Most genomic variation is attributable to single nucleotide polymorphisms (SNPs), which therefore offer the highest resolution for tracking disease genes and population history. It has been proposed that a dense map of 30,000-500,000 SNPs can be used to scan the human genome for haplotypes associated with common diseases. Here we describe a simple but powerful method, called reduced representation shotgun (RRS) sequencing, for creating SNP maps. RRS re-samples specific subsets of the genome from several individuals, and compares the resulting sequences using a highly accurate SNP detection algorithm. The method can be extended by alignment to available genome sequence, increasing the yield of SNPs and providing map positions. These methods are being used by The SNP Consortium, an international collaboration of academic centres, pharmaceutical companies and a private foundation, to discover and release at least 300,000 human SNPs. We have discovered 47,172 human SNPs by RRS, and in total the Consortium has identified 148,459 SNPs. More broadly, RRS facilitates the rapid, inexpensive construction of SNP maps in biomedically and agriculturally important species. SNPs discovered by RRS also offer unique advantages for large-scale genotyping.

We describe a map of 1.42 million single nucleotide polymorphisms (SNPs) distributed throughout the human genome, providing an average density on available sequence of one SNP every 1.9 kilobases. These SNPs were primarily discovered by two projects: The SNP Consortium and the analysis of clone overlaps by the International Human Genome Sequencing Consortium. The map integrates all publicly available SNPs with described genes and other genomic features. We estimate that 60,000 SNPs fall within exon (coding and untranslated regions), and 85% of exons are within 5 kb of the nearest SNP. Nucleotide diversity varies greatly across the genome, in a manner broadly consistent with a standard population genetic model of human history. This high-density SNP map provides a public resource for defining haplotype variation across the genome, and should help to identify biomedically important genes for diagnosis and therapy.

SummaryWe determined the in vivo translational efficiency of 'unleadered' lacZ compared with a conventionally leadered lacZ with and without a Shine-Dalgarno (SD) sequence in Escherichia coli and found that changing the SD sequence of leadered lacZ from the consensus 5Ј-AGGA-3Ј to 5Ј-UUUU-3Ј results in a 15-fold reduction in translational efficiency; however, removing the leader altogether results in only a twofold reduction. An increase in translation coincident with the removal of the leader lacking a SD sequence suggests the existence of stronger or novel translational signals within the coding sequence in the absence of the leader. We examined, therefore, a change in the translational signals provided by altering the AUG initiation codon to other naturally occurring initiation codons (GUG, UUG, CUG) in the presence and absence of a leader and find that mRNAs lacking leader sequences are dependent upon an AUG initiation codon, whereas leadered mRNAs are not. This suggests that mRNAs lacking leader sequences are either more dependent on perfect codon-anticodon complementarity or require an AUG initiation codon in a sequence-specific manner to form productive initiation complexes. A mutant initiator tRNA with compensating anticodon mutations restored expression of leadered, but not unleadered, mRNAs with UAG start codons, indicating that codon-anticodon complementarity was insufficient for the translation of mRNA lacking leader sequences. These data suggest that a cognate AUG initiation codon specifically serves as a stronger and different translational signal in the absence of an untranslated leader.

A comprehensive gene-based map of a genome is a powerful tool for genetic studies and is especially useful for the positional cloning and positional candidate approaches. The availability of gene maps for multiple organisms provides the foundation for detailed conserved-orthology maps showing the correspondence between conserved genomic segments. These maps make it possible to use cross-species information in gene hunts and shed light on the evolutionary forces that shape the genome. Here we report a radiation hybrid map of mouse genes, a combined project of the Whitehead Institute/Massachusetts Institute of Technology Center for Genome Research, the Medical Research Council UK Mouse Genome Centre, and the National Center for Biotechnology Information. The map contains 11,109 genes, screened against the T31 RH panel and positioned relative to a reference map containing 2,280 mouse genetic markers. It includes 3,658 genes homologous to the human genome sequence and provides a framework for overlaying the human genome sequence to the mouse and for sequencing the mouse genome.