Data_Sheet_1_Evolution and Diversity of Biosynthetic Gene Clusters in Fusarium.docx

<p>Plant pathogenic fungi in the Fusarium genus cause severe damage to crops, resulting in great financial losses and health hazards. Specialized metabolites synthesized by these fungi are known to play key roles in the infection process, and to provide survival advantages inside and outside the host. However, systematic studies of the evolution of specialized metabolite-coding potential across Fusarium have been scarce. Here, we apply a combination of bioinformatic approaches to identify biosynthetic gene clusters (BGCs) across publicly available genomes from Fusarium, to group them into annotated families and to study gain/loss events of BGC families throughout the history of the genus. Comparison with MIBiG reference BGCs allowed assignment of 29 gene cluster families (GCFs) to pathways responsible for the production of known compounds, while for 57 GCFs, the molecular products remain unknown. Comparative analysis of BGC repertoires using ancestral state reconstruction raised several new hypotheses on how BGCs contribute to Fusarium pathogenicity or host specificity, sometimes surprisingly so: for example, a gene cluster for the biosynthesis of hexadehydro-astechrome was identified in the genome of the biocontrol strain Fusarium oxysporum Fo47, while being absent in that of the tomato pathogen F. oxysporum f.sp. lycopersici. Several BGCs were also identified on supernumerary chromosomes; heterologous expression of genes for three terpene synthases encoded on the Fusarium poae supernumerary chromosome and subsequent GC/MS analysis showed that these genes are functional and encode enzymes that each are able to synthesize koraiol; this observed functional redundancy supports the hypothesis that localization of copies of BGCs on supernumerary chromosomes provides freedom for evolutionary innovations to occur, while the original function remains conserved. Altogether, this systematic overview of biosynthetic diversity in Fusarium paves the way for targeted natural product discovery based on automated identification of species-specific pathways as well as for connecting species ecology to the taxonomic distributions of BGCs.</p

Data_Sheet_2_Evolution and Diversity of Biosynthetic Gene Clusters in Fusarium.xlsx

<p>Plant pathogenic fungi in the Fusarium genus cause severe damage to crops, resulting in great financial losses and health hazards. Specialized metabolites synthesized by these fungi are known to play key roles in the infection process, and to provide survival advantages inside and outside the host. However, systematic studies of the evolution of specialized metabolite-coding potential across Fusarium have been scarce. Here, we apply a combination of bioinformatic approaches to identify biosynthetic gene clusters (BGCs) across publicly available genomes from Fusarium, to group them into annotated families and to study gain/loss events of BGC families throughout the history of the genus. Comparison with MIBiG reference BGCs allowed assignment of 29 gene cluster families (GCFs) to pathways responsible for the production of known compounds, while for 57 GCFs, the molecular products remain unknown. Comparative analysis of BGC repertoires using ancestral state reconstruction raised several new hypotheses on how BGCs contribute to Fusarium pathogenicity or host specificity, sometimes surprisingly so: for example, a gene cluster for the biosynthesis of hexadehydro-astechrome was identified in the genome of the biocontrol strain Fusarium oxysporum Fo47, while being absent in that of the tomato pathogen F. oxysporum f.sp. lycopersici. Several BGCs were also identified on supernumerary chromosomes; heterologous expression of genes for three terpene synthases encoded on the Fusarium poae supernumerary chromosome and subsequent GC/MS analysis showed that these genes are functional and encode enzymes that each are able to synthesize koraiol; this observed functional redundancy supports the hypothesis that localization of copies of BGCs on supernumerary chromosomes provides freedom for evolutionary innovations to occur, while the original function remains conserved. Altogether, this systematic overview of biosynthetic diversity in Fusarium paves the way for targeted natural product discovery based on automated identification of species-specific pathways as well as for connecting species ecology to the taxonomic distributions of BGCs.</p

GRAbB: Selective Assembly of Genomic Regions, a New Niche for Genomic Research

<div><p>GRAbB (Genomic Region Assembly by Baiting) is a new program that is dedicated to assemble specific genomic regions from NGS data. This approach is especially useful when dealing with multi copy regions, such as mitochondrial genome and the rDNA repeat region, parts of the genome that are often neglected or poorly assembled, although they contain interesting information from phylogenetic or epidemiologic perspectives, but also single copy regions can be assembled. The program is capable of targeting multiple regions within a single run. Furthermore, GRAbB can be used to extract specific loci from NGS data, based on homology, like sequences that are used for barcoding. To make the assembly specific, a known part of the region, such as the sequence of a PCR amplicon or a homologous sequence from a related species must be specified. By assembling only the region of interest, the assembly process is computationally much less demanding and may lead to assemblies of better quality. In this study the different applications and functionalities of the program are demonstrated such as: exhaustive assembly (rDNA region and mitochondrial genome), extracting homologous regions or genes (IGS, RPB1, RPB2 and TEF1a), as well as extracting multiple regions within a single run. The program is also compared with MITObim, which is meant for the exhaustive assembly of a single target based on a similar query sequence. GRAbB is shown to be more efficient than MITObim in terms of speed, memory and disk usage. The other functionalities (handling multiple targets simultaneously and extracting homologous regions) of the new program are not matched by other programs. The program is available with explanatory documentation at <a href="https://github.com/b-brankovics/grabb" target="_blank">https://github.com/b-brankovics/grabb</a>. GRAbB has been tested on Ubuntu (12.04 and 14.04), Fedora (23), CentOS (7.1.1503) and Mac OS X (10.7). Furthermore, GRAbB is available as a docker repository: brankovics/grabb (<a href="https://hub.docker.com/r/brankovics/grabb/" target="_blank">https://hub.docker.com/r/brankovics/grabb/</a>).</p></div

Pairwise comparison of the four populations in phenotypic differences.

a<p>“n” indicated no significant differences found between the two populations.</p>b<p>“+” indicated the population above significantly higher than the population below at <i>P</i><0.05.</p>c<p>“−” indicated the population above significantly lower than the population below at <i>P</i><0.05.</p

Map of China indicating the 175 sampling sites in 15 provinces.

<p>Map of China indicating the 175 sampling sites in 15 provinces.</p

Comparison between GRAbB and MITObim using our <i>in silico</i> generated paired-end read library.

<p>Comparison between GRAbB and MITObim using our <i>in silico</i> generated paired-end read library.</p

The proportion of wheat, rice and maize planting area and the distribution of <i>F. graminearum</i> s. str. and <i>F. asiaticum</i> in 13 provinces of four regions.

<p>The proportion of wheat, rice and maize planting area and the distribution of <i>F. graminearum</i> s. str. and <i>F. asiaticum</i> in 13 provinces of four regions.</p

Multilocus linkage disequilibrium (LD) and percentage of NIV producers in POP2 genotype of <i>F. asiaticum</i> in five regions.

a<p>Genotypic diversity (<i>GD</i>).</p>b<p>Gene diversity (<i>H</i>).</p>c<p>Measure of multilocus LD.</p><p>*indicates significant at <i>P</i><0.01.</p

Pairwise comparisons of effective number of migrants (<i>N</i>m), above diagonal, and genetic differentiation (<i>F</i>st), below diagonal, among 3 populations.

<p>*indicates significant at <i>P</i><0.001.</p

Distribution of <i>Fusarium</i> isolates in 15 provinces in China.

<p>Distribution of <i>Fusarium</i> isolates in 15 provinces in China.</p