Search

‘Electronic PCR’ (e-PCR) refers to a computational procedure that is used to search DNA sequences for sequence tagged sites (STSs), each of which is defined by a pair of primer sequences and an expected PCR product size. To gain speed, our implementation extracts short ‘words’ from the 3′ end of each primer and stores them in a sorted hash table that can be accessed efficiently during the search. One recent improvement is the use of overlapping discontinuous words to allow matches to be found despite the presence of a mismatch. Moreover, it is possible to allow gaps in the alignment between the primer and the sequence. The effect of these changes is to improve sensitivity without significantly affecting specificity. The new software provides a search mode using a query STS against a sequence database to augment the previously available mode using a query sequence against an STS database. Finally, e-PCR may now be used through a web service, with search results linked to other web resources such as the UniSTS database and the MapViewer genome browser. The e-PCR web server may be found at www.ncbi.nlm.nih.gov/sutils/e-pcr.

To date, despite the increasing number of genomic tools, there is no repository of ordered human BAC clones that covers entire chromosomes. This project presents a resource of mapped large DNA fragments that span eight human chromosomes at ∼1-Mb resolution. These DNA fragments are bacterial artificial chromosome (BAC) clones anchored to sequence tagged site (STS) markers. This clone collection, which currently contains 759 mapped clones, is useful in a wide range of applications from microarray-based gene mapping to identification of chromosomal mutations. In addition to the clones themselves, we describe a database, GenMapDB (http://genomics.med.upenn.edu/genmapdb), that contains information about each clone in our collection.

The highly specific and sensitive PCR provides the basis for sequence-tagged sites (STSs), unique landmarks that have been used widely in the construction of genetic and physical maps of the human genome. Electronic PCR (e-PCR) refers to the process of recovering these unique sites in DNA sequences by searching for subsequences that closely match the PCR primers and have the correct order, orientation, and spacing that they could plausibly prime the amplification of a PCR product of the correct molecular weight. A software tool was developed to provide an efficient implementation of this search strategy and allow the sort of en masse searching that is required for modern genome analysis. Some sample searches were performed to demonstrate a number of factors that can affect the likelihood of obtaining a match. Analysis of one large sequence database record revealed the presence of several microsatellite and gene-based markers and allowed the exact base-pair distances among them to be calculated. This example provides a demonstration of how e-PCR can be used to integrate the growing body of genomic sequence data with existing maps, reveal relationships among markers that existed previously on different maps, and correlate genetic distances with physical distances.

The human genome is thought to harbor 50,000 to 100,000 genes, of which about half have been sampled to date in the form of expressed sequence tags. An international consortium was organized to develop and map gene-based sequence tagged site markers on a set of two radiation hybrid panels and a yeast artificial chromosome library. More than 16,000 human genes have been mapped relative to a framework map that contains about 1000 polymorphic genetic markers. The gene map unifies the existing genetic and physical maps with the nucleotide and protein sequence databases in a fashion that should speed the discovery of genes underlying inherited human disease. The integrated resource is available through a site on the World Wide Web at http://www.ncbi.nlm.nih.gov/SCIENCE96/.

A map of 30,181 human gene–based markers was assembled and integrated with the current genetic map by radiation hybrid mapping. The new gene map contains nearly twice as many genes as the previous release, includes most genes that encode proteins of known function, and is twofold to threefold more accurate than the previous version. A redesigned, more informative and functional World Wide Web site ( www.ncbi.nlm.nih.gov/genemap ) provides the mapping information and associated data and annotations. This resource constitutes an important infrastructure and tool for the study of complex genetic traits, the positional cloning of disease genes, the cross-referencing of mammalian genomes, and validated human transcribed sequences for large-scale studies of gene expression.

We have placed 7,600 cytogenetically defined landmarks on the draft sequence of the human genome to help with the characterization of genes altered by gross chromosomal aberrations that cause human disease. The landmarks are large-insert clones mapped to chromosome bands by fluorescence in situ hybridization. Each clone contains a sequence tag that is positioned on the genomic sequence. This genome-wide set of sequence-anchored clones allows structural and functional analyses of the genome. This resource represents the first comprehensive integration of cytogenetic, radiation hybrid, linkage and sequence maps of the human genome; provides an independent validation of the sequence map1,2 and framework for contig order and orientation; surveys the genome for large-scale duplications, which are likely to require special attention during sequence assembly; and allows a stringent assessment of sequence differences between the dark and light bands of chromosomes. It also provides insight into large-scale chromatin structure and the evolution of chromosomes and gene families and will accelerate our understanding of the molecular bases of human disease and cancer. Supplementary information The online version of this article (doi:10.1038/35057192) contains supplementary material, which is available to authorized users.

Gene expression quantifying techniques promise to shape our understanding of the distribution and regulation of the products of transcription in normal and abnormal cell types. cDNA microarray (DeRisi 1997), high-density oligo DNA array (Wodicka 1997) and serial analysis of gene expression (Velculescu 1995) techniques have all been developed to quickly and efficiently survey genome-wide transcript expression. However, each of these techniques has the potential to produce, in a single experiment, vast amounts of data which must be sifted and ordered for useful information to become apparent. Additional challenges are met when attempts are made to compare, merge and contrast data from experiments conducted under differing conditions and locales. As a prototype for the handling, analysis and exchange of gene expression data in the public forum, we have undertaken the production of a public repository and resource for a particular set of gene expression data, i.e., serial analysis of gene expression (SAGE) data. This repository was designed initially to archive SAGE data produced through the Cancer Genome Anatomy Project (CGAP) (Strausberg 1997; http://www.ncbi.nlm.nih.gov/cgap) but is now capable of accepting submissions of SAGE sequence data from any source, without fee or restriction on dissemination or use. It is our goal to provide free and open access to raw SAGE sequence data, precomputed tag extractions, and several modest analysis tools. This resource currently contains over two million tags from 47 SAGE libraries. We call this resource SAGEmap. Its two online components are available via the World Wide Web (http://www.ncbi.nlm.nih.gov/sage) and anonymous FTP (ftp://ncbi.nlm.nih.gov/pub/sage).

A crucial event in the history of the Human Genome Project was the decision to use sequence-tagged sites (STSs) as common landmarks for genomic mapping. Following several years of constructing STS-based maps of ever-increasing detail, the emphasis has recently shifted towards large-scale genomic sequencing. A computational procedure called 'electronic PCR' allows STS landmarks to be revealed as data emerge from the sequencing pipeline, thereby bridging the gap between mapping and sequencing activities.