Human chromosome 7 has historically received prominent attention in the human genetics community, primarily related to the search for the cystic fibrosis gene and the frequent cytogenetic changes associated with various forms of cancer. Here we present more than 153 million base pairs representing 99.4% of the euchromatic sequence of chromosome 7, the first metacentric chromosome completed so far. The sequence has excellent concordance with previously established physical and genetic maps, and it exhibits an unusual amount of segmentally duplicated sequence (8.2%), with marked differences between the two arms. Our initial analyses have identified 1,150 protein-coding genes, 605 of which have been confirmed by complementary DNA sequences, and an additional 941 pseudogenes. Of genes confirmed by transcript sequences, some are polymorphic for mutations that disrupt the reading frame.

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The sequence of any genome becomes most useful for biological experimentation when a complete and accurate gene set is available. Gene prediction programs offer an efficient way to generate an automated gene set. Manual annotation, when performed by experienced annotators, is more accurate and complete than automated annotation. However, it is a laborious and expensive process, and by its nature, introduces a degree of variability not found with automated annotation. EAnnot (Electronic Annotation) is a program originally developed for manually annotating the human genome. It combines the latest bioinformatics tools to extract and analyze a wide range of publicly available data in order to achieve fast and reliable automatic gene prediction and annotation. EAnnot builds gene models based on mRNA, EST, and protein alignments to genomic sequence, attaches supporting evidence to the corresponding genes, identifies pseudogenes, and locates poly(A) sites and signals. Here, we compare manual annotation of human chromosome 6 with annotation performed by EAnnot in order to assess the latter's accuracy. EAnnot can readily be applied to manual annotation of other eukaryotic genomes and can be used to rapidly obtain an automated gene set