BMC Genomics 2009, 10:576 http://www.biomedcentral.com/1471-2164/10/576 window to a matrix of the likelihood for each position (Additional files 2 &3) along the 10 bp consensus sequence (the Position Weight Matrix, PWM). Each base pair is given a value equivalent to the decimal percentage of its match to the known YY1 binding motifs. The four base pair core, CCAT, is scored at 100% for each base plus 2. Flanking bases vary in score from 0 to 1 based upon their frequency in known YY1 binding motifs. The total score for each 10 bp window is calculated and compared to our cutoff score of 8.0 which indicates a good match. Our previous work revealed that scores above 8.0 correlate with good YY1 binding in vitro [1,35]. Output was gener- ated in the WIG format for each chromosome with each YY1 binding motif score represented by start and end position and bar height corresponding to the PWM score match. Position weight matrix scores and location infor- mation were loaded into the University of California, Santa Cruz (UCSC) Genome Browser for visualization of YY1 location (Figure 1) [36]. Motif finding and scoring Our Perl script was run against the mouse, human and zebrafish mRNA available from NCBI ftp:// ftp.ncbi.nih.gov/genomes/. Each gene was scored for number and quality of YY1 motifs. Results were sorted by a YY1 density score, the combined score of YY1 motifs divided by the length of the gene. Predicted and hypothet- ical genes were removed from the mouse yielding 40,009 total genes (19,818 removed, 20,191 remaining), with 19,083 non-olfactory and 1,108 olfactory genes. Hypo- thetical genes were removed from the human transcrip- tome, yielding 24,886 total genes with 24,506 non- olfactory and 380 olfactory genes. Hypothetical genes were removed from the zebrafish transcriptome, yielding 9,092 genes with 9,067 non-odorant genes and 25 odor- ant receptors. We removed the hypothetical and predicted genes because they may not contain complete ORFs. The upstream 1 kb regions of 20419 Refseq genes in the mouse was obtained from UCSC http://hgdown load.cse.ucsc.edu/downloads.html. Histograms were made in Microsoft Excel 2007 by sorting the genes by YY1 density from high to low, then assigning a count to order the genes. Olfactory receptor genes were separated from non-olfactory receptor genes and the count numbers were used as position information to make a histogram which shows the distribution of OLFRs along the range of YY1 containing genes (Figure 2). Protein motif correlation testing The mouse proteome was downloaded from NCBI ftp:ftp.ncbi.nih.gov/genomes/M_musculus/protein/pro tein.fa.gz which contains 34,966 peptide sequences and nomenclature. Olfactory receptor proteins (1,178) were separated from non-olfactory proteins (33,788). A Perl script, dipep-singlefile.pl was used to generate a count of each of the 400 possible dipeptides in each of these groups (see Additional file 4). A Z-test was performed according to the formula Z = (observed - μ)/δ where observed is the count of each pos- sible dipeptide found in olfactory receptors, μ is the mean of the counts from the whole population of non-olfactory proteins, and δ is the standard deviation of the population count. Z-score units are given in standard deviations from the mean. Expected count was calculated by multiplying the frequency of each dipeptide from all non-olfactory receptor proteins by the total number of dipeptides seen in OLFR proteins. Figure 4 shows the plot generated in Microsoft Excel 2007 comparing the observed to expected ratio for all 400 possible dipeptides and the subset of 49 YY1 core-forming dipeptides which exhibits no difference in the distribution of the subset. We found 21 of the 49 dipeptides which can make up a YY1 binding site had greater than expected values, but only 2 were over 3 standard deviations away from the mean (Table 1, Figure 4). Table 1 shows only the dipep- tides in which the observed count in olfactory genes was higher than the expected count in mouse. Global alignment was done using ClustalW with 1,178 OLFR and 6 hist1 h4 amino acid sequences from mouse (Figure 5) [37]. All Perl scripts are available for download on our website at http://JooKimLab.lsu.edu[38]. Abbreviations YY1: Yin-Yang 1; SINE: Short interspersed element; LINE: Long interspersed element; OLFR: Olfactory receptor; OR: Odorant receptor; PWM: Position weight matrix; UCSC: University of California at Santa Cruz; ORF: Open reading frame; WIG: Wiggle format; NCBI: National center for biotechnology information. Authors' contributions CF carried out the coding, genome scanning, performed the statistical analyses, and participated in the design of the study. JK conceived of the study, and participated in its design and coordination. All authors read and approved of the final manuscript. Additional material Additional file 1 Position Weight Matrix Perl program. Perl program "matrix-bidirec- tional.pl.txt" uses position weight matrix files and fasta formatted input files to generate positional and scoring data for YY1 binding sites. Click here for file [http://www.biomedcentral.com/content/supplementary/1471- 2164-10-576-S1.TXT] Page 9 of 10 (page number not for citation purposes)