Data from: Condition‐dependent co‐regulation of genomic clusters of virulence factors in the grapevine trunk pathogen Neofusicoccum parvum

<p>The ascomycete <em>Neofusicoccum parvum</em>, one of the causal agents of Botryosphaeria dieback, is a destructive wood‐infecting fungus and a serious threat to grape production worldwide. The capability to colonize woody tissue, combined with the secretion of phytotoxic compounds, is thought to underlie its pathogenicity and virulence. Here, we describe the repertoire of virulence factors and their transcriptional dynamics as the fungus feeds on different substrates and colonizes the woody stem. We assembled and annotated a highly contiguous genome using single‐molecule real‐time DNA sequencing. Transcriptome profiling by RNA sequencing determined the genome‐wide patterns of expression of virulence factors both <em>in vitro</em> (potato dextrose agar or medium amended with grape wood as substrate) and <em>in planta</em>. Pairwise statistical testing of differential expression, followed by co‐expression network analysis, revealed that physically clustered genes coding for putative virulence functions were induced depending on the substrate or stage of plant infection. Co‐expressed gene clusters were significantly enriched not only in genes associated with secondary metabolism, but also in those associated with cell wall degradation, suggesting that dynamic co‐regulation of transcriptional networks contributes to multiple aspects of <em>N. parvum</em> virulence. In most of the co‐expressed clusters, all genes shared at least a common motif in their promoter region, indicative of co‐regulation by the same transcription factor. Co‐expression analysis also identified chromatin regulators with correlated expression with inducible clusters of virulence factors, suggesting a complex, multi‐layered regulation of the virulence repertoire of <em>N. parvum</em>. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Link to Supporting Information.</p> <p>File Name: Web Page, url: <a href="https://bsppjournals.onlinelibrary.wiley.com/doi/10.1111/mpp.12491#support-information-section">https://bsppjournals.onlinelibrary.wiley.com/doi/10.1111/mpp.12491#support-information-section</a> </p><p>Link to Supporting Information at <em>Molecular Plant Pathology</em>. Files are:</p> <p>Appendix S1 Supplementary tables and figures - Download</p> <ol> <li>Table S1: Statistics and SRA accession numbers of PacBio and Illumina genome sequences of N. parvum UCD646So.</li> <li>Table S2: Comparison of repeat content between assemblies generated with PacBio (N. parvum isolate UCD646So) and Illumina reads (N. parvum isolate UCR-NP2; Blanco-Ulate et al., 2013).</li> <li>Table S3: Comparison of the predicted proteomes in N. parvum isolate UCD646So and N. parvum isolate UCR-NP2 (Blanco-Ulate et al., 2013).</li> <li>Table S4: Gene space completeness estimations using CEGMA (Parra et al., 2009) and BUSCO (Simão et al., 2015).</li> <li>Table S5: N. parvum CAZymes families involved in plant cell wall degradation.</li> <li>Table S6: Summary of the major putative virulence categories of differentially expressed genes.</li> <li>Table S7: Summary of RNA-seq data and mapping metrics.</li> <li>Fig. S1: (A) Contig length distribution (log10 scale) over the N. parvum genome in the assemblies generated using PacBio reads and Illumina reads. (B) Dot plot showing the nucmer alignments between the contigs of the N. parvum UCD646So and N. parvum UCR-NP2 genomes.</li> <li>Fig. S2: Graphical representation of telomere sequences found at the ends of the N. parvum contigs. Figure was prepared using WebLogo (Crooks et al., 2004).</li> <li>Fig. S3: Number of reads mapped onto N. parvum UCD646So transcriptome per sample in the in planta (A) and in vitro (B) experiments.</li> <li>Fig. S4: Hierarchical clustering analysis of the 78 DE genes during N. parvum infections of grapevine woody stems, using Pearson’s correlation distance (MeV; Saeed et al., 2003).</li> <li>Fig. S5: Identification of putatively constitutively expressed genes during N. parvum stem infections using Pearson correlation (R) coefficient and coefficient of variation (CV) cutoffs.</li> <li>Fig. S6: Estimation of most appropriate number of clusters for k-means clustering. Line plot shows “Figure of merit value (FOM; y-axis) values” in function of the number of clusters. (1-20 clusters, 100 iterations) (MeV v.4.9; Saeed et al., 2003).</li> </ol> <p>Appendix S2 Genome assemblies and protein‐coding gene coordinates - Download</p> <p>Appendix S3 Functional annotations - Download Excel (.xlsx) file.</p> <p>Appendix S4 Normalized RNA‐sequencing counts - Download Normalized RNA‐sequencing counts in the in vitro (A) and in planta (B) experiments, list of genes up‐regulated in the presence of wood (C) and exclusively expressed in planta (D), and groups of co‐expressed genes during Neofusicoccum parvum colonization obtained by both K‐means and hierarchical clustering analysis (E). Gene co‐expression modules obtained from Weighted Gene Co‐expression Network Analysis (WGCNA) and the corresponding degree of connectivity in the unweighted network (F), genomic clusters identified among the gene co‐expression modules (G), network properties of the gene co‐expression modules (H) and transcription factor‐coding genes and PHD finger domain‐containing protein genes identified among the most highly connected genes (5%) (I).</p> <p>Appendix S5 Shared motifs showing similarity to yeast motifs - Download Shared motifs showing similarity to yeast motifs (MacIsaac_v1 database) and Saccharomyces cerevisiae motifs and motif‐associated proteins (ScAPs) (SCPD database) (E < 1 and motif length ≤ 9) (A) and Neofusicoccum parvum protein homologues of ScAPs (B).</p> <p></p></li></ul><p></p>

Bibliographic Details

Main Authors:	Mélanie Massonnet (3293217), Abraham Morales‐Cruz (17956646), Rosa Figueroa‐Balderas (17956649), Daniel P. Lawrence (10322138), Kendra Baumgartner (709023), Dario Cantu (17479758)
Format:	Dataset biblioteca
Published:	2018
Subjects:	Crop and pasture production, Genomics and transcriptomics, Genetics, Botryosphaeria dieback, Condition‐dependent co‐regulation, CAZymes, cell wall degradation, RNA-Seq, SMRT sequencing, data.gov, ARS,
Online Access:	https://figshare.com/articles/dataset/Data_from_Condition_dependent_co_regulation_of_genomic_clusters_of_virulence_factors_in_the_grapevine_trunk_pathogen_Neofusicoccum_parvum/24852897
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