Developmental and Metabolic Plasticity of White-Skinned Grape Berries in Response to Botrytis cinerea during Noble Rot.

Noble rot results from exceptional infections of ripe grape (Vitis vinifera) berries by Botrytis cinerea. Unlike bunch rot, noble rot promotes favorable changes in grape berries and the accumulation of secondary metabolites that enhance wine grape composition. Noble rot-infected berries of cv Sémillon, a white-skinned variety, were collected over 3 years from a commercial vineyard at the same time that fruit were harvested for botrytized wine production. Using an integrated transcriptomics and metabolomics approach, we demonstrate that noble rot alters the metabolism of cv Sémillon berries by inducing biotic and abiotic stress responses as well as ripening processes. During noble rot, B. cinerea induced the expression of key regulators of ripening-associated pathways, some of which are distinctive to the normal ripening of red-skinned cultivars. Enhancement of phenylpropanoid metabolism, characterized by a restricted flux in white-skinned berries, was a common outcome of noble rot and red-skinned berry ripening. Transcript and metabolite analyses together with enzymatic assays determined that the biosynthesis of anthocyanins is a consistent hallmark of noble rot in cv Sémillon berries. The biosynthesis of terpenes and fatty acid aroma precursors also increased during noble rot. We finally characterized the impact of noble rot in botrytized wines. Altogether, the results of this work demonstrated that noble rot causes a major reprogramming of berry development and metabolism. This desirable interaction between a fruit and a fungus stimulates pathways otherwise inactive in white-skinned berries, leading to a greater accumulation of compounds involved in the unique flavor and aroma of botrytized wines.

Distinctive expansion of gene families associated with plant cell wall degradation, secondary metabolism, and nutrient uptake in the genomes of grapevine trunk pathogens.

BACKGROUND: Trunk diseases threaten the longevity and productivity of grapevines in all viticulture production systems. They are caused by distantly-related fungi that form chronic wood infections. Variation in wood-decay abilities and production of phytotoxic compounds are thought to contribute to their unique disease symptoms. We recently released the draft sequences of Eutypa lata, Neofusicoccum parvum and Togninia minima, causal agents of Eutypa dieback, Botryosphaeria dieback and Esca, respectively. In this work, we first expanded genomic resources to three important trunk pathogens, Diaporthe ampelina, Diplodia seriata, and Phaeomoniella chlamydospora, causal agents of Phomopsis dieback, Botryosphaeria dieback, and Esca, respectively. Then we integrated all currently-available information into a genome-wide comparative study to identify gene families potentially associated with host colonization and disease development. RESULTS: The integration of RNA-seq, comparative and ab initio approaches improved the protein-coding gene prediction in T. minima, whereas shotgun sequencing yielded nearly complete genome drafts of Dia. ampelina, Dip. seriata, and P. chlamydospora. The predicted proteomes of all sequenced trunk pathogens were annotated with a focus on functions likely associated with pathogenesis and virulence, namely (i) wood degradation, (ii) nutrient uptake, and (iii) toxin production. Specific patterns of gene family expansion were described using Computational Analysis of gene Family Evolution, which revealed lineage-specific evolution of distinct mechanisms of virulence, such as specific cell wall oxidative functions and secondary metabolic pathways in N. parvum, Dia. ampelina, and E. lata. Phylogenetically-informed principal component analysis revealed more similar repertoires of expanded functions among species that cause similar symptoms, which in some cases did not reflect phylogenetic relationships, thereby suggesting patterns of convergent evolution. CONCLUSIONS: This study describes the repertoires of putative virulence functions in the genomes of ubiquitous grapevine trunk pathogens. Gene families with significantly faster rates of gene gain can now provide a basis for further studies of in planta gene expression, diversity by genome re-sequencing, and targeted reverse genetic approaches. The functional validation of potential virulence factors will lead to a more comprehensive understanding of the mechanisms of pathogenesis and virulence, which ultimately will enable the development of accurate diagnostic tools and effective disease management.

tRNA signatures reveal a polyphyletic origin of SAR11 strains among alphaproteobacteria.

