7 research outputs found

    Additional file 1: of In silico screening for candidate chassis strains of free fatty acid-producing cyanobacteria

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    Table S1. Classification of orthologous groups. Table S2. Proteins used to construct Fig. 1. Table S3. Compilation of control dataset. Table S4. Constructed target species dataset. Table S5. Comparison of FFASC and Model SEED. Table S6. Free fatty acid (FFA) protein/enzyme domains. Table S7. Orthologous group hit number matrix of 49 OGs and 128 (cyanobacteria and diatom) strains. Table S8. Ranked list of 125 strains using FFASC. Table S9. 128 strains clustered using K-mean. Table S10. Ranked list of 125 cyanobacteria using FFASC without optimization. (XLSX 373 kb

    Additional file 1: of In silico exploration of Red Sea Bacillus genomes for natural product biosynthetic gene clusters

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    Table S1. Basic statistics relating to the PacBio SMRT sequencing that was done for B. paralicheniformis B48 and B84. A single SMRT cell was sequenced for each strain. Table S2. Levels of completeness and contamination in Bac48 and Bac84 as determined in CheckM. Figure S1. Similarity between the genomes of B. paralicheniformis Bac48 and B. paralicheniformis Bac84. A) Circos figure showing synteny blocks between B. paralicheniformis Bac48 and B. paralicheniformis Bac84. Table S3. List of genomic island regions in the genomes of B. paralicheniformis Bac48 and B. paralicheniformis Bac84, predicted using IslandViewer [4]. Table S4. Predicted prophage regions in B. paralicheniformis Bac48 and B. paralicheniformis Bac84 and their overlap with GIs. Scores were obtained using PHASTER [5] scoring scheme. Most Common Phage shows the phage ID(s) with the highest number of proteins most similar to proteins in the region. Overlap percentage show the length of overlap region with respect to the length of prophage. Figure S2. Similarity network showing 54 groups of similar BGCs. Strains are color coded as per the legend. A product is assigned - shown on top of each group of nodes- if the clusters in the group share more than 60% similarity to the product. Similar gene clusters from different genomes were classified into groups based on homology using BiG-SCAPE [33] and visualized using Cytoscape [6]. (DOCX 4336 kb
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