Architecture and Dynamics of the Jasmonic Acid Gene Regulatory Network.

Jasmonic acid (JA) is a critical hormonal regulator of plant growth and defense. To advance our understanding of the architecture and dynamic regulation of the JA gene regulatory network, we performed a high-resolution RNA-seq time series of methyl JA-treated Arabidopsis thaliana at 15 time points over a 16-h period. Computational analysis showed that methyl JA (MeJA) induces a burst of transcriptional activity, generating diverse expression patterns over time that partition into distinct sectors of the JA response targeting specific biological processes. The presence of transcription factor (TF) DNA binding motifs correlated with specific TF activity during temporal MeJA-induced transcriptional reprogramming. Insight into the underlying dynamic transcriptional regulation mechanisms was captured in a chronological model of the JA gene regulatory network. Several TFs, including MYB59 and bHLH27, were uncovered as early network components with a role in pathogen and insect resistance. Analysis of subnetworks surrounding the TFs ORA47, RAP2.6L, MYB59, and ANAC055, using transcriptome profiling of overexpressors and mutants, provided insights into their regulatory role in defined modules of the JA network. Collectively, our work illuminates the complexity of the JA gene regulatory network, pinpoints and validates previously unknown regulators, and provides a valuable resource for functional studies on JA signaling components in plant defense and development.

SnapperDB: a database solution for routine sequencing analysis of bacterial isolates.

Summary: Real-time surveillance of infectious disease using whole genome sequencing data poses challenges in both result generation and communication. SnapperDB represents a set of tools to store bacterial variant data and facilitate reproducible and scalable analysis of bacterial populations. We also introduce the 'SNP address' nomenclature to describe the relationship between isolates in a population to the single nucleotide resolution. We announce the release of SnapperDB v1.0 a program for scalable routine SNP analysis and storage of microbial populations. Availability and implementation: SnapperDB is implemented as a python application under the open source BSD license. All code and user guides are available at https://github.com/phe-bioinformatics/snapperdb. Reference genomes and SnapperDB configs are available at https://github.com/phe-bioinformatics/snapperdb_references.

Genome analysis following a national increase in Scarlet Fever in England 2014.

BACKGROUND: During a substantial elevation in scarlet fever (SF) notifications in 2014 a national genomic study was undertaken of Streptococcus pyogenes (Group A Streptococci, GAS) isolates from patients with SF with comparison to isolates from patients with invasive disease (iGAS) to test the hypotheses that the increase in SF was due to either the introduction of one or more new/emerging strains in the population in England or the transmission of a known genetic element through the population of GAS by horizontal gene transfer (HGT) resulting in infections with an increased likelihood of causing SF. Isolates were collected to provide geographical representation, for approximately 5% SF isolates from each region from 1st April 2014 to 18th June 2014. Contemporaneous iGAS isolates for which genomic data were available were included for comparison. Data were analysed in order to determine emm gene sequence type, phylogenetic lineage and genomic clade representation, the presence of known prophage elements and the presence of genes known to confer pathogenicity and resistance to antibiotics. RESULTS: 555 isolates were analysed, 303 from patients with SF and 252 from patients with iGAS. Isolates from patients with SF were of multiple distinct emm sequence types and phylogenetic lineages. Prior to data normalisation, emm3 was the predominant type (accounting for 42.9% of SF isolates, 130/303 95%CI 37.5-48.5; 14.7% higher than the percentage of emm3 isolates found in the iGAS isolates). Post-normalisation emm types, 4 and 12, were found to be over-represented in patients with SF versus iGAS (p < 0.001). A single gene, ssa, was over-represented in isolates from patients with SF. No single phage was found to be over represented in SF vs iGAS. However, a "meta-ssa" phage defined by the presence of :315.2, SPsP6, MGAS10750.3 or HK360ssa, was found to be over represented. The HKU360.vir phage was not detected yet the HKU360.ssa phage was present in 43/63 emm12 isolates but not found to be over-represented in isolates from patients with SF. CONCLUSIONS: There is no evidence that the increased number of SF cases was a strain-specific or known mobile element specific phenomenon, as the increase in SF cases was associated with multiple lineages of GAS.

Genomic determination of minimum multi-locus sequence typing schemas to represent the genomic phylogeny of Mycoplasma hominis.

