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The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.

Sequence similarity between a translated nucleotide sequence and a known biological protein can provide strong evidence for the presence of a homologous coding region, even between distantly related genes. The computer program BLASTX performed conceptual translation of a nucleotide query sequence followed by a protein database search in one programmatic step. We characterized the sensitivity of BLASTX recognition to the presence of substitution, insertion and deletion errors in the query sequence and to sequence divergence. Reading frames were reliably identified in the presence of 1% query errors, a rate that is typical for primary sequence data. BLASTX is appropriate for use in moderate and large scale sequencing projects at the earliest opportunity, when the data are most prone to containing errors.

Single nucleotide polymorphisms (SNPs) are valuable genetic markers of human disease. They also comprise the highest potential density marker set available for mapping experimentally derived mutations in model organisms such as Caenorhabditis elegans. To facilitate the positional cloning of mutations we have identified polymorphisms in CB4856, an isolate from a Hawaiian island that shows a uniformly high density of polymorphisms compared with the reference Bristol N2 strain. Based on 5.4 Mbp of aligned sequences, we predicted 6,222 polymorphisms. Furthermore, 3,457 of these markers modify restriction enzyme recognition sites ('snip-SNPs') and are therefore easily detected as RFLPs. Of these, 493 were experimentally confirmed by restriction digest to produce a snip-SNP map of the worm genome. A mapping strategy using snip-SNPs and bulked segregant analysis (BSA) is outlined. CB4856 is crossed into a mutant strain, and exclusion of CB4856 alleles of a subset of snip-SNPs in mutant progeny is assessed with BSA. The proximity of a linked marker to the mutation is estimated by the relative proportion of each form of the biallelic marker in populations of wildtype and mutant genomes. The usefulness of this approach is illustrated by the rapid mapping of the dyf-5 gene.

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Sequence similarity search programs are versatile tools for the molecular biologist, frequently able to identify possible DNA coding regions and to provide clues to gene and protein structure and function. While much attention had been paid to the precise algorithms these programs employ and to their relative speeds, there is a constellation of associated issues that are equally important to realize the full potential of these methods. Here, we consider a number of these issues, including the choice of scoring systems, the statistical significance of alignments, the masking of uninformative or potentially confounding sequence regions, the nature and extent of sequence redundancy in the databases and network access to similarity search services.

Single-nucleotide polymorphisms (SNPs) are the most abundant form of human genetic variation and a resource for mapping complex genetic traits. The large volume of data produced by high-throughput sequencing projects is a rich and largely untapped source of SNPs (refs 2, 3, 4, 5). We present here a unified approach to the discovery of variations in genetic sequence data of arbitrary DNA sources. We propose to use the rapidly emerging genomic sequence as a template on which to layer often unmapped, fragmentary sequence data and to use base quality values to discern true allelic variations from sequencing errors. By taking advantage of the genomic sequence we are able to use simpler yet more accurate methods for sequence organization: fragment clustering, paralogue identification and multiple alignment. We analyse these sequences with a novel, Bayesian inference engine, POLYBAYES, to calculate the probability that a given site is polymorphic. Rigorous treatment of base quality permits completely automated evaluation of the full length of all sequences, without limitations on alignment depth. We demonstrate this approach by accurate SNP predictions in human ESTs aligned to finished and working-draft quality genomic sequences, a data set representative of the typical challenges of sequence-based SNP discovery.

We report the generation of 319,311 single-pass sequencing reactions (known as expressed sequence tags, or ESTs) obtained from the 5' and 3' ends of 194,031 human cDNA clones. Our goal has been to obtain tag sequences from many different genes and to deposit these in the publicly accessible Data Base for Expressed Sequence Tags. Highly efficient automatic screening of the data allows deposition of the annotated sequences without delay. Sequences have been generated from 26 oligo(dT) primed directionally cloned libraries, of which 18 were normalized. The libraries were constructed using mRNA isolated from 17 different tissues representing three developmental states. Comparisons of a subset of our data with nonredundant human mRNA and protein data bases show that the ESTs represent many known sequences and contain many that are novel. Analysis of protein families using Hidden Markov Models confirms this observation and supports the contention that although normalization reduces significantly the relative abundance of redundant cDNA clones, it does not result in the complete removal of members of gene families.