Key message Four QTL for ergot resistance (causal pathogen Claviceps purpurea) have been identified in the durum wheat cultivar Greenshank. Abstract Claviceps purpurea is a pathogen of grasses that infects flowers, replacing the seed with an ergot sclerotium. Ergot presents a significant problem to rye, barley and wheat, in particular hybrid seed production systems. In addition, there is evidence that the highly toxic alkaloids that accumulate within sclerotia can cross-contaminate otherwise healthy grain. Host resistance to C. purpurea is rare, few resistance loci having been identified. In this study, four ergot resistance loci are located on chromosomes 1B, 2A, 5A and 5B in the durum wheat cv. Greenshank. Ergot resistance was assessed through analysis of phenotypes associated with C. purpurea infection, namely the number of inoculated flowers that produced sclerotia, or resulted in ovary death but no sclerotia, the levels of honeydew produced, total sclerotia weight and average sclerotia weight and size per spike. Ergot testing was undertaken in Canada and the UK. A major effect QTL, QCp.aafc.DH-2A, was detected in both the Canadian and UK experiments and had a significant effect on honeydew production levels. QCp.aafc.DH-5B had the biggest influence on total sclerotia weight per spike. QCp.aafc.DH-1B was only detected in the Canadian experiments and QCp.aafc.DH-5A in the UK experiment. An RNASeq analysis, undertaken to identify wheat differentially expressed genes associated with different combinations of the four ergot resistance QTL, revealed a disproportionate number of DEGs locating to the QCp.aafc.DH-1B, QCp.aafc.DH-2A and QCp.aafc.DH-5B QTL intervals.

Background The tall wheatgrass species Thinopyrum elongatum carries a strong fusarium head blight (FHB) resistance locus located on the long arm of chromosome 7 (7EL) as well as resistance to leaf and stem rusts, all diseases with a significant impact on wheat production. Towards understanding the contribution of Th. elongatum 7EL to improvement of disease resistance in wheat, the genomic sequence of the 7EL fragment present in the wheat Chinese Spring (CS) telosomic addition line CS-7EL was determined and the contribution and impact of 7EL on the rachis transcriptome during FHB infection was compared between CS and CS-7EL. Results We assembled the Th. elongatum 7EL chromosome arm using a reference-guided approach. Combining this assembly with the available reference sequence for CS hexaploid wheat provided a reliable reference for interrogating the transcriptomic differences in response to infection conferred by the 7EL fragment. Comparison of the transcriptomes of rachis tissues from CS and CS-7EL showed expression of Th. elongatum transcripts as well as modulation of wheat transcript expression profiles in the CS-7EL line. Expression profiles at 4 days after infection with Fusarium graminearum, the causal agent of FHB, showed an increased in expression of genes associated with an effective defense response, in particular glucan endo-1,3-beta-glucosidases and chitinases, in the FHB-resistant line CS-7EL while there was a larger increase in differential expression for genes associated with the level of fungal infection in the FHB-susceptible line CS. One hundred and seven 7EL transcripts were expressed in the smallest 7EL region defined to carry FHB resistance. Conclusion 7EL contributed to CS-7EL transcriptome by direct expression and through alteration of wheat transcript profiles. FHB resistance in CS-7EL was associated with transcriptome changes suggesting a more effective defense response. A list of candidate genes for the FHB resistance locus on 7EL has been established.

In biomedical research, gel band size estimation in electrophoresis analysis is a routine process. To facilitate and automate this process, numerous software have been released, notably the GelApp mobile app. However, the band detection accuracy is limited due to a band detection algorithm that cannot adapt to the variations in input images. To address this, we used the Monte Carlo Tree Search with Upper Confidence Bound (MCTS-UCB) method to efficiently search for optimal image processing pipelines for the band detection task, thereby improving the segmentation algorithm. Incorporating this into GelApp, we report a significant enhancement of gel band detection accuracy by 55.9 ± 2.0% for protein polyacrylamide gels, and 35.9 ± 2.5% for DNA SYBR green agarose gels. This implementation is a proof-of-concept in demonstrating MCTS-UCB as a strategy to optimize general image segmentation. The improved version of GelApp-GelApp 2.0-is freely available on both Google Play Store (for Android platform), and Apple App Store (for iOS platform).

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