BACKGROUND: Mycoplasma hominis is an opportunistic human pathogen, associated with clinically diverse disease. Currently, there is no standardised method for typing M. hominis, which would aid in understanding pathogen epidemiology and transmission. Due to availability and costs of whole genome sequencing and the challenges in obtaining adequate M. hominis DNA, the use of whole genome sequence analysis to provide clinical guidance is unpractical for this bacterial species as well as other fastidious organisms. RESULTS: This study identified pan-genome set of 700 genes found to be present in four published reference genomes. A subset of 417 genes was identified to be core genome for 18 isolates and 1 reference. Leave-one-out analysis of the core genes highlighted set of 48 genes that are required to recapture the original phylogenetic relationships observed using whole genome SNP analysis. Three 7-locus MLST schemas with high diversity index (97%) and low dN/dS ratios (0.1, 0.13, and 0.11) were derived that could be used to confer good discrimination between strains and could be of practical use in future studies direct on clinical specimens. CONCLUSIONS: The genes proposed in this study could be utilised to design a cost-effective and rapid PCR-based MLST assay that could be applied directly to clinical isolates, without prior isolation. This study includes additional genomic analysis revealing high levels of genetic heterogeneity among this species. This provides a novel and evidence based approach for the development of MLST schema that accurately represent genomic phylogeny for use in epidemiology and transmission studies.

Wigwams: identifying gene modules co-regulated across multiple biological conditions.

MOTIVATION: Identification of modules of co-regulated genes is a crucial first step towards dissecting the regulatory circuitry underlying biological processes. Co-regulated genes are likely to reveal themselves by showing tight co-expression, e.g. high correlation of expression profiles across multiple time series datasets. However, numbers of up- or downregulated genes are often large, making it difficult to discriminate between dependent co-expression resulting from co-regulation and independent co-expression. Furthermore, modules of co-regulated genes may only show tight co-expression across a subset of the time series, i.e. show condition-dependent regulation. RESULTS: Wigwams is a simple and efficient method to identify gene modules showing evidence for co-regulation in multiple time series of gene expression data. Wigwams analyzes similarities of gene expression patterns within each time series (condition) and directly tests the dependence or independence of these across different conditions. The expression pattern of each gene in each subset of conditions is tested statistically as a potential signature of a condition-dependent regulatory mechanism regulating multiple genes. Wigwams does not require particular time points and can process datasets that are on different time scales. Differential expression relative to control conditions can be taken into account. The output is succinct and non-redundant, enabling gene network reconstruction to be focused on those gene modules and combinations of conditions that show evidence for shared regulatory mechanisms. Wigwams was run using six Arabidopsis time series expression datasets, producing a set of biologically significant modules spanning different combinations of conditions. AVAILABILITY AND IMPLEMENTATION: A Matlab implementation of Wigwams, complete with graphical user interfaces and documentation, is available at: warwick.ac.uk/wigwams. .

Conserved noncoding sequences highlight shared components of regulatory networks in dicotyledonous plants.

Conserved noncoding sequences (CNSs) in DNA are reliable pointers to regulatory elements controlling gene expression. Using a comparative genomics approach with four dicotyledonous plant species (Arabidopsis thaliana, papaya [Carica papaya], poplar [Populus trichocarpa], and grape [Vitis vinifera]), we detected hundreds of CNSs upstream of Arabidopsis genes. Distinct positioning, length, and enrichment for transcription factor binding sites suggest these CNSs play a functional role in transcriptional regulation. The enrichment of transcription factors within the set of genes associated with CNS is consistent with the hypothesis that together they form part of a conserved transcriptional network whose function is to regulate other transcription factors and control development. We identified a set of promoters where regulatory mechanisms are likely to be shared between the model organism Arabidopsis and other dicots, providing areas of focus for further research.

Recombinants between Deformed wing virus and Varroa destructor virus-1 may prevail in Varroa destructor-infested honeybee colonies.

We have used high-throughput Illumina sequencing to identify novel recombinants between Deformed wing virus (DWV) and Varroa destructor virus-1 (VDV-1), which accumulate to higher levels than DWV in both honeybees and Varroa destructor mites. The recombinants, VDV-1(VVD) and VDV-1(DVD), exhibit crossovers between the 5'-UTR and the regions encoding the structural (capsid) and non-structural viral proteins. This implies that the genomes are modular and that each region may evolve independently, as demonstrated in human enteroviruses. Individual honeybee pupae were infected with a mixture of observed recombinants and DWV. A strong correlation was observed between VDV-1(DVD) levels in honeybee pupae and associated mites, suggesting that this recombinant, with a DWV-derived 5'-UTR and non-structural protein region flanking a VDV-1-derived capsid-encoding region, is better adapted to transmission between V. destructor and honeybees than the parental DWV or a recombinant bearing the VDV-1-derived 5'-UTR (VDV-1(VVD)).