addition to NLB resistance, qNLB1.02B73 was associated with resistance to Stewarts wilt and common rust, while qNLB1.06Tx303 conferred resistance to Stewarts wilt. The non-specific resistance may be attributed to pleiotropy or linkage.ConclusionsOur research has led to successful identification of two reliably-expressed QTL that can potentially be utilized to protect maize from S. turcica in different environments. This approach to identifying and dissecting quantitative resistance in plants will facilitate the application of quantitative resistance in crop protection.

Analysis of quantitative disease resistance to southern leaf blight and of multiple disease resistance in maize, using near-isogenic lines

Maize inbred lines NC292 and NC330 were derived by repeated backcrossing of an elite source of southern leaf blight (SLB) resistance (NC250P) to the SLB-susceptible line B73, with selection for SLB resistance among and within backcross families at each generation. Consequently, while B73 is very SLB susceptible, its sister lines NC292 and NC330 are both SLB resistant. Previously, we identified the 12 introgressions from NC250P that differentiate NC292 and NC330 from B73. The goals of this study were to determine the effects of each introgression on resistance to SLB and to two other foliar fungal diseases of maize, northern leaf blight and gray leaf spot. This was achieved by generating and testing a set of near isogenic lines carry single or combinations of just two or three introgressions in a B73 background. Introgressions 3B, 6A, and 9B (bins 3.03–3.04, 6.01, and 9.02–9.03) all conferred significant levels of SLB resistance in the field. Introgression 6A was the only introgression that had a significant effect on juvenile plant resistance to SLB. Introgressions 6A and 9B conferred resistance to multiple diseases.

Strawberry foliar anthracnose assessment by hyperspectral imaging

Hyperspectral imaging has proven to be an effective non-destructive method for assessing strawberry foliar anthracnose.The incubation stage, in which symptoms are not yet visible, can be distinguished.Several hyperspectral imaging analysis methods were investigated using 3 duplicate sets of experiments.Significant wavelengths for strawberry foliar anthracnose are 551, 706, 750 and 914nm. Hyperspectral imaging provides comprehensive spectral and spatial information about observed objects. This technology has been applied to many fields, such as geology, mining, surveillance and agriculture. Strawberry qualities have been examined using hyperspectral imaging in several studies. However, none of the previous literature presented a non-destructive method for diagnosing the infection stages of anthracnose, a devastating disease for strawberries. This study examined strawberry foliar anthracnose using three different hyperspectral imaging analyzing methods: spectral angle mapper (SAM), stepwise discriminant analysis (SDA) and self-developed correlation measure (CM). Three different infection stages, including healthy, incubation and symptomatic stages, were investigated using these methods. The incubation stage is a stage at which the symptoms are still not yet visible. The three infection stage classification results were promising, with a classification accuracy of approximately 80%. For two infection stage classification (healthy and symptomatic stages), an average accuracy of high 80% was attained. In fact, an average accuracy of 93% was achieved by SDA for two-stage classification. This study not only proves the feasibility of hyperspectral imaging for diagnosing strawberry foliar anthracnose infection, but also identifies a smaller set of significant wavelengths at which similar classification performance was accomplished. For significant wavelength selection, partial least squares (PLS) regression is an standard wavelength selection method and it was applied to be compared with SDA and CM. Wavelengths of 551, 706, 750 and 914nm formed the multispectral imaging observing bands that showed an accuracy of 80% when classifying the three infection stages. Therefore, using either hyperspectral or multispectral imaging to detect anthracnose infected foliar areas is more practical and efficient than classic destructive methods. In particular, early detection (the incubation stage), something that cannot be seen via naked eyes, reaches 80% classification accuracy with both SDA and CM. Strawberry farmers could profit greatly from this technology.

A remorin gene is implicated in quantitative disease resistance in maize

Key messageQuantitative disease resistance is used by plant breeders to improve host resistance. We demonstrate a role for a maize remorin (ZmREM6.3) in quantitative resistance against northern leaf blight using high-resolution fine mapping, expression analysis, and mutants. This is the first evidence of a role for remorins in plant-fungal interactions.AbstractQuantitative disease resistance (QDR) is important for the development of crop cultivars and is particularly useful when loci also confer multiple disease resistance. Despite its widespread use, the underlying mechanisms of QDR remain largely unknown. In this study, we fine-mapped a known quantitative trait locus (QTL) conditioning disease resistance on chromosome 1 of maize. This locus confers resistance to three foliar diseases: northern leaf blight (NLB), caused by the fungus Setosphaeria turcica; Stewart’s wilt, caused by the bacterium Pantoea stewartii; and common rust, caused by the fungus Puccinia sorghi. The Stewart’s wilt QTL was confined to a 5.26-Mb interval, while the rust QTL was reduced to an overlapping 2.56-Mb region. We show tight linkage between the NLB QTL locus and the loci conferring resistance to Stewart’s wilt and common rust. Pleiotropy cannot be excluded for the Stewart’s wilt and the common rust QTL, as they were fine-mapped to overlapping regions. Four positional candidate genes within the 243-kb NLB interval were examined with expression and mutant analysis: a gene with homology to an F-box gene, a remorin gene (ZmREM6.3), a chaperonin gene, and an uncharacterized gene. The F-box gene and ZmREM6.3 were more highly expressed in the resistant line. Transposon tagging mutants were tested for the chaperonin and ZmREM6.3, and the remorin mutant was found to be more susceptible to NLB. The putative F-box is a strong candidate, but mutants were not available to test this gene. Multiple lines of evidence strongly suggest a role for ZmREM6.3 in quantitative disease resistance.

