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The Del(13)Svea36H mutation (referred to hereafter as Del36H) is a microscopically visible deletion of ∼20% of mouse chromosome 13 (Arkell et al. 2001). Mice that are heterozygous for Del36H display a phenotype that varies with genetic background and that can involve reduced size, craniofacial malformation, eyes open at birth, and a mild tail kink. These mice may model some aspects of human genetic disease, because the Del36H region shows conserved synteny with regions of human chromosome 6p22.1-6p22.3 and 6p25 that are lost in some deletion syndromes (Davies et al. 1999). Furthermore, several disease loci map to this region in humans: two eye defects (iridogoniodysgenesis and Axenfeld-Rieger anomaly; Mears et al. 1998; Nishimura et al. 1998), haemochromatosis (Feder et al. 1996), dyslexia (Grigorenko et al. 2003), and schizophrenia susceptibility (Straub et al. 2002). Mice with interstitial chromosome deletions like Del36H are potent experimental tools for functional genomics. In particular, they can be used to reveal recessive phenotypes due to mutations that map to a specific chromosomal region. However, the positional candidate approach to identifying mutations in genes underlying mutant phenotypes remains nontrivial, especially for point mutations such as those induced by ENU (Brown and Hardisty 2003). A prerequisite for effective mutation detection using this approach is a comprehensive gene list, with exhaustive annotation of exons and regulatory elements. A limited catalog of the genes deleted in Del36H can be found in genetic and radiation hybrid maps (Arkell et al. 2001; Avner et al. 2001; Hudson et al. 2001), and an automatically annotated genomic sequence is available (Waterston et al. 2002), but the current public mouse genome assembly is a mixture of draft and finished sequence and, by definition, draft genomic sequence contains gaps and regions of lower sequence quality. These artefacts can influence gene annotation and, therefore, the subsequent design of mutation detection assays. Manual annotation, in contrast, should provide a gold standard reference set. As well as being an invaluable resource for functional genomics, a large genomic region of this kind provides an opportunity to investigate the organization and evolution of a significant piece of the mouse genome. Such studies also rely on high-quality sequence and manual gene annotation to avoid errors in sequence alignment, identification of coding and pseudogenes, classification of repetitive elements, and so on. The accumulating information on genome sequences from a number of species raises many questions about genome evolution. Important among these are the relative roles of whole-genome, segmental, and individual gene duplication, and the mechanisms underlying these processes (Lynch and Conery 2000; Dehal et al. 2001; Eichler and Sankoff 2003; Friedman and Hughes 2004); the usefulness of inter-genome comparisons for identifying selectively conserved regions in genomes, including not only genes, but regulatory regions and functional RNA genes (Mallon et al. 2000; Dehal et al. 2001; Dermitzakis et al. 2002; Kondrashov and Shabalina 2002; Margulies et al. 2003; Frazer et al. 2004); the roles of repeated (transposable element-like) and repetitive (satellites, microsatellites, and minisatellites) sequences in genome evolution (Toth et al. 2000; Hancock 2002; Babcock et al. 2003; Alba and Guigo 2004; Han et al. 2004; Kazazian Jr. 2004); and the characteristics of sites of evolutionary chromosome breakpoints (Puttagunta et al. 2000; Dehal et al. 2001; Pevzner and Tesler 2003). Here, we describe the genomic architecture of Del36H based on 12.66 Mb of finished DNA sequence, annotated using a combination of manual annotation with synteny and comparative sequence analysis. We find that the region is gene rich, primarily as the result of high gene densities in regions containing gene families that are smaller or absent in the orthologous human regions, and which appear to contribute to the special requirements of the lifestyle of the mouse. We consider forces and processes that may have contributed to the expansion of these gene families during evolution. We also identify a segment of Del36H containing two nearby evolutionary breakpoints, and show that these lie in a gene desert, a potentially optimal site for chromosome breakage. Finally, we consider the evolutionary dynamics of Evolutionarily Conserved Regions (ECRs; Mallon et al. 2000) within Del36H and their potential application to the identification of regulatory, and potentially other functional sequences within noncoding regions of the mouse genome.

The stem cell leukemia (SCL) gene encodes a bHLH transcription factor with a pivotal role in hematopoiesis and vasculogenesis and a pattern of expression that is highly conserved between mammals and zebrafish. Here we report the isolation and characterization of the zebrafish SCL locus together with the identification of three neighboring genes, IER5,MAP17, and MUPP1. This region spans 68 kb and comprises the longest zebrafish genomic sequence currently available for comparison with mammalian, chicken, and pufferfish sequences. Our data show conserved synteny between zebrafish and mammalian SCL and MAP17 loci, thus suggesting the likely genomic domain necessary for the conserved pattern ofSCL expression. Long-range comparative sequence analysis/phylogenetic footprinting was used to identify noncoding conserved sequences representing candidate transcriptional regulatory elements. The SCL promoter/enhancer, exon 1, and the poly(A) region were highly conserved, but no homology to other known mouseSCL enhancers was detected in the zebrafish sequence. A combined homology/structure analysis of the poly(A) region predicted consistent structural features, suggesting a conserved functional role in mRNA regulation. Analysis of the SCL promoter/enhancer revealed five motifs, which were conserved from zebrafish to mammals, and each of which is essential for the appropriate pattern or level ofSCL transcription.[The following individuals kindly provided reagents, samples, or unpublished information as indicated in the paper: N. Tanese.]

Ensembl (http://www.ensembl.org/) is a bioinformatics project to organize biological information around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of individual genomes, and of the synteny and orthology relationships between them. It is also a framework for integration of any biological data that can be mapped onto features derived from the genomic sequence. Ensembl is available as an interactive Web site, a set of flat files, and as a complete, portable open source software system for handling genomes. All data are provided without restriction, and code is freely available. Ensembl's aims are to continue to “widen” this biological integration to include other model organisms relevant to understanding human biology as they become available; to “deepen” this integration to provide an ever more seamless linkage between equivalent components in different species; and to provide further classification of functional elements in the genome that have been previously elusive.

Comparative analysis of genomic sequences is becoming a standard technique for studying gene regulation. However, only a limited number of tools are currently available for the analysis of multiple genomic sequences. An extensive data set for the testing and training of such tools is provided by the SCL gene locus. Here we have expanded the data set to eight vertebrate species by sequencing the dog SCL locus and by annotating the dog and rat SCL loci. To provide a resource for the bioinformatics community, all SCL sequences and functional annotations, comprising a collation of the extensive experimental evidence pertaining to SCL regulation, have been made available via a Web server. A Web interface to new tools specifically designed for the display and analysis of multiple sequence alignments was also implemented. The unique SCL data set and new sequence comparison tools allowed us to perform a rigorous examination of the true benefits of multiple sequence comparisons. We demonstrate that multiple sequence alignments are, overall, superior to pairwise alignments for identification of mammalian regulatory regions. In the search for individual transcription factor binding sites, multiple alignments markedly increase the signal-to-noise ratio compared to pairwise alignments.