Figure 1.
Visual representation of the data flow through each of the steps in the CMG-biotools system. The figure shows the analysis input and program name along with the analysis output type. Green arrows indicate data extraction from a GenBank file format, this data needs to be available in the file for these steps to work. Red arrows indicate local genefinding which results in gene FASTA, protein FASTA and GenBank files.
Table 1.
Genome information.
Table 2.
Genome statistics.
Table 3.
Genefinding and published genes.
Figure 2.
Each genome sequence was searched for 16S rRNA patterns and candidate sequences were extracted. The best sequence from each genome was selected. For two genomes, no sequences were found, Centipeda periodontii DSM 2778, Megamonas hypermegale ART12 1. For 6 additional genomes, the located sequences were shorter than the default acceptable length. The short sequences sequences are marked with a “*”. Length criteria was changed from minimum 1 400 to 1 100 and maximum 1 800 unchanged. The distance tree was made with 1 000 bootstraps.
Table 4.
Ribosomal RNA analysis using RNAmmer.
Figure 3.
Genome atlases, DNA structures.
A DNA structural atlas was generated for each of the 6 complete genomes. DNA, RNA and gene annotations are from the published GenBank data. Each lane of the circular atlas shows a different DNA feature. From the innermost circle: size of genome (axis), percent AT (red = high AT), GC skew (blue = most G’s), inverted and direct repeats (color = repeat), position preference, stacking energy and intrinsic curvature. Orange arrows indicate changes in the skew of G and C, which frequently indicate origin and terminus of replication. Blue arrows show the location of rRNA operons, as annotated in the GenBank file. Dark red arrows highlight areas of the genome that show significantly different DNA structures than the rest of the genome. A higher resolution pdf is available as a supplemental figure. A high resolution figure can be found as supplemental Figure S1.
Figure 4.
The bias in third codon position is visualized for each of the 6 complete genomes. The bias was defined as −1 in the case of 100% A or T in third position, +1 is the case of 100% G or C.
Figure 5.
Amino acid and codon usage heatmaps.
Amino acid and codon usage were for all 31 genomes calculated based on the genes identified by gene finding (Prodigal). The percentage of codon and amino acid usage was plotted in two heatmaps using R. The heatmaps were clustered in 2D, thus reordering the organisms and the amino acids/codon to show the shortest distance between them. Dendograms were draw for both and can be used to visualize the difference in usage between organisms.
Figure 6.
An all against all protein comparison was performed using BLAST to define homologs. A BLAST hit is considered significant if 50% of the alignment consists of identical matches and the length of the alignment is 50% of the longest gene. Internal homology (paralogs) is defined as proteins within a genome matching the same 50–50 requirement as for between-proteome comparisons. Self-matches are here ignored. A comparison of 31 Negativicutes genomes was performed on the CMG-biotools system (9 hours). A high resolution figure can be found as supplemental Figure S2.
Figure 7.
Core and pan genome using BLAST.
A pan- and core-genome calculation was performed using BLAST. A BLAST cutoff of 50% identity and 50% coverage of the longest gene was used. If two proteins within a genome matched according to the 50/50% cutoff, they were clustered into one protein family. Protein families were extended via single linkage clustering. If a protein family includes proteins from all genomes in the comparison, the family is a core protein family.