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Additional file 2: Table S1. List of the 16 CpG and 33 non-CpG genomic ranges used in the combined prediction model. Each of the chr, start, and end columns indicate chromosome and location information. R is the Pearson’s correlation coefficient, and p is the f-test result p-value. The type column indicates a CpG or non-CpG region.

Additional file 2: Table S1. List of the 16 CpG and 33 non-CpG genomic ranges used in the combined prediction model. Each of the chr, start, and end columns indicate chromosome and location information. R is the Pearson’s correlation coefficient, and p is the f-test result p-value. The type column indicates a CpG or non-CpG region.

Additional file 1: Figure S1. Distributions of correlation coefficients between pluripotent and differentiation marker gene expressions and cell orders of each ordering method. Figure S2. Pluripotent gene expression levels according to cell pseudo-time. Figure S3. Overall CpG methylation and non-CpG methylation levels relative to cell culture environment. Figure S4. Prediction of cell culture environmnet by proposed model using external dataset. Figure S5. Distributions of estimated cell pseudo-times by linear regression analysis. Figure S6. A sliding window approach to define methylation levels at each genomic interval. Figure S7. Selection of λ values of pluripotency prediction models.

Figure S1. Selection of prognostic candidate-genes based on log-rank test. Table S1. The prediction of patientsâ outcome based on log-rank test according to varied correlation thresholds. Table S2. The gene list of module 1 including previously defined prognostic factor. (DOCX 179 kb)

E. coli sequence type 131 (ST131) is one of pathogens that causes resistant infections. Comparative genome analyses allow interpretations of the virulence factors of pathogens. Thus, in this study, we analysis the genomic differences between the pathogenic E. coli ST131 and the non-pathogenic E. coli K-12. In this study, we identify the genomic differences between 96 E. coli ST131 strains and the E. coli K-12 in gene elements and their non-coding regulation elements. Using next-generation whole-genome sequencing data, we investigated genetic variations of protein-coding regions and their regulation regions. After the alignment of the sequence reads, large numbers of single nucleotide variants (SNVs) were observed in the regulation and protein-coding sequences. In the regulation regions, we found strong conserved regions, in this case, ribosome binding sites. In the gene regions, we found conserved start and stop codons with the specific position varying commonly in each codon. Except for these well-conserved regions, other variations were randomly distributed in regulation regions. Even a region having well-known conserved sequences such as -10 and -35 in the promoter had a similar level of variation. In this study, we found genomic variations between the pathogenic E. coli ST 131 strain and the non-pathogenic E. coli K-12. In addition, the numbers of sequence variations were determined in both the protein-coding regions and the regulation regions. However, we found that the effects of variations on the protein-coding regions are less significant than those on the regulation regions.