| Summary: | Abstract Background The crucial factor in the production of bio-fuels is the choice of potent microorganisms used in fermentation processes. Despite the evolving trend of using bacteria, yeast is still the primary choice for fermentation. Molecular characterization of many genes from baker’s yeast (Saccharomyces cerevisiaea), and fission yeast (Schizosaccharomyces pombe), have improved our understanding in gene structure and the regulation of its expression. This in silico study was done with the aim of analyzing the promoter regions, transcription start site (TSS), and CpG islands of genes encoding for alcohol production in S. cerevisiaea S288C and S. pombe 972h-. Results The analysis revealed the highest promoter prediction scores (1.0) were obtained in five sequences (AAD4, SFA1, GRE3, YKL071W, and YPR127W) for S. cerevisiaea S288C TSS while the lowest (0.8) were found in three sequences (AAD6, ADH5, and BDH2). Similarly, in S. pombe 972h-, the highest (0.99) and lowest (0.88) prediction scores were obtained in five (Adh1, SPBC8E4.04, SPBC215.11c, SPAP32A8.02, and SPAC19G12.09) and one (erg27) sequences, respectively. Determination of common motifs revealed that S. cerevisiaea S288C had 100% coverage at MSc1 with an E value of 3.7e−007 while S. pombe 972h- had 95.23% at MSp1 with an E value of 2.6e+002. Furthermore, comparison of identified transcription factor proteins indicated that 88.88% of MSp1 were exactly similar to MSc1. It also revealed that only 21.73% in S. cerevisiaea S288C and 28% in S. pombe 972h- of the gene body regions had CpG islands. A combined phylogenetic analysis indicated that all sequences from both S. cerevisiaea S288C and S. pombe 972h- were divided into four subgroups (I, II, III, and IV). The four clades are respectively colored in blue, red, green, and violet. Conclusion This in silico analysis of gene promoter regions and transcription factors through the actions of regulatory structure such as motifs and CpG islands of genes encoding alcohol production could be used to predict gene expression profiles in yeast species.
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