Identifying rice grains using image analysis and sparse-representation-based classification

A microscope system was developed for acquiring high resolution grain images of 30 rice varieties.The morphological, textural, and color traits of the rice grains were quantified using image processing.Trait discrepancies among varieties were observed and explained.Sparse-representation-based classifier was developed to identify the varieties of the grains.The classification achieved an accuracy of 89.1% and a standard deviation of 7.0%. Rice (Oryza sativa L.) is a major staple food worldwide, and is traded extensively. The objective of this study is to distinguish the rice grains of 30 varieties nondestructively using image processing and sparse-representation-based classification (SRC). SRC uses over-complete bases to capture the representative traits of rice grains. In the experiments, rice grain images were acquired by microscopy. The morphological, color, and textural traits of the grain body, sterile lemmas, and brush were quantified. An SRC classifier was subsequently developed to identify the varieties of the grains using the traits as the inputs. The proposed approach could discriminate rice grain varieties with an accuracy of 89.1%.

The Genetic Structure of Phellinus noxius and Dissemination Pattern of Brown Root Rot Disease in Taiwan.

Since the 1990s, brown root rot caused by Phellinus noxius (Corner) Cunningham has become a major tree disease in Taiwan. This fungal pathogen can infect more than 200 hardwood and softwood tree species, causing gradual to fast decline of the trees. For effective control, we must determine how the pathogen is disseminated and how the new infection center of brown root rot is established. We performed Illumina sequencing and de novo assembly of a single basidiospore isolate Daxi42 and obtained a draft genome of ~40 Mb. By comparing the 12,217 simple sequence repeat (SSR) regions in Daxi42 with the low-coverage Illumina sequencing data for four additional P. noxius isolates, we identified 154 SSR regions with potential polymorphisms. A set of 13 polymorphic SSR markers were then developed and used to analyze 329 P. noxius isolates collected from 73 tree species from urban/agricultural areas in 14 cities/counties all around Taiwan from 1989 to 2012. The results revealed a high proportion (~98%) of distinct multilocus genotypes (MLGs) and that none of the 329 isolates were genome-wide homozygous, which supports a possible predominant outcrossing reproductive mode in P. noxius. The diverse MLGs exist as discrete patches, so brown root rot was most likely caused by multiple clones rather than a single predominant strain. The isolates collected from diseased trees near each other tend to have similar genotype(s), which indicates that P. noxius may spread to adjacent trees via root-to-root contact. Analyses based on Bayesian clustering, F ST statistics, analysis of molecular variance, and isolation by distance all suggest a low degree of population differentiation and little to no barrier to gene flow throughout the P. noxius population in Taiwan. We discuss the involvement of basidiospore dispersal in disease dissemination.

The Genetic Structure, Virulence, and Fungicide Sensitivity of Fusarium fujikuroi in Taiwan.

The rice disease bakanae, caused by Fusarium fujikuroi Nirenberg, has been present in Taiwan for over a century. To better understand the genetic diversity and structure of F. fujikuroi, a set of 16 polymorphic simple sequence repeat (SSR) markers were newly developed and used to analyze 637 F. fujikuroi isolates collected in 14 cities or counties around Taiwan from 1996 to 2013. On the basis of Bayesian clustering, the isolates were classified into four highly differentiated clusters: cluster B likely derived from the more widespread and genetically diversified clusters A or C, and cluster D was restricted to four cities or counties and may have been introduced from unknown sources genetically distinct from clusters A, B, and C. The coexistence of both mating types (MAT1-1:MAT1-2 = 1:1.88) and the highly diversified vegetative compatibility groups (VCG) (16 VCG among the 21 assessed isolates) suggest the likelihood of sexual reproduction in the field. However, the biased mating type ratios and linkage disequilibrium in the population suggest nonrandom mating between individuals. A significant pattern of isolation by distance was also detected, which implies a geographical restricted gene flow and low dissemination ability of F. fujikuroi. Evaluation of 24 representative isolates on eight rice varieties revealed differential levels of virulence, however no clear pattern of specific variety x isolate interaction was observed. Investigations of the differences in virulence and fungicide sensitivity between 8 early isolates (1998 and 2002) and 52 recent isolates (2012) indicate the evolution of increased resistance to the fungicide prochloraz in F. fujikuroi in Taiwan.

