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Eastern Africa is a significant region of common bean (Phaseolus vulgaris L.) production and genetic diversity. Insect pests are a major biotic constraint in subsistence crop production systems. Bean fly (Ophiomyia spencerella) is a serious pest of beans in eastern Africa highlands. Breeding efforts focus on combining adaptability traits with user preferred seed types. However, lack of information on molecular markers linked to genes modulating bean fly resistance has slowed breeding progress. The objectives were to: (i) characterize genetic diversity and uncover putative bean fly resistant genotypes within diverse seed types and market classes and (ii) identify genomic regions controlling bean fly resistance using genome-wide association analysis (GWAS). A set of 276 diverse genotypes comprising local landraces and varieties from Kenya alongside introductions from International Centre for Tropical Agriculture (CIAT), were assembled. The germplasm represented varied bean production ecologies and seed types. Genetic diversity conforming to Andean and Mesoamerican genepools was established. Out of 276 genotypes evaluated, 150 were Andean, 74 were Mesoamerican and 52 were admixed. Twenty-two genotypes were resistant to bean fly. Association mapping results for stem damage score and plant mortality identified six significant single-nucleotide polymorphisms (SNPs) on chromosomes Pv01 and Pv09. The most significant SNP marker was 12 kilobases downstream of Phvul.001G074900 gene with LOD score > 4.0 hence in linkage disequilibrium with the postulated gene. The identified candidate gene is pleiotropic and modulates both flowering time and plant responses to stress. These findings are a key step towards marker-enabled breeding in common bean for sub-Saharan Africa.

Plant pathogens suppress defense responses to evade recognition and promote successful colonization. Although identifying the genes essential for pathogen ingress has traditionally relied on screening mutant populations, the post-genomic era provides an opportunity to develop novel approaches that accelerate identification. Here, RNA-seq analysis of 68 pathogen-infected bread wheat (Triticum aestivum) varieties, including three (Oakley, Solstice and Santiago) with variable levels of susceptibility, uncovered a branched-chain amino acid aminotransferase (termed TaBCAT1) as a positive regulator of wheat rust susceptibility. We show that TaBCAT1 is required for yellow and stem rust infection and likely functions in branched-chain amino acid (BCAA) metabolism, as TaBCAT1 disruption mutants had elevated BCAA levels. TaBCAT1 mutants also exhibited increased levels of salicylic acid (SA) and enhanced expression of associated defense genes, indicating that BCAA regulation, via TaBCAT1, has a key role in SA-dependent defense activation. We also identified an association between the levels of BCAAs and resistance to yellow rust infection in wheat. These findings provide insight into SA-mediated defense responses in wheat and highlight the role of BCAA metabolism in the defense response. Furthermore, TaBCAT1 could be manipulated to potentially provide resistance to two of the most economically damaging diseases of wheat worldwide.

Common bean (Phaesolus vulgaris L.) distribution across eastern, central and southern Africa region is widely driven by choice of grain types, which is affecting the genetic composition and adaptation to target production environments for biotic and abiotic constraints. Two bean fly species, Ophiomyia spencerella and Ophiomyia phaseoli are harmful insect pests of beans causing significant yield losses. Our objectives were to assess the population structure of common bean germplasm of different market classes and to identify polymorphic loci associated with resistance to O. spencerella. The study was carried out on a diversity panel of 284 genotypes using 9040 SNP markers. The genotypes were differentiated in to 14 distinct clusters. The mean FST of 0.4849, revealed major differentiation among the populations. Andean gene pool was more diverse compared to Mesoamerica gene pool which could be attributed to preference for large seeded cultivars. Multi-dimensional scaling and structure analyses revealed admixture among seed types. From genome wide association studies (GWAS), major genomic regions associated with O. spencerella resistance were identified on chromosome 1 (Pv01). The most significant SNP on Pv01 was aligned to gene PHAVU_001G075500g that is related to the Interleukin-1 receptor-associated kinase (IRAK) pathway, critical in regulating inherent immune responses to disease infection and insect herbivore attack. The diversity uncovered on the basis of market classes of beans and the presence of QTL regions associated with resistance to bean fly could serve as a valuable genetic resource for improvement of beans of different seed types in eastern and southern Africa region.nnCore IdeasO_LIGWAS revealed major loci associated with bean fly resistance on chromosome 01.nC_LIO_LINew sources of resistance to bean fly were uncovered from different market classes.nC_LIO_LIGenetic diversity uncovered is based on recent farmer preferences selection events.nC_LI

Background Traditional Map based Cloning approaches, used for the identification of desirable alleles, are extremely labour intensive and years can elapse between the mutagenesis and the detection of the polymorphism. High throughput sequencing based Mapping-by-sequencing approach requires an ordered genome assembly and cannot be used with fragmented, un-scaffolded draft genomes, limiting its application to model species and precluding many important organisms. Results We addressed this gap in resource and presented a computational method and software implementations called CHERIPIC (Computing Homozygosity Enriched Regions In genomes to Prioritise Identification of Candidate variants). We have successfully validated implementation of CHERIPIC using three different types of bulk segregant sequence data from Arabidopsis, maize and barley, respectively. Conclusions CHERIPIC allows users to rapidly analyse bulk segregant sequence data and we have made it available as a pre-packaged binary with all dependencies for Linux and MacOS and as Galaxy tool. Electronic supplementary material The online version of this article (10.1186/s12859-018-2515-5) contains supplementary material, which is available to authorized users.

