A mapping population was created to detect quantitative trait loci (QTL) for resistance to stem rust caused by Puccinia graminis subsp. graminicola in Lolium perenne. A susceptible and a resistant plant were crossed to produce a pseudo-testcross population of 193 F(1) individuals. Markers were produced by the restriction-site associated DNA (RAD) process, which uses massively parallel and multiplexed sequencing of reduced-representation libraries. Additional simple sequence repeat (SSR) and sequence-tagged site (STS) markers were combined with the RAD markers to produce maps for the female (738 cM) and male (721 cM) parents. Stem rust phenotypes (number of pustules per plant) were determined in replicated greenhouse trials by inoculation with a field-collected, genetically heterogeneous population of urediniospores. The F(1) progeny displayed continuous distribution of phenotypes and transgressive segregation. We detected three resistance QTL. The most prominent QTL (qLpPg1) is located near 41 cM on linkage group (LG) 7 with a 2-LOD interval of 8 cM, and accounts for 30-38% of the stem rust phenotypic variance. QTL were detected also on LG1 (qLpPg2) and LG6 (qLpPg3), each accounting for approximately 10% of phenotypic variance. Alleles of loci closely linked to these QTL originated from the resistant parent for qLpPg1 and from both parents for qLpPg2 and qLpPg3. Observed quantitative nature of the resistance may be due to partial-resistance effects against all pathogen genotypes, or qualitative effects completely preventing infection by only some genotypes in the genetically mixed inoculum. RAD markers facilitated rapid construction of new genetic maps in this outcrossing species and will enable development of sequence-based markers linked to stem rust resistance in L. perenne.
SUMMARYBrachypodium distachyon is small annual grass that has been adopted as a model for the grasses. Its small genome, high-quality reference genome, large germplasm collection, and selfing nature make it an excellent subject for studies of natural variation. We sequenced six divergent lines to identify a comprehensive set of polymorphisms and analyze their distribution and concordance with gene expression. Multiple methods and controls were utilized to identify polymorphisms and validate their quality. mRNA-Seq experiments under control and simulated drought-stress conditions, identified 300 genes with a genotype-dependent treatment response. We showed that large-scale sequence variants had extremely high concordance with altered expression of hundreds of genes, including many with genotype-dependent treatment responses. We generated a deep mRNA-Seq dataset for the most divergent line and created a de novo transcriptome assembly. This led to the discovery of >2400 previously unannotated transcripts and hundreds of genes not present in the reference genome. We built a public database for visualization and investigation of sequence variants among these widely used inbred lines.
Disease predictive systems are intended to be management aids. With a few exceptions, these systems typically do not have direct sustained use by growers. Rather, their impact is mostly pedagogic and indirect, improving recommendations from farm advisers and shaping management concepts. The degree to which a system is consulted depends on the amount of perceived new, actionable information that is consistent with the objectives of the user. Often this involves avoiding risks associated with costly disease outbreaks. Adoption is sensitive to the correspondence between the information a system delivers and the information needed to manage a particular pathosystem at an acceptable financial risk; details of the approach used to predict disease risk are less important. The continuing challenge for researchers is to construct tools relevant to farmers and their advisers that improve upon their current management skill. This goal requires an appreciation of growers' decision calculus in managing disease problems and, more broadly, their overall farm enterprise management.
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