Chickpea (Cicer arietinum) is the second most widely grown legume crop after soybean, accounting for a substantial proportion of human dietary nitrogen intake and playing a crucial role in food security in developing countries. We report the ∼ 738-Mb draft whole genome shotgun sequence of CDC Frontier, a kabuli chickpea variety, which contains an estimated 28,269 genes. Resequencing and analysis of 90 cultivated and wild genotypes from ten countries identifies targets of both breeding-associated genetic sweeps and breeding-associated balancing selection. Candidate genes for disease resistance and agronomic traits are highlighted, including traits that distinguish the two main market classes of cultivated chickpea—desi and kabuli. These data comprise a resource for chickpea improvement through molecular breeding and provide insights into both genome diversity and domestication.

The plant-pathogenic fungus Mycosphaerella graminicola (asexual stage: Septoria tritici) causes septoria tritici blotch, a disease that greatly reduces the yield and quality of wheat. This disease is economically important in most wheat-growing areas worldwide and threatens global food production. Control of the disease has been hampered by a limited understanding of the genetic and biochemical bases of pathogenicity, including mechanisms of infection and of resistance in the host. Unlike most other plant pathogens, M. graminicola has a long latent period during which it evades host defenses. Although this type of stealth pathogenicity occurs commonly in Mycosphaerella and other Dothideomycetes, the largest class of plant-pathogenic fungi, its genetic basis is not known. To address this problem, the genome of M. graminicola was sequenced completely. The finished genome contains 21 chromosomes, eight of which could be lost with no visible effect on the fungus and thus are dispensable. This eight-chromosome dispensome is dynamic in field and progeny isolates, is different from the core genome in gene and repeat content, and appears to have originated by ancient horizontal transfer from an unknown donor. Synteny plots of the M. graminicola chromosomes versus those of the only other sequenced Dothideomycete, Stagonospora nodorum, revealed conservation of gene content but not order or orientation, suggesting a high rate of intra-chromosomal rearrangement in one or both species. This observed “mesosynteny” is very different from synteny seen between other organisms. A surprising feature of the M. graminicola genome compared to other sequenced plant pathogens was that it contained very few genes for enzymes that break down plant cell walls, which was more similar to endophytes than to pathogens. The stealth pathogenesis of M. graminicola probably involves degradation of proteins rather than carbohydrates to evade host defenses during the biotrophic stage of infection and may have evolved from endophytic ancestors. The plant-pathogenic fungus Mycosphaerella graminicola causes septoria tritici blotch, one of the most economically important diseases of wheat worldwide and a potential threat to global food production. Unlike most other plant pathogens, M. graminicola has a long latent period during which it seems able to evade host defenses, and its genome appears to be unstable with many chromosomes that can change size or be lost during sexual reproduction. To understand its unusual mechanism of pathogenicity and high genomic plasticity, the genome of M. graminicola was sequenced more completely than that of any other filamentous fungus. The finished sequence contains 21 chromosomes, eight of which were different from those in the core genome and appear to have originated by ancient horizontal transfer from an unknown donor. The dispensable chromosomes collectively comprise the dispensome and showed extreme plasticity during sexual reproduction. A surprising feature of the M. graminicola genome was a low number of genes for enzymes that break down plant cell walls; this may represent an evolutionary response to evade detection by plant defense mechanisms. The stealth pathogenicity of M. graminicola may involve degradation of proteins rather than carbohydrates and could have evolved from an endophytic ancestor.

Fungi are of primary ecological, biotechnological and economic importance. Many fundamental biological processes that are shared by animals and fungi are studied in fungi due to their experimental tractability. Many fungi are pathogens or mutualists and are model systems to analyse effector genes and their mechanisms of diversification. In this study, we report the genome sequence of the phytopathogenic ascomycete Leptosphaeria maculans and characterize its repertoire of protein effectors. The L. maculans genome has an unusual bipartite structure with alternating distinct guanine and cytosine-equilibrated and adenine and thymine (AT)-rich blocks of homogenous nucleotide composition. The AT-rich blocks comprise one-third of the genome and contain effector genes and families of transposable elements, both of which are affected by repeat-induced point mutation, a fungal-specific genome defence mechanism. This genomic environment for effectors promotes rapid sequence diversification and underpins the evolutionary potential of the fungus to adapt rapidly to novel host-derived constraints.