Comparative and population genomic landscape of Phellinus noxius: A hypervariable fungus causing root rot in trees

The order Hymenochaetales of white rot fungi contain some of the most aggressive wood decayers causing tree deaths around the world. Despite their ecological importance and the impact of diseases they cause, little is known about the evolution and transmission patterns of these pathogens. Here, we sequenced and undertook comparative genomic analyses of Hymenochaetales genomes using brown root rot fungus Phellinus noxius, wood‐decomposing fungus Phellinus lamaensis, laminated root rot fungus Phellinus sulphurascens and trunk pathogen Porodaedalea pini. Many gene families of lignin‐degrading enzymes were identified from these fungi, reflecting their ability as white rot fungi. Comparing against distant fungi highlighted the expansion of 1,3‐beta‐glucan synthases in P. noxius, which may account for its fast‐growing attribute. We identified 13 linkage groups conserved within Agaricomycetes, suggesting the evolution of stable karyotypes. We determined that P. noxius has a bipolar heterothallic mating system, with unusual highly expanded ~60 kb A locus as a result of accumulating gene transposition. We investigated the population genomics of 60 P. noxius isolates across multiple islands of the Asia Pacific region. Whole‐genome sequencing showed this multinucleate species contains abundant poly‐allelic single nucleotide polymorphisms with atypical allele frequencies. Different patterns of intra‐isolate polymorphism reflect mono‐/heterokaryotic states which are both prevalent in nature. We have shown two genetically separated lineages with one spanning across many islands despite the geographical barriers. Both populations possess extraordinary genetic diversity and show contrasting evolutionary scenarios. These results provide a framework to further investigate the genetic basis underlying the fitness and virulence of white rot fungi.

A Comparison of Machine Learning Methods on Hyperspectral Plant Disease Assessments

Abstract As plant diseases could cause agricultural production and economic loses, there is a need of fast and effective plant disease detection and assessment methods. Non-destructive methods have gained popularity among these methods as they do not affect plant growth while examining plant health conditions. Not only plant diseases can be detected but also production can be improved with proper quality controls. Hyperspectral imaging is one of the non-destructive examination techniques which have been widely applied in agriculture. Hyperspectral image analysis has been applied to different problems including plant disease detection and assessments. It provides not only spatial image but also spectral information of the observed object. This research has aimed to compare two hyperspectral image analysis methods: stepwise discriminant analysis (SDA) and spectral angle mapper (SAM) and the proposed Simple Slope Measure (SSM) method in strawberry foliage Anthracnose assessment. Anthracnose is one of the most devastating diseases for strawberries. Anthracnose disease can affect the whole plant and may result in 100 percent fruit loss from crown and fruit rot. Hence, an early detection of the Anthracnose disease will be beneficial to ensure production and quality of strawberries. This research has shown that the three different Anthracnose infection status (healthy, incubation and symptomatic) could be separated by the methods examined. The performance of these disease assessment models were evaluated and compared. The examination outcomes prove the feasibility to assess strawberry foliage Anthracnose nondestructively and as early as the symptoms not visible to naked eyes. As soon as early detections of the Anthracnose disease are achievable in the strawberry field, the damage to strawberry production due to the spread of Anthracnose disease could be reduced.

Determinants of Virulence and In Vitro Development Colocalize on a Genetic Map of Setosphaeria turcica

Generating effective and stable strategies for resistance breeding requires an understanding of the genetics of host-pathogen interactions and the implications for pathogen dynamics and evolution. Setosphaeria turcica causes northern leaf blight (NLB), an important disease of maize for which major resistance genes have been deployed. Little is known about the evolutionary dynamics of avirulence (AVR) genes in S. turcica. To test the hypothesis that there is a genetic association between avirulence and in vitro development traits, we (i) created a genetic map of S. turcica, (ii) located candidate AVRHt1 and AVRHt2 regions, and (iii) identified genetic regions associated with several in vitro development traits. A cross was generated between a race 1 and a race 23N strain, and 221 progeny were isolated. Genotyping by sequencing was used to score 2,078 single-nucleotide polymorphism markers. A genetic map spanning 1,981 centimorgans was constructed, consisting of 21 linkage groups. Genetic mapping extended prior evidence for the location and identity of the AVRHt1 gene and identified a region of interest for AVRHt2. The genetic location of AVRHt2 colocalized with loci influencing radial growth and mycelial abundance. Our data suggest a trade-off between virulence on Ht1 and Ht2 and the pathogens vegetative growth rate. In addition, in-depth analysis of the genotypic data suggests the presence of significant duplication in the genome of S. turcica.