Here we report a high-quality draft genome sequence of the domestic dog (Canis familiaris), together with a dense map of single nucleotide polymorphisms (SNPs) across breeds. The dog is of particular interest because it provides important evolutionary information and because existing breeds show great phenotypic diversity for morphological, physiological and behavioural traits. We use sequence comparison with the primate and rodent lineages to shed light on the structure and evolution of genomes and genes. Notably, the majority of the most highly conserved non-coding sequences in mammalian genomes are clustered near a small subset of genes with important roles in development. Analysis of SNPs reveals long-range haplotypes across the entire dog genome, and defines the nature of genetic diversity within and across breeds. The current SNP map now makes it possible for genome-wide association studies to identify genes responsible for diseases and traits, with important consequences for human and companion animal health.

Genomewide association mapping in model organisms such as inbred mouse strains is a promising approach for the identification of risk factors related to human diseases. However, genetic association studies in inbred model organisms are confronted by the problem of complex population structure among strains. This induces inflated false positive rates, which cannot be corrected using standard approaches applied in human association studies such as genomic control or structured association. Recent studies demonstrated that mixed models successfully correct for the genetic relatedness in association mapping in maize and Arabidopsis panel data sets. However, the currently available mixed-model methods suffer from computational inefficiency. In this article, we propose a new method, efficient mixed-model association (EMMA), which corrects for population structure and genetic relatedness in model organism association mapping. Our method takes advantage of the specific nature of the optimization problem in applying mixed models for association mapping, which allows us to substantially increase the computational speed and reliability of the results. We applied EMMA to in silico whole-genome association mapping of inbred mouse strains involving hundreds of thousands of SNPs, in addition to Arabidopsis and maize data sets. We also performed extensive simulation studies to estimate the statistical power of EMMA under various SNP effects, varying degrees of population structure, and differing numbers of multiple measurements per strain. Despite the limited power of inbred mouse association mapping due to the limited number of available inbred strains, we are able to identify significantly associated SNPs, which fall into known QTL or genes identified through previous studies while avoiding an inflation of false positives. An R package implementation and webserver of our EMMA method are publicly available. W ITH the recent development of high-throughput genotyping technologies, genetic variation in many model organisms such as mice, Arabidopsis, and maize is being discovered on a genomewide scale ( Jander et al. 2002;Pletcher et al. 2004;Flint-Garcia et al. 2005;Frazer et al. 2007). Genomewide association mapping in model organisms has great potential to identify risk factors for complex traits related to human diseases. Despite the disadvantage that direct inferences from model organisms are not always applicable to human traits, model organism association mapping is potentially more powerful than human association mapping because it is possible to reduce the effect of environmental factors by replicating phenotype measurements in genetically identical organisms (Belknap 1998). In addition, it is often easier and more cost effective to verify associated signals in model organisms than in human subjects. Moreover, many ongoing genotyping and phenotyping projects in model organisms such as the Mouse Phenome Database (MPD) (http://www.jax. org/phenome), the Mouse HapMap project (http:/ /www. broad.mit.edu/personal/clair...

The sequence of the mouse genome is a key informational tool for understanding the contents of the human genome and a key experimental tool for biomedical research. Here, we report the results of an international collaboration to produce a high-quality draft sequence of the mouse genome. We also present an initial comparative analysis of the mouse and human genomes, describing some of the insights that can be gleaned from the two sequences. We discuss topics including the analysis of the evolutionary forces shaping the size, structure and sequence of the genomes; the conservation of large-scale synteny across most of the genomes; the much lower extent of sequence orthology covering less than half of the genomes; the proportions of the genomes under selection; the number of protein-coding genes; the expansion of gene families related to reproduction and immunity; the evolution of proteins; and the identification of intraspecies polymorphism.

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We report a high-quality draft sequence of the genome of the horse (Equus caballus). The genome is relatively repetitive, but has little segmental duplication. Chromosomes appear to have undergone few historical rearrangements – 48% of equine chromosomes show conserved synteny to a single human chromosome. Equine chromosome 11 is shown to have an evolutionary novel centromere devoid of centromeric satellite DNA, suggesting that centromeric function may arise prior to satellite repeat accumulation. Linkage disequilibrium, showing the influences of early domestication of large herds of female horses, is intermediate in length between dog and human, and there is long-range haplotype sharing among breeds.

We report a high-quality draft of the genome sequence of the grey, short-tailed opossum (Monodelphis domestica). As the first metatherian ('marsupial') species to be sequenced, the opossum provides a unique perspective on the organization and evolution of mammalian genomes. Distinctive features of the opossum chromosomes provide support for recent theories about genome evolution and function, including a strong influence of biased gene conversion on nucleotide sequence composition, and a relationship between chromosomal characteristics and X chromosome inactivation. Comparison of opossum and eutherian genomes also reveals a sharp difference in evolutionary innovation between protein-coding and non-coding functional elements. True innovation in protein-coding genes seems to be relatively rare, with lineage-specific differences being largely due to diversification and rapid turnover in gene families involved in environmental interactions. In contrast, about 20% of eutherian conserved non-coding elements (CNEs) are recent inventions that postdate the divergence of Eutheria and Metatheria. A substantial proportion of these eutherian-specific CNEs arose from sequence inserted by transposable elements, pointing to transposons as a major creative force in the evolution of mammalian gene regulation.

With several hundred genetic diseases and an advantageous genome structure, dogs are ideal for mapping genes that cause disease. Here we report the development of a genotyping array with approximately 27,000 SNPs and show that genome-wide association mapping of mendelian traits in dog breeds can be achieved with only approximately 20 dogs. Specifically, we map two traits with mendelian inheritance: the major white spotting (S) locus and the hair ridge in Rhodesian ridgebacks. For both traits, we map the loci to discrete regions of <1 Mb. Fine-mapping of the S locus in two breeds refines the localization to a region of approximately 100 kb contained within the pigmentation-related gene MITF. Complete sequencing of the white and solid haplotypes identifies candidate regulatory mutations in the melanocyte-specific promoter of MITF. Our results show that genome-wide association mapping within dog breeds, followed by fine-mapping across multiple breeds, will be highly efficient and generally applicable to trait mapping, providing insights into canine and human health.

A dense map of genetic variation in the laboratory mouse genome will provide insights into the evolutionary history of the species and lead to an improved understanding of the relationship between inter-strain genotypic and phenotypic differences. Here we resequence the genomes of four wild-derived and eleven classical strains. We identify 8.27 million high-quality single nucleotide polymorphisms (SNPs) densely distributed across the genome, and determine the locations of the high (divergent subspecies ancestry) and low (common subspecies ancestry) SNP-rate intervals for every pairwise combination of classical strains. Using these data, we generate a genome-wide haplotype map containing 40,898 segments, each with an average of three distinct ancestral haplotypes. For the haplotypes in the classical strains that are unequivocally assigned ancestry, the genetic contributions of the Mus musculus subspecies--M. m. domesticus, M. m. musculus, M. m. castaneus and the hybrid M. m. molossinus--are 68%, 6%, 3% and 10%, respectively; the remaining 13% of haplotypes are of unknown ancestral origin. The considerable regional redundancy of the SNP data will facilitate imputation of the majority of these genotypes in less-densely typed classical inbred strains to provide a complete view of variation in additional strains.