Stagonospora nodorum is a major necrotrophic fungal pathogen of wheat (Triticum aestivum) and a member of the Dothideomycetes, a large fungal taxon that includes many important plant pathogens affecting all major crop plant families. Here, we report the acquisition and initial analysis of a draft genome sequence for this fungus. The assembly comprises 37,164,227 bp of nuclear DNA contained in 107 scaffolds. The circular mitochondrial genome comprises 49,761 bp encoding 46 genes, including four that are intron encoded. The nuclear genome assembly contains 26 classes of repetitive DNA, comprising 4.5% of the genome. Some of the repeats show evidence of repeat-induced point mutations consistent with a frequent sexual cycle. ESTs and gene prediction models support a minimum of 10,762 nuclear genes. Extensive orthology was found between the polyketide synthase family in S. nodorum and Cochliobolus heterostrophus, suggesting an ancient origin and conserved functions for these genes. A striking feature of the gene catalog was the large number of genes predicted to encode secreted proteins; the majority has no meaningful similarity to any other known genes. It is likely that genes for host-specific toxins, in addition to ToxA, will be found among this group. ESTs obtained from axenic mycelium grown on oleate (chosen to mimic early infection) and late-stage lesions sporulating on wheat leaves were obtained. Statistical analysis shows that transcripts encoding proteins involved in protein synthesis and in the production of extracellular proteases, cellulases, and xylanases predominate in the infection library. This suggests that the fungus is dependant on the degradation of wheat macromolecular constituents to provide the carbon skeletons and energy for the synthesis of proteins and other components destined for the developing pycnidiospores.

The impact of gene annotation quality on functional and comparative genomics makes gene prediction an important process, particularly in non-model species, including many fungi. Sets of homologous protein sequences are rarely complete with respect to the fungal species of interest and are often small or unreliable, especially when closely related species have not been sequenced or annotated in detail. In these cases, protein homology-based evidence fails to correctly annotate many genes, or significantly improve ab initio predictions. Generalised hidden Markov models (GHMM) have proven to be invaluable tools in gene annotation and, recently, RNA-seq has emerged as a cost-effective means to significantly improve the quality of automated gene annotation. As these methods do not require sets of homologous proteins, improving gene prediction from these resources is of benefit to fungal researchers. While many pipelines now incorporate RNA-seq data in training GHMMs, there has been relatively little investigation into additionally combining RNA-seq data at the point of prediction, and room for improvement in this area motivates this study. CodingQuarry is a highly accurate, self-training GHMM fungal gene predictor designed to work with assembled, aligned RNA-seq transcripts. RNA-seq data informs annotations both during gene-model training and in prediction. Our approach capitalises on the high quality of fungal transcript assemblies by incorporating predictions made directly from transcript sequences. Correct predictions are made despite transcript assembly problems, including those caused by overlap between the transcripts of adjacent gene loci. Stringent benchmarking against high-confidence annotation subsets showed CodingQuarry predicted 91.3% of Schizosaccharomyces pombe genes and 90.4% of Saccharomyces cerevisiae genes perfectly. These results are 4-5% better than those of AUGUSTUS, the next best performing RNA-seq driven gene predictor tested. Comparisons against whole genome Sc. pombe and S. cerevisiae annotations further substantiate a 4-5% improvement in the number of correctly predicted genes. We demonstrate the success of a novel method of incorporating RNA-seq data into GHMM fungal gene prediction. This shows that a high quality annotation can be achieved without relying on protein homology or a training set of genes. CodingQuarry is freely available ( https://sourceforge.net/projects/codingquarry/ ), and suitable for incorporation into genome annotation pipelines.

Repeat-induced point mutation (RIP) is a fungal-specific genome defence mechanism that alters the sequences of repetitive DNA, thereby inactivating coding genes. Repeated DNA sequences align between mating and meiosis and both sequences undergo C:G to T:A transitions. In most fungi these transitions preferentially affect CpA di-nucleotides thus altering the frequency of certain di-nucleotides in the affected sequences. The majority of previously published in silico analyses were limited to the comparison of ratios of pre- and post-RIP di-nucleotides in putatively RIP-affected sequences – so-called RIP indices. The analysis of RIP is significantly more informative when comparing sequence alignments of repeated sequences. There is, however, a dearth of bioinformatics tools available to the fungal research community for alignment-based RIP analysis of repeat families.