Additional file 4: of A core phylogeny of Dictyostelia inferred from genomes representative of the eight major and minor taxonomic divisions of the group

Tree error compensation by concatenation. Concatenated alignments of two or three proteins that individually yielded trees with a single non-consensual node at different positions were subjected to Bayesian inference as described for Additional file 3. Four out of five concatenated alignments (B-E) yielded the consensus tree (A). Only aco1 required two additional proteins to correct its topology errors. (PDF 122 kb

Additional file 3: of A core phylogeny of Dictyostelia inferred from genomes representative of the eight major and minor taxonomic divisions of the group

Phylogenies inferred from 47 individual proteins. Consensus alignments of orthologous sequences of 47 proteins retrieved from 14 amoebozoan genomes were determined using M-coffee, with eight alignment algorithms. Regions with poor consensus alignment or with long insertions in only few proteins were deleted. Phylogenies were inferred by Bayesian inference using a mixed amino-acid substitution models with rate variation between sites estimated by a gamma distribution with a proportion of invariable sites. Analysis were run for one million generations. Trees were rooted at midpoint using Figtree ( http://tree.bio.ed.ac.uk/software/figtree/ ), with posterior probabilities shown at the nodes. Panel A: proteins a-h; Panel B: proteins m-x. The consensus phylogeny of all 47 concatenated proteins (see also Fig. 2) is shown top left in Panel A. (PDF 156 kb

Additional file 2: of Gen2Epi: an automated whole-genome sequencing pipeline for linking full genomes to antimicrobial susceptibility and molecular epidemiological data in Neisseria gonorrhoeae

Technical details. (DOCX 20 kb

Additional file 1: of Gen2Epi: an automated whole-genome sequencing pipeline for linking full genomes to antimicrobial susceptibility and molecular epidemiological data in Neisseria gonorrhoeae

Table S1. Datasets used for pipeline testing and evaluation. Table S2. Names and accession numbers of input data used by the Gen2Epi pipeline. Table S3. List of third-party software incorporated into Gen2Epi. Table S4. Sample output generated from Gen2Epi’s AMR & Molecular Epidemiological Analysis step shown in tabular form. (DOCX 25 kb

Additional file 3: of Gen2Epi: an automated whole-genome sequencing pipeline for linking full genomes to antimicrobial susceptibility and molecular epidemiological data in Neisseria gonorrhoeae

Figure S1. Genome alignment of the Gen2Epi-produced WHO G scaffold against the corresponding Neisseria gonorrhoeae reference genome using Mauve. The extent of the colored bar indicates the strong similarity between the scaffold and the reference genome. (DOCX 48 kb

Additional file 2: Figure S3. of Improved annotation with de novo transcriptome assembly in four social amoeba species

Annotated domain diagrams for 16 D. discoideum developmentally relevant proteins which have had their protein sequence altered. (PDF 367 kb

Additional file 1: Figure S1. of Improved annotation with de novo transcriptome assembly in four social amoeba species

TAGC plot for D. fasciculatum (A) and D. lacteum (B) before and after filtering. Each colour blob represents different taxa with unmatched transcripts are shaded in grey. The unannotated grey coloured transcripts after filtration set further filtered by high GC and low read coverage. This plot shows a major blob of transcripts that are annotated with the Dictyostelium fasciculatum species with high coverage and lower GC content. Other contaminations form E.coli, pseudomonas fluorescence and other species has also been highlighted with different colours. These contaminations clearly make different blobs with lower read coverage and high GC content. However, it’s good to see that there are some other transcripts that showing matched to dictyostelium discoideum- that clearly reflect the presence of some novel unannotated transcripts in the new assembly. Figure S2 A comparison of assembled transcripts read count. The boxplots represent the range between the 1st and 3rd quartiles of the data by the coloured boxes, the median is the horizontal bar and points shown beyond the whiskers are >95% of the data. Table S3 Transrate good contigs. Table S4 Olignucleotide sequences. Table S5 Alignment with DNA sequence of PCR product. (DOCX 787 kb

Additional file 4: Table S2. of Improved annotation with de novo transcriptome assembly in four social amoeba species

List of PASAua novel genes in D. discoideum. (XLSX 13 kb

Additional file 3: Table S1. of Improved annotation with de novo transcriptome assembly in four social amoeba species

D. discoideum GFF file of genomic positions with introns < 5 bp. (TXT 9 kb

Supplementary Data, Supplementary Figures and Legends 1-13 from Inhibition of O-GlcNAc Transferase Renders Prostate Cancer Cells Dependent on CDK9

Supplementary figure 1. Validation of synthetic lethal interaction between OGT inhibition and AT7519 in LNCaP cells. Supplementary figure 2. Validation of synthetic lethal interaction between OSMI-2 and AT7519 in additional cell lines. Supplementary figure 3. Combination of OSMI-2 with AT7519 induces cells death in prostate cancer cells but not in cells derived from normal prostate epithelia. Supplementary figure 4. Characterization of RNA-seq data of cells treated with OGT inhibitor OSMI-2. Supplementary figure 5. OGT inhibition decreases phosphorylation of the carboxyterminal domain of RNA polymerase II. Supplementary figure 6. AT7519 enhances the effects of OGT inhibition by blocking the upregulation of OGT in PC3 cells. Supplementary figure 7. Summary of the RNA-seq data. Supplementary figure 8. Specific CDK9 inhibitor NVP2 is synthetically lethal in combination with OGT inhibition to LNCaP prostate cancer cells. Supplementary figure 9. OGT inhibition potentiates the anti-proliferative effects of CDK9 inhibitors Dinaciclib and SB1317 on prostate cancer cells. Supplementary figure 10. Knockdown of CDK9 sensitizes LNCaP prostate cancer cells to OGT inhibition. Supplementary figure 11. Combination of OSMI-2 with AT7519 further decreases the mRNA abundance of most mRNAs with half-life less than 4 hours. Supplementary figure 12. Determination of CDK9 inhibitor dose suitable for organoid experiments. Supplementary figure 13. Validation of synthetic lethality between inhibitors of OGT and CDK9 using models of castration-resistant prostate cancer (CRPC).</p