Long Human–Mouse Sequence Alignments Reveal Novel Regulatory Elements: A Reason to Sequence the Mouse Genome

The utility of sequencing entire genomes of bacteria and fungi is amply demonstrated. For instance, as the complete set of genes for each species is catalogued, one can ascertain the full complement of encoded proteins, obtain insights into the function of new proteins by sequence matches to known proteins, and measure the transcriptional levels of all genes in a genome under various environmental conditions or at different stages of the cell cycle (Boguski et al. 1996; Velculescu et al. 1997). The currently sequenced genomes consist primarily of coding regions with little sequence between the genes, and the amount of genetic information in each segment is usually quite high. Larger genomes from more complex organisms have a considerable amount of DNA between the genes and in introns that interrupt the coding regions, and one could question whether it is useful to determine the sequences of all of these noncoding regions. Indeed, the concerted efforts to determine partial sequences of normalized cDNA libraries have generated rich and very useful databases, such as the TIGR database (TDB) and dbEST (Adams et al. 1991; Boguski 1995). Efforts from Schuler and his colleagues to unite the several sequences from each set of cDNA clones representing a unique gene, the UniGene project, will organize this large amount of sequence data. As of late 1996, the UniGene database contained samples of sequences of almost 50,000 genes, which could represent a majority of human genes (Schuler et al. 1996). Of these UniGene clusters, 16,000 have been placed on the human genome map, which will greatly aid in positional cloning of interesting genes. Although TDB, dbEST, and UniGene are extremely useful, they do have limitations. For instance, comparison of a long genomic DNA sequence with the expressed sequence tag (EST) databases is a very effective method for identifying many of the exons. A recent comparison of programs for predicting gene structures revealed that inclusion of protein sequence similarity searches improved performance (Burset and Guigo 1996), and the most efficient approach to identifying genes in a 284-kb sequence from the end of the short arm of human chromosome 16 was by comparison with the EST databases (Flint et al. 1997). However, it is rare for the EST entries to encompass the complement to an entire mRNA, and hence all exon assignments usually cannot be obtained from the ESTs. In constrast, an alignment of complete sequences of homologous loci between mouse and human will reveal almost all of the exons as regions of particularly high sequence conservation, at least for most loci (see below). This approach is not limited by the abundance of the mRNA in the tissue samples or the completeness of coverage of the cDNA sequence in the EST databases. A second limitation of the EST databases is the paucity of noncoding sequence in the entries; such sequences are limited to the 58and 38-untranslated regions of the mRNA. Most DNA sequences involved in regulation of gene expression are in noncoding regions; obviously these DNA segments flanking and interrupting the coding regions will have to be sequenced to obtain sequences of regulatory regions. This will occur as the projects determining the complete human genome sequence are completed. But how does one extract information about potential regulatory sequences, and is that information useful in designing experiments to test proposed functions? One standard approach is to determine the DNA sequence from additional species and seek out candidates for conserved sequences, that is, sequences that change only slowly during evolution because such sequence alterations Corresponding author. E-MAIL webb@cse.psu.edu; FAX (814) 865-3176. PERSPECTIVE