Large-scale integration of human genetic and physical maps.

Genetic maps are used routinely in family-based linkage studies to identify the rough location of genes that influence human traits and diseases. Unlike physical maps, genetic maps are based on the amount of recombination occurring between adjacent loci rather than the actual number of bases separating them. Genetic maps are constructed by statistically characterizing the number of crossovers observed in parental meioses leading to the transmission of alleles to their offspring. Considerations such as the number of meioses observed, the heterozygosity and physical distance between the loci studied, and the statistical methods used can impact the construction and reliability of a genetic map. As is well known, poorly constructed genetic maps can have adverse effects on linkage mapping studies. With the availability of sequence-based maps, as well as genetic maps generated by different researchers (such as those generated by the Marshfield and deCODE groups), one can investigate the compatibility and properties of different maps. We have integrated information from the most current human genome sequence data (UCSC genome assembly Human July 2003) as well as 8399 microsatellite markers used in the Marshfield and deCODE maps to reconcile the these maps. Our efforts resulted in updated sex-specific genetic maps.

Automated whole-genome multiple alignment of rat, mouse, and human.

We have built a whole-genome multiple alignment of the three currently available mammalian genomes using a fully automated pipeline that combines the local/global approach of the Berkeley Genome Pipeline and the LAGAN program. The strategy is based on progressive alignment and consists of two main steps: (1) alignment of the mouse and rat genomes, and (2) alignment of human to either the mouse-rat alignments from step 1, or the remaining unaligned mouse and rat sequences. The resulting alignments demonstrate high sensitivity, with 87% of all human gene-coding areas aligned in both mouse and rat. The specificity is also high: <7% of the rat contigs are aligned to multiple places in human, and 97% of all alignments with human sequence >100 kb agree with a three-way synteny map built independently, using predicted exons in the three genomes. At the nucleotide level <1% of the rat nucleotides are mapped to multiple places in the human sequence in the alignment, and 96.5% of human nucleotides within all alignments agree with the synteny map. The alignments are publicly available online, with visualization through the novel Multi-VISTA browser that we also present.

HAPPY days for the Dictyostelium genome project.

Without the HAPPY map, the collaborators in the genome project would have found assembly to be extremely difficult, and the Dictyostelium genome sequence would perhaps have been left highly incomplete. With the HAPPY Map the YAC clones can be remapped and the original YAC skim strategy followed. In conclusion, this method has already made one community very happy and seems sure to make its mark in many other genome projects.

Expression-based genetic/physical maps of single-nucleotide polymorphisms identified by the cancer genome anatomy project.

SNPs (Single-Nucleotide Polymorphisms), the most common DNA variant in humans, represent a valuable resource for the genetic analysis of cancer and other illnesses. These markers may be used in a variety of ways to investigate the genetic underpinnings of disease. In gene-based studies, the correlations between allelic variants of genes of interest and particular disease states are assessed. An extensive collection of SNP markers may enable entire molecular pathways regulating cell metabolism, growth, or differentiation to be analyzed by this approach. In addition, high-resolution genetic maps based on SNPs will greatly facilitate linkage analysis and positional cloning. The National Cancer Institute's CGAP-GAI (Cancer Genome Anatomy Project Genetic Annotation Initiative) group has identified 10,243 SNPs by examining publicly available EST (Expressed Sequence Tag) chromatograms. More than 6800 of these polymorphisms have been placed on expression-based integrated genetic/physical maps. In addition to a set of comprehensive SNP maps, we have produced maps containing single nucleotide polymorphisms in genes expressed in breast, colon, kidney, liver, lung, or prostate tissue. The integrated maps, a SNP search engine, and a Java-based tool for viewing candidate SNPs in the context of EST assemblies can be accessed via the CGAP-GAI web site (http://cgap.nci.nih.gov/GAI/). Our SNP detection tools are available to the public for noncommercial use.