Fusarium head blight resistance in European winter wheat: insights from genome-wide transcriptome analysis

Background Fusarium head blight (FHB) is a devastating disease of wheat worldwide. Resistance to FHB is quantitatively controlled by the combined effects of many small to medium effect QTL. Flowering traits, especially the extent of extruded anthers, are strongly associated with FHB resistance. Results To characterize the genetic basis of FHB resistance, we generated and analyzed phenotypic and gene expression data on the response to Fusarium graminearum (Fg) infection in 96 European winter wheat genotypes, including several lines containing introgressions from the highly resistant Asian cultivar Sumai3. The 96 lines represented a broad range in FHB resistance and were assigned to sub-groups based on their phenotypic FHB severity score. Comparative analyses were conducted to connect sub-group-specific expression profiles in response to Fg infection with FHB resistance level. Collectively, over 12,300 wheat genes were Fusarium responsive. The core set of genes induced in response to Fg was common across different resistance groups, indicating that the activation of basal defense response mechanisms was largely independent of the resistance level of the wheat line. Fg-induced genes tended to have higher expression levels in more susceptible genotypes. Compared to the more susceptible non-Sumai3 lines, the Sumai3-derivatives demonstrated higher constitutive expression of genes associated with cell wall and plant-type secondary cell wall biogenesis and higher constitutive and Fg-induced expression of genes involved in terpene metabolism. Gene expression analysis of the FHB QTL Qfhs.ifa-5A identified a constitutively expressed gene encoding a stress response NST1-like protein (TraesCS5A01G211300LC) as a candidate gene for FHB resistance. NST1 genes are key regulators of secondary cell wall biosynthesis in anther endothecium cells. Whether the stress response NST1-like gene affects anther extrusion, thereby affecting FHB resistance, needs further investigation. Conclusion Induced and preexisting cell wall components and terpene metabolites contribute to resistance and limit fungal colonization early on. In contrast, excessive gene expression directs plant defense response towards programmed cell death which favors necrotrophic growth of the Fg pathogen and could thus lead to increased fungal colonization.

Establishment and characteristics analysis of a crop–drought vulnerability curve: a case study of European winter wheat

As an essential component of drought risk, crop–drought vulnerability refers to the degree of the adverse response of a crop to a drought event. Different drought intensities and environments can cause significant differences in crop yield losses. Therefore, quantifying drought vulnerability and then identifying its spatial characteristics will help understand vulnerability and develop risk-reduction strategies. We select the European winter wheat growing area as the study area and 0.5∘ × 0.5∘ grids as the basic assessment units. Winter wheat drought vulnerability curves are established based on the erosion–productivity impact calculator model simulation. Their loss change and loss extent characteristics are quantitatively analysed by the key points and cumulative loss rate, respectively, and are then synthetically identified via K-means clustering. The results show the following. (1) The regional yield loss rate starts to rapidly increase from 0.13 when the drought index reaches 0.18 and then converts to a relatively stable stage with the value of 0.74 when the drought index reaches 0.66. (2) In contrast to the Pod Plain, the stage transitions of the vulnerability curve lags behind in the southern mountain area, indicating a stronger tolerance to drought. (3) According to the loss characteristics during the initial, development, and attenuation stages, the vulnerability curves can be divided into five clusters, namely low-low-low, low-low-medium, medium-medium-medium, high-high-high, and low-medium-high loss types, corresponding to the spatial distribution from low latitude to high latitude and from mountain to plain. The paper provides ideas for the study of the impact of environment on vulnerability and for the possible application of vulnerability curve in the context of climate change.

Fusarium Head Blight Resistance in European Winter Wheat: Insights From Genome-Wide Transcriptome Analysis