Molecular phylogenetics and phylogenomics are subject to noise from horizontal gene transfer (HGT) and bias from convergence in macromolecular compositions. Extensive variation in size, structure and base composition of alphaproteobacterial genomes has complicated their phylogenomics, sparking controversy over the origins and closest relatives of the SAR11 strains. SAR11 are highly abundant, cosmopolitan aquatic Alphaproteobacteria with streamlined, A+T-biased genomes. A dominant view holds that SAR11 are monophyletic and related to both Rickettsiales and the ancestor of mitochondria. Other studies dispute this, finding evidence of a polyphyletic origin of SAR11 with most strains distantly related to Rickettsiales. Although careful evolutionary modeling can reduce bias and noise in phylogenomic inference, entirely different approaches may be useful to extract robust phylogenetic signals from genomes. Here we develop simple phyloclassifiers from bioinformatically derived tRNA Class-Informative Features (CIFs), features predicted to target tRNAs for specific interactions within the tRNA interaction network. Our tRNA CIF-based model robustly and accurately classifies alphaproteobacterial genomes into one of seven undisputed monophyletic orders or families, despite great variability in tRNA gene complement sizes and base compositions. Our model robustly rejects monophyly of SAR11, classifying all but one strain as Rhizobiales with strong statistical support. Yet remarkably, conventional phylogenetic analysis of tRNAs classifies all SAR11 strains identically as Rickettsiales. We attribute this discrepancy to convergence of SAR11 and Rickettsiales tRNA base compositions. Thus, tRNA CIFs appear more robust to compositional convergence than tRNA sequences generally. Our results suggest that tRNA-CIF-based phyloclassification is robust to HGT of components of the tRNA interaction network, such as aminoacyl-tRNA synthetases. We explain why tRNAs are especially advantageous for prediction of traits governing macromolecular interactions from genomic data, and why such traits may be advantageous in the search for robust signals to address difficult problems in classification and phylogeny.

Adaptive genomic structural variation in the grape powdery mildew pathogen, Erysiphe necator.

BACKGROUND: Powdery mildew, caused by the obligate biotrophic fungus Erysiphe necator, is an economically important disease of grapevines worldwide. Large quantities of fungicides are used for its control, accelerating the incidence of fungicide-resistance. Copy number variations (CNVs) are unbalanced changes in the structure of the genome that have been associated with complex traits. In addition to providing the first description of the large and highly repetitive genome of E. necator, this study describes the impact of genomic structural variation on fungicide resistance in Erysiphe necator. RESULTS: A shotgun approach was applied to sequence and assemble the genome of five E. necator isolates, and RNA-seq and comparative genomics were used to predict and annotate protein-coding genes. Our results show that the E. necator genome is exceptionally large and repetitive and suggest that transposable elements are responsible for genome expansion. Frequent structural variations were found between isolates and included copy number variation in EnCYP51, the target of the commonly used sterol demethylase inhibitor (DMI) fungicides. A panel of 89 additional E. necator isolates collected from diverse vineyard sites was screened for copy number variation in the EnCYP51 gene and for presence/absence of a point mutation (Y136F) known to result in higher fungicide tolerance. We show that an increase in EnCYP51 copy number is significantly more likely to be detected in isolates collected from fungicide-treated vineyards. Increased EnCYP51 copy numbers were detected with the Y136F allele, suggesting that an increase in copy number becomes advantageous only after the fungicide-tolerant allele is acquired. We also show that EnCYP51 copy number influences expression in a gene-dose dependent manner and correlates with fungal growth in the presence of a DMI fungicide. CONCLUSIONS: Taken together our results show that CNV can be adaptive in the development of resistance to fungicides by providing increasing quantitative protection in a gene-dosage dependent manner. The results of this work not only demonstrate the effectiveness of using genomics to dissect complex traits in organisms with very limited molecular information, but also may have broader implications for understanding genomic dynamics in response to strong selective pressure in other pathogens with similar genome architectures.

Discovery of core biotic stress responsive genes in Arabidopsis by weighted gene co-expression network analysis.

Intricate signal networks and transcriptional regulators translate the recognition of pathogens into defense responses. In this study, we carried out a gene co-expression analysis of all currently publicly available microarray data, which were generated in experiments that studied the interaction of the model plant Arabidopsis thaliana with microbial pathogens. This work was conducted to identify (i) modules of functionally related co-expressed genes that are differentially expressed in response to multiple biotic stresses, and (ii) hub genes that may function as core regulators of disease responses. Using Weighted Gene Co-expression Network Analysis (WGCNA) we constructed an undirected network leveraging a rich curated expression dataset comprising 272 microarrays that involved microbial infections of Arabidopsis plants with a wide array of fungal and bacterial pathogens with biotrophic, hemibiotrophic, and necrotrophic lifestyles. WGCNA produced a network with scale-free and small-world properties composed of 205 distinct clusters of co-expressed genes. Modules of functionally related co-expressed genes that are differentially regulated in response to multiple pathogens were identified by integrating differential gene expression testing with functional enrichment analyses of gene ontology terms, known disease associated genes, transcriptional regulators, and cis-regulatory elements. The significance of functional enrichments was validated by comparisons with randomly generated networks. Network topology was then analyzed to identify intra- and inter-modular gene hubs. Based on high connectivity, and centrality in meta-modules that are clearly enriched in defense responses, we propose a list of 66 target genes for reverse genetic experiments to further dissect the Arabidopsis immune system. Our results show that statistical-based data trimming prior to network analysis allows the integration of expression datasets generated by different groups, under different experimental conditions and biological systems, into a functionally meaningful co-expression network.

