Abstract:
We read the genome as proteins in the cell would – by studying the distributions of 5–6 base motifs of DNA in the whole genome or smaller stretches such as parts of, or whole chromosomes. This led us to some interesting findings about motif clustering and chromosome organization. It is quite clear that the motif distribution in genomes is not random at the length scales we examined: 1 kb to entire chromosomes. The observed-to-expected (OE) ratios of motif distributions show strong correlations in pairs of chromosomes that are susceptible to translocations. With the aid of examples, we suggest that similarity in motif distributions in promoter regions of genes could imply co-regulation. A simple extension of this idea empowers us with the ability to construct gene regulatory networks. Further, we could make inferences about the spatial proximity of genomic fragments using these motif distributions. Spatially proximal regions, as deduced by Hi-C or pcHi-C, were ∼3.5 times more likely to have their motif distributions correlated than non-proximal regions. These correlations had strong contributions from the CTCF protein recognizing motifs which are known markers of topologically associated domains. In general, correlating genomic regions by motif distribution comparisons alone is rife with functional information.