Background Fusarium head blight (FHB) is a devastating disease of wheat worldwide. Resistance to FHB is quantitatively controlled by the combined effects of many small to medium effect QTL. Flowering traits, especially the extent of extruded anthers, are strongly associated with FHB resistance. Results To characterize the genetic basis of FHB resistance, we generated and analyzed phenotypic and gene expression data on the response to Fusarium graminearum (Fg) infection in 96 European winter wheat genotypes, including several lines containing introgressions from the highly resistant Asian cultivar Sumai3. The 96 lines represented a broad range in FHB resistance and were assigned to sub-groups based on their phenotypic FHB severity score. Comparative analyses were conducted to connect sub-group-specific expression profiles in response to Fg infection with FHB resistance level. Collectively, over 12300 wheat genes were Fusarium responsive. The core set of genes induced in response to Fg was common across different resistance groups, indicating that the activation of basal defense response mechanisms was largely independent of the resistance level of the wheat line. Fg-induced genes tended to have higher expression levels in more susceptible genotypes. Compared to the more susceptible non-Sumai3 lines, the Sumai3-derivatives demonstrated higher constitutive expression of genes associated with cell wall and plant-type secondary cell wall biogenesis and higher constitutive and Fg-induced expression of genes involved in terpene metabolism. Gene expression analysis of the FHB QTL Qfhs.ifa-5A identified a constitutively expressed gene encoding a stress response NST1-like protein (TraesCS5A01G211300LC) as a candidate gene for FHB resistance. NST1 genes are key regulators of secondary cell wall biosynthesis in anther endothecium cells. Whether the stress response NST1-like gene affects anther extrusion, thereby affecting FHB resistance, needs further investigation. Conclusion Induced and preexisting cell wall components and terpene metabolites contribute to resistance and limit fungal colonization early on. In contrast, excessive gene expression directs plant defense response towards programmed cell death which favors necrotrophic growth of the Fg pathogen and could thus lead to increased fungal colonization.

Ghat: An R package for identifying adaptive polygenic traits

Identifying selection on polygenic complex traits in crops and livestock is key to understanding evolution and helps prioritize important characteristics for breeding. However, the QTL that contribute to polygenic trait variation exhibit small or infinitesimal effects. This hinders the ability to detect QTL controlling polygenic traits because enormously high statistical power is needed for their detection. Recently, we circumvented this challenge by introducing a method to identify selection on complex traits by evaluating the relationship between genome-wide changes in allele frequency and estimates of effect-size. The method involves calculating a composite-statistic across all markers that captures this relationship, followed by implementing a linkage disequilibrium-aware permutation test to evaluate if the observed pattern differs from that expected due to drift during evolution and population stratification. In this manuscript, we describe “Ghat”, an R package developed to implement the method to test for selection on polygenic traits. We demonstrate the package by applying it to test for polygenic selection on 15 published European winter wheat traits including yield, biomass, quality, morphological characteristics, and disease resistance traits. The results highlight the power of Ghat to identify selection on complex traits. The Ghat package is accessible on CRAN, The Comprehensive R Archival Network, and on GitHub.

Establishment and characteristics analysis of a crop-drought vulnerability curve: a case study of European winter wheat

As an essential component of drought risk, crop-drought vulnerability refers to the degree of the adverse response of a crop to a drought event. Different drought intensities and environments can cause significant differences in crop yield losses. Therefore, quantifying the drought vulnerability and then identifying its spatial distribution pattern will contribute to understanding vulnerability and the development of risk-reduction strategies. We select the European winter wheat growing area as the study area and a 0.5° × 0.5° grid as the basic assessment unit. Winter wheat drought vulnerability curves are established based on the Erosion-Productivity Impact Calculator model simulation. Their loss transmutation and loss extent characteristics are quantitatively analyzed by the key points and cumulative loss rate, respectively, and are then synthetically identified VIA K-means clustering. The results show the following. (1) The regional yield loss rate starts to rapidly increase from 0.13 when the drought index reaches 0.18 and then converts to a relatively stable stage with the value of 0.74 when the drought index reaches 0.66. (2) The stage transitions of the vulnerability curve lag in the southern mountain area, indicating a stronger tolerance to drought in the system, in contrast to the Pod Plain. (3) According to the loss characteristics during the initial, development and attenuation stages, the vulnerability curves can be divided into five clusters, namely, Low-Low-Low, Low-Low-Medium, Medium-Medium-Medium, High-High-High and Low-Medium-High loss types, corresponding to the spatial distribution from low latitude to high latitude and from mountain to plain. It is recommended to improve the integrated mitigation capability in the Medium-Medium-Medium-loss and High-High-High -loss areas and to develop the ability to mitigate droughts in the 0.3–0.6 intensity range, as non-engineering measures for the droughts greater than 0.6 intensity in low-medium-high areas are needed.