Summary In recent years, the number of emergent plant pathogens (EPPs) has grown substantially, threatening agroecosystem stability and native biodiversity. Contributing factors include, among others, shifts in biogeography, with EPP spread facilitated by the global unification of monocultures in modern agriculture, high volumes of trade in plants and plant products and an increase in sexual recombination within pathogen populations. The unpredictable nature of EPPs as they move into new territories is a situation that has led to sudden and widespread epidemics. Understanding the underlying causes of pathogen emergence is key to managing the impact of EPPs. Here, we review some factors specifically influencing the emergence of oomycete and fungal EPPs, including new introductions through anthropogenic movement, natural dispersal and weather events, as well as genetic factors linked to shifts in host range.

Wheat stem rust, a devastating disease of wheat and barley caused by the fungal pathogen Puccinia graminis f. sp. tritici, was largely eradicated in Western Europe during the mid-to-late twentieth century. However, isolated outbreaks have occurred in recent years. Here we investigate whether a lack of resistance in modern European varieties, increased presence of its alternate host barberry and changes in climatic conditions could be facilitating its resurgence. We report the first wheat stem rust occurrence in the United Kingdom in nearly 60 years, with only 20% of UK wheat varieties resistant to this strain. Climate changes over the past 25 years also suggest increasingly conducive conditions for infection. Furthermore, we document the first occurrence in decades of P. graminis on barberry in the UK . Our data illustrate that wheat stem rust does occur in the UK and, when climatic conditions are conducive, could severely harm wheat and barley production. Clare Lewis et al. report the first identification in nearly 60 years of a cultivated wheat plant infected with the fungal pathogen Puccinia graminis f.sp. tritici (wheat stem rust) in the United Kingdom. They find that only 20% of UK wheat varieties are resistant to this strain and urge growers to resume resistance breeding programs.

Whole genome sequencing using high-throughput sequencing (HTS) technologies offers powerful opportunities to study genetic variation. Mapping the mutations responsible for different phenotypes is generally an involved and time-consuming process so researchers have developed user-friendly tools for mapping-by-sequencing, yet they are not applica- ble to organisms with non-sequenced genomes. We introduce SDM (SNP Distribution Method), a reference independent method for rapid discovery of mutagen-induced muta- tions in typical forward genetic screens. SDM aims to order a disordered collection of HTS reads or contigs such that the fragment carrying the causative mutation can be identified. SDM uses typical distributions of homozygous SNPs that are linked to a phenotype-altering SNP in a non-recombinant region as a model to order the fragments. To implement and test SDM, we created model genomes with an idealised SNP density based on Arabidop- sis thaliana chromosome 1 and analysed fragments with size distribution similar to reads or contigs assembled from HTS sequencing experiments. SDM groups the contigs by their normalised SNP density and arranges them to maximise the fit to the expected SNP distribution. We tested the procedure in existing datasets by examining SNP distributions in recent out-cross and back-cross experiments in Arabidopsis thaliana backgrounds. In all the examples we analysed, homozygous SNPs were normally distributed around the causal mutation. We used the real SNP densities obtained from these experiments to prove the efficiency and accuracy of SDM. The algorithm was able to successfully identify small sized (10-100 kb) genomic regions containing the causative mutation.

Recent disease outbreaks caused by (re-)emerging plant pathogens have been associated with expansions in pathogen geographic distribution and increased virulence. For example, in the past two decades’ wheat yellow (stripe) rust, Puccinia striiformis f. sp. tritici, has seen the emergence of new races that are adapted to warmer temperatures, have expanded virulence profiles, and are more aggressive than previous races, leading to wide-scale epidemics. Here, we used field-based genotyping to generate high-resolution data on P. striiformis genetics and carried out global population analysis. We also undertook comparative analysis of the 2014 and 2013 UK populations and assessed the temporal dynamics and host specificity of distinct pathogen genotypes. Our analysis revealed that P. striiformis lineages recently detected in Europe are extremely diverse and in fact similar to globally dispersed populations. In addition, we identified a considerable shift in the UK P. striiformis population structure including the first identification of one infamous race known as Kranich. Next, by establishing the genotype of both the pathogen and host within a single infected field sample, we uncovered evidence for varietal specificity for genetic groups of P. striiformis. Finally, we found potential seasonal specificity for certain genotypes of the pathogen with several lineages identified only in samples collected in late spring and into the summer, whereas one lineage was identified throughout the wheat growing season. Our discovery of which wheat varieties are susceptible to which specific P. striiformis isolates, and when those isolates are prevalent throughout the year, represents a powerful tool for disease management.