In the past decade, bioinformatics has become an integral part of research and development in the biomedical sciences. Bioinformatics now has an essential role both in deciphering genomic, transcriptomic and proteomic data generated by high-throughput experimental technologies and in organizing information gathered from traditional biology. Sequence-based methods of analyzing individual genes or proteins have been elaborated and expanded, and methods have been developed for analyzing large numbers of genes or proteins simultaneously, such as in the identification of clusters of related genes and networks of interacting proteins. With the complete genome sequences for an increasing number of organisms at hand, bioinformatics is beginning to provide both conceptual bases and practical methods for detecting systemic functional behaviors of the cell and the organism.

Alternative splicing of mRNA allows many gene products with different functions to be produced from a single coding sequence. It has recently been proposed as a mechanism by which higher-order diversity is generated. Here we show, using large-scale expressed sequence tag (EST) analysis, that among seven different eukaryotes the amount of alternative splicing is comparable, with no large differences between humans and other animals.

Troyer syndrome (TRS) is an autosomal recessive complicated hereditary spastic paraplegia (HSP) that occurs with high frequency in the Old Order Amish. We report mapping of the TRS locus to chromosome 13q12.3 and identify a frameshift mutation in SPG20, encoding spartin. Comparative sequence analysis indicates that spartin shares similarity with molecules involved in endosomal trafficking and with spastin, a molecule implicated in microtubule interaction that is commonly mutated in HSP.

Although approximately one-quarter of the roughly 4,000 genetically inherited diseases currently recorded in respective databases (LocusLink, OMIM) are already linked to a region of the human genome, about 450 have no known associated gene. Finding disease-related genes requires laborious examination of hundreds of possible candidate genes (sometimes, these are not even annotated; see, for example, refs 3,4). The public availability of the human genome draft sequence has fostered new strategies to map molecular functional features of gene products to complex phenotypic descriptions, such as those of genetically inherited diseases. Owing to recent progress in the systematic annotation of genes using controlled vocabularies, we have developed a scoring system for the possible functional relationships of human genes to 455 genetically inherited diseases that have been mapped to chromosomal regions without assignment of a particular gene. In a benchmark of the system with 100 known disease-associated genes, the disease-associated gene was among the 8 best-scoring genes with a 25% chance, and among the best 30 genes with a 50% chance, showing that there is a relationship between the score of a gene and its likelihood of being associated with a particular disease. The scoring also indicates that for some diseases, the chance of identifying the underlying gene is higher.

Cloning procedures aided by homology searches of EST databases have accelerated the pace of discovery of new genes, but EST database searching remains an involved and onerous task. More than 1.6 million human EST sequences have been deposited in public databases, making it difficult to identify ESTs that represent new genes. Compounding the problems of scale are difficulties in detection associated with a high sequencing error rate and low sequence similarity between distant homologues. We have developed a new method, coupling BLAST-based searches with a domain identification protocol, that filters candidate homologues. Application of this method in a large-scale analysis of 100 signalling domain families has led to the identification of ESTs representing more than 1,000 novel human signalling genes. The 4,206 publicly available ESTs representing these genes are a valuable resource for rapid cloning of novel human signalling proteins. For example, we were able to identify ESTs of at least 106 new small GTPases, of which 6 are likely to belong to new subfamilies. In some cases, further analyses of genomic DNA led to the discovery of previously unidentified full-length protein sequences. This is exemplified by the in silico cloning (prediction of a gene product sequence using only genomic and EST sequence data) of a new type of GTPase with two catalytic domains.

Species phylogenies derived from comparisons of single genes are rarely consistent with each other, due to horizontal gene transfer, unrecognized paralogy and highly variable rates of evolution. The advent of completely sequenced genomes allows the construction of a phylogeny that is less sensitive to such inconsistencies and more representative of whole-genomes than are single-gene trees. Here, we present a distance-based phylogeny constructed on the basis of gene content, rather than on sequence identity, of 13 completely sequenced genomes of unicellular species. The similarity between two species is defined as the number of genes that they have in common divided by their total number of genes. In this type of phylogenetic analysis, evolutionary distance can be interpreted in terms of evolutionary events such as the acquisition and loss of genes, whereas the underlying properties (the gene content) can be interpreted in terms of function. As such, it takes a position intermediate to phylogenies based on single genes and phylogenies based on phenotypic characteristics. Although our comprehensive genome phylogeny is independent of phylogenies based on the level of sequence identity of individual genes, it correlates with the standard reference of prokarytic phylogeny based on sequence similarity of 16s rRNA. Thus, shared gene content between genomes is quantitatively determined by phylogeny, rather than by phenotype, and horizontal gene transfer has only a limited role in determining the gene content of genomes.

The exponential growth of sequence data does not necessarily lead to an increase in knowledge about the functions of genes and their products. Prediction of function using comparative sequence analysis is extremely powerful but, if not performed appropriately, may also lead to the creation and propagation of assignment errors. While current homology detection methods can cope with the data flow, the identification, verification and annotation of functional features need to be drastically improved.

Chediak-Higashi syndrome (CHS) is a rare, autosomal recessive disorder characterized by hypopigmentation, severe immunologic deficiency with neutropenia and lack of natural killer (NK) cells, a bleeding tendency and neurologic abnormalities. Most patients die in childhood. The CHS hallmark is the occurrence of giant inclusion bodies and organelles in a variety of cell types, and protein sorting defects into these organelles. Similar abnormalities occur in the beige mouse, the proposed model for human CHS. Two groups have recently reported the identification of the beige gene, however the two cDNAs were not at all similar. Here we describe the sequence of a human cDNA homologous to mouse beige, identify pathologic mutations and clarify the discrepancies of the previous reports. Analysis of the CHS polypeptide demonstrates that its modular architecture is similar to the yeast vacuolar sorting protein, VPS15.

The X-lined gene for Norrie disease, which is characterized by blindness, deafness and mental retardation has been cloned recently. This gene has been thought to code for a putative extracellular factor; its predicted amino acid sequence is homologous to the C-terminal domain of diverse extracellular proteins. Sequence pattern searches and three-dimensional modelling now suggest that the Norrie disease protein (NDP) has a tertiary structure similar to that of transforming growth factor beta (TGF beta). Our model identifies NDP as a member of an emerging family of growth factors containing a cystine knot motif, with direct implications for the physiological role of NDP. The model also sheds light on sequence related domains such as the C-terminal domain of mucins and of von Willebrand factor.