Distribution of transcription factor binding sites in the yeast genome suggests abundance of coordinately regulated genes.

The availability of whole genomic DNA sequences makes it possible to analyze regulatory DNA regions on a genomewide scale. Characterization of such regions will be crucial to understand how the parts of an organism cooperate to build the whole. This is a difficult undertaking, as the example of eukaryotic promoter (enhancer) regions shows. It is common practice among molecular biologists to search for binding sites of transcription factors (TFs) in the noncoding regions surrounding a gene to form hypotheses about transcriptional regulation of the gene. This method often fails, because many TF binding sites are frequent in genomic DNA, and the occurrence of one binding site alone does not indicate its functional significance. When analyzing multi-megabase regions for regulatory regions, one would hope that it is possible to devise more sensitive techniques that take advantage of the large amounts of statistical information extractable from whole genome sequences. For the analysis of regulatory regions, an important question in this regard is whether the genome-wide distribution of TF binding sites could be used to make inferences about transcriptional regulation of individual genes. The transcription of many, if not most, eukaryotic genes is cooperatively regulated via one kind (homotypic cooperativity) or several kinds (heterotypic cooperativity) of TFs. Such cooperativity requires binding of transcriptional regulators to closely spaced binding sites in regulatory regions. While the exact spacing and order of TF binding sites are often irrelevant, the fact alone that TF binding sites are spaced more closely in these regions than expected “by chance alone” may be used to detect regulatory regions on a genome-wide scale. In other words, if a TF shows cooperativity for at least some of the genes it regulates, closely spaced TF binding sites in a region of the genome may indicate that a nearby gene is regulated by the TF, a hypothesis that can then be tested experimentally. This approach requires some notion of statistically significant groups (“clusters”) of TF binding sites; that is, what does it mean to say that a group of binding sites is linked more tightly than expected by chance alone? Recently, a statistical technique for whole genome analysis was proposed (9) that makes the notion of significant clustering of TF binding sites precise and that allows detection of significant binding site clusters in a genome. Given one or more TFs with well-defined binding sites, the method identifies the best candidate genes for regulation by the TFs in a genome, based on significant binding site clusters. When applied to the genome of Saccharomyces cerevisiae for homotypic site clusters, the technique detects binding site clusters (i) upstream of genes experimentally known to be regulated by the respective TFs and (ii) upstream of genes that play a role in the same biochemical process as the TF (e.g., cell-cycle regulation), but for which it is not known whether the TF regulates their expression. Notably, while there can be thousands of binding sites for a specific TF in the genome, the number of significant clusters of binding sites is typically small (9). When analyzing the distribution of individual sites belonging to such clusters, one finds that they occur with strong preference in noncoding regions, as would be expected for yeast TF binding sites that play a role in transcriptional regulation. Although base composition may be a rather poor predictor of site frequency (4), it may be worth pointing out that this bias cannot be explained on the basis of different base compositions in coding and noncoding regions. Further validation of the method is currently limited by published information on specific TFs and the genes they regulate, but will soon become easier as vast amounts of expression data from transcript arrays become available for yeast. While a technique like this can help generate hypotheses on particular TFs and genes they regulate, application to a larger sample of TFs can reveal patterns that cannot be detected by looking at individual factors, but may reveal information about genome organization or global regulatory patterns. The information displayed in Table 1 shows a potential example of such a pattern. It is based on analysis of the yeast genome for homotypic binding site clusters of a larger sample of TFs than the previous study. TFs represented in this list were chosen from a public database (10) on the basis of two criteria for their DNA binding sites. First, their binding sites are among the best characterized in yeast. Second, their binding sites occur at an intermediate frequency (.50 copies) in the genome. Very frequent binding sites, such as the heat shock factor (HSF) binding site with .10 occurrences, were excluded, because they are closely spaced throughout the entire genome. The resulting list of sites in Table 1 includes TFs involved in particular cellular processes (e.g., SBF, cell-cycle regulation; 6), but also general TFs involved in the regulation of many different kinds of genes (REB1; Ref. 3), and factors that also have functions other than transcriptional regulation (e.g., CBF1, implicated in centromere function; Ref. 5). The number of individual binding sites that are part of significant clusters is listed separately for coding and noncoding regions in columns 2 and 3 of Table 1. Given that approximately 72% of the yeast genome is protein-coding (2), one would expect a 72:28 percentage ratio of sites in coding and noncoding regions, respectively. When testing the null hypothesis that the observed number of sites is consistent with this expectation by a x test, one finds that clusters for 1 Address correspondence to author at University of New Mexico, Department of Biology, 167A Costetter Hall, Albuquerque, New Mexico 87131-1091. Telephone: (505) 984-8800, Ext. 231. Fax: (505) 982-0565. E-mail: aw@santafe.edu.