Comparative transcriptomics of Central Asian Vitis vinifera accessions reveals distinct defense strategies against powdery mildew.

Grape powdery mildew (PM), caused by the biotrophic ascomycete Erysiphe necator, is a devastating fungal disease that affects most Vitis vinifera cultivars. We have previously identified a panel of V. vinifera accessions from Central Asia with partial resistance to PM that possess a Ren1-like local haplotype. In this study, we show that in addition to the typical Ren1-associated late post-penetration resistance, these accessions display a range of different levels of disease development suggesting that alternative alleles or additional genes contribute to determining the outcome of the interaction with the pathogen. To identify potential Ren1-dependent transcriptional responses and functions associated with the different levels of resistance, we sequenced and analyzed the transcriptomes of these Central Asian accessions at two time points of PM infection. Transcriptomes were compared to identify constitutive differences and PM-inducible responses that may underlie their disease resistant phenotype. Responses to E. necator in all resistant accessions were characterized by an early up-regulation of 13 genes, most encoding putative defense functions, and a late down-regulation of 32 genes, enriched in transcriptional regulators and protein kinases. Potential Ren1-dependent responses included a hotspot of co-regulated genes on chromosome 18. We also identified 81 genes whose expression levels and dynamics correlated with the phenotypic differences between the most resistant accessions 'Karadzhandahal', DVIT3351.27, and O34-16 and the other genotypes. This study provides a first exploration of the functions associated with varying levels of partial resistance to PM in V. vinifera accessions that can be exploited as sources of genetic resistance in grape breeding programs.

FAST: FAST Analysis of Sequences Toolbox.

FAST (FAST Analysis of Sequences Toolbox) provides simple, powerful open source command-line tools to filter, transform, annotate and analyze biological sequence data. Modeled after the GNU (GNU's Not Unix) Textutils such as grep, cut, and tr, FAST tools such as fasgrep, fascut, and fastr make it easy to rapidly prototype expressive bioinformatic workflows in a compact and generic command vocabulary. Compact combinatorial encoding of data workflows with FAST commands can simplify the documentation and reproducibility of bioinformatic protocols, supporting better transparency in biological data science. Interface self-consistency and conformity with conventions of GNU, Matlab, Perl, BioPerl, R, and GenBank help make FAST easy and rewarding to learn. FAST automates numerical, taxonomic, and text-based sorting, selection and transformation of sequence records and alignment sites based on content, index ranges, descriptive tags, annotated features, and in-line calculated analytics, including composition and codon usage. Automated content- and feature-based extraction of sites and support for molecular population genetic statistics make FAST useful for molecular evolutionary analysis. FAST is portable, easy to install and secure thanks to the relative maturity of its Perl and BioPerl foundations, with stable releases posted to CPAN. Development as well as a publicly accessible Cookbook and Wiki are available on the FAST GitHub repository at https://github.com/tlawrence3/FAST. The default data exchange format in FAST is Multi-FastA (specifically, a restriction of BioPerl FastA format). Sanger and Illumina 1.8+ FastQ formatted files are also supported. FAST makes it easier for non-programmer biologists to interactively investigate and control biological data at the speed of thought.

Genome-wide transcriptional profiling of Botrytis cinerea genes targeting plant cell walls during infections of different hosts.

Cell walls are barriers that impair colonization of host tissues, but also are important reservoirs of energy-rich sugars. Growing hyphae of necrotrophic fungal pathogens, such as Botrytis cinerea (Botrytis, henceforth), secrete enzymes that disassemble cell wall polysaccharides. In this work we describe the annotation of 275 putative secreted Carbohydrate-Active enZymes (CAZymes) identified in the Botrytis B05.10 genome. Using RNAseq we determined which Botrytis CAZymes were expressed during infections of lettuce leaves, ripe tomato fruit, and grape berries. On the three hosts, Botrytis expressed a common group of 229 potentially secreted CAZymes, including 28 pectin backbone-modifying enzymes, 21 hemicellulose-modifying proteins, 18 enzymes that might target pectin and hemicellulose side-branches, and 16 enzymes predicted to degrade cellulose. The diversity of the Botrytis CAZymes may be partly responsible for its wide host range. Thirty-six candidate CAZymes with secretion signals were found exclusively when Botrytis interacted with ripe tomato fruit and grape berries. Pectin polysaccharides are notably abundant in grape and tomato cell walls, but lettuce leaf walls have less pectin and are richer in hemicelluloses and cellulose. The results of this study not only suggest that Botrytis targets similar wall polysaccharide networks on fruit and leaves, but also that it may selectively attack host wall polysaccharide substrates depending on